Search Results (108)

Objective: Preanalytical errors account for the vast majority of preanalytical incidents and remain a fundamental threat to the reliability of test results. Although the types and frequencies of these errors have been extensively studied in the literature, their time-dependent variability has received comparatively little attention. This study aimed to evaluate how preanalytical specimen rejection rates vary across intraday time intervals and to assess the independent influence of time on preanalytical quality. Methods: This retrospective observational study included a total of 579,845 specimens accepted by the central laboratory of Istanbul Atlas University Hospital between January 2024 and December 2025. Specimens were analyzed with respect to preanalytical rejection reasons, the distribution and rate of these reasons across clinical units, and time of day. Each day was divided into six equal four-hour intervals: Z1 (00:00–04:00), Z2 (04:00–08:00), Z3 (08:00–12:00), Z4 (12:00–16:00), Z5 (16:00–20:00), and Z6 (20:00–24:00). Statistical analyses were performed using the Pearson chi-square test, and effect sizes were quantified using Cramér’s V coefficient. Results: Of the 579,845 specimens examined, 4365 were rejected, yielding an overall rejection rate of 0.79%. Rejection rates were found to be non-uniformly distributed across the day (p < 0.001). The highest rejection rate was observed during the Z2 interval (04:00–08:00) at 1.98%, whereas the lowest was recorded during Z3 (08:00–12:00) at 0.45%. Negative binomial regression analysis identified the Z2 interval as the only time period independently associated with an increased rejection risk Incidence Rate Ratio (IRR) = 1.63; 95% Confidence Interval (CI): 1.22–2.19. Among clinical units, the highest rejection rate was recorded in the emergency department (1.92%). Analysis of error types revealed that the majority of rejections were attributable to hemolysis (47.5%) and clotted specimens (26.3%). Hemolysis rates peaked in the emergency department, while clotted specimens occurred more frequently within intensive care units. Analysis of time and error interactions revealed that clotted specimens peaked during Z1 and Z2, whereas hemolysis became the primary cause of rejection during Z3 and Z4. Conclusions: Preanalytical specimen rejection rates exhibited significant variation according to time of day, clinical unit, and error type, with time emerging as a factor independently associated with preanalytical quality. The coexistence of elevated rejection risk during Z2 (04:00–08:00) and markedly low rejection rates during Z3 (08:00–12:00) indicates that the relationship between workload and error frequency is not linear. Although hemolysis and clotted specimens constituted the dominant error types, their distribution followed distinct patterns depending on the clinical unit and time interval. These results underscore the necessity of time-based monitoring to pinpoint unit-specific risks, providing a clear roadmap for targeted quality improvement interventions. Full article

Background/Objectives: Nanopore sequencing is increasingly used in mycobacterial diagnostics, where clinical microbiologists and diagnostic laboratories must decide when broad metagenomic next-generation sequencing (mNGS) or focused targeted next-generation sequencing (tNGS) is most appropriate. This review examined reported clinical and laboratory roles of nanopore mNGS and tNGS in tuberculosis (TB) and nontuberculous mycobacterial (NTM) settings. Methods: Targeted searches of PubMed/MEDLINE, Embase, Web of Science Core Collection, and Scopus were refreshed on 4 April 2026. Thirty-five records spanning original clinical studies, evidence syntheses, and guideline-context documents were included. Results: Nanopore mNGS is most useful for broad organism detection and diagnostic rescue in unresolved pulmonary and extrapulmonary presentations, particularly when first-line testing is negative, discordant, low-yield, or when mixed infection is suspected. Nanopore tNGS appears better aligned with predefined TB confirmation and resistance-focused workflows because targeted regions allow more standardized interpretation. Agreement is strongest for rifampicin- and isoniazid-related resistance targets. In NTM settings, evidence is stronger for detection and species identification than for disease-level diagnosis. Common implementation constraints include pre-analytical variation, contamination control, host-background interference, inconsistent bioinformatics, and limited workforce capacity. Conclusions: A practical tiered approach is supported in which mNGS is positioned mainly for diagnostic rescue and discovery, whereas tNGS is considered for predefined workflows requiring standardized target interrogation and resistance-associated mutation reporting under local validation and quality systems. Full article

Cross-basin tropical cyclone variability may exhibit complex, non-linear dependence structures influenced by large-scale climate modes and potential regime shifts. Reliance on traditional linear correlation measures without accounting for structural changes can therefore lead to misleading interpretations of global storm relationships. This study investigates the regional dependence structures of tropical cyclone counts across six major ocean basins (NA, ENP, WNP, NI, SI, and SP) from 1980 to 2024. We adopt a two-stage analytical framework integrating changepoint detection and copula modeling to address non-stationarity in both marginal distributions and dependence structures. First, we identify a significant structural break in the year 2000 via a penalised likelihood applied jointly to the $d=6$-variate Poisson series, with inter-basin dependence captured by a latent Gaussian process (the construction used by Lund et al. (2025). This is mathematically equivalent to a Gaussian copula with Poisson margins (Genest and Nešlehová (2007)). Then, we apply bivariate copula models separately to the pre- and post-2000 regimes using the randomized probability integral transform with results averaged over 500 replications of the auxiliary uniforms to mitigate randomization noise. The results reveal substantial non-stationarity, most notably a 59% increase in North Atlantic storm frequency and a fundamental reorganization of global dependence structures, while dependence structures evolved from primarily symmetric and weak (dominated by Gaussian and Clayton copulas) to more complex and stronger dependencies (increased Frank and Gumbel copulas). Notably, a statistically significant ($p<0.001$) and strong negative dependence emerged between the Southern Pacific and Northern Indian basins ($\tau =-0.464$) in the recent regime. The inclusion of changepoint detection significantly improves model fit and reveals a fundamental reorganization of global tropical cyclone teleconnections, with enhanced coordination between basins in the contemporary climate regime. Modeling these regimes separately, as opposed to a single stationary period, uncovers a shift towards more complex, tail-dependent copula families (Gumbel, Clayton) in the recent era. These findings have important implications for climate risk assessment, seasonal forecasting, and understanding the impacts of climate change on global storm patterns. The proportion of Gumbel copulas (capturing upper-tail dependence) increased from 7% to 20%, while Gaussian copulas decreased from 53% to 33%, indicating more complex, extreme-value-focused dependencies in the contemporary climate. Due to small sample sizes ($n_1=20$, $n_2=25$), copula and dependence estimates are exploratory, not confirmatory. Interpretations reflect this power constraint, utilizing Benjamini–Hochberg adjustments for significance. Full article

Background/Objectives: Large language models (LLMs) are increasingly consulted for information about cleft lip and palate (CLP), yet the reliability of their outputs across clinical domains has not been evaluated. This study aimed to compare the quality of CLP-related information generated by GPT-4o and Gemini 2.5 Pro across multiple thematic domains using a validated quality instrument and a reliability-first analytic framework. Methods: Fifty-four standardized CLP questions across six domains were submitted to GPT-4o (OpenAI) and Gemini 2.5 Pro (Google DeepMind) on 25 September 2024 via their public interfaces, using new, history-free sessions and default settings, yielding 108 responses. Three independent, CLP-experienced raters scored each response using the Global Quality Score (GQS; 1–5 scale assessing accuracy, completeness, and clinical usefulness). Before comparing models, we applied a reliability-first filter: only domains where all three raters showed substantial agreement (Fleiss’ kappa [κ] ≥ 0.60) were included in statistical comparisons. Domains that failed this threshold were analyzed qualitatively to identify the source of disagreement. A descriptive taxonomy of errors was developed for low-scoring responses. Results: Three domains met the reliability threshold (General Care Information, General Cleft Information, and Pre-Treatment Information; 30 paired questions). Both models performed at a high and practically equivalent level: GPT-4o median GQS 4.33 (IQR 4.00–5.00) versus Gemini 2.5 Pro 5.00 (IQR 4.00–5.00); the difference was not statistically significant (Wilcoxon V = 139.00, p = 0.691; Hodges–Lehmann median difference 0.00, 95% CI −0.33 to 0.67). Three domains were excluded because rater agreement was insufficient; qualitative review showed this reflected genuine clinical practice variation rather than clear model errors. The most common inaccuracies were overgeneralization of outcomes, outdated surgical timing, and omission of multidisciplinary team roles. Conclusions: Both models provided high-quality CLP information in domains supported by clinical consensus, indicating they may serve as useful adjuncts for general patient and family counseling. Clinicians should, however, verify any treatment-specific content against current institutional protocols before relaying it to patients. Future research should assess readability, alignment with health literacy, and patient comprehension of AI-generated CLP information. Full article

This study examines how individual political predispositions and national mobilisation contexts jointly structure protest participation in contemporary Europe across the pre-pandemic, pandemic and post-pandemic periods. Using data from Rounds 9, 10 and 11 of the European Social Survey (2018–2023), the analytical sample includes 106,106 respondents from 33 countries. Descriptively, protest participation remains a minority behaviour, yet displays pronounced cross-national heterogeneity, with participation rates ranging from below 3% in several Central and Eastern European countries to nearly 20% in the most mobilised contexts and remains remarkably stable across rounds at approximately 8.5%. Building on resource mobilisation theory, political process approaches and New Social Movements perspectives, the analysis conceptualises protest participation not as an isolated behavioural act but as the outcome of interactions between individual resources, evaluative orientations toward democratic institutions and broader mobilisation environments. Logistic regression models, country fixed-effects specifications and multilevel models with random intercepts are used to assess these relationships. At the individual level, political engagement emerges as the strongest predictor of participation: higher political interest is associated with substantially higher protest propensity, while ideological self-placement indicates lower participation among respondents positioned further to the right. Younger age and higher education also increase participation. Lower satisfaction with democracy and stronger perceptions of inequality are consistently associated with protest behaviour, supporting grievance-based interpretations linked to democratic evaluations rather than material deprivation alone. Country fixed-effects and multilevel models confirm that these individual-level associations are robust within countries, while significant between-country variation persists (random-intercept SD = 0.554), indicating that national mobilisation environments shape baseline levels of protest participation. Multilevel results further reveal that protest participation was significantly lower during the pandemic period (Round 10) relative to the pre-pandemic baseline, with only partial recovery in the post-pandemic period. A cross-round comparison demonstrates that the core individual-level associations are stable across all three periods, indicating that these relationships reflect durable structural patterns rather than dynamics specific to any particular mobilisation cycle. Beyond this overall stability, the analysis identifies two theoretically informative exceptions: subjective financial difficulty is significant only in the pre-pandemic period and gender differences in protest participation attenuate over time—patterns consistent with broader shifts in protest repertoires during and after the pandemic. These findings make three contributions to the comparative literature on contentious politics. First, by extending the analysis across three ESS rounds, the study demonstrates the temporal robustness of individual-level determinants of protest—an empirical question rarely addressed in the existing literature. Second, the multilevel design with round fixed effects allows for direct estimation of pandemic-related suppression and post-pandemic recovery in protest activity at the aggregate level. Third, the cross-national scope and temporally structured comparison provide new evidence on how individual political predispositions interact with shifting mobilisation environments across a period of exceptional socio-political strain in Europe. Full article

Arid region ecosystems are among the most fragile ecological types worldwide. They depend heavily on limited water resources and are strongly influenced by intensive human activities, leading their ecosystem services to exhibit nonlinear and threshold responses to driving factors. Identifying the thresholds of ecosystem services under the combined influence of natural and socio-economic interactive drivers is of great significance for regional ecological risk warning and differentiated management. Taking the Tarim River Basin as a case study, this research establishes an integrated analytical framework that combines causal inference, interaction term construction, interpretable machine learning (XGBoost-SHAP), and piecewise linear regression. The framework is used to evaluate the variations in four types of ecosystem services in 2000, 2010, and 2023, to analyze the interactive effects of driving factors, and to identify their thresholds influencing ecosystem service functions. The results indicate that (1) different types of ecosystem service functions exhibited distinct trends from 2000 to 2023, with habitat quality and water yield showing declining tendencies, while soil conservation and Windbreak and sand fixation demonstrated gradual increases; (2) Causal Screening and interaction modeling revealed that the interaction between precipitation and population density (Pre × Pop) served as the key synergistic driver of changes in the four ecosystem service functions. Both the ecosystem services and the coupled natural–social driving processes exhibited pronounced nonlinear characteristics, with evident trend shifts occurring within specific threshold intervals. (3) The precise coupling thresholds of different ecosystem services under natural–social drivers were identified, intuitively revealing the coupling threshold characteristics of various ecosystem services; (4) The integration of causal inference with interpretable machine learning enhances the reliability of threshold identification, revealing the heterogeneous response mechanisms of different services and providing a quantitative basis for the zoning regulation and differentiated management of regional ecosystems. The findings offer a transferable methodological framework to support ecological governance in arid regions. Full article

The North China Craton (NCC) hosts numerous world-class Au deposits and these Au deposits can be classified into the Au-only and Ag-Au polymetallics, respectively. The former is mostly located in the eastern NCC, such as in the giant Jiaodong Province, and the latter is mostly distributed along the northern and southern margins of the NCC. Compared with Au-only deposits, the ore genesis of the Ag-Au deposits remains controversial. This paper focuses on the Niujuan Ag-Au deposit in the Fengning ore cluster of the northern margin of the NCC. Detailed deposit geology investigation, texture analysis, and analyses of the in situ trace element and sulfur isotope compositions of pyrite, coupled with H-O isotope compositions of quartz from different stages, were conducted to elucidate the ore-forming processes and metal sources. The results showed that the formation of the Niujuan deposit can be divided into four stages, including a pre-ore siliceous breccia stage (stage 1), syn-ore quartz-pyrite stage (stage 2), syn-ore polymetallic sulfide stage (stage 3), and post-ore fluorite-calcite stage (stage 4). Among these, stage 3 represents the major Ag-Au mineralization stage. Pyrite is well developed within stage 2 and stage 3, representing the intensive sulfidation of the wall rock. Microscopic analytical techniques including gamma-enhanced reflected light and scanning electron microscopy backscattered electron (BSE) reveal that pyrite samples from stage 2 and stage 3 have distinct textures. Pyrite (Py1) from stage 2 is homogeneous but with numerous pores. In contrast, pyrite (Py2) from stage 3 has overgrowth textures, and be divided into three sub-stages from core to rim (Py2a, Py2b, and Py2c) with different BSE brightness levels. LA-ICP-MS trace elements analyses results show that these different stages of pyrite show different composition such as Au, As, Ag, Co, and Ni. Py1 has low Au and Ag concentrations ranging from <0.1 ppm to 0.02 ppm and <0.1 ppm to 21.8 ppm, respectively. Py2a has low Au and Ag concentrations ranging from <0.1 ppm to 0.4 ppm and 0.4 ppm to 118.4 ppm, respectively. Py2b is characterized by high As and low Au contents, with average values of 6670.8 ppm for As and 1.4 ppm for Au. Py2c shows relatively low Co and Ni concentrations ranging from 0.02 ppm to 255.2 ppm and <0.1 ppm to 9.9 ppm, respectively. The sulfur isotope composition of Py1 and Py2 is relatively consistent, ranging from 3.8‰ to 6.7‰. The H and O isotope compositions of quartz from stage 1, stage 2, and stage 3 have insignificant variations, ranging from −119.5‰ to −101.3‰ for δD and −6.8‰ to −3.7‰ for δ¹⁸O_fluid, respectively. The results show that sulfur and, possibly, Au and Ag were mainly derived from magmatic hydrothermal fluids, and a significant amount of meteoric water was involved. Combined with the published mineralizing ages (~140 Ma), this paper suggests that the Niujuan Ag-Au deposit formed during the Early Cretaceous under an extensional setting in response to the eastward retreating subduction of the Paleo-Pacific oceanic plate. Evidence from deposit geology and geochemistry reveals that the mixture of magmatic and meteoric water, together with intensive sulfidation, is the key factor controlling Au and Ag deposition. Full article

Estimating the post-mortem interval (PMI) using microRNAs (miRNAs) in vitreous humor (VH) is a promising technique in forensic pathology. However, the reliability of quantitative Real-Time PCR (qPCR) data in this matrix is currently constrained by a critical methodological challenge: the lack of a rigorously validated endogenous reference gene (normalizer) capable of correcting for non-biological variations without being influenced by decomposition. This study aimed to identify a robust reference gene for VH analysis by performing a comparative validation of two candidates proposed in the literature: miR-222-3p and miR-96-5p. VH samples were collected from 47 forensic autopsy cases with estimated PMIs ranging from 3 to 24 h. The validation process assessed three key parameters: amplification detectability, expression stability (Coefficient of Variation, CV), and statistical independence from both the PMI and the pre-analytical freezing interval using regression models. MiR-222-3p was rejected as a normalizer due to poor detectability, failing to reach the detection threshold (Cq < 35) in 61.7% of cases (29/47). Conversely, hsa-miR-96-5p was validated as a stable reference gene. It demonstrated high detectability and expression stability (CV = 9.07%) among valid samples. Crucially, linear regression analysis showed no significant correlation between hsa-miR-96-5p levels and either the PMI (p = 0.69) and the pre-freezing time (p = 0.70). This study demonstrates that miR-222-3p is unsuitable for forensic casework in VH due to instability. We identified and validated hsa-miR-96-5p as a robust endogenous reference gene. Its adoption is recommended to standardize future molecular thanatochronology studies and improve the accuracy of PMI estimation models. Full article

Metabolic profiling enables comprehensive characterisation of the small molecules that are part of the biochemical composition of biological fluids. The most widely profiled biofluids include serum and plasma. Additionally synovial fluid provides a direct reflection of the metabolomic environment of joints and holds promise for biomarker discovery in arthropathies. However, the reproducibility of metabolomics data is highly sensitive to pre-analytical variation, and at the present time, standardised protocols for synovial fluid remain underdeveloped. This review aims to identify and evaluate the existing literature on effects of biofluid pre-analytical handling treatments on metabolic profiles. This review was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. A search was carried out to identify studies employing LC-MS, GC-MS, and NMR spectroscopy for the investigation of factors including sample collection variables, pre-centrifugation conditions, centrifugation parameters, post-centrifugations conditions, sample storage conditions, and freeze/thaw cycling. Best practice recommendations emerging from this review include the use of additive free serum and heparin plasma tubes, the centrifugation of samples within two hours of collection, immediate storage of samples at −80 °C, and avoidance of repeated freeze/thaw cycling. However, while pre-analytical influences have been extensively characterised for plasma and serum, evidence for synovial fluid remains limited. Overall, the findings highlight the existing recommendations for plasma and serum and demonstrate the need for standardised pre-analytical protocols and validation of quality control markers to advance synovial fluid metabolomics. Full article

Hepatitis B virus (HBV) pregenomic RNA (pgRNA), transcribed directly from nuclear covalently closed circular DNA (cccDNA), is an essential component in viral replication. The synthesis and encapsidation of pgRNA depend significantly on the transcriptional activity of cccDNA, making serum pgRNA a recently recognized non-invasive biomarker for evaluating cccDNA activity. However, its clinical application is limited by factors including preanalytical variables, methodological inconsistencies in detection, and a lack of standardization in quantification. This review provides an overview of the biological origins of pgRNA and its critical role in the HBV replication cycle, highlighting the stability challenges encountered during the collection, processing, and storage of plasma/serum samples. Furthermore, it analyzes recent significant advancements in pgRNA detection technologies, encompassing modified reverse transcription quantitative polymerase chain reaction (RT-qPCR), nucleocapsid-captured methodologies, automated testing platforms, multiplex digital PCR, isothermal amplification, and clustered regularly interspaced short palindromic repeats-based assays. A comparison of these technologies revealed that discrepancies in pgRNA quantification arise primarily from variations in sample processing and measurement systems, rather than from inherent biological limitations. Therefore, establishing standardized sample handling procedures, harmonized detection methods, and unified measurement systems is imperative before pgRNA can be reliably applied to monitor treatment, guide cessation decisions, or evaluate cure in chronic hepatitis B. Full article

Extracellular vesicles (EVs) are known as potential biomarkers for several diseases; nevertheless, the degree of technical and biological variability is not yet adequately characterized. Because pre-analytical factors such as blood collection time and EV subpopulation could confound biomarker studies, we performed a pilot study systematically quantifying methodological and biological variability including EV-Array (surface proteins), and proteome characterization of cargo. Plasma samples from six healthy adults were collected at two time points (morning and afternoon) and plasma was analyzed with EV-Array, and isolated EVs were analyzed using nanoparticle tracking analysis (NTA), and label-free mass spectrometry (LC-MS/MS). Methodological repeatability was high for NTA particle size (3.3% CV) and LC-MS (8.2% CV), and lower for EV-Array surface markers (22.6% CV). Variations between samples were reasonable for NTA-size, EV-Array and LC-MS/MS (5–21%) and substantially lower than between-subject variation. No evidence of systemic morning–afternoon shifts in particle size and concentration or EV cargo was observed, although small effects cannot be excluded. The same was true for most surface markers, but minor but statistically significant reductions in a few specific surface markers occurred in afternoon EV-Array samples. In this pilot we therefore do not observe any major systemic diurnal bias in healthy individuals in samples collected a.m. vs. p.m. Despite the small sample size, this study underscores the importance of accounting for individual variability and methodological standardization when designing EV-based biomarker research. Full article

Controlling pre-analytical conditions for medical biology tests, particularly during transport, is crucial for complying with the ISO 15189 standard and ensuring high-quality medical services. The use of drones, also known as unmanned aerial vehicles, to transport clinical samples is growing in scale, but requires prior validation to verify that there is no negative impact on the test results provided to doctors. This study aimed to establish a secure, high-quality solution for transporting biological samples by drone in a coastal region of France. The 80 km routes passed over several densely populated urban areas, with take-off and landing points within hospital grounds. The analytical and clinical impact of this mode of transport was compared according to two protocols: an interventional clinical trial on 30 volunteers compared to the reference transport by car, and an observational study on samples from 126 hospitalized patients compared to no transport. The system enabled samples to be transported without damage by maintaining freezing, refrigerated, and room temperatures throughout the flight, without any significant gain in travel time. Analytical variations were observed for sodium, folate, GGT, and platelet levels, with no clinical impact on the interpretation of the results. There is a risk of time-dependent alterations of blood glucose measurements in heparin tubes, which can be corrected by using fluoride tubes. This demonstrated the feasibility and security of transporting biological samples over long distances in line with the ISO 15189 standard. Controlling transport times remains crucial to assessing the quality of analyses. It is imperative to devise contingency plans for backup solutions to ensure the continuity of transportation in the event of inclement weather. Full article

The fire performance of existing reinforced concrete (RC) bridge decks strengthened by external prestressing systems is investigated, with particular attention to the vulnerability of externally applied tendons under realistic fire scenarios. Fire exposure represents a critical condition for such retrofitted structures, as the structural response is strongly influenced by load level, prestressing effectiveness, and thermal degradation of the strengthening system. A comprehensive assessment framework is proposed, combining thermal and mechanical analyses applied to representative highway overpass bridges. The thermal input adopted for the analyses is first validated through computational fluid dynamics (CFD) simulations, aimed at evaluating temperature development in typical RC beam–girder grillage decks subjected to fire from below. The CFD study considers variations in clearance height and span length and confirms that, in the case of hydrocarbon tanker accidents with fuel spilled on the roadway, conventional fire curves commonly adopted in the literature provide a reliable and conservative representation of both the temperature levels reached and their rate of increase within structural elements, thus supporting their use for rapid and simplified assessments. The validated thermal input is then employed in an analytical fire safety procedure applied to several realistic bridge case-studies. A parametric investigation is carried out by varying deck geometry, span length, reinforcement layout, and the presence of external prestressing retrofit, allowing the evaluation of the reduction in bending capacity and the time-dependent degradation of mechanical properties under fire exposure. The results highlight the critical role of external prestressing in fire scenarios, showing that significant loss of prestressing effectiveness may occur within the first minutes of fire, potentially leading to critical conditions even at service load levels. Finally, a multi-hazard assessment is performed by combining fire effects with pre-existing aging-related deterioration, such as reinforcement corrosion and long-term prestressing losses, demonstrating a marked increase in failure risk and, in the most severe cases, the possibility of premature collapse under dead loads. Full article

In flooded soils, the concentrations of exchangeable Mn²⁺ and, especially, Fe²⁺ can be high and must be considered when determining the cation exchange capacity (CEC) of the soil under flooded conditions. However, these reduced forms of Mn and Fe are oxidized and precipitated during the extraction process used in traditional CEC methods. This procedure underestimates the exchangeable portion of these cations and, consequently, the CEC value of the flooded soil. We introduce a pH-gradient-based model to predict ECEC and exchangeable Fe²⁺ in flooded soils, circumventing oxidation artifacts inherent in conventional methods. The objective of this study is to propose an alternative to estimate the exchangeable Fe²⁺ and the effective CEC (ECEC) of flooded soils. To achieve this goal, 21 surface samples (0–20 cm) of soil from rice fields were collected and distributed in the cultivation regions of southern Brazil. The soils were flooded for 50 days. The soil solution was collected on the first day and after 50 days of flooding and pH, Na, K, Ca, Mg, Fe and Mn were determined. In these samples, exchangeable cations (K, Na, Ca, Mg, Mn, Al and H + Al) were determined to calculate ECEC and CEC at pH 7 of unflooded soil and after 50 days of flooding. There was a wide range of variation in the exchangeable cation contents among the soil samples. The K contents ranged from 0.12 to 0.54 cmol_c kg⁻¹, the Na contents from 0.00 to 1.18 cmol_c kg⁻¹, the Ca contents from 0.48 to 37.31 cmol_c kg⁻¹, the Mg contents from 0.10 to 15.53 cmol_c kg⁻¹, the Mn contents from 0.01 to 0.36 cmol_c kg⁻¹, the Al contents from 0.10 to 1.74 cmol_c kg⁻¹ and the H + Al contents from 2.01 to 8.42 cmol_c kg⁻¹. The results were used to develop models to predict ECEC and exchangeable Fe content after 50 days of flooding. Estimating the ECEC after flooding using the pH gradient before and after flooding yielded values closer to CEC pH 7.0, correcting for the possible underestimation of the ECEC during flooding. The amount of exchangeable Fe estimated was higher than the exchangeable Fe determined, correcting the possible underestimation of these quantities determined during flooding. It is concluded that the estimations of ECEC after flooding through the equation ${ECEC}_{after}=ECEC+\left({pH}_{sol.after}-{pH}_{sol.before}\right)\times {\displaystyle \frac{({CEC}_{pH7}-ECEC)}{(7-{pH}_{sol.before})}}$, where pH_sol.before is pre-flooding soil pH, pH_sol.after is after flooding pH, ECEC_after is effective CEC after flooding and the exchangeable Fe²⁺ after flooding through the equation ${Fe}_{exc.after.estimated}={ECEC}_{after}-\left(Ca+Mg+K+Na+Mn\right)$ where Fe_{exc.after.estimated} is estimated exchangeable Fe²⁺ after flooding corrected the problem of underestimating the values of these variables by analytical methods, demonstrating its viability for use in flood-prone soils. Full article

This paper presents an analytically derived optimal control strategy for wound-rotor synchronous machines (WRSM) based on minimising the Joule losses in both the stator and rotor windings. The presented control strategy is analysed in terms of analytical derivation, machine current ratios, working regions and constraints. It is experimentally verified on a salient-pole wound-rotor synchronous machine with strongly non-linear equivalent circuit parameters. The verification was performed in two stages: first, considering constant equivalent circuit parameters while assessing strong non-linear behaviour of the machine leading to significant discrepancies in the resulting machine torque. In the second stage, after determination of non-linear machine parameters using measured flux maps, identical control methodology is analysed in terms of variations in ratios between machine currents. Using pre-calculated current ratios the same control methodology is extended for machines with strongly non-linear equivalent circuit parameters and verified in a real environment. The measurement confirms expected machine behaviour in all available control regions achievable by used synchronous motor as well as limits between these control regions. The results of the verification in a real environment show a discrepancy of approximately 5% in measured machine torque in comparison to expected value confirming the validity of the analytically derived approach and introduced modifications for machines with non-linear equivalent circuit parameters. Full article