Search Results (2,957)

S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) are essential intermediates in one-carbon metabolism and key regulators of cellular methylation capacity. Their concentrations and the SAM/SAH ratio are increasingly studied as biomarkers across metabolic, cardiovascular, neurological, and cancer-related diseases. This review outlines validated analytical methods for quantifying SAM and SAH, focusing primarily on liquid chromatography–tandem mass spectrometry (LC–MS/MS), which is considered the gold standard in both clinical and research settings. A comprehensive literature search identified studies on method development, validation, and clinical use of SAM and SAH measurements. Special attention is given to analytical challenges arising from their high polarity, structural similarity, endogenous presence, and limited stability. The review also discusses preanalytical variables, including biological matrix selection, sample handling, and storage conditions. LC–MS/MS methods are compared with alternative techniques, such as immunoassays, with respect to sensitivity, specificity, matrix effects, and clinical relevance. Additionally, the review summarizes the concentration ranges of SAM and SAH, and their ratio, in healthy and patient populations, noting current standardization limitations. Overall, the review highlights the importance of harmonized analytical protocols and matrix-specific validation to enable reliable clinical interpretation of SAM and SAH as methylation biomarkers. Full article

Model Predictive Control (MPC) is widely employed in three-phase two-level voltage source inverters (2L-VSIs) due to its fast dynamic response and straightforward implementation. However, conventional MPC requires the evaluation of all eight candidate voltage vectors (VVs), which increases computational burden and current prediction time, introduces higher common-mode voltage (CMV), and may degrade steady-state performance. To address these limitations, this paper investigates the effect of reducing the number of candidate VVs on CMV suppression, the reduction in current prediction time, and the enhancement of 2L-VSI performance. First, a five-voltage-vectors MPC approach is developed, achieving noticeable CMV suppression compared with the conventional approach. Although this approach achieved CMV suppression, it still incurred a high computational burden. Therefore, it was further developed into a systematic switching approach based on three VVs, in which only three candidate VVs are selected at each sampling instant. The proposed approach achieves two primary objectives: suppressing CMV and reducing the current prediction time by 50%. Experimental validation is conducted to compare the proposed approach with the conventional MPC in terms of CMV, current prediction time, Total Harmonic Distortion (THD), inductance variation sensitivity, dynamic response, and power loss. The results demonstrate that the proposed approach achieves superior steady-state and dynamic performance while significantly reducing the current prediction time and achieving suppression of the CMV at Vdc/2, thereby enhancing the performance of 2L-VSIs. Full article

The transition toward more sustainable crop protection under the European Green Deal has accelerated the adoption of biopesticides, which are widely considered safer alternatives to synthetic pesticides. Botanical biopesticides derived from plant extracts, essential oils, and secondary metabolites are increasingly used in both conventional and organic agriculture. However, their growing use raises important questions regarding human health risks. Botanical biopesticides are complex mixtures of bioactive compounds whose composition and toxicological profiles can vary substantially depending on plant chemotype, extraction method, and manufacturing processes. This review critically examined the toxicological properties of botanical biopesticides and evaluated their regulatory assessment within the European Union (EU) framework. Particular attention is paid to scientific uncertainties, gaps in toxicological data, challenges in hazard characterization of complex mixtures, and limitations of current human exposure assessments. The review also considered how regulatory practices, user behavior, and risk perception may influence real-world exposure and potential health outcomes. By integrating experimental toxicology studies, EU risk assessment documents, and evidence on agricultural use patterns, this review assessed whether reduced intrinsic toxicity of botanical biopesticides translates into lower human health risk under current regulatory frameworks and agricultural practices. The findings underscore the need for strengthened toxicological evidence, harmonized regulatory approaches, and improved risk communication to ensure that the use of botanical biopesticides remains aligned with good agricultural practice and human health protection. Full article

Existing model predictive control (MPC) schemes based on virtual voltage vectors (VVVs) for dual three-phase permanent magnet synchronous motors (DT-PMSMs) typically employ a limited set of voltage vectors, which restricts further improvement in steady-state performance. Moreover, the design of switching sequences lacks systematic consideration, focusing mainly on harmonic current suppression while neglecting practical engineering challenges associated with software-layer implementation. This paper proposes an optimized model predictive torque control (MPTC) method for DT-PMSMs using an expanded voltage vector set. First, to enhance steady-state performance, an extended control set of voltage vectors is designed, which introduces not only new directions but also two distinct voltage amplitude levels, resulting in a total of 48 voltage vectors. Second, to alleviate the significant computational burden caused by traversing the extended set for prediction, a candidate voltage vector selection table is constructed based on the sector position of the stator flux linkage and the requirements for torque and flux adjustment. This approach reduces the computational load to only 10 predictive calculations per control cycle, avoiding exhaustive traversal of the extended set. Furthermore, for all VVVs in the control set, a switching sequence combining active voltage vectors with zero vectors is designed to facilitate straightforward digital implementation. Finally, experimental results are provided to validate the effectiveness of the proposed method. Full article

The development of new technologies, particularly autonomous vehicles, poses significant challenges and opportunities for international trade law. Legal frameworks must adapt to technological shifts while facilitating cross-border commerce. This paper examines the relationship between emerging technologies and the existing infrastructure of world trade law, focusing specifically on how current WTO agreements address technological developments. The analysis employs a legal doctrinal approach, examining the applicability of key WTO agreements to new technologies through the lens of technology-neutral interpretation. Departing from ‘dialectical relationship theory’ (Cottier), the research investigates the influence of new technologies on the legal infrastructure of international trade and how the latter can respond to their use and development. Current WTO frameworks demonstrate technology-neutral applicability to emerging technologies, including autonomous vehicles and related services. However, the paper identifies significant practical limitations arising from the ‘mosaic’ nature of member state commitments and varying levels of liberalization across relevant technology-related sectors. The findings suggest that, while the existing WTO infrastructure theoretically has the capacity to accommodate technological advances, realizing the full benefits of global trade in new technologies may require either the harmonized extension of WTO member-state commitments or the adoption of specific legislation to address current regulatory fragmentation. Full article

The recent advent of charging infrastructure on an Electric Vehicles (EVs) poses a severe problem with effect on the power grid in terms of harmonic distortion, mostly caused by the nonlinear loads on the electric power produced by charging stations, diode bridge rectifiers, and switching converters. These harmonics continuously negatively influence power quality by increasing system and grid current, voltage total harmonic distortion (THD), power factor, and voltage regulation, and lowering the overall efficiency of the system at high rates that exceed IEEE 519 harmonic standards. This paper develops a thorough design and critical analysis of four topologies of harmonic passive filter, including single-tuned filter (STF), double-tuned filter (DTF), high-pass filter (HPF), and C-type high-pass filter (CHPF), to alleviate harmonics and enhance power quality on grid-tied charging stations of electric vehicles. A generalized structure is modeled and simulated in MATLAB/Simulink R2021a at a charging load of an EV charging load for all the filters under the same conditions and evaluated based on the current THD (ITHD), voltage THD (VTHD), input power factor (PF), voltage regulation (VR), and efficiency (η). The findings show that STF has an ITHD of 8.3%, VTHD of 4.6%, PF of 0.92, VR of 6.2%, and efficiency of 91.3%; DTF has an ITHD of 6.1%, VTHD of 3.9%, PF of 0.95, VR of 5.4%, and 93.5%; HPF has an ITHD of 5.6%, VTHD of 3.5%, 0.96 PF, 5.0% of VR, and 94.2% efficiency. The effectiveness of the proposed CHPH is superior to all other traditional approaches and has the lowest ITHD and VTHD, 3.7% and 2.1%, respectively, the highest PF of 0.987, a better VR of 3.8%, and a higher efficiency of 96.2%. The proposed CHPF shows the high-performance characteristics as reflected in the harmonic reduction, improved voltage stability, power factor, and efficiency. The suggested CHPF complies with IEEE 519 standards and provides better grid compatibility with modern EV charging applications. Full article

This review synthesizes recent progress in modern energy storage technologies and proposes a selection-oriented comparison for power-system stabilization. Technologies are grouped into electrochemical, mechanical, chemical, and thermal storage, and evaluated using harmonized criteria (power and energy capability, response time, round-trip efficiency, lifetime, cost proxies, and maturity level). A comparative dataset and use-case mapping are used to link technology characteristics to grid services, with emphasis on voltage support, operational durability, and waste-heat utilization. The analysis highlights pumped-storage hydropower as the most robust option for long-duration, high-capacity applications, while battery energy storage systems are best suited for fast ancillary services, provided that cycle life, safety, and system integration constraints are met. Finally, the review discusses current technology trends (e.g., LFP and sodium-ion deployment, solid-state development, and commercialization barriers for lithium-sulfur) and identifies evidence-based directions for future research and deployment. Full article

Bio-CO₂ is part of the natural carbon cycle and represents a sustainable carbon source for the production of Renewable Fuels of Non-Biological Origin (RFNBOs), such as synthetic methanol. This study addresses the critical knowledge gap in aligning diverse biogenic CO₂ sources with e-methanol requirements in the EU by providing harmonized mapping, based on datasets, literature sources, and reported industrial statistics at the sectoral and country level. Bio-CO₂ streams from biogas and biogas upgrading, biomass combustion, pulp and paper, bioethanol production, and the food and beverage sector are evaluated for total emissions, CO₂ concentrations and purity, the geographical distribution, seasonality, and impurity profiles. Results show that approximately 350 Mtpa of bio-CO₂ are emitted across the EU, with highly heterogeneous characteristics. Biogas upgrading and fermentation-based processes generate highly pure CO₂ streams (>98–99%), yet their small and dispersed nature complicates logistics. In contrast, biomass-combustion and pulp and paper sectors provide large volumes (around 214.6–298.2 Mtpa and 73.9 Mtpa CO₂, respectively), but in diluted streams (typically 3–15% and 10–20%). Replacing just 10% of the EU maritime fuel demand with e-methanol would require 53.6 Mtpa of bio-CO₂ and 58 GW of electrolyzer capacity, a stark contrast to the current operational 385 MW. The findings highlight the need for infrastructure planning and aggregation hubs to enable the large-scale deployment of RFNBO methanol in the maritime sector. Full article

The fast growth of electric vehicles (EVs) and renewable energy motivates reliable charging infrastructure with balanced energy management and good power quality. However, conventional converter controllers like proportional and integral (PI) and fuzzy logic controllers (FLCs) exhibit slow dynamic response, poor adaptability to varying solar conditions, unbalanced energy management, low power quality, and higher total harmonic distortion (THD). To overcome these limitations, this work proposes an adaptive neuro-fuzzy inference system (ANFIS) controller for balanced energy management and improved power quality in EV charging stations. The ANFIS controller is a combination of a fuzzy inference system (FIS) and a neural network (NN). The FIS provides the best maximum power point tracking and robust control during changing solar PV conditions. The NN optimally controls the flow of power between the solar PV system, energy storage battery (ESB), EV, and utility grid. The entire system is simulated in MATLAB/Simulink. It consists of a PV system with a capacity of 2 kW, an ESB with a capacity of 10 kWh and an EV battery with a capacity of 4 kWh, which are linked by bidirectional DC/DC converters. A 30 kVA bidirectional inverter, along with an LCL filter, is connected between the 500 V DC bus and 440 V utility grid, allowing for both directions. The results validate the effectiveness of the proposed ANFIS controller in terms of DC bus voltage stability, faster dynamic response, enhanced renewable energy utilization, improved efficiency to 98.86%, reduced voltage and current THD to 4.65% and 2.15% respectively, reduced utility grid stress, and enhanced energy management compared to conventional PI and FLCs. Full article

High-resolution microdisplay driver applications impose stringent requirements on the static linearity and dynamic performance of digital-to-analog converters (DACs). To meet these requirements, this paper presents a 200 MS/s 12-bit current-steering DAC. To reduce mismatches among high-weight current sources, a split–sort–symmetric grouping calibration (SSSGC) scheme is introduced, in which each most-significant-bit (MSB) current source is split into sub-cells and reorganized through sorting and symmetric pairing. This approach improves static linearity without complex current measurement or compensation loops. Additionally, a group-domain dynamic element matching (DEM) technique is employed to randomize current-source selection and suppress harmonic distortion. Designed in a 0.18 μm BCD process, the proposed DAC achieves an integral nonlinearity (INL) of 0.79 LSB, a differential nonlinearity (DNL) of 0.42 LSB, and a spurious-free dynamic range (SFDR) of 74.9 dB at an output signal of 4.05 MHz. Full article

The emergence of artificial intelligence tools in scientific production is generating significant challenges for scientific integrity and editorial governance, prompting journals and publishers to develop normative guidelines for their use. This study analyzes the current state of guideline implementation among Latin American journals indexed in Scopus and classified according to the Scimago Journal Rank (SJR). A quantitative approach was adopted, complemented by a descriptive documentary analysis based on a detailed review of the websites of 1119 journals from 17 Latin American countries. The collected data were systematized using Excel and analyzed through descriptive and inferential statistical techniques. The results indicate that only 27.2% of journals have explicit guidelines on the use of artificial intelligence, with a predominantly regulatory rather than punitive orientation that prioritizes technical support while restricting practices that compromise human intellectual control. Additionally, statistically significant differences were identified according to quality indicators, showing that journals with higher quality levels are more likely to have such guidelines. Overall, the findings reveal an incipient and heterogeneous regulatory development, underscoring the need to strengthen and harmonize editorial guidelines on artificial intelligence in order to safeguard transparency, clarify the responsibilities of the actors involved in the production and publication process, and protect the integrity of scientific communication. Full article

This paper proposes a single-stage three-phase AC-DC converter based on an LLC resonant topology utilizing a front-end matrix switch. Unlike traditional two-stage solutions, the proposed topology synthesizes a fluctuating equivalent DC voltage from the three-phase input, achieving direct power conversion with high efficiency. To maintain a stable DC output voltage against the time-varying input, a trajectory-based Pulse Frequency Modulation (PFM) control strategy is developed. By employing State-Plane Analysis (SPA), the operational trajectory is divided into four calculation segments, allowing precise derivation of the switching frequency and duty cycles for both boost and buck modes within a single line cycle. Furthermore, to improve power density and reduce parasitic parameters, a high-frequency planar inductor with interleaved windings and a planar transformer are designed for 500 kHz operation. A pipeline control architecture based on a single DSP is implemented to handle the complex real-time computations. A 500 W prototype is built and tested under 100 V input and 130 V output conditions. Experimental results demonstrate that the converter achieves a peak efficiency of 97%, a power factor of 0.99, and a grid current Total Harmonic Distortion (THD) of 3.95%, validating the effectiveness of the proposed topology and control scheme. Full article

This review summarizes current scientific knowledge on the use of protein hydrolyzate-based biostimulants in fruit production through evidence mapping, cross-species comparison, and evaluation of protocol-dependent responses within an agronomic framework, centered on foliar applications and their role in sustainable production systems. Research across a broad range of fruit species reports that protein hydrolyzates can significantly enhance yield, improve fruit quality, and mitigate the adverse effects of abiotic stresses such as drought and high temperatures. Treated plants often exhibit improved nutrient uptake, increased photosynthetic efficiency, and enhanced morphological traits, including better root development and vegetative growth. However, the effectiveness of these biostimulants varies depending on the fruit species, developmental stage, and application frequency, indicating the need for more tailored and crop-specific protocols. In conclusion, the literature confirms the functional role of protein hydrolyzates in enhancing resilience and productivity in fruit crops, while highlighting the need for further research to optimize their use under diverse agroecological conditions. Protocol harmonization and robust field validation will be essential for improving the reliability, interpretability, and practical relevance of future research on protein hydrolyzates in fruit production. Full article

This paper presents an evaluation methodology for multiphase Permanent Magnet Synchronous Motors (PMSMs) using winding function theory. The study extends a previously developed space harmonic model and focuses on deriving comparative indicators for making decisions on slot, pole, and phase number combinations. Thus, it contributes a unified framework that integrates diverse performance indicators for the early-stage evaluation of multiphase motors, complemented by an experimental validation that defines the accuracy limits of such analytical models. Key performance metrics such as cogging torque harmonic order, torque ripple harmonic order, winding factor, inductance value, and inductance balance among harmonic planes are analytically derived and applied to two motor configurations: a Three-Phase (TP) and a Dual Three-Phase (DTP) motor, both with 24 slots and 10 pole pairs. Theoretical analysis reveals that the DTP winding offers improved torque capability, higher fundamental inductance ratio, and lower torque ripple, contributing to enhanced torque production and reduced airgap harmonic content. Experimental validation confirms the analytical predictions, demonstrating a 3.5% increase in torque and a 4–5% reduction in inductance for the DTP configuration. Additionally, vibration and torque ripple measurements show lower harmonic content in the DTP motor. While minor discrepancies existed between the analytical and experimental data, they were deemed within acceptable limits for a tool designed for preliminary comparative analysis rather than exact performance prediction. However, the analytical model was unable to predict the inductance balance across the various harmonic planes; addressing this would require a more complex model, which was beyond the scope of the current study. These findings underscore the effectiveness of winding function theory as a rapid design tool for evaluating multiphase motor windings. Full article

Background/Objectives: There is little information on the definition and management of dyslipidemia in patients and survivors of childhood, adolescent and young adult (CAYA) cancer. However, it is known that this population is at higher risk of developing cardiovascular disease (CVD). Dyslipidemia, hypertension, and metabolic syndrome are common among CAYA cancer survivors due to the cancer itself or the treatment received. Therefore, managing dyslipidemia in this population is crucial to mitigate the risk of long-term CVD. The aim of this systematic review was to summarize currently used definitions and cutoffs for dyslipidemia, its prevalence, and management strategies in CAYA cancer survivors. This review further describes reported pharmacological and lifestyle interventions and their impact on lipid levels. Methods: We conducted a systematic literature search in PubMed, including studies published in English, German or French between January 2015 and February 2025. The population included individuals diagnosed with any type of CAYA cancer prior to 25 years of age and either receiving cancer treatment or in follow-up care. We considered all types of publications except for Phase I and II studies. We followed PRISMA guidelines, assessed the quality of the eligible studies according to the respective Joanna Briggs Institute’s Critical Appraisal Tools, and reported the results descriptively. Results: Of 575 identified publications, 53 fulfilled the inclusion criteria. Forty-three studies reported on the definitions of abnormal lipid values, 40 stated the prevalence of abnormal lipid values, and 17 studies described management approaches, of which 12 were case reports and small case series. For all three outcomes, the results were very heterogeneous. Using the example of triglycerides (TGs), the cutoff values for high TGs ranged from 5.17 mmol/L to 6.2 mmol/L and the reported prevalence of high TGs ranged from 0% to 75%, with an average of 31%. The only reported intervention to prevent dyslipidemia in CAYA cancer survivors was lifestyle modification. Preventive strategies that started during treatment were lifestyle modifications and fish oil supplements. Conclusions: Our systematic review provides a comprehensive overview of existing definitions, prevalences, and management of abnormal lipid values in CAYA cancer patients and survivors. However, the identified heterogeneities indicate that reported prevalences and results of interventions must be interpreted cautiously. An internationally harmonized approach to defining and reporting lipid values in CAYA cancer survivors is urgently needed to enable tailored screening and treatment strategies. Full article