Search Results (716)

Supercritical CO₂ (S-CO₂) extraction is one of the most employed techniques for the extraction of bioactive compounds for its safety, effectiveness, cost-efficiency, and good environmental compliance. Smyrnium olusatrum L. (Apiaceae) is an aromatic plant of great interest due to its potential applications in pharmaceutical, agrochemical, and oleochemical fields. Its bioactivity is caused by furanosesquiterpenes, mainly represented by isofuranodiene (IFD). The extraction of this compound is usually achieved through Soxhlet or hydrodistillation. However, the latter usually leads to the thermal Cope rearrangement of IFD into its isomer curzerene, resulting in low recovery. This study reported for the first time the optimization of S-CO₂ extraction of IFD from S. olusatrum schizocarps. Pressure (MPa), extraction time (min), and static mode (%) were varied while the temperature was maintained at 45 °C to avoid IFD thermal degradation. The optimized process (50 MPa, 60 min, 25% static mode) provided an extraction yield and an IFD recovery of 8.50 and 0.94% and avoided the thermal degradation of the compound. This study demonstrated that S-CO₂ extraction is a valuable alternative to conventional hydrodistillation (extraction yield and IFD recovery of 2.64 and 0.77%) and Soxhlet (extraction yield and IFD recovery of 9.49 and 0.85%) to recover IFD from S. olusatrum. Full article

Thedeep score-based diffusion (DeScoD) model performs well in electrocardiogram (ECG) denoising tasks. However, due to the theoretical error lower bound in approximating functions with linear transformations, it often lacks flexibility when fitting non-stationary noise, baseline wander, or morphologically variable features such as QRS complexes in ECG signals. In this paper, we propose a Kolmogorov–Arnold network enhanced deep score-based diffusion (KAN-DeScoD) model, which is the first to integrate Kolmogorov–Arnold network (KAN) layers into an ECG denoising diffusion model. By leveraging KAN’s adaptive activation functions, which more finely capture the complex structures within ECG signals, the model’s robustness in high-noise environments, as well as the accuracy and stability of signal reconstruction, are improved. We validate the effectiveness of the proposed method on the QT Database and the MIT-BIH Noise Stress Test Database (NSTDB). Experimental results show that under different shots and noise intensities, ours outperforms the DeScoD model across multiple metrics. The research results demonstrate the effectiveness of introducing KAN, which improves the model’s robustness in high-noise environments and the accuracy of signal reconstruction. Full article

Background: The landscape of hepatitis C virus (HCV) infection has been changing with the introduction of direct-acting antivirals (DAAs). This study evaluates 15-year temporal trends of anti-HCV and HCV-RNA positivity in a regional referral center in Türkiye, analyzing the impact of DAA treatments, the COVID-19 pandemic, and the 2023 earthquakes on disease dynamics. Methods: Laboratory data of patients tested for anti-HCV antibodies and HCV-RNA between 2011 and 2025 were retrospectively analyzed after excluding repeat records. Positive patients were categorized by antibody titers (1–4.99 S/Co and ≥5 S/Co) and viremia status. Poisson, beta, and quantile regression models were determined annual trends in case numbers, positivity rates, and median ages. Results: A total of 402,557 patients underwent anti-HCV screening over 15 years. While annual test volume increased 2.25-fold, the number and rate of high-titer (≥5 S/Co) positive patients decreased four-fold, significantly. HCV-RNA positivity rates remained stable between 2011 and 2016 but declined sharply from 2017, falling approximately 19.2% annually (p < 0.001). Significant diagnostic disruptions occurred in 2020 (pandemic) and 2023 (earthquakes). An “aging trend” was identified; the median age of viremic patients increased by over 5.5 years throughout the study period. Conclusions: The introduction of DAAs in 2016 marked a milestone, leading to a nearly 90% reduction in the viremic patient burden in our region. The steady aging of the HCV-positive population suggests that the infected pool is shrinking and is not replenished. However, global and regional crises can hinder screening efforts, necessitating resilient public health strategies to achieve World Health Organization 2030 elimination targets. Full article

Supercritical carbon dioxide (sCO₂) is characterized by low viscosity and a peak in specific heat capacity near the pseudo-critical point, making it a promising coolant for microelectronics. However, most existing sCO₂ test rigs are designed for large-scale thermodynamic cycle studies and lack the capability for controlled, localized heat transfer measurements in small channels. This work presents CO₂-SASS (Scientific Assessment of heat transfer in the Supercritical State), a modular, high-pressure test rig designed to measure local heat transfer coefficients and pressure drops in stainless-steel tubes with diameters on the order of 1–3 mm. The system provides independent control of pressure, mass flow and heating, with direct local wall and fluid temperature as well as precise absolute and differential pressure measurements. Particular emphasis is placed on high-accuracy temperature acquisition, including individual thermocouple calibration and cold-junction bias correction. A detailed uncertainty analysis highlights the dominant role of temperature measurement accuracy, especially for small wall–fluid temperature differences near the pseudo-critical point. Full article

Increasing genomic data are driving changes in the selection of phylogenetic markers and analysis strategies. Databases enable the extraction of established markers, such as single and multilocus sequence typing (MLST), but are often limited by the number of informative sites or availability with respect to incomplete source data sets or reductive evolution in bacteria such as the Mollicutes. Genome-wide analyses like average nucleotide identity (ANI) often overcome these problems but also depend on the alignment percentage. Complementary analyses help validate results and address limitations of primary approaches. However, how genome-wide compositional signals and reduced core gene sets affect phylogenomic resolution across a large and taxonomically diverse dataset of complete Mollicutes genomes remains unclear. Therefore, we applied an advanced MLST approach based on single-copy orthologs (SCOs), alongside codon usage analysis. The reliability and impact of these approaches were first analyzed using Acholeplasmatales as the foundation, with 16S rRNA gene, ANI, SCOs, and codon usage. Codon usage analysis revealed lineage-associated compositional signatures across the 52 strains that were broadly consistent with current genus and subgroup assignments, whereas ANI and 16S rRNA gene identified species with ≥96.5% and ≥97%, respectively. Among these, SCOs showed the most matches to the current taxonomy, supporting the approach being extended to Mollicutes. Applied to 807 Mollicutes strains, the analysis revealed 16 shared SCOs. Concatenation of this core set significantly enhanced phylogenomic resolution, providing a robust framework for reconstructing evolutionary relationships within Mollicutes. Full article

Indian senna (Senna alexandrina Mill.), a perennial medicinal species belonging to the family Fabaceae, holds significant therapeutic and commercial importance owing to its rich content of sennosides and rhein derivatives, which confer well-established laxative properties. Its high market demand, however, renders the species vulnerable to deliberate or inadvertent adulteration. While previous investigations have utilized functional marker systems such as SCoT (Start Codon Targeted Polymorphism)- and CBDP (CAAT Box Derived Polymorphism)-derived SCAR (Sequence Characterised Amplified Region) markers for genetic characterization, the present study is the first to report the development of sequence-specific RAPD- and ISSR-based SCAR markers consolidated into a single-tube multiplex PCR assay. Genomic DNA isolated from young leaves of S. alexandrina and its commonly encountered adulterant species was amplified using RAPD primer OPI-02 and ISSR primer UBC-835. Polymorphic amplicons were cloned, sequenced, and employed for the design of SCAR primers, which were rigorously validated for specificity. Species-specific SCAR markers were successfully integrated into a single multiplex reaction, enabling precise and unequivocal identification of S. alexandrina, Cassia fistula and Senna sophera. The multiplex amplification profiles were entirely consistent with corresponding uniplex assays, endorsing the method’s robustness and reproducibility. This streamlined, one-tube multiplex SCAR-PCR system represents a significant advancement toward reliable, high-throughput molecular authentication of Indian senna and its closely related medicinal plant species (adulterants). Full article

Within the carbon capture, utilization and storage (CCUS) chain, buried CO₂ pipelines are an indispensable engineering solution under complex topographic conditions. Experimental investigations show that leakage from buried supercritical CO₂ (sCO₂) pipelines features a two-stage pressure decline: an initial rapid drop driven by high leaking medium mass flow, followed by a linear decrease governed by homogeneous liquid CO₂ vaporization. Notably, the choking flow effect homogenizes linear pressure drop rates across distinct experimental conditions. Leakage orifice diameter is a dominant factor for pipeline temperature distribution: small orifices yield consistent temperature drop rates at different vertical pipeline positions, while larger ones cause faster cooling at the pipeline bottom, forming significant vertical temperature gradients that intensify closer to the leakage orifice. Leakage direction and initial pipeline pressure are key regulators of leakage dynamics: vertical upward leakage (0°) leads to faster pressure drops due to the reduced soil resistance, and elevated initial pressure not only intensifies the pressure drop rate and amplifies CO₂’s endothermic effect but also modulates the phase transition pathway of sCO₂ during leakage. Full article

Industrial production of single-cell oils (SCOs) by oleaginous yeasts relies predominantly on nitrogen limitation, which constrains process flexibility when nitrogen-rich substrates are used. Although phosphate limitation has been reported as an alternative lipid induction strategy, its process-level performance relative to nitrogen limitation remains insufficiently resolved under controlled reactor-scale conditions. In this study, phosphate-limited, nitrogen-limited and nutrient-replete cultivations of Cutaneotrichosporon oleaginosum ATCC 20509, Saitozyma podzolica DSM 27192, Scheffersomyces segobiensis DSM 27193 and Apiotrichum porosum DSM 27194 were benchmarked in 2.5 L stirred-tank reactors operated under identical media compositions and process parameters. Biomass formation, lipid titres, specific lipid production rates, biomass composition and fatty acid profiles were systematically compared. Nitrogen limitation resulted in the highest lipid titres, reaching up to 9.2 g L⁻¹ (A. porosum), while maximum lipid titres under phosphate-limited conditions reached 5.0 g L⁻¹ (C. oleaginosum) and nutrient-replete conditions 3.9 g L⁻¹ (A. porosum), respectively. The highest specific lipid production rate under nitrogen limitation was 0.0028 g gCDW⁻¹ h⁻¹ (S. podzolica), while phosphate limitation yielded a maximum of 0.0037 g gCDW⁻¹ h⁻¹ (S. podzolica). These results demonstrate that phosphate limitation can decouple cellular lipid productivity from biomass formation and represents a process-relevant alternative for SCO production from nitrogen-rich feedstocks. Full article

Specifying non-functional requirements (NFRs) for rapidly evolving domains such as trustworthy APIs in the AI era is challenging as best practices emerge through practitioner discourse faster than traditional requirements engineering can capture them. We present a systematic methodology for deriving prioritized NFR specifications from multimedia practitioner discourse combining AI-assisted transcript analysis, grounded theory principles, and Theme Coverage Score (TCS) validation. Our five-task approach integrates purposive sampling, automated transcription with speaker diarization, grounded theory coding extracting stakeholder-specific themes with TCS quantification, MoSCoW prioritization using empirically derived thresholds (Must Have ≥85%, Should Have 65–84%, Could Have 45–64%, and Won’t Have <45%), and NFR specification consistent with ISO/IEC 25010:2023 principles of stakeholder perspective, measurable quality criteria, and explicit rationale. Applying this methodology to 22 expert presentations on trustworthy APIs yields Weighted Coverage Score of 0.71 and 30 prioritized NFR specifications across five trustworthiness dimensions. MoSCoW classification produces 11 Must Have requirements (Robustness and Transparency), 9 Should Have, 6 Could Have, and 4 Won’t Have. The analysis reveals systematic disparities where Fairness contributes zero Must Have or Should Have requirements due to insufficient practitioner consensus. Each NFR emphasizes stakeholder perspective, measurable quality criteria, and explicit rationale, enabling systematic verification. The validated methodology with complete replication package enables empirically grounded, prioritized NFR derivation from practitioner discourse in any rapidly evolving domain. Full article

Machine learning was employed to make fluid agnostic laminar heat transfer prediction in supercritical conditions, encompassing three fluids (sCO₂, sH₂O, sC₁₀H₂₂) representing a wide range of operating conditions. High-fidelity training data, consisting of both non-dimensional and dimensional (operating parameter) as inputs and Nu and T_wall as outputs, were generated from grid-converged, steady-state, computational fluid dynamic (CFD) simulations. The Random Forest (RF) algorithm outperformed the artificial neural networks (ANNs) across all scenarios on the small multi-fluid dataset (~1600 data points) employed during the training process. When using non-dimensional parameters as inputs, Nu prediction fidelities were better than T_wall predictions for both ML algorithms across both horizontal and vertical configurations. The RF model trained on data from a specific flow configuration (horizontal/vertical) could predict T_wall within an accuracy of +/−1% with dimensional, operational parameters as inputs while being agnostic to the working fluid. Furthermore, by including the gravity vector as an additional variable during the training process, the RF model could predict T_wall accurately in a mixed, multi-fluid dataset containing data from both horizontal and vertical configurations. Full article

Theileria haneyi, a recently discovered tick-borne hemoparasite infecting equids globally, has significant implications for equine health. Although it is closely related to T. equi (sharing 23% genomic divergence), it establishes an asymptomatic carrier state in persistently infected horses, creating a silent transmission reservoir. Its discovery and unique genetics justify its classification as a new taxon. A critical diagnostic challenge is that the lack of the ema-1 gene in T. haneyi prevents its detection by the standard T. equi cELISA, emphasizing the need for species-specific tools. Although species-specific PCR assays, including PCR and qPCR targeting genes like chr1sco or ema-11, respectively, and an indirect ELISA targeting the EMA-11 recombinant protein, have been developed, global genetic variations may limit their serological utility. Therapeutically, T. haneyi exhibits resistance to the key antiparasitic drug, imidocarb dipropionate (ID), and interferes with the clearance of co-infecting T. equi. Major knowledge gaps persist, particularly regarding the identification of its competent vector. The current work presents an overview of T. haneyi virulence, transmission, diagnostics, and therapeutic gaps while pinpointing the deficits in current information necessary for advancing our understanding of the parasite’s biology. Finally, the review discusses and recommends further studies to develop effective control and surveillance strategies for T. haneyi infection. Full article

This study develops and optimizes a hybrid plant that couples a recompression sCO₂ Brayton cycle to a central-tower particle receiver with a bottoming Organic Rankine Cycle (ORC), including environmental and exergy balances. The two scenarios revealed Pareto points that raised the exergy efficiency to 0.65 in winter and reduced the fuel flow to 15 kg/s. Scenario number two achieves an overall thermal efficiency of 0.50 with total daily emissions of 2520 t CO₂ and 2850 kg NO_x, enabling nearly constant net power. Exergy destruction is concentrated in the high-temperature recuperator (HTR) and ORC turbines (27% each) and the ORC condenser (25%). Compared to a non-optimized baseline, the best solutions increased the ORC and Brayton efficiencies by 6.8–12.66% and 33.4–33.5%, respectively; cut gas-turbine power by 34% and ORC power to 10%; and lowered daily CO₂ and NO_x emissions by 52%. The gains stem from the coordinated adjustments of key levers: lower gas-turbine inlet temperature (about 10%), reduced Brayton mass flow (23%), and tuned ORC turbine inlet pressure. Full article

The oil-bearing rose (Rosa damascena Mill.), traditionally cultivated in Bulgaria for centuries, and the rose oil produced from it are of major cultural and economic importance. Its distinctive fragrance and rich aromatic profile are highly valued worldwide. In this study, a set of 15 start codon-targeted (SCoT) molecular markers was used to evaluate the genetic diversity and relationships of 38 rose accessions. The analyzed materials included Bulgarian-bred R. damascena cultivars, a locally improved population (‘Population 5’), three oil-bearing species (Rosa alba L., Rosa gallica L., and Rosa centifolia L.), Romanian heritage roses, and an unidentified rose genotype from an old Bulgarian plantation (Rosa sp.). The SCoT primers yielded a cumulative count of 238 bands, with an average of 12.9 bands per primer. The range of diversity markers, such as PIC (0.20–0.78), number of different alleles (1.5–2.00), Shannon’s information index (0.24–0.69), and gene diversity (0.15–0.50), provided evidence of genetic differences among the examined accessions. Analysis of Molecular Variance (AMOVA) revealed higher genetic variation within groups (61%) than among the groups (39%). Multivariate analyses (UPGMA, PCoA, and STRUCTURE) resolved the accessions into major genetic clusters corresponding to their taxonomic identity or breeding history. The unidentified Rosa sp. formed a distinct genetic group, showing closer affinity to R. gallica. The locally improved R. damascena ‘Population 5’ exhibited higher genetic diversity than the Bulgarian cultivars. Overall, our results demonstrate the effectiveness of SCoT markers and the value of local and traditional rose germplasm as reservoirs of genetic diversity. The study provides a molecular framework to support breeding, conservation, and sustainable management of oil-bearing rose genetic resources. Full article

The supercritical carbon dioxide (SCO₂) Brayton cycle presents a promising alternative to the traditional steam Rankine cycle, owing to its superior thermal efficiency, high power density, and compact design. As a key component governing system performance, the heat exchanger requires a highly compact and efficient design. This study proposes a novel additively manufactured (AM) wavy microchannel heat exchanger that achieves a compactness of 1670 m²/m³. The design incorporates adaptive flow channels to accommodate SCO₂’s density variation, along with wavy patterns and ribs to enhance thermal performance. A comprehensive fluid–thermal–mechanical coupling numerical analysis was conducted to evaluate its thermal–hydraulic and mechanical performance. Within the Reynolds number range of about 900–6000, the wavy structures improve the heat transfer rate by 21–58%, compared with the straight channel. The maximum effectiveness (ε = 0.66) occurs at a Reynolds number of 900. Compared with other heat exchangers used in the SCO₂ cycle, the overall performance of the hot and cold channels has improved by 12–44% and 3–89%, respectively. Structural analysis confirms that the average total stress under operating conditions remains below the yield strength of the Inconel 617 material, with thermal stress being the dominant contributor. This work underscores the potential of the proposed AM heat exchanger to deliver a superior combination of compactness, thermal–hydraulic performance, and structural integrity for advanced SCO₂ power cycles. Full article

The transition toward carbon-neutral energy systems has revived interest in nuclear technologies, particularly small and micro modular reactors (SMRs and MMRs) as flexible, safe and efficient alternatives to conventional large-scale power plans. In the Czech Republic, Centrum výzkumu Řez (CVŘ) is developing Energy Well (EW), a molten salt-cooled micro modular reactor concept employing FLiBe (Fluoride Lithium Beryllium) as primary and secondary coolant and a supercritical CO₂ (sCO₂) tertiary loop. A dedicated experimental facility was built to reproduce EW operating conditions and provide critical data on thermohydraulic behavior, fuel properties and heat-transfer mechanisms. This paper presents the development and assessment of a TRACE (TRAC/RELAP Advanced Computational Engine) model of the experimental facility, including specific methodologies for the main heater and the heat exchanger. Model accuracy was assessed through comparison with experimental commissioning data. The simulations demonstrated overall model consistency, especially regarding the heat exchanger and the main heater general performances, while some discrepancies were observed inside the main heater graphitic core. Other discrepancies were observed along the loop, mainly resulting from modeling simplifications and lack of information regarding certain experimental loop phenomena. In particular, the pressure calculation showed large inconsistencies mainly connected to the complexity of pressure measurements in molten salt circuits and the lack of specific head loss correlations. This study also helped identify broader issues in both the code (persistent error in generating CO₂ property tables and instabilities resulting from FLiBe interactions with non-condensable gases) and the experimental loop (defect in the heat exchanger filling and uncertainties on sensors location), also contributing to resolving sensor-related inconsistencies in the facility. Results confirm TRACE as a reliable tool for modeling molten salt systems, regarding the temperature distribution and the heat transfer. However, depending on the specific experimental case, this paper introduces specific limitations, such as some inconsistencies in the pressure drops distribution, in order to support the future development of TRACE code. Beyond technical advances, this work provides unique experimental data and fosters international collaboration in advancing SMR and molten salt reactor technologies. Full article