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As part of a systematic investigation into the ternary system CaO-Fe2O3-SiO2, we discovered a phase with a general chemical composition of A14O20 (where A represents Ca, Fe, and Si) and previously unknown symmetry. Synthesis experiments were conducted at 1200 °C in air with an oxide ratio of CaO:Fe2O3:SiO2 = 3:5:1 in the starting mixture. In addition to β-Ca2SiO4, and hematite (Fe2O3), powder X-ray diffraction analysis indicated the presence of compounds related to the aluminum-free counterpart of a silico-ferrite of calcium and aluminum (SFCA), one of the major bonding phases in iron ore sinter. Single crystals of this so-called SFC phase, large enough for diffraction experiments, were found in the sintered pellet fragments under a digital microscope. The compound with composition Ca2.68Fe10.32Si1.00O20 crystallizes in space group I2/c and has the following basic crystallographic data: a = 10.4643(10) Å, b = 15.2740(11) Å, c = 5.3050(5) Å, β = 110.017(9)°, V = 796.69(13) Å3 and Z = 2. The final composition, as determined by crystal structure refinement, differs slightly from the weight-specified starting mixture of Ca3Fe10SiO20 and suggests the presence of both Fe(III) and small amounts of Fe(II) in the sample. The crystal structure is related to that of the triclinic polytype-1A of SFC, but exhibits a higher degree of disorder due to the partial occupation of additional octahedrally and tetrahedrally coordinated sites. This results in a smaller unit cell and an increased space-group symmetry. The described phase can be regarded as a basic or family structure, from which the two simplest polytypes (1A and hypothetical 2M) can be derived through ordering processes of cations among different possible vacancies. The chemical similarity to one of the phases of the SFCA-family suggests that such disordered compounds could also occur in industrial sinters. [ABSTRACT FROM AUTHOR]

As part of a systematic investigation into the ternary system CaO-Fe2O3-SiO2, we discovered a phase with a general chemical composition of A14O20 (where A represents Ca, Fe, and Si) and previously unknown symmetry. Synthesis experiments were conducted at 1200 °C in air with an oxide ratio of CaO:Fe2O3:SiO2 = 3:5:1 in the starting mixture. In addition to β-Ca2SiO4, and hematite (Fe2O3), powder X-ray diffraction analysis indicated the presence of compounds related to the aluminum-free counterpart of a silico-ferrite of calcium and aluminum (SFCA), one of the major bonding phases in iron ore sinter. Single crystals of this so-called SFC phase, large enough for diffraction experiments, were found in the sintered pellet fragments under a digital microscope. The compound with composition Ca2.68Fe10.32Si1.00O20 crystallizes in space group I2/c and has the following basic crystallographic data: a = 10.4643(10) Å, b = 15.2740(11) Å, c = 5.3050(5) Å, β = 110.017(9)°, V = 796.69(13) Å3 and Z = 2. The final composition, as determined by crystal structure refinement, differs slightly from the weight-specified starting mixture of Ca3Fe10SiO20 and suggests the presence of both Fe(III) and small amounts of Fe(II) in the sample. The crystal structure is related to that of the triclinic polytype-1A of SFC, but exhibits a higher degree of disorder due to the partial occupation of additional octahedrally and tetrahedrally coordinated sites. This results in a smaller unit cell and an increased space-group symmetry. The described phase can be regarded as a basic or family structure, from which the two simplest polytypes (1A and hypothetical 2M) can be derived through ordering processes of cations among different possible vacancies. The chemical similarity to one of the phases of the SFCA-family suggests that such disordered compounds could also occur in industrial sinters. [ABSTRACT FROM AUTHOR]

NFV (Network Function Virtualization) is an innovative paradigm that seeks to improve the flexibility and efficiency of network services. NFV focuses on virtualizing network functions, allowing them to be executed on generic hardware, which decouples software and hardware and allows for more agile and scalable implementations. Through NFV, the concept of SFC (Service Function Chain) emerges, which consists of a sequence of VNFs (Virtual Network Functions), such as gateways, firewalls, and routers, arranged in an orderly manner. A critical challenge faced by SFC is its sensitivity to latency: delay increases as the chain of VNFs lengthens, which can compromise the quality of service. Minimizing this latency is crucial to ensure the efficiency of SFC systems. However, testing different SFC architectures in real environments is costly. As a solution, this study proposes using Stochastic Petri Nets (SPNs) for a performance evaluation of SFC architectures. The developed SPN model allows for analyzing different configurations of VNFs in sequential, parallel, and hybrid architectures. Four case studies were carried out exploring the behavior of the proposed model under different analyses and scenarios. The results obtained were validated through simulations in GNS3 (Graphical Network Simulator-3). The data demonstrate that changes in the SFC architecture can result in significant performance improvements and latency reduction. [ABSTRACT FROM AUTHOR]

Background: Stepwise functional connectivity (SFC) detects whole‐brain functional couplings of a selected region of interest at increasing link‐step topological distances. Objective: This study applied SFC to test the hypothesis that stepwise architecture propagating from the disease epicenter would shape patterns of brain atrophy in patients with progressive supranuclear palsy–Richardson's syndrome (PSP‐RS). Methods: Thirty‐six patients with PSP‐RS and 44 age‐matched healthy control subjects underwent brain magnetic resonance imaging on a 3‐T scanner. The disease epicenter was defined as the peak of atrophy observed in an independent cohort of 13 cases with postmortem confirmation of PSP pathology and used as seed region for SFC analysis. First, we explored SFC rearrangements in patients with PSP‐RS, as compared with age‐matched control subjects. Subsequently, we tested SFC architecture propagating from the disease epicenter as a determinant of brain atrophy distribution. Results: The disease epicenter was identified in the left midbrain tegmental region. Compared with age‐matched control subjects, patients with PSP‐RS showed progressively widespread decreased SFC of the midbrain with striatal and cerebellar regions through direct connections and sensorimotor cortical regions through indirect connections. A correlation was found between average link‐step distance from the left midbrain in healthy subjects and brain volumes in patients with PSP‐RS (r = 0.38, P < 0.001). Conclusions: This study provides comprehensive insights into the topology of functional network rearrangements in PSP‐RS and demonstrates that the brain architectural topology, as described by SFC propagating from the disease epicenter, shapes the pattern of atrophic changes in PSP‐RS. Our findings support the view of a network‐based pathology propagation in this primary tauopathy. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Chromatographic analysis of phenolic phytochemicals in foods has significantly advanced over the past decade (2014–2024), meeting increasing demands for precision and efficiency. This review covers both conventional and advanced chromatographic techniques used for detecting phenolic phytochemicals in foods. Conventional methods like High-Performance Liquid Chromatography, Ultra High-Performance Liquid Chromatography, Thin-Layer Chromatography, and Gas Chromatography are discussed, along with their benefits and limitations. Advanced techniques, including Hydrophilic Interaction Liquid Chromatography, Nano-LC, Multidimensional Liquid Chromatography, and Capillary Electrophoresis, are highlighted for their innovations and improved capabilities. The review addresses challenges in current chromatographic methods, emphasizing the need for standardized and validated procedures according to the Food and Drug Administration, European Cooperation for Accreditation of Laboratories, and The International Organization for Standardization guidelines to ensure reliable and reproducible results. It also considers novel strategies for reducing the environmental impact of chromatographic methods, advocating for sustainable practices in analytical chemistry. [ABSTRACT FROM AUTHOR]

The proposed ICH Q14 guideline "Analytical procedure development" describes science and risk‐based approaches for development and maintenance of analytical procedures suitable for the assessment of the quality of drug substances and drug products. As a case study, the systematic development and validation of a supercritical fluid chromatography (SFC)‐based purity method for carbamazepine is presented. Systematic analytical quality by design (AQbD) principles were applied using the software package Fusion QbD to the method development approach. The relationship between chromatographic parameters and the responses of interest were examined to improve the reliability of the method by understanding, reducing, and controlling sources of variability. Method performance qualification in terms of method robustness was finally carried out with the parameters that were classified as critical after method development and a validation study met previously set acceptance criteria. The developed SFC purity method for carbamazepine demonstrated readiness as a viable alternative to the official HPLC method published in the Ph.Eur. with improved peak resolution, improved peak symmetry, and faster analysis times (3 min vs. 80 min for the official method). Its inherent reliability illustrates the superiority of AQbD in method development and application for drug quality assurance. [ABSTRACT FROM AUTHOR]

Because of their performance‐enhancing effect, anabolic androgenic steroids (AAS) are often misused in sports. Nearly half of the adverse analytical findings (AAF) in 2022 doping controls are correlated to AAS misuse. Metabolites play a crucial role in the bioanalysis of endogenous and exogenous steroids. Therefore, one important field in antidoping research is the investigation on drug metabolizing and steroidogenic enzymes. The introduction of a hydroxy group is the most common reaction, which is catalyzed by cytochrome P450 (CYP) enzymes in phase‐I metabolism. Analysis of AAS metabolites is commonly performed using gas chromatography mass spectrometry (GC‐MS) systems. Laborious sample preparation and extended run times compared to liquid chromatography (tandem) mass spectrometry (LC‐MS/MS) methods are usually correlated with this type of analysis. On the other hand, liquid chromatography (tandem) mass spectrometry (LC‐MS[/MS]) methods have a lower separation efficiency than GC‐MS methods. Both techniques lack selectivity for hydroxylated 17α‐methyltestosterone metabolites. Therefore, as an orthogonal analytical approach, a supercritical fluid chromatography tandem mass spectrometry method was developed to separate four hydroxy metabolites of 17α‐methyltestosterone (2α‐/2β‐/4‐/6β‐hydroxy‐17α‐methyltestosterone). This project aimed to get a more in‐depth look at the metabolization and analysis of 17α‐methyltestosterone and its hydroxylated metabolites. The developed method revealed lower limits of quantitation between 0.6 and 6 ng/ml at an accuracy of 85–115% using a matrix matched calibration. An in vitro study with human liver microsomes shows 6β‐hydroxy‐17α‐methyltestosterone as main metabolite (15.9%) as well as the metabolite 2β‐hydroxy‐17α‐methyltestosterone (0.5%). The results show that the developed method is sensitive and robust. In addition, the method allows a previously missing discrimination of the hydroxylated metabolites in a short analysis time without prior, complex derivatizations. [ABSTRACT FROM AUTHOR]

ABSTRAK Untuk mereduksi emisi Gas Rumah Kaca (GRK), Pemerintah Indonesia mengajukan kebijakan untuk mengaplikasikan teknologi berbasis Energi Terbarukan (EBT) di PT PLN (Persero) dengan menerapkan co-firing di PLTU batubara. Untuk mengevaluasi karakteristik co-firing biomassa BBJP dilakukan pengujian dengan metode direct co-firing dan uji laboratorium untuk mendapatkan komposisi biomassa BBJP melalui Analisis Proksimat dan Analisis Ultimate. Hasil pengujian menunjukkan bahwa Gross Caloric Value (as received) dan Hardgrove Grindability Index (as received) biomassa BBJP 2646 Kcal/kg dan 20. Hasil uji arus pulverizer, pulverizer outlet temperature, AFR pulverizer mengalami peningkatan seiring kenaikan persentase biomassa BBJP dan sebaliknya untuk coal flow mengalami penurunan. Hasil uji Specific Fuel Consumption (SFC) co-firing biomassa BBJP 5% sebesar 0,58 dan NPHR 2.687 kcal/kWh. Kata kunci: co-firing, SFC, biomassa, pulverizer, Hardgrove Grindability Index ABSTRACT To reduce greenhouse gas (GHG) emissions, the Government of Indonesia has proposed a policy to apply Renewable Energy-based technology (EBT) at PT PLN (Persero) by implementing co-firing in coal-fired power plants. To evaluate the co-firing characteristics of BBJP biomass, tests were conducted using the direct co-firing method and laboratory tests to obtain the composition of BBJP biomass through Proximate Analysis and Ultimate Analysis. The test results showed that the Gross Caloric Value (as received) and Hardgrove Grindability Index (as received) of BBJP biomass were 2,646 Kcal/kg and 20. The test results of pulverizer flow, pulverizer outlet temperature, AFR pulverizer increased as the percentage of BBJP biomass increased and vice versa for coal flow decreased. Specific Fuel Consumption (SFC) test results of co-firing 5% BBJP biomass amounted to 0.58 and NPHR of 2,687 kcal/kWh. Keywords: co-firing, SFC, biomass, pulverizer, Hardgrove Grindability Index

In the analysis, design, and optimization of a wide range of engineering applications involving stretching surfaces and fluid flow, the skin friction coefficient (SFC) at a stretching surface with heat transfer is an important parameter that reflects the fluid dynamics, heat transfer characteristics, and surface interactions. Owing such importance, the purpose of present article is offer artificial neural networking remedy for evaluation of SFC for Williamson flow field with thermal slip and heat source effects. The Williamson fluid flow is realized by considering surface stretching with an externally supplied magnetic field. The energy equation is used to address the heat transmission. The constructed differential system for flow field is solved by conjecturing artificial neural networking with Lie symmetry and shooting methods. Artificial Neural Networking (ANN) model is developed to predict the surface quantity namely SFC at thermally magnetized surface. The major findings includes the variation in SFC for pertinent flow parameters and we found that in the presence of heat transfer aspects, the SFC admits declining nature towards Weissenberg number while opposite is the case for magnetic field parameter.

Microfluidic chips represent a cutting-edge technology for manipulating fluids within micrometer-scale spaces and are gradually becoming a new favorite platform in life science research. Precise and fast zonal temperature control is essential for accelerating biological experiments. However, current multi-channel temperature controllers typically rely on multiple channel sets to achieve single set-point control, which results in discrepancies between the fluid temperature distribution and sensor temperature due to the distributed temperature field in the fluid channel. To estimate the actual temperature and implement gradient temperature control, this paper introduces an extension of the target tracking (TT) two degrees of freedom (2DOF) state feedback control (SFC) method, followed by a presentation of simulation and experimental results. Through comparisons with an enhanced PID system in both simulation and experimentation, the paper demonstrates an 8.96% reduction in the maximum temperature difference across different regions and a 27.89% decrease in the time taken to reach various temperatures. This solution effectively addresses the existing challenges in temperature control for microfluidic chips, offering a more precise and stable control within the desired temperature range. [ABSTRACT FROM AUTHOR]

Auto-scaler system enables high Quality of Service (QoS) with low cost to survive in a competitive market. Indeed, the auto-scaling of Virtual Network Functionality (VNFs) can adaptively allocate the Cloud resources for various VNFs based on workload demands at any time. However, the intensity of workload is dynamically changed because of the variation in service demand over time. The predominant auto-scaling approaches use scaling rules (threshold-based reactive approach) or scaling policies (schedule-based proactive approach) to adapt resources and meet the performance requirements of each VNF. The reactive approaches can significantly degrade the VNF performance for improper reconfiguration or variation of auto-scaling rules. Conversely, the proactive approaches dynamically adjust the scaling policies according to the workload variation. These approaches rely on accurate workload predictive models (e.g., time-series models). This paper proposes a real-time proactive auto-scalar system based on a deep learning model that can efficiently predict the future values of CPU, Memory, and Bandwidth for VNFs for a Service Function Chain (SFC) to proactively auto-scale the resources allocated to each VNF in a Cloud platform. A hybrid model of MLP-LSTM is used to forecast the values of different features. Auto-correlation is used to identify the abnormal events of instances in the Cloud platform by measuring the repeated pattern for each identified impact feature. Moreover, the auto-scalar system enables to predict the abnormal values for some features during the online stage using the Auto-regression model to meet the QoS requirements of an SFC.

Due to a great demand for amylose and cellulose polymeric chromatographic chiral columns, the enantiomeric separation of thiourea derivatives of naringenin was achieved on the different amylose (Chiralpak‐IB) and cellulose chiral (Chiralcel‐OJ and Chiralcel‐OD‐3R) columns with varied chromatographic conditions. The isocratic mobile phases used were ethanol and methanol, where ethanol/hexane and methanol/hexane were used as gradient mode and were prepared in volume/volume relation. The separation and resolution factors for all the enantiomers were in the range of 1.25 to 3.47 and 0.48 to 1.75, respectively. The enantiomeric resolution was obtained within 12 min making fast separation. The docking studies confirmed the chiral recognition mechanisms with binding affinities in the range of −4.7 to −5.7 kcal/mol. The reported compounds have good anticoagulant activities and may be used as anticoagulants in the future. Besides, chiral separation is fast and is useful for enantiomeric separation in any laboratory in the world. [ABSTRACT FROM AUTHOR]

A simultaneous rapid, sensitive supercritical fluid chromatography and tandem mass spectrometry method for the separation and quantification of valsartan (VAL) and hydrochlorothiazide (HCT) is developed and validated. Separation was done in a Nucleosil (250 mm × 4.6 mm) 10 mm, Nucleosil-C18 column with acetonitrile modified supercritical fluid carbon dioxide (15 mL min–1) as mobile phase. The column temperature was 45°C and the outlet pressure was set at 17 MPa. The analytes were quantitated in negative ionization by multiple reaction monitoring (MRM) with a mass spectrometer, the mass ionizations m/z 434.2 – 350.2 and m/z 295.9 – 204.9 used to measure VAL and HCT respectively. The assay exhibited a linear dynamic range of 3.2 – 3200 ng/mL for VAL and 0.8 – 800 ng/ml for HCT. The method was validated and successfully used for simultaneous determination of drugs in tablets. [ABSTRACT FROM AUTHOR]

_ Cocoa butter is a highly prized and versatile product with a wide range of applications. It is a crucial component of chocolate due to its unique melting properties and ability to dissolve other ingredients. Therefore, it is essential to evaluate the compositional characteristics of cocoa butter from different sources to ensure its quality and authenticity. This study aimed to analyze the triacylglycerols, fatty acids, sterols, sterene compounds, extinction coefficient, and Solid Fat Content (SFC) of cocoa butter from nine diverse samples. The findings revealed that the main triacylglycerols were POP (16.07-17.74), SOS (25.73-28.91), and POS (39.12-40.25), while the primary fatty acids were palmitic (26.25-28.96), stearic (32.46-35.64), and oleic acids (31.51-32.47). The dominant sterols were (55.04-56.98 %), stigmasterol (25.4-26.2 %), and campesterol (9.22-10.53 %), with the ratio of stigmasterol to campesterol (2.5 to 2.7) serving as an indicator of authenticity. The study also found minimal levels of stigmastadiene (0.0001–0.0039 ppm), indicating low oxidation products, and measured the SFC content at different temperatures. Overall, this comprehensive analysis provides valuable insights into the composition of cocoa butter from various sources, offering important information for quality control and detection of adulteration.

The advent of Network Function Virtualization (NFV) technology has brought flexible provisioning to Fog–Cloud Computing-based Networks (FCCNs) for enterprises to outsource their network functions to data center networks. Service Function Chaining (SFC) is a networking concept in NFV by which traffic is steered through an ordered set of Virtual Network Functions (VNFs) composing an end-to-end service. When hundreds of users outsource their network functions to FCCN, the optimal placement of VNFs in the network becomes important for assembling SFCs with the aim of resource utilization efficiency. Motivated by the scalability shortcomings of existing schemes, we propose Deep Reinforcement Learning (DRL)-based approaches by simultaneously considering parallelized SFC and reuse of VNFs to solve this problem, i.e., Asynchronous Advantage Actor–Critic (A3C). A parallelized SFC consists of several sub-SFCs, which can reduce delay and guarantee availability. Also, reuse of preliminary VNFs in SFC placement can improve computation acceleration. The proposed scheme pursues the maximization of the long-term cumulative reward for the trade-off between Quality of Service (QoS) and service cost. The results of the experiments show that the proposed scheme performs better than the state-of-the-art methods.

This study presents a comprehensive exploration of the performance of a proposed controller within dynamic system contexts. The controller is rooted in Model Reference Adaptive Control (MRAC) and State Feedback Controller (SFC) techniques, offering a robust approach tailored specifically for Series Elastic Actuators (SEAs). This hybrid technique aims to overcome system uncertainties and attenuate load disturbances, thereby enhancing system performance and stability. Lyapunov stability analysis is employed to derive the adaptation mechanism, ensuring both the stability and efficacy of the controller. Additionally, the controller can be fine-tuned using a parameter, b. The study thoroughly analyzes the impact of this tuning parameter on suspension response. Through systematic simulations, an optimal value of is identified, and the controller's performance is investigated in terms of achieving the desired output with minimal settling time and control torque. At b = -80, the results demonstrate that the proposed controller efficiently achieves input tracking with a settling time of 1.95 seconds and a control torque reaching 7.39 Nm. The investigation extends to parameter uncertainties, highlighting the controller's adaptability to variations and showcasing its ability to proportionally adjust torque in response to parameter changes. Furthermore, the controller's resilience is validated under load disturbances, effectively demonstrating its capability to mitigate torque fluctuations and maintain desired angular positions. The results also indicate that the unit step disturbance causes a 49.9% increase in control torque, while the sinusoidal disturbance causes a 25% increase in control torque. Overall, this study underscores the controller's versatility, efficacy, and adaptive nature, positioning it as a valuable asset in the realm of SEA control applications. [ABSTRACT FROM AUTHOR]

The paper compares stock-flow consistent (SFC) versions of extended canonical neo-Kaleckian and Supermultiplier models that deal with either households' or firms' debt accumulation. This comparison aim is twofold: (i) to evaluate the differences of a debt accumulation process in these models due to their specific closures; (ii) to provide a pedagogical tool for understanding the basic features of each model when dealing with similar issues. In the short run, we find that the relation of debt ratios, demand and growth is similar for both models. In the long run of the Supemultiplier model, only the Minskyan debt regime is economically viable for the firms' sector. As for the household sector, the paradox of debt is indeed a feature of the canonical Supermultiplier model, yet there may be episodes of rising debt-toincome ratios. As for the neo-Kaleckian model, firms' leverage ratio can be either pro- or anti-cyclical; in the household sector, the absence of the paradox of debt seems to be the most likely scenario. [ABSTRACT FROM AUTHOR]

Cocoa butter is a highly prized and versatile product with a wide range of applications. It is a crucial component of chocolate due to its unique melting properties and ability to dissolve other ingredients. Therefore, it is essential to evaluate the compositional characteristics of cocoa butter from different sources to ensure its quality and authenticity. This study aimed to analyze the triacylglycerols, fatty acids, sterols, styrene compounds, extinction coefficient, and Solid Fat Content (SFC) of cocoa butter from nine diverse samples. The findings revealed that the main triacylglycerols were POS (39.12-40.25), SOS (25.73-28.91) and POP (16.07-17.74) while the primary fatty acids were stearic acid (32.46-35.64), oleic acid (31.51-32.47) and palmitic acid (26.25-28.96) The dominant sterols were (55.04-56.98 %), stigmasterol (25.4-26.2 %), and campesterol (9.22-10.53 %), with the ratio of stigmasterol to campesterol (2.5 to 2.7) serving as an indicator of authenticity. The study also found minimal levels of stigmastadiene (0.0001–0.0039 ppm), indicating low content dehydrated sterols, and measured the SFC content at different temperatures. Overall, this comprehensive analysis provides valuable insights into the composition of cocoa butter from various sources, offering important information for quality control and detection of adulteration. [ABSTRACT FROM AUTHOR]

Zopiclone (ZOP) is a hypnotic drug prescribed to treat insomnia. Due to the chiral nature of ZOP, the psychologically active S‐form and inactive R‐form need to be determined enantiomerically in a forensic drug analysis. In the present study, a supercritical fluid chromatography (SFC) method was designed with a faster analysis ability than that of previously reported techniques. The SFC–tandem mass spectrometry (SFC–MS/MS) method was optimized using a column with a chiral polysaccharide stationary phase (Trefoil CEL2). ZOP was extracted from pooled human serum using solid‐phase extraction (Oasis HLB) and analyzed. The developed SFC–MS/MS method achieved the baseline separation of S‐ZOP and R‐ZOP within 2 min. The fit‐for‐purpose method validation indicated that the optimized solid‐phase extraction achieved near complete recovery and approximately 70% of the matrix effect. Both the retention time and peak area showed sufficient precision. The lower and upper limits of quantification (LOQ) were 5.7 × 10−2 ng/mL and 25 ng/mL for R‐ZOP, and 5.2 × 10−2 ng/mL and 25 ng/mL for S‐ZOP. The calibration line was linear in the range from lower LOQ to upper LOQ. The stability test indicated that ZOP in serum stored in a refrigerator (4°C) degraded and about 55% remained in 31 days. The quick analysis of the SFC–MS/MS method makes it a valid option for the enantiomeric analysis of ZOP. [ABSTRACT FROM AUTHOR]

In this paper, we report our progress on integrating a model‐based system engineering methodology with a system architectural trade study applied to flight control systems of a locally owned and operated, cost effective Unmanned Aerial Vehicles (UAV) design utilizing the concepts of Model‐Based Systems Architecture Processes (MBSAP). The primary objective of the UAV is to monitor wildfires and to gather information and to provide surveillance data for predicting and preventing wildfires [1]. We describe our experience with a holistic approach to architect flight controls (the System‐of‐Interest), in a way that is tightly coupled with high‐level stakeholder needs and concerns, operational scenarios, (normal, inadvertent, and mis‐) use cases, Context System, and Enabling Systems. Several architectural variants of the Surface‐less Flight Controls (SFC) were traded. Our systemic approach showed that classical flight controls are feasible for the baseline UAV. It also helped us identify a novel architecture with a potential to drastically improve UAV performance (range, survey time), UAV weight, and specific cost. Our approach has resulted in an architecture that has the potential to significantly reduce the costs of manufacturing as well as operating UAVs, at the same time it drastically improves their performance. This development could mean widely increased availability and improved effectiveness of UAVs in fire detection and prevention. [ABSTRACT FROM AUTHOR]

Chromatography and mass spectrometry based techniques are the most commonly employed procedures to quantitate the analytes in pharmaceutical research. However, sensitivity of analytical methods significantly varies due to the difference in physicochemical characteristics of analytes. Sensitivity of methods greatly affects the quality of analytical results. Establishment of a sufficiently sensitive method ensures the suitability of a technique for its intended purpose. Although various types of advancement in chromatographic science are witnessed, issues related to sensitivity remain a major challenge for the analyte with low detection limit. Highly sensitive analytical methods are specifically essential to quantitate the analytes in the samples from dissolution study of sustained release formulations, cross-contamination study, impurity analysis, metabolite profiling, bioanalysis of highly potent and low bioavailable drugs. In recent years, huge involvement of researchers toward sensitivity enhancement of quantitative methods is evidenced. Wide verities of approaches are being reported in the field. Derivatization technique, introduction of ion-pairing reagents, sample pretreatment, and utilization of innovative methods such as 2-dimensional liquid chromatography, nano liquid chromatography, 2-dimensional gas chromatography, supercritical fluid chromatography, use of microcolumn are some approaches that are being employed. Online sample preparation techniques can significantly improve the sensitivity of a method by reducing sample loss and degradation. This review summarizes and critically discussed the approaches to improve the sensitivity of chromatographic and mass spectrometry based analytical methods. This article can guide the researchers to select suitable approaches for achieving the desired detection limit of analytical and bioanalytical methods based on their specific requirements. [ABSTRACT FROM AUTHOR]

Mobile Edge Computing (MEC) is a well-known network architecture that extends cloud computing to the network edge. Compared with cloud computing, Network Function Virtualization (NFV) can provide flexible services in MEC for mobile users. Virtual Network Functions (VNFs) have emerged as software-based hardware middleboxes by NFV technology to host real-time applications. Basically, the combination of multiple VNF instances is defined as a Service Function Chain (SFC), which can provide dynamic service requirements in the MEC. Despite the rapid growth of MEC and the widespread support of service providers for SFC, many issues are still challenging and need to be addressed. In MEC scenarios with limited resources, the effective placement of SFCs with the aim of resource efficiency remains a challenging problem. Motivated by the scalability shortcomings of existing schemes to solve dynamic placement of SFCs, we propose Deep Reinforcement Learning (DRL)-based approaches to solve this problem, i.e., Asynchronous Advantage Actor-Critic (A3C). The proposed scheme is based on the reuse of initialized VNFs to improve the Quality of Service (QoS), which is developed with the aim of maximizing the long-term cumulative reward. In addition, a parallel processing approach of SFCs is included in the proposed scheme, which can split the traffic in each flow into sub-flows. This shares the processing load by instantiating duplicate instances of each VNF type in the SFC. The simulation results guarantee the efficiency of the proposed scheme and improves the average performance between 6% and 24% compared to the state-of-the-art clustering methods.

The characterization of any compound is important in the field of chemistry. As the field of cannabinoid chemistry grows so does the need for the characterization of new cannabinoids or rare cannabinoids that gain popularity within the consumer and research fields. Hexahydrocannabinol (HHC) a hydrogenated analogue of Δ9-tetrahydrocannabinol (THC), also found in trace amounts naturally within the Cannabis sativa plant, has been gaining attention and popularity within the cannabis industry. Hexahydrocannabidiol (H4CBD) is a synthetic hydrogenated analogue to cannabidiol (CBD). Identifying the diastereomers of the cannabinoids with instrumentation plays a huge role within the chemistry field adding valuable information of the structure and the parameters for others to identify such cannabinoids. Elucidation and characterization of HHC and H4CBD were performed using current analytical techniques such as 1D and 2D nuclear magnetic resonance (NMR), high performance liquid chromatography (HPLC), and gas chromatography-mass spectrometry (GC-MS), effectively characterizing both the diastereomers of HHC and H4CBD. [ABSTRACT FROM AUTHOR]

The enantioselective potential of two macrocyclic glycopeptide-based chiral stationary phases for analysis of 28 structurally diverse biologically active compounds such as derivatives of pyrovalerone, ketamine, cathinone, and other representatives of psychostimulants and antidepressants was evaluated in sub/supercritical fluid chromatography. The chiral selectors immobilized on 2.7 μm superficially porous particles were teicoplanin (TeicoShell column) and modified macrocyclic glycopeptide (NicoShell column). The influence of the organic modifier and different mobile phase additives on the retention and enantioresolution were investigated. The obtained results confirmed that the mobile phase additives, especially water as a single additive or in combination with basic and acidic additives, improve peak shape and enhance enantioresolution. In addition, the effect of temperature was evaluated to optimize the enantioseparation process. Both columns exhibited comparable enantioselectivity, approximately 90% of the compounds tested were enantioseparated, and 30% out of them were baseline enantioresolved under the tested conditions. The complementary enantioselectivity of the macrocyclic glycopeptide-based chiral stationary phases was emphasized. This work can be useful for the method development for the enantioseparation of basic biologically active compounds of interest. [ABSTRACT FROM AUTHOR]

• First development of nanospray supercritical fluid chromatography-MS. • Rapid separation of positional isomers in unsaturated fatty acids. • Changes to fatty acid levels upon pharmacological inhibitors in mammalian cell culture. A nanospray emitter coupled to a supercritical fluid chromatograph (SFC-nSI-MS) for mass spectrometric (MS) analysis of fatty acids (FA) positional isomers is introduced. The experimental setup uses conventional bore columns before the SF back-pressure regulator (pre-BPR). The flow is then split and nanosprayed using a short emitter post-BPR. A C18 column was used to resolve positional isomers of unsaturated FA with a 5 min gradient. Chromatographic resolution of the nSFC was compared to a LC-MS system with superior resolving power demonstrated in the nSFC MS system. This system has proven quantitative performance for analyzing pharmaceutical effects on FA composition in a complex biological matrix like E coli l ysate. [ABSTRACT FROM AUTHOR]

Software-defined networks and network function virtualization can effectively solve the problems of difficult management and control of large-scale networks and diffi culties in resource scheduling.Applying the software-defi ned network architecture model and network function virtualization technologies to the large-scale satellite internet can eff ectively solve some problems.This paper proposed a new SDN/NFV-based new satellite internet architecture, different satellite domains could be responsibled for different functions, inter-satellite and inter-domain could used SDN and NVF for eff ective collaboration, effi cient used of network resources, research and optimization of its service function resource allocation technology after VNF deployment, a simulated annealing algorithm based on resource awareness was proposed.Simulation results showed that this algorithm could effectively reduced the end-to-end delay and bandwidth consumption of SFC data fl ow during transmission, and could provided users with better services.

The pumps in RHPP Bajina Bašta are started via a static frequency converter (SFC). This resulted in increased level of higher harmonics within the RHPP. However, it was not known whether the operation of this SFP could endanger the consumers supplied from the mentioned RHPP via the distribution transformer. For this purpose, it is necessary to check the possibilities of the existence of a parallel resonant circuit, both in the RHPP itself, and in the part of the distribution network that was of interest. Analyzes were performed in the linear simulation model created in the DIgSILENT PowerFactory software package. The simulation model was created so that it corresponds to the state of minimum load of the distribution area supplied by TS Metaljka. Also, several variants were analyzed in TS Đurići (depending on the number of motor engines in operation). The results show the existence of parallel resonant circuit in the vicinity of the 13th harmonic at the level of 10 kV busbars in TS Metaljka, while its existence was not identified at the transmission system busbar, which is in accordance with the measurements

Abstract Background Genetic variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began to emerge in 2020 and have been spreading globally during the coronavirus disease 2019 (COVID-19) pandemic. Despite the presence of different COVID-19 vaccines, the discovery of effective antiviral therapeutics for the treatment of patients infected with SARS-CoV-2 are still urgently needed. A natural amino acid, 5-aminolevulinic acid (5-ALA), has exhibited both antiviral and anti-inflammatory activities. In a previous study, we demonstrated an in vitro antiviral effect of 5-ALA against SARS-CoV-2 infection without significant cytotoxicity. In the present study, we sought to investigate whether 5-ALA with or without sodium ferrous citrate (SFC) can inhibit in vitro both the original SARS-CoV-2 Wuhan strain and its variants, including the Alpha, Beta, Gamma and Delta strains. Methods The antiviral activity of ALA with or without SFC was determined in Vero-E6 cell. The virus inhibition was quantified by real time RT-PCR. Results Co-administration of 5-ALA and SFC inhibited the Wuhan, Alpha and Delta variants of SARS-CoV-2 with IC50 values of 235, 173 and 397 µM, respectively, and the Beta and Gamma variants with IC50 values of 1311 and 1516 µM. Conclusion Our study suggests that 5-ALA with SFC warrants accelerated clinical evaluation as an antiviral drug candidate for treating patients infected with SARS-CoV-2 variants.

Network Function Virtualization (NFV) can support customized on- demand network services with flexibility and cost-efficiency. Virtual Network Function (VNF) instances need to be scaled out, scaled in, and reallocated across the NFV infrastructure (NFVI) to avoid a violation of service agreements when the demand traffic changes. However, selecting the new placement of VNFs for migrating a service function chain (SFC) is an issue of efficient NFV control. We propose two novel integer linear programming (ILP) models and two approximation algorithms for SFC placement and migration to maximize the cost-efficiency of an NFV network regarding the changes of service demands and dynamic routing. The ILP models allow us to obtain the optimal solutions of SFC placement and migration with explicit dynamic paths. The approximation migration results provided by our proposed heuristic and reinforcement learning algorithms are close to the optimal solution. Evaluation results carried out with real datasets and synthetic network topologies provide a helpful suggestion of a migration strategy for an NFV service provider to optimize the operating cost of an NFV network in the long term.

The service function chain (SFC) routing has been increasingly associated with multi-domain networks. However, several multi-domain SFC routing issues, linked to cross-domain interactions and emphasized by the heterogeneity of substrate topologies and administrative authorities, present a challenge. We propose the Cooperative Multi-agent Reinforcement Learning (CMRL) based algorithm for multi-domain SFC routing problem. Simulations on the real-world network topology demonstrate that our proposal can provide more than two and four times reduction in terms of the run time and network resource cost, respectively. [ABSTRACT FROM AUTHOR]

WHO is searching most active antibiotics due to the bacterial resistance problem. The activities of the racemic antibiotics may be augment by preparing optically active antibiotics by the chiral separation. Chiral separation of potential antibiotics such as cefotaxime and ofloxacin was studied using amylose‐based packing chiral stationary phases (CSPs) such as Chiralpak IA and Chiralpak IG. Supercritical fluid chromatography (SFC) was employed to carry out this study. Both immobilized CSPs such as Chiralpak IA and IG have sown remarkable selectivity for the reported drugs by using SFC. The values of retention factor (k) for ofloxacin enantiomers were 9.63 and 11.81, followed by 2.94 and 5.96 for cefotaxime enantiomers. The values of separation factor (α) for both the reported drugs were 1.22 and 2.03, respectively Similarly, the values of resolution factor (Rs) for both the enantio‐selective drugs were 1.49 and 2.06, separately and respectively. The chiral recognition mechanism was developed and it was observed that the π‐π interactions are playing a major role. The developed method is effective, reproducible, eco‐friendly, and may be used to discriminate the enantiomers of the reported drugs in any sample. [ABSTRACT FROM AUTHOR]

Free and esterified (bound) tocopherols, tocotrienols and other tocochromanol-related compounds, often referred to "tocols", are lipophilic antioxidants of great importance for health. For instance, α-tocopherol is the only tocochromanol with vitamin E activity, while tocotrienols have a positive impact on health and are proposed in the prevention and therapy of so-called modern diseases. Tocopherols, tocotrienols and plastochromanol-8 are the most well-known tocochromanols; in turn, knowledge about tocodienols, tocomonoenols, and other rare tocochromanol-related compounds is limited due to several challenges in analytical chemistry and/or low concentration in plant material. The presence of free, esterified, and non-extractable tocochromanols in plant material as well as their biological function, which may be of great scientific, agricultural and medicinal importance, is also poorly studied. Due to the lack of modern protocols as well as equipment and tools, for instance, techniques suitable for the efficient and simultaneous chromatographical separation of major and minor tocochromanols, the topic requires attention and new solutions, and/or standardization, and proper terminology. This review discusses the advantages and disadvantages of different chromatographic techniques, tools and approaches used for the separation and detection of different tocochromanols in plant material and foodstuffs. Sources of tocochromanols and procedures for obtaining different tocochromanol analytical standards are also described. Finally, future challenges are discussed and perspective green techniques for tocochromanol determination are proposed along with best practice recommendations. The present manuscript aims to present key aspects and protocols related to tocochromanol determination, correct identification, and the interpretation of obtained results. [ABSTRACT FROM AUTHOR]

A local scale Aerothermodynamic Generic Cycle Model (AGCM) is proposed. The AGCM accounts for several improvements not considered in similar models, such as compressor bleed extraction for aircraft Environmental Control System (ECS), parasitic shaft power extraction, and the enthalpy of the fuel entering the combustor. The AGCM is intended for steady-state Design Point (DP) and Off-Design (OD) performance analyses. The underlying physics is presented for the DP model. The turbomachinery component maps scaling and the system of nonlinear equations necessary to define the OD model are thoroughly discussed. The AGCM is compared with an equivalent model developed in the Numerical Propulsion System Simulation (NPSS). The comparisons were performed considering a DP envisioned to approximate a General Electric CF34-8C5B1 engine. The average errors found in these comparisons for the Specific Fuel Consumption (SFC) and net thrust were −0.111% and 0.193%, respectively. Finally, the predictions of the absolute levels of performance intended for the -8C5B1 engine are compared with empirical correlations derived from a comprehensive turbofan engine database. It was found that the predictions of the AGCM are in agreement with the empirical correlations; the errors found in SFC and net thrust at cruise flight condition were −0.43% and 2.06%, respectively. [ABSTRACT FROM AUTHOR]

The simultaneous separation of the enantiomers of six anticoagulant rodenticides, derived from 4-hydroxycoumarin, has been studied in this work. Ten different stationary phases (zwitterionic, Pirkle-type, polysaccharides and macrocyclic antibiotics derivatives) were evaluated by using supercritical fluid chromatography coupled to two different detectors (circular dichroism and mass spectrometry-single quadrupole). The effect of the type of organic modifier and temperature on the chiral separation was investigated, and the best results were obtained with the column Regis S,S-Whelk-O1 at 25 °C when using a gradient elution program with methanol as organic modifier. Considering detection, the highest sensitivity was obtained with the single quadrupole mass spectrometry detector. Under these conditions, eighteen stereoisomers were baseline resolved within 18 min. It should be also mentioned that the columns Chiralpak AS-H, Lux Cellulose-2, Chiralpak AD and Chiralpak Zwix (+) provided also good results for the enantiomeric separation of some individual compounds., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

This study evaluates the effectiveness of five types of Granular Activated Carbon (GAC) and one anion exchange resin in a pilot plant for treating groundwater for drinking water production, specifically targeting the removal of persistent compounds like PFAS. Using liquid chromatography and supercritical fluid chromatography coupled with high-resolution mass spectrometry, hundreds of features (i.e. peak at specific mass and retention time) were detected in the groundwater by non-target analysis. Initially, after treating <3200 bed volumes (BV), the GAC filter materials showed < 6 % breakthrough for all features from the groundwater, with decreasing efficiency down to 79 % breakthrough after seven month (69,000 treated BV for µGAC). Using resin as a lag filter after GAC did not improve the removal of compounds detected in positive electrospray ionization mode. However, it enhanced removal by up to 35% for compounds detected in negative electrospray ionization mode, indicating higher selectivity of resin for acidic compounds like PFAS. The shortest detected PFAS (PFBA and PFPeA) broke through completely for all GAC and the resin material except the proprietary blended GAC (at 15,700 treated BV), which had only 19% breakthrough for PFPeA. The so far rarely detected perfluoro(4-ethylcyclohexane)sulfonic acid (PFECHS) was well adsorbed by GAC coupled to resin and by the proprietary blended GAC. Pesticides were effectively removed by GACs, but not by the resin filter. Contaminants not previously detected in groundwater, 2,4,5-trichlorobenzenesulfonic acid (TCBS) and 2-amino-4-chloro-5-methylbenzenesulfonic acid (ACMBS), were effectively removed (>92 %), but high ACMBS concentrations (360 ng/L) in groundwater are of concern. The drinking water after the resin filter revealed 20 new contaminants, such as tributylamine derivatives and monobutyl phthalate, indicating resin filters contribution to drinking water contamination. Accelerated migration experiments of the resin revealed additional contaminants, such as NDBA and further phthalates, highlighting the need for continued monitoring and evaluation of resin materials in water treatment systems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Pembangkit Listrik Tenaga Gas (PLTG) merupakan pembangkit dengan keunggulan waktu pengoperasian yang singkat dengan daya pembangkitan relatif besar. Dibalik kecepatan pembangkit tersebut untuk dioperasikan terdapat kelemahan yaitu tingkat efisiensi pembangkit yang tergolong rendah atau boros dalam penggunaan bahan bakar. Pada saat proses pengoperasian pembangkit di industri sering terjadi perubahan permintaan pasokan beban, untuk memenuhi permintaan tersebut pembangkit harus siap tertutama dalam ketersediaan bahan bakar. Permasalahan yang terjadi adalah PLTG tidak bisa dibebani daya maksimal karena sumber bahan bakarnya juga digunakan untuk bahan baku proses pokok industri. Penelitian ini bertujuan untuk mencari variasi temperatur inlet PLTG dengan besar nilai heat rate dan spesific fuel consumption (SFC) pada pola operasi PLTG yang paling optimal. Selanjutnya melakukan analisis keterkaitannya dengan efisiensi bahan bakar yang bisa dihemat di objek yang diteliti. Hasilnya dengan 39,7 % pembukaan katup gas dan temperatur masuk udara sebesar 30oC dan tekanan kompresi 7 bar menghasilkan nilai paling optimum dengan nilai SFC 0,627dan heat rate 8059.663 kcal/kWh. Pembukaan katup gas lain yaitu sebesar 42,9% pembukaan katup gas dan temperature masuk udara sebesar 30oC dan tekanan kompresi 7 bar menghasilkan nilai paling baik yaitu SFC 0.654 dan heat rate 8408.248 kcal/kWh.

Abstract The coronavirus disease 2019 (COVID 19) pandemic continues to pose a threat to global health. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant (B.1.1.529) has spread rapidly worldwide and became dominant in many countries. A natural 5-aminolevulinic acid (5-ALA) with sodium ferrous citrate (SFC) has demonstrated antiviral activity in Wuhan, Alpha, Beta, Gamma, and Delta variants of SARS-CoV-2 infections in vitro. In this study, we report antiviral activity of 5-ALA, 5-ALA with SFC led to IC50 of 329 and 765/191, respectively after infection with Omicron variant of SARS-CoV-2 in vitro. Our finding suggests that 5-ALA could be used as antiviral drug candidate to treat Omicron variant infected patients.

In today’s datacenters (DCs), IT resources virtualization is leveraged to realize Network Function Virtualization (NFV) over general-purpose servers. Meanwhile, most of the service providers (SPs) are planning to use Virtual Network Functions (VNFs) to provide agile and flexible network services. In service provisioning, the VNF selection and mapping greatly affect IT resource utilization in DCs and spectrum resource utilization in optical networks. This paper proposes a Deep Reinforce Learning (DRL)-based algorithm for VNF provisioning. By selecting appropriate VNFs for the service requests, the algorithm intelligently guarantees efficient reusing of deployed VNFs while consuming fewer spectrum resources in inter-DC elastic optical networks (EONs). To facilitate the decision-making of the DRL agent, we first decompose the complex VNF-based service chaining (VNF-SC) into several VNF components (VNFCs), which can be solved one-by-one in turn. Then, a feature matrix-based encoding scheme is designed to represent the set of the VNFCs, the available DCs for the VNFCs, and the VNFC being operated, i.e., the input of neural networks. In addition, considering the complexity and difficulty of the VNF-SC provisioning problem, Double Deep Q Network (DDQN) is introduced in the proposed algorithm. Finally, compared with the benchmark heuristics, the extensive simulation results in different network topologies show that the proposed algorithm can reduce the IT and spectrum resource consumption by at least 9.6% and 1.6%, which proves the effectiveness of the proposed DRL-based VNF provisioning algorithm. [ABSTRACT FROM AUTHOR]

Fat crystallisation in emulsions is a complex process. One of the important parameters is the solid fat content (SFC). Up to now, there is no standardised method to measure the SFC in emulsions, let alone to determine the SFC of the fat inside droplets, thus avoiding the signal of the aqueous phase. This work evaluates the capabilities of deconvolution of the free induction decay (FID)‐Carr–Purcell–Meiboom–Gill (CPMG) signal of emulsions. Three models were evaluated. The first model was a combination of a Gaussian function and a bi‐exponential function (GBE model). The second model combined a Gaussian function with multiple exponential functions (GME model). The last model contained multiple Gaussian functions and multiple exponential functions (MGME model). The latter two models used a simplified CONTIN analysis. Based on the analysis of the determination coefficient R2, the calculated water content and the estimated SFC of nonemulsified two‐phase systems, the GBE model was selected to analyse the FID‐CPMG signal of emulsified systems. However, the results obtained with the other models did not differ substantially, and hence, they could be used to obtain a full relaxation time distribution. When the GBE model was applied on different emulsion systems, no significant differences in estimated SFC of the fat phase were found, thus indicating that the emulsion formulation (i.e. water‐in‐oil [W/O], oil‐in‐water [O/W] or water‐in‐oil‐in‐water [W/O/W]) only had a minor effect on the SFC in the systems considered here. [ABSTRACT FROM AUTHOR]

The enantioseparation of syn- and anti-3,5-disubstituted hydantoins 5a–i was investigated on three immobilized polysaccharide-based columns (CHIRAL ART Amylose-SA, CHIRAL ART Cellulose-SB, CHIRAL ART Cellulose-SC) by high performance liquid chromatography (HPLC) using n-hexane/2-PrOH (90/10, v/v) or 100% dimethyl carbonate (DMC) as mobile phases, respectively, and by supercritical fluid chromatography (SFC) using CO2/alcohol (MeOH, EtOH, 2-PrOH; 80/20, v/v) as a mobile phase. The chromatographic parameters, such as separation and resolution factors, have indicated that Amylose-SA is more suitable for enantioseparation of the most analyzed syn- and anti-3,5-disubstituted hydantoins than Celullose-SB and Cellulose-SC in both HPLC and SFC modalities. All three tested columns showed better enantiorecognition ability toward anti-hydantoins compared to syn-hydantoins, both in HPLC and SFC modes. We have demonstrated that environmentally friendly solvent DMC can be efficiently used as the mobile phase in HPLC mode for enantioseparation of hydantoins on the immobilized polysaccharide-based chiral stationary phases. [ABSTRACT FROM AUTHOR]

The determination and separation of enantiomers is an interesting and important topic of research in various fields, e.g., biochemistry, food science, pharmaceutical industry, environment, etc. Although these compounds possess identical physicochemical properties, a pair of enantiomers often has different pharmacological, toxicological, and metabolic activities. For this reason, chiral discrimination by using chromatographic and electromigration techniques has become an urgent need in the pharmaceutical field. This review intends to offer the “state of the art” about the separation of chiral antifungal drugs and several related precursors by both liquid and gas chromatography, as well as electromigration methods. This overview is organized into two sections. The first one describes general considerations on chiral antifungal drugs. The second part deals with the main analytical methods for the enantiomeric discrimination of these drugs, including a brief description of chiral selectors and stationary phases. Moreover, many recent applications attesting the great interest of analytical chemists in the field of enantiomeric separation are presented.