Low Standard Deviation Values Research Articles

Design, modelling and optimisation of ultra high-performance fibre reinforced concrete incorporating waste materials

The adoption of ultra-high-performance fibre-reinforced concrete (UHPFRC) in modern-day construction has gradually increased because of its high compressive and flexural strength at the early production ages. The UHPFRC's high initial cost discourages its production and widespread use. This cost can be reduced by incorporating waste materials in UHPFRC production. This study aims to design, model, and optimise a three-day heat-cured UHPFRC incorporating waste materials. To produce a sustainable UHPFRC mixture, this study combines rice husk ash (RHA) and recycled tire steel fibre (RTSF) as the primary waste components, with Portland limestone cement, river sand, superplasticizer, and water. The concrete is heat-cured in a hot water bath at 90 °C for 3 days, resulting in rapid strength development. A D-optimal mixture design technique was used to optimise the mix proportions, and mathematical models were developed to predict the compressive and flexural strengths. The non-significant lack-of-fit results and the high values of coefficient of determination (R2) revealed the accuracy of the models in predicting the compressive and flexural strengths of the UHPFRC. The low values of standard deviation (SD) and coefficient of variation (CV) confirmed the consistency and reliability of the prediction models. A numerical optimisation revealed that it is possible to design a UHPFRC mixture with a lower cement content of 38.29% of the UHPFRC mix, resulting in a compressive strength of 117.62 MPa and a flexural strength of 36.32 MPa. The study reveals that integrating RHA and RTSF into UHPFRC can yield high-performance properties, offering innovative solutions for resource scarcity and environmental sustainability in the construction sector.

Stochastic modeling of periodic beams under uncertain boundary conditions and environmental fluctuations

Periodic structures have been attracting a great deal of academic and industrial interest lately, due to their distinctive vibration and wave propagation behavior, which can be explored for the development of innovative solutions to structural dynamics and vibroacoustic problems. Although such a potential has been demonstrated in a large number of studies, the investigation of detrimental effects, which can be present in practical applications, is still necessary. This paper reports investigations on the combined influence of uncertainties affecting ambient temperature — which alters material properties and induces stress-stiffening due to constrained thermal dilatation — and boundary conditions (BCs) on the bandgap characteristics of periodic beams. The space-dependent temperature fluctuations are represented as a one-dimensional stationary Gaussian random field, discretized using the Karhunen-Loève expansion, while non-ideal BCs, represented as springs, are modeled as discrete random variables. Sampling-based stochastic analyses of the central frequency and bandwidth of the beam’s attenuation bands are performed using Monte Carlo simulations. The results demonstrate that the variability in the attenuation band features is influenced not only by the coefficients of variation (CVs) of the input random quantities, but also by the correlation length of the random temperature fluctuations. Numerical simulations reveal that the bandgap central frequency is primarily affected by the temperature random field, while the BCs govern the bandwidth. Although low CV and standard deviation values are obtained for the dispersion of the bandgap features, reliability analyses indicate that some designs exhibit low reliability. Increased variability in both the bandgap central frequency and bandwidth is observed for greater temperature correlation lengths and CVs. The contributions of the study include the proposal of a comprehensive stochastic modeling procedure duly accounting for relevant random influences, and evidencing that those influences can be significant, requiring consideration in the design of robust periodic structures.

Binary aqueous solutions of choline salts: Determination and modelling of liquid density (298.15 or 313.15 K) and Vapour Pressure Osmometry (313.15 K)

Salts composed of the cholinium cation (such as choline hydroxide and choline chloride) have become one of the main reactants for the synthesis of greener ionic liquids, but, for a proper description of the aqueous solutions of these strong electrolytes by thermodynamic modelling, reliable data on liquid density (ρ) and vapour pressure (p) are needed, which are often unavailable. So, in this work, the liquid density (ρ) of binary aqueous solutions of choline bicarbonate ([Ch][Bic]), choline (2R,3R)-bitartrate ([Ch][Bit]), choline chloride ([Ch]Cl), choline dihydrogen citrate ([Ch][H2Cit]) and choline hydroxide ([Ch]OH) were measured at 298.15 or 313.15 K and 0.1 MPa and correlated using second-degree polynomials with salt molality (m), obtaining determination coefficients (R2) higher than 0.9974. Furthermore, the osmotic coefficients (ϕ) of these binaries were determined using vapour pressure osmometry (VPO), at 313.15 K and 0.1 MPa, being satisfactorily described by the Extended Pitzer Model of Archer, which yielded low values of standard deviation (3.58<σϕ·103<12.86). Then, the mean molal activity coefficients (γ±) and excess Gibbs free energies (GE/RT) were calculated, following the order [Ch][H2Cit] > [Ch][Bit] > [Ch][Bic] > [Ch]OH > [Ch]Cl, which corresponds to the decreasing polarity of the choline salts and agrees with the empirical law of matching water affinities (LMWA).

Monitoring Soil Temperature and Humidity in an IoT-Based Green House to Improve Plant Management

This study aims to develop and validate a soil temperature and humidity monitoring system using DHT 11 and YL 69 sensors connected to an ESP 8266 microcontroller. Calibration was performed by comparing sensor data with a reference instrument, followed by regression analysis to determine sensor accuracy. Validation involved calculating the standard deviation and accuracy of the sensor measurements. Temperature and soil humidity monitoring was conducted over five days in September, with average temperature measurements ranging from 22.4°C to 32.6°C and soil humidity ranging from 66.47% to 88.78%. The results showed that the temperature sensor had an average accuracy of 99.19%, while the humidity sensor had an average accuracy of 97.95%. The low standard deviation values for both sensors indicate good measurement consistency. These findings align with the literature emphasizing the importance of high-performance sensors for environmental monitoring in smart agriculture systems. The implementation of this system is expected to enhance the efficiency and effectiveness of agricultural management and support the sustainability of agricultural practices.

Enhancing vascular network visualization in 3D photoacoustic imaging: in vivo experiments with a vasculature filter

Filter-based vessel enhancement algorithms facilitate the extraction of vascular networks from medical images. Traditional filter-based algorithms struggle with high noise levels in images with false vessel extraction, and a low standard deviation (σ) value may introduce gaps at the centers of wide vessels. In this paper, a robust technique with less sensitivity to parameter tuning and better noise suppression than other filter-based methods for two-dimensional and three-dimensional images is implemented. In this study, we propose a filter that employs non-local means (NLM) for denoising, applying the vesselness function to suppress blob-like structures and filling the gaps in wide vessels without compromising edge quality or details. Acoustic resolution photoacoustic microscopy (AR-PAM) systems generate high-resolution volumetric photoacoustic images, but their vascular structure imaging suffers from out-of-focal signal-to-noise ratio (SNR) and lateral resolution loss. Implementing a synthetic aperture focusing technique (SAFT) based on a virtual detector (VD) improves out-of-focal region resolution and SNR. Combining the proposed filter with the SAFT algorithm enhances vascular structural imaging in AR-PAM systems. The proposed method is robust and applicable for animal tissues with less error of vasculature structure extraction in comparison to traditional fliter-based methods like Frangi and Sato filter. Also, the method is faster in terms of processing speed and less tuning parameters. We applied the method to a digital phantom to validate our approach and conducted in vivo experiments to demonstrate its superiority for real volumetric tissue imaging.

Estimation of Imatinib Mesylate by Extractive Colorimetric Methods in Bulk and Pharmaceutical Dosage Form

Simple sensitive and accurate extractive spectrophotometric methods have developed for the estimation of Imatinib mesylate in pharmaceutical dosage form. The methods are based on the formation of coloured complexes by the drug with reagents like bromophenol blue, solochrome dark blue and bromocresol green in acidic medium. The ion associated complexes were formed and quantitatively extracted under the experimental condition in chloroform. The absorbance values were measured at 420 nm, 495 nm and 430 nm respectively. The proposed methods were validated statistically. Recoveries of methods were carried out by standard addition methods. The linearity was found to be 1-8 μg/ml, 2 -16μg/ml, 1-16 μg/ ml for methods 1, 2 and 3 respectively. The low values of standard deviation and percentage RSD indicate high precision of methods. Hence these methods are useful for routine estimation of Imatinib mesylate in tablets.

A study on the attitude towards digital learning of Malda district graduate students

In the era of pervasive digital technology, the educational landscape is undergoing a profound transformation. This study investigates the attitudes of graduate students in Malda District towards digital learning, focusing on how these attitudes vary with gender and locality. The study aims to estimate the attitudes of Malda District graduate students towards digital learning and to compare these attitudes with reference to gender and locality. The null hypothesis (Ho.1) posits no significant mean difference in attitudes towards digital learning based on gender and locality. To achieve this, a proportionate stratified random sampling technique was employed to select 200 college students and 100 university students, further stratified by gender and locality. Data were collected via questionnaires and analyzed using appropriate statistical techniques. The results indicated a moderate attitude towards digital learning among the students. The data distribution was normal, with low standard deviation values and slight differences between mean and median values. The analysis revealed no significant mean difference in attitudes between male and female students. However, a significant mean difference was found between urban and rural students, indicating that locality plays a crucial role in shaping attitudes towards digital learning. Gender does not significantly influence attitudes towards digital learning, while locality does. Urban students show different attitudes compared to their rural counterparts. Interventions to improve digital learning attitudes should consider locality-specific challenges and perceptions to be more effective. This study contributes to the understanding of the opportunities and challenges in digital learning, informing pedagogical practices and policy-making in the digital age.

Determination of trace amounts of metobromuron herbicide residues in fruits by QuEChERS and DLLME methods

Food products have the potential to contain herbicide residues that may pose a threat to human health and the environment, and the determination of these residues at trace levels is extremely important. In this study, a rapid, simple, accurate and environmentally friendly DLLME-QuEChERS method was developed for the sensitive determination of metobromuron at trace levels in coconut-strawberry samples. Mass spectrometry coupled to gas chromatography was used to perform the analysis. Limit of detection (LOD) and limit of quantitation (LOQ) for the DLLME-GC-MS method providing a highly linear range with a coefficient of determination of >0.99, were found to be 4.2 and 13.9 ng/mL, respectively. Following QuEChERS and DLLME, recovery studies on coconut-strawberry samples showed that the developed method can be accurately applied to food matrices with the giving results close to 100 % and low standard deviation values.

Determination of Imatinib mesylate from Pharmaceutical Dosage Form by extractive ion pair complex colorimetric Method

Simple sensitive and accurate extractive colorimetric method was developed for the estimation of Imatinib mesylate in Pharmaceutical dosage forms. The method was based on the formation of colored ion pair complexes by the drugs with thiocynate ions. These ion pair complexes were quantitatively extracted under the experimental condition in chloroform. The absorbance values were measured at 618 respectively. The proposed method was validated statistically. A recovery of method was carried out by standard addition methods. The Beer’s law ranges were found to be 1-12μg/ml, respectively. The low values of standard deviation and percentage RSD indicate high precision of method. Hence the method is useful for routine estimation of Imatinib mesylate in tablets respectively.

Determination of Methdilazine by Extractive Colorimetric Method from Pharmaceutical Dosage Form

Simple sensitive and accurate ion pair complex formation, extractive spectrophotometric methods have developed for the estimation of methdilazine hydrochloride in pharmaceutical dosage form. The methods are based on the formation of ion paired coloured complexes by the drug with reactive dyes like Congo red, picric acid and methyl orange in acidic medium. The ion associated complexes were formed and quantitatively extracted under the experimental condition in chloroform. The absorbance values were measured at 490 nm, 400 nm, and 430 nm respectively. The proposed methods were validated statistically. Recoveries of methods were carried out by standard addition method. The linearity was found to be 1-10 μg/ml, 2-12 μg/ml, and 1-14 μg/ml for methods respectively. The low values of standard deviation and percentage RSD indicate high precision of methods. Hence these methods are useful for routine estimation of methdilazine hydrochloride in pharmaceutical dosages.

Temperature dependence investigations of molecular interactions and excess thermodynamic parameters of binary mixtures of ionic liquids and water using Flory's statistical theory

AbstractFlory's Statistical Theory (FST) has been applied to investigate excess thermodynamical parameters viz., excess enthalpy, excess entropy, and excess Gibbs free energy for eight binary mixtures of ionic liquids and water at different concentration and temperatures. The concentration and temperature dependent variations of excess enthalpy suggest that ionic liquid mixtures exhibit an endothermic nature and the presence of weak dispersive forces among their constituents. The positive excess Gibbs free energy of mixing points out that the pure components do not mix thoroughly for the systems under study. Overall, these binary systems are thermodynamically unfavorable suggesting that the mixing of ionic liquids and water is not energetically favored or spontaneous. Experimental molar volumes are compared with those calculated using FST and these values show excellent agreement. It affirms the validity of FST's application to these systems. Additionally, some partial properties have also been determined to explore the solute‐solvent interactions. The Redlich‐Kister (R‐K) polynomial model has been applied to excess thermodynamical parameters The high R2 values and low standard deviation values confirm the validity of fitting the RK polynomial model to the functions obtained using FST of liquids for these systems within the given temperature range.

Dynamics of heart rhythm disorders in combatants with acute myocarditis during a 6-month follow-up

The main factors of an unfavorable prognosis, are life-threatening heart rhythm disorders which determine the severity of the clinical course of myocarditis, in addition to impaired contractility and dilatation of the left ventricle (LV). The aim of the study was to assess the frequency and nature of arrhythmias and establish predictors of their long-term persistence, assess the severity of anxiety and depression, changes in heart rate variability in combatants on the background of changes in the structural and functional state of the left ventricle during a 6-month follow-up. The study included 52 male servicemen (combatants) with acute myocarditis (AM) with an average age of 33.4±2.5 years. All patients were assessed by Questionnaire according to the Hospital Anxiety and Depression Scale (HADS) and underwent 24 hour ECG monitoring, transthoracic echocardiography and cardiac magnetic resonance (CMR) with late enhancement using gadovist. At the onset of AM frequent supraventricular (30.7% of cases) and frequent ventricular (42.3% of cases) extrasystolic arrhythmia, as well as paroxysms of non-sustained ventricular tachycardia (26.9% of cases) on the background of heart rhythm variability disorders were recorded. After 6 months, there was an improvement in the structural and functional state of the heart, which was characterized by a decrease in dilatation and an improvement of LV systolic function, a decrease in the volume of the inflammatory lesion and the total number of affected LV segments revealed on cardiac MRI, which was associated with a decrease in the number of ventricular rhythm disorders and reduction of clinical manifestations of anxiety according to the HADS scale. The obtained data indicate that the persistence of supraventricular rhythm disorders is associated with the long-term presence of anxiety and low values of standard deviation of RR intervals (SDNN) and root mean square of successive differences between normal heartbeats (RMSSD). Also predictors of persistence of non-sustained ventricular tachycardia paroxysms were established – SDNN value ≤80.0 ms, LV end-diastolic volume index ≥95 ml/m2, total number of affected LV segments ≥6 segments, presence of delayed contrasting in ≥3 LV segments, pre­sence of ≥12 points on the HADS scale and predictors of atrial fibrillation – SDNN value ≤80.0 ms, RMSSD value ≤12.0 ms, total number of affected segments of LV≥6 seg. and ≥12 points on the HADS anxiety scale, determined at the onset of AM.

Modified Archimedes optimization algorithm for global optimization problems: a comparative study

Archimedes Optimization Algorithm (AOA) is a recent optimization algorithm inspired by Archimedes’ Principle. In this study, a Modified Archimedes Optimization Algorithm (MDAOA) is proposed. The goal of the modification is to avoid early convergence and improve balance between exploration and exploitation. Modification is implemented by a two phase mechanism: optimizing the candidate positions of objects using the dimension learning-based (DL) strategy and recalculating predetermined five parameters used in the original AOA. DL strategy along with problem specific parameters lead to improvements in the balance between exploration and exploitation. The performance of the proposed MDAOA algorithm is tested on 13 standard benchmark functions, 29 CEC 2017 benchmark functions, optimal placement of electric vehicle charging stations (EVCSs) on the IEEE-33 distribution system, and five real-life engineering problems. In addition, results of the proposed modified algorithm are compared with modern and competitive algorithms such as Honey Badger Algorithm, Sine Cosine Algorithm, Butterfly Optimization Algorithm, Particle Swarm Optimization Butterfly Optimization Algorithm, Golden Jackal Optimization, Whale Optimization Algorithm, Ant Lion Optimizer, Salp Swarm Algorithm, and Atomic Orbital Search. Experimental results suggest that MDAOA outperforms other algorithms in the majority of the cases with consistently low standard deviation values. MDAOA returned best results in all of 13 standard benchmarks, 26 of 29 CEC 2017 benchmarks (89.65%), optimal placement of EVCSs problem and all of five real-life engineering problems. Overall success rate is 45 out of 48 problems (93.75%). Results are statistically analyzed by Friedman test with Wilcoxon rank-sum as post hoc test for pairwise comparisons.

Nanomaterial-Coated Carbon-Fiber-Based Multicontact Array Sensors for In Vitro Monitoring of Serotonin Levels.

In this study, we demonstrated the fabrication of multicontact hierarchical probes for the in vitro detection of serotonin levels. The basic three-dimensional (3D) bendable prototypes with 3 (C1), 6 (C2), or 9 (C3) contact surfaces were printed from polymeric resin via the digital light processing (DLP) technique. We chose ultrasonicated carbon fiber strands to transform these designs into multicontact carbon fiber electrodes (MCCFEs). The exposed carbon fiber (CF) surfaces were modified with aminopropyl alkoxysilane (APTMS), followed by the subsequent loading of palladium nanoclusters (PdNPs) to build active recording sites. CF functionalization with PdNPs was achieved by the wet chemical reduction of Pd(II) to Pd(0). The MCCFE configurations demonstrated an enhancement in the electroactive surface area and an improved voltammetric response toward 5-HT oxidation by increasing the points of the contacts (i.e., from C1 to C3). These MCCFEs are comparable to 3D-protruding electrodes as they can enable multipoint analyte detection. Along with the electrode patterns, morphological irregularities associated with both Pd-doped and undoped CFs supported the creation of proximal diffusion layers for facile mass transfer. Low detection limits of 0.8-10 nM over a wide concentration range, from 0.005 nM to 1 mM, were demonstrated. The MCCFE sensors had a relatively low standard deviation value of ∼2%. This type of sensitive and cost-effective electrochemical sensor may prove useful for collecting electrical impulses and long-term monitoring of 5-HT in vivo in addition to in vitro testing.

TOWARDS A QUALITY FRAMEWORK FOR RESPONSIVE COACHING AND MENTORING PRACTICE OF MASTER TEACHERS FOR POLICY AMENDMENTS

This research aimed to develop a quality framework for responsive coaching and mentoring practices of 164 master teachers for policy amendments at the Schools Division of Zambales. Employing a quantitative descriptive research approach, the study utilized a validated and reliable researcher-made questionnaire for data collection and applied both descriptive and inferential statistics for data analysis. Findings revealed that master teachers exhibited the highest extent of responsive coaching practices in goal setting and clarity, as well as the highest extent of responsive mentoring practices in communication and collaboration. The relatively low standard deviation values indicated a strong consensus among master teachers, suggesting a high level of agreement about the effectiveness of these responsive coaching and mentoring practices. No significant difference was identified regarding the effect of demographic profiles particularly age, gender, length of service, and highest educational attainment of master teachers on the relationship between responsive coaching and mentoring practices. The regression analysis affirmed the significant findings on the impact of responsive coaching and mentoring practices of master teachers. A quality framework for policy amendments on responsive coaching and mentoring practices of master teachers plays a pivotal role in enhancing teaching performance by providing structured guidelines and systematic approaches.

A Novel Method for Vibrotactile Proprioceptive Feedback Using Spatial Encoding and Gaussian Interpolation.

The bidirectional communication between the user and the prosthesis is an important requirement when developing prosthetic hands. Proprioceptive feedback is fundamental to perceiving prosthesis movement without the need for constant visual attention. We propose a novel solution to encode wrist rotation using a vibromotor array and Gaussian interpolation of vibration intensity. The approach generates tactile sensation that smoothly rotates around the forearm congruently with prosthetic wrist rotation. The performance of this scheme was systematically assessed for a range of parameter values (number of motors and Gaussian standard deviation). Fifteen non-disabled subjects and one individual with congenital limb deficiency used vibrational feedback to control a virtual hand in the target-achievement control test. Performance was assessed by end-point error and efficiency as well as subjective impressions. The results showed a preference for smooth feedback and a higher number of motors (8 and 6 versus 4). With 8 and 6 motors, the standard deviation, determining the sensation spread and continuity, could be modulated through a broad range of values (0.1 - 2) without a significant performance loss. The overall average error and efficiency across these feedback configurations were ∼ 10% and ∼ 30%, respectively. For low values of standard deviation (0.1-0.5), the number of motors could be reduced to 4 without a significant performance decrease. The study demonstrated that the developed strategy provided meaningful rotation feedback. Moreover, the results indicate that the Gaussian standard deviation could be used as an independent parameter to encode an additional feedback variable. The proposed method is a flexible and effective approach to provide proprioceptive feedback while adjusting the trade-off between sensation quality and the number of vibromotors.

Parameter identification of transformer lumped element network model through genetic algorithm‐based gray‐box modelling technique

AbstractThe lumped element network model has been proven to be an efficient tool for the interpretation of transformer Frequency Response Analysis. However, it is challenging to obtain parameters of the model if transformer design information is unavailable. In such a case, optimisation algorithms can be used for gray‐box model parameter estimation. A methodology is developed by the authors to establish a transformer network model without winding design data, and instead, end‐to‐end open circuit Frequency Response and other terminal test results are utilised; and Genetic Algorithm is applied to approximate the unknown parameters of the model. The modelling approach developed is independent of the unit number of the network model and therefore guarantees the accuracy of optimisation. Furthermore, it can deal with transformers with a complicated winding structure such as interleaved disc type winding. Two single windings, helical and interleaved disc type, and a single‐phase 144/13 kV 60 MVA transformer are used to demonstrate the method. FRA spectra produced by the best estimated gray‐box model and the corresponding white‐box model are compared. The main features in amplitude and phase spectra are well matched, with low values of Relative Standard Deviation, for both single windings and transformer. Estimated electrical parameters show a high consistency with reference values, which are calculated based on winding design data. This validates the methodology and gives confidence to apply grey‐box modelling for FRA interpretation.

A novel modified Archimedes optimization algorithm for optimal placement of electric vehicle charging stations in distribution networks

The number of electric vehicle charging stations (EVCSs) is increasing alongside electric vehicles (EVs). The unplanned rollout of EVCSs can lead to problems such as deterioration of the voltage profile, increased active power losses, and maximum load demand in distribution networks (DNs). Therefore, EVCSs should be placed in optimum locations on the DNs. The complexity of the problem requires efficiency and performance. In this paper, a novel modified Archimedes optimization algorithm (MAOA) is proposed for optimal placement of EVCSs in DNs. Five parameters of the AOA were modified using the Honey Badger Algorithm (HBA). This placement is based on a combination of indexes: power loss, voltage deviation, and voltage stability index (VSI). Next, Newton-Raphson based load flow analysis is used to compute the minimum cost. MAOA, AOA and eight other optimization algorithms are compared. The results provide the most appropriate buses in the DN. The efficiency of the proposed algorithm was tested on IEEE 33, 69, and 10-bus Hatay power network systems. In all test systems, the proposed MAOA provided the best results with consistently low standard deviation values. The results suggest that the proposed method is more effective in the integration of EVCSs into the DN. © 2017 Elsevier Inc. All rights reserved.

Validation of Molnupiravir by Application of Reactive Dyes from Pharmaceutical Dosages

Simple sensitive and accurate ion pair complex formation with reactive dyes, extractive spectrophotometric methods have developed for the estimation of molnupiravir in pharmaceutical dosage form. The methods are based on the formation of ion paired coloured complexes by the drug with reactive dyes like Congo red, eriochrome black T and methyl orange in acidic medium. The ion associated complexes were formed and quantitatively extracted under the experimental condition in chloroform. The absorbance values were measured at 490nm, 500nm, and 430nm respectively. The proposed methods were validated statistically. Recoveries of methods were carried out by standard addition method. The linearity was found to be 4.0-24.0μg/ml, 2-12μg/ml, and 2-16μg/ml for methods respectively. The low values of standard deviation and percentage RSD indicate high precision of methods. Hence these methods are useful for routine estimation of molnupiravir in pharmaceutical dosages.

Simultaneous complexation and extraction of manganese in melissa tea sample by deep eutectic solvent based liquid phase microextraction

Manganese at trace levels cannot be detected by flame atomic absorption spectrophotometer (FAAS) without a preconcentration method. In the presented study, an accurate and sensitive analytical method for the determination of manganese at trace levels in melissa tea samples was established. Deep eutectic solvent based liquid phase microextraction (DES-LPME) was used to preconcentrate the analyte from aqueous medium. Several important parameters were individually optimized to achieve high signal to noise ratio for the analyte in FAAS system. Under the optimum experimental conditions, limit of detection (LOD), limit of quantitation (LOQ) and linear range (LR) for the developed DES-LPME-FAAS system were found as 1.7 µg/kg, 5.8 µg/kg and 6.5–202.8 µg/kg, respectively. Enhancement in detection power was calculated as 112.2 folds by dividing manganese LOD value in FAAS system to value obtained by DES-LPME-FAAS system. Three different melissa tea samples were analyzed by the proposed method to find their manganese content. Percent recovery results for the tea samples ranged between 80.4% and 122.6% with low standard deviation values.