Low Standard Deviation Values Research Articles

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.

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.

A novel potentiometric approach for the sensitive detection of cadmium in real samples using modified carbon paste electrodes

AbstractThe goal of this study was to demonstrate a novel potentiometric technique for the measurement of Cd(II) ion. A new ionophore called [5′‐(ethane‐1,2‐diylbis(sulfanediyl))bis(3‐phenyl‐4H‐1,2,4‐triazol‐4‐amine) (ESPTA)] was prepared and used as an electroactive material in the fabrication of new carbon paste electrode (CPE) for the quantification of Cd(II) ion. The paste was prepared by mixing ESPTA, graphite, graphene, and TCP or o‐NPOE as a plasticizer in different weight percent ratios. The developed electrodes I, II, III, and IV showed divalent Nernstian response of 29.80±0.05, 29.80±0.08, 29.86±±0.04 and 29.75±0.33 mV decade−1 over the concentration ranges of 1.0×10−5–1.0×10−1, 1.0×10−8–1.0×10−1, 1.0×10−6–1.0×10−1 and 1.0×10−7–1.0×10−1 mol L−1 with percentage of (2.65 ESPTA: 66.32 graphite: 31.03 TCP), (2.65 ESPTA: 13.27 graphite : 53.05 graphene : 31.03 TCP), (2.75 ESPTA: 68.68 graphite: 28.57 o‐NPOE) and (2.75 ESPTA: 13.74 graphite : 54.94 graphene : 28.57 o‐NPOE), for electrodes I, II, III, and IV, respectively. In order to improve the performance characteristics of electrodes I, II, III, and IV, response time, the effect of temperature, and pH were examined. The electrodes showed high selectivity for Cd(II) over different mono‐, di‐ or trivalent cations. These modified electrodes were applied for the determination of the concentration of Cd(II) in different real samples like Nido Milk, juice extractions and tap water samples with high percentage recovery. The F‐ and t‐test values showed that there is no statistically significant difference between the results obtained and those from the stated method of inductively coupled plasma. Low standard and relative standard deviation values, good percentage recovery, and modest detection and quantification limitations were all displayed by the electrodes. The outcomes showed the potentiometric method‘s effectiveness in detecting Cd(II) in actual samples and its potential for use in routine analysis.

Rapid extraction and detection of ellagic acid in plant samples using a selective magnetic molecularly imprinted polymer coupled to a fluorescence method

A remarkable growth was noticed in the development of molecularly imprinted polymers (MIPs), which have used as efficient synthetic antibodies that contain selective cavities to the target molecule. Hereunder, a novel strategy using MIP as a sorbent in solid-phase extraction was coupled to a fluorescence method for ellagic acid (EA) purification and immediate detection. The synthesis of magnetic-MIP (MMIP) using a rapid and green ultrasound technology was assessed by central composite design to determine the optimal polymerization conditions for a high-imprinting polymer. The MMIP was characterized by Fourier transform infrared spectroscopy, X-ray diffraction, thermogravimetric analysis, and scanning/transmission electron microscopy, which accurately confirmed the functional, magnetic, and morphological features of MMIP. The prepared MMIP was demonstrated to be selective for EA compared to many similar phenols. The spectrofluorometric method showed a linear range from 0.05 to 2 μg·mL−1 of EA, and the limits of detection (LOD) and quantification (LOQ) were 0.005 and 0.02 μg·mL−1, respectively. Besides, the novel proposed smartphone method using the ultraviolet lamp as the excitation source presented a linear range from 0.2 to 4 μg·mL−1, a LOQ of 0.2 μg·mL−1, and a LOD of 0.07 μg.mL−1. The proposed strategy revealed high efficiency in the extraction and detection of EA in grape, redberry, and green tea. Effectively, the calculated recoveries were ranging from 80 to 102% with low values of relative standard deviation (<3%). The proposed strategy could be used in many analytical fields for selective, rapid, user-friendly, visual, and cost-effective detection.

Functional Magnetic Resonance Urography in Children-Tips and Pitfalls.

MR urography can be an alternative to other imaging methods of the urinary tract in children. However, this examination may present technical problems influencing further results. Special attention must be paid to the parameters of dynamic sequences to obtain valuable data for further functional analysis. The analysis of methodology for renal function assessment using 3T magnetic resonance in children. A retrospective analysis of MR urography studies was performed in a group of 91 patients. Particular attention was paid to the acquisition parameters of the 3D-Thrive dynamic with contrast medium administration as a basic urography sequence. The authors have evaluated images qualitatively and compared contrast-to-noise ratio (CNR), curves smoothness, and quality of baseline (evaluation signal noise ratio) in every dynamic in each patient in every protocol used in our institution. Quality analysis of the image (ICC = 0.877, p < 0.001) was improved so that we have a statistically significant difference in image quality between protocols (χ2(3) = 20.134, p < 0.001). The results obtained for SNR in the medulla and cortex show that there was a statistically significant difference in SNR in the cortex (χ2(3) = 9.060, p = 0.029). Therefore, the obtained results show that with the newer protocol, we obtain lower values of standard deviation for TTP in the aorta (in ChopfMRU: first protocol SD = 14.560 vs. fourth protocol SD = 5.599; in IntelliSpace Portal: first protocol SD = 15.241 vs. fourth protocol SD = 5.506). Magnetic resonance urography is a promising technique with a few challenges that arise and need to be overcome. New technical opportunities should be introduced for everyday practice to improve MRU results.

Artificial intelligence-based refractive error prediction and EVO-implantable collamer lens power calculation for myopia correction

BackgroundImplantable collamer lens (ICL) has been widely accepted for its excellent visual outcomes for myopia correction. It is a new challenge in phakic IOL power calculation, especially for those with low and moderate myopia. This study aimed to establish a novel stacking machine learning (ML) model for predicting postoperative refraction errors and calculating EVO-ICL lens power.MethodsWe enrolled 2767 eyes of 1678 patients (age: 27.5 ± 6.33 years, 18–54 years) who underwent non-toric (NT)-ICL or toric-ICL (TICL) implantation during 2014 to 2021. The postoperative spherical equivalent (SE) and sphere were predicted using stacking ML models [support vector regression (SVR), LASSO, random forest, and XGBoost] and training based on ocular dimensional parameters from NT-ICL and TICL cases, respectively. The accuracy of the stacking ML models was compared with that of the modified vergence formula (MVF) based on the mean absolute error (MAE), median absolute error (MedAE), and percentages of eyes within ± 0.25, ± 0.50, and ± 0.75 diopters (D) and Bland-Altman analyses. In addition, the recommended spheric lens power was calculated with 0.25 D intervals and targeting emmetropia.ResultsAfter NT-ICL implantation, the random forest model demonstrated the lowest MAE (0.339 D) for predicting SE. Contrarily, the SVR model showed the lowest MAE (0.386 D) for predicting the sphere. After TICL implantation, the XGBoost model showed the lowest MAE for predicting both SE (0.325 D) and sphere (0.308 D). Compared with MVF, ML models had numerically lower values of standard deviation, MAE, and MedAE and comparable percentages of eyes within ± 0.25 D, ± 0.50 D, and ± 0.75 D prediction errors. The difference between MVF and ML models was larger in eyes with low-to-moderate myopia (preoperative SE > − 6.00 D). Our final optimal stacking ML models showed strong agreement between the predictive values of MVF by Bland-Altman plots.ConclusionWith various ocular dimensional parameters, ML models demonstrate comparable accuracy than existing MVF models and potential advantages in low-to-moderate myopia, and thus provide a novel nomogram for postoperative refractive error prediction and lens power calculation.

Simple Extractive Spectrophotometric Method for Determination of Molnupiravir from Pharmaceutical Formulation

Simple sensitive and accurate spectrophotometric methods have developed for the estimation of molnupiravir 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 420nm, 495nm and 430nm respectively. The proposed methods were validated statistically. Recoveries of methods were carried out by standard addition methods. The linearity was found to be 1.0-12.0μg/ml, 2 -14μg/ml, 1-10μg/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 molnupiravir in tablets.

Face-to-face classroom learning produced greater brain synchronisation in children than a zoom-based online session.

The shift to online learning during the pandemic posed significant challenges for children, including reduce attention.1 Reports have also suggested that significantly more is learnt during face-to-face interactions, than via screens, such as language acquisition.2 The ability to learn and react to stimuli can be assessed with electroencephalography (EEG). Zivan et al focused on two groups of preschool children aged 4–5 years who took part in a six-week experiment that compared face-to-face and screen-based storytelling. The screen group showed more slow theta band waves on the EEG and fewer fast beta and gamma band waves than the face-to-face group when they rested after the intervention.3 Those patterns have been associated with attention difficulties and load. We looked at how face-to-face interaction facilitates learning and how can it be measured. This study compared learning outcomes and neurobiological correlates during face-to-face and online learning, using behavioural EEG data collected in a unique manner. Hyperscanning shows the neural synchrony between two or more individuals that results in brain synchronisation matrices. We hypothesised that the face-to-face interaction would produce better learning outcomes, and higher neural synchrony in the alpha and beta band waves, than online learning. We recruited a science teacher and six typically developing adolsecents, five female, with an average age of 11 ± 1.2 years and no developmental or neurological deficits. Data from the students were simultaneously recorded in the two learning conditions while connected to EEG devices (Figure 1). The parents and children provided written consent and assent, respectively, and the children could leave the study at any time. The institutional review board of the Technion, Haifa, Israel approved the study and the school provided permission. The learning sessions focused on two different, but comparable, scientific themes and included 15-min of explicit tutoring and a short video explaining the topic. The teacher and students also conducted a short experiment while they were connected to the EEG device. During the face-to-face condition the children sat in the laboratory, in front of the teacher, so they could see each other. During the online Zoom call, in gallery mode, the participants were all in separate rooms but they could see each other (Figure 1). Five written comprehension questions were administered at the end of each session. Means and standard deviations were calculated for the comprehension levels following each condition. No statistical analysis was possible due to the sample size. The EEG data were processed using multidimensional matrices containing the neural synchrony values between every pair of frontal electrodes associated with joint attention abilities. These were namely AF3, AF4, F4, F3, F8, and F7. The 6X6 synchronisation matrices for the online condition were subtracted from the face-to-face condition for alpha (8–12 Hz) and beta bands (12–30 Hz). They were averaged across time for all subjects and separately for each condition, namely within the children and between the children and teacher. The processing pipeline has previously been described.4 The results demonstrated higher comprehension levels for the face-to-face than online learning condition (X = 93.33 ± 10.32% vs. X = 76.66 ± 36.69%). More electrodes were highly synchronised between the teacher and pupils and between the pupils during the face-to-face versus online conditions in the alpha and beta frequency bands (72.2% vs. 75.1%). Children showed higher comprehension levels during the face-to-face condition, as hypothesised. There were lower standard deviation values and higher brain-to-brain synchronisation between the teacher and the pupils and within the pupils. Dialogue and peer interaction during interactive classroom learning have been reported for various domains, including language acquisition.2 Classroom dialogue can include interactions between small groups of students and whole class discussions orchestrated by the teacher.5 The class design in our study involved discussions in both the face-to-face condition and an online Zoom call. However, our study highlighted individual differences in the ability to be actively engaged in class while learning online, with regard to EEG and behavioural learning outcomes. It has been suggested that face-to-face learning, mediated by joint attention, is more beneficial than online learning. Zivan et al found this when they compared online and face-to-face storytelling.3 Although the information received during face-to-face learning may be cognitively demanding, the learning outcomes are greater. Online learning may also lack the joint attention and synchronisation that are created between class participants during face-to-face learning, due to external or internal disruptions. In our study, the interactive nature of face-to-face learning, with joint attention and eye contact between the participants, resulted in greater synchronisation and outcomes. Providing neuroscientific evidence for the differences in brain synchrony between these two learning conditions can deepen our understanding of the effect they have on children's outcomes. None. None.

Application of reactive dyes in Validation of favipiravir from pharmaceutical dosages

Simple sensitive and accurate ion pair complex formation with reactive dyes, extractive spectrophotometric methods have developed for the estimation of favipiravir 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 490 nm, 500 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 5.0-30.0 μg/ml, 5 -12 μg/ml, and 2-20 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 favipiravir in pharmaceutical dosages.

Development of a rapid and efficient analytical method for trace lead determination: Manganese dioxide nanoflower based dispersive solid-phase extraction

Lead (Pb) is a heavy metal that is highly toxic and a major environmental pollutant. Anthropogenic activities are the main sources of Pb release into the air, water and food, from which humans and other organisms become exposed. In this study, a suitable, rapid, and environmental friendly dispersive solid phase extraction procedure based on manganese dioxide nanoflower (MnO 2 NF-DSPE) was developed for the effective enrichment of Pb coupled with flame atomic absorption spectrometry (FAAS). Under the optimal experimental conditions, limit of detection (LOD), quantification (LOQ) values and enhancement in detection power (EDP) obtained for the MnO 2 NFs-DSPE-FAAS system were calculated as 6.1 µg/L, 20.3 µg/L and 44, respectively. Three different ginger tea samples were used in recovery studies to investigate the applicability/accuracy of the proposed method. Matrix matching calibration strategy was performed in recovery studies and percentage recoveries were calculated between 106 and 122% with low standard deviation values. • Trace level lead was preconcentrated by DSPE prior to FAAS measurement. • MnO 2 nanoflowers were used as adsorbent in the extraction procedure. • LOD and LOQ for ginger tea matrix were 6.09 µg/L and 20.29 µg/L, respectively. • The detection limit for conventional FAAS system was improved by about 43.7 folds. • Recovery results for the prepared ginger tea were found in the range of 106.1–121.5%.

Association of coronary artery calcium with heart rate variability in the Brazilian Longitudinal Study of Adult Health - ELSA-Brasil

Current data shows that the autonomic and vascular systems can influence each other. However, only a few studies have addressed this association in the general population. We aimed to investigate whether heart rate variability (HRV) was associated with coronary artery calcium (CAC) in a cross-sectional analysis of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). We examined baseline data from 3138 participants (aged 35 to 74 years) without previous cardiovascular disease who underwent CAC score assessment and had validated HRV recordings. Prevalent CAC was defined as a CAC score>0, and HRV analyses were performed over 5-min segments. We detected CAC score>0 in 765 (24.4%) participants. Subgroup analyses in older participants (≥49 years) adjusted for sociodemographic and clinical variables revealed that CAC score>0 was associated with lower values of standard deviation of NN intervals (SDNN) (odds ratio [OR]=1.32; 95%CI: 1.05,1.65), root mean square of successive differences between adjacent NN intervals (RMSSD) (OR=1.28; 95%CI: 1.02,1.61), and low frequency (LF) (OR=1.53, 95%CI: 1.21,1.92). Interaction analysis between HRV indices and sex in age-stratified groups revealed significant effect modification: women showed increased OR for prevalent CAC in the younger group, while for men, the associations were in the older group. In conclusion, participants aged ≥49 years with low SDNN, RMSSD, and LF values were more likely to present prevalent CAC, suggesting a complex interaction between these markers in the pathogenesis of atherosclerosis. Furthermore, our results suggested that the relationship between CAC and HRV might be sex- and age-related.

Multi-characteristic optimization and modeling analysis of electrocoagulation treatment of abattoir wastewater using iron electrode pairs

Multi-characteristic optimization and modeling analysis of electrocoagulation (EC) treatment of abattoir wastewater (AWW) using iron‑iron electrodes are reported. Response Surface Methodology (RSM) and Artificial Intelligent (AI) modeling tools viz. Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used for the modeling while the numerical method of RSM and RSM-based Genetic Algorithm (RSM-GA) were used to optimize the response variable. The independent variables were pH, current intensity, electrolysis time, settling time, and temperature while the dependent variable was percentage turbidity removal. Based on high determination coefficient (R2) and low standard deviation (SD) values, the quadratic model was selected from the ANOVA of the RSM model. For the ANN model, the number of neurons were varied between 2 and 10 but based on low MSE and high R2 values, 10 was selected as the optimum number of neurons. The ANFIS network used the triangular input membership function (trimf) with 100 epochs. The three models depicted linear adequacy with respective R2 values of 0.9978, 0.9995, and 0.8285 for RSM, ANFIS, and ANN respectively. However, the performance error indices indicated that the prediction accuracy of the three models followed the order — ANFIS > ANN > RSM. Further, the validated optimization results produced 94.74 % and 97.42 % turbidity removal for the RSM and RSM-GA optimization methods respectively. This proved that RSM, ANN, and ANFIS can reliably be used to model the EC treatment of AWW using FeFe electrodes; while the response variable can successfully be optimized by RSM and RSM-GA methods.

Simple Extractive Spectrophotometric Method for Determination of Favipiravir from Pharmaceutical Formulation

Simple sensitive and accurate extractive spectrophotometric methods have developed for the estimation of favipiravir 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 420nm, 495nm and 430nm respectively. The proposed methods were validated statistically. Recoveries of methods were carried out by standard addition methods. The linearity was found to be 1.0-12.0μg/ml, 2-20μg/ml, 1-16μg/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 favipiravir in tablets.

Determination of Molnupiravir by Extractive Colorimetric Method from Pharmaceutical Dosage Form

Simple and accurate extractive colorimetric method was developed for the estimation of molnupiravir 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 organic solvent like chloroform. The absorbance values were measured at 620 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 1-14 μg/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 molnupiravir in tablets respectively.