Curve Method Research Articles

Changes in the air temperature regime across the Dniester River basin at the beginning of the 21st century

The relevance of the chosen topic is based on the goals and objectives of the Water Strategy of Ukraine until 2050 that provides for promotion of studies on the impact of climate change on the water content of Ukrainian rivers. The Dniester River is a transboundary river. It supplies water to Moldova and several regions of Ukraine. Predicting possible changes in the Dniester River's runoff due to global warming will help our society adapt to new climate conditions and take preventive measures. The research of the mountainous part of the watershed is of particular importance, as it is the area of runoff formation. Warming can change contribution of the snow component to the river's feed pattern and affect the total river flow. The object of the study: changes in air temperature due to global warming. The subject of the study: assessment of changes in the temperature regime within the Dniester watershed and impact of such changes on formation of its mountainous part's runoff. The study is aimed at assessing the changes in the air temperature regime within the Dniester River watershed at the beginning of the 21st century and assessing the impact of warming during winter season on formation of mountain rivers' spring floods. The main research methods include the method of difference integral curves and the method of regression analysis. The research materials include average monthly and annual air temperatures at 13 meteorological stations located within the Dniester watershed for the period of 1947-2021. The research indicated that the Dniester watershed is subject to warming. Statistically significant changes in air temperature began in 1988. Fluctuations in average annual air temperatures occur synchronously. Positive statistically significant trends over the entire observation period (1947-2021) were found for average annual air temperatures, average monthly temperatures of both warm and cold periods, and for the winter season. When considering two measurement periods (before 1989 and after), it was found that no statistically significant trends were observed before 1989. They were formed after 1989. It was also discovered that mountainous watersheds of the Ukrainian Carpathians respond to warming by forming negative trends in the fluctuations of average monthly runoff of spring floods.

Quantitative estimation of doxylamine succinate by zero-order derivative area under curve Spectrophotometric methods in bulk and in-tablet dosage form

The purpose of this study is to establish Zero-order UV-Spectrophotometric - absorbance and Zero Order- Area under curve (AUC) methods for estimation of Doxylamine succinate in bulk and in pharmaceutical dosage form . Doxylamine succinate is Histamine H1 antagonist with pronounced sedative properties. It is used in allergies and as an antitussive, antiemetic, and hypnotic. Doxylamine has also been administered in veterinary applications and was formerly used in parkinsonism, distilled water was used as solvent for solubilization of Doxylamine succinate. Maximum absorption for Doxylamine succinate was found to be at wavelength 260nm when dissolved in Distilled water. The methods are based upon measurement of absorbance at 260nm and integration of area under curve for analysis of Doxylamine succinate in the wavelength range of 251.20-267.20 nm. The drug followed linearity in the concentration range of 10 - 60µg/mL with correlation coefficient value r> 0.99 . The proposed methods were validated for accuracy (% recovery), precision, repeatability and ruggedness, as per ICH guidelines. The proposed methods were applied for qualitative and quantitative estimation of Doxylamine succinate in tablet and results were found in good agreement with the label claimed. Developed methods can be used for routine analysis of Doxylamine succinate in bulk and pharmaceutical tablet.

Structure, impedance spectroscopy, and magnetic properties of nanostructured composites (1-x)CoFe2O4–xPbTiO3

The article presents a comprehensive investigation of the crystal structure, impedance spectra, magnetic, magnetodielectric, and magnetoresistive properties of (1-x)CoFe2O4–xPbTiO3 composites with varying concentrations (х = 0, 0.2, 0.4, and 0.6). The study also examines the effects of applying a uniaxial pressure of 1 GPa to the synthesized powders using Bridgman anvils. Our findings reveal that the synthesis of these composites results in the formation of an additional phase, lead hexaferrite PbFe12O19, which exhibits multiferroic properties. Additionally, the coherent scattering region of the components is significantly reduced after mechanical activation. Notably, the real part of the resistivity ρ′(ω) of nanostructured CoFe2O4 ceramics increases eightfold at T = 240 °C. The composites demonstrate significant magnetoresistance at room temperature, reaching up to 250 %. The study also reveals that the signs of the magnetodielectric MD(B) and magnetoresistive coefficient MR(B) vary with the frequency of the measuring field for certain concentrations. Using the first-order reversal curve (FORC) method, it was observed that after nanostructuring CoFe2O4 through mechanical activation, the interaction field Hu shifts from ± 0.6 kOe to ± 0.8 kOe, while the coercive field Hc increases from 1.05 kOe to 5 kOe. Moreover, the two-dimensional FORC maps of the composites show increased complexity, due to the formation of additional magnetic phases.

Temporal dynamic alterations of regional homogeneity in major depressive disorder: a study integrating machine learning

Previous studies have found alterations in the local regional homogeneity of brain activity in individuals diagnosed with major depressive disorder. However, many studies have failed to consider that even during resting states, brain activity is dynamic and time-varying. The lack of investigation into the dynamic regional homogeneity has hindered the discovery of biomarkers for depression. This study aimed to assess the utility of the dynamic regional homogeneity by a machine learning model (support vector machine). Sixty-five individuals with dynamic regional homogeneity and 57 healthy controls participated in resting-state functional magnetic resonance rescanning and scale estimating. The dynamic regional homogeneity and receiver operating characteristic curve methods were used for analysis of the imaging data. Relative to healthy controls, major depressive disorder patients displayed increased dynamic regional homogeneity values in the left precuneus and right postcentral gyrus. Additionally, receiver operating characteristic curve results of the dynamic regional homogeneity values in the left precuneus and right postcentral gyrus could distinguish major depressive disorder patients from healthy controls; furthermore, changes in the dynamic regional homogeneity were correlated with depression severity.

Method for determining reagent optimum volume for acid treatments of carbonate reservoirs based on a pressure build-up curve method

Relevance. The need to increase the efficiency of acid treatments of carbonate reservoirs. Often, the design of treatments does not take into account the actual operating conditions of production wells, which leads to an overestimation or underestimation of the required volume of the reagent. Aim. To propose a method for determining the optimal amount of reagent for carrying out acid treatments of carbonate reservoirs in order to restore the permeability of the rock in the near-well zone, taking into account the actual operating conditions of the well, which allows rationalizing the use of subsoil user resources. Objects. Producing oil wells exploiting oil deposits in carbonate deposits of the Perm region, as well as the results of hydrodynamic studies carried out on these wells. Methods. Theoretical substantiation of the possibility of determining the zone of deteriorated permeability around the well using the pressure recovery curve graph, graphical processing of diagnostic graphs of the pressure recovery curve, mathematical calculation of technological indicators based on hydrodynamic testing data of wells, integration of inflow volumes, analysis of technological data and conditions of applicability of the methodology. Results. The authors have developed the methodology for determining the optimal volume of reagent for acid treatments of carbonate reservoirs based on the pressure recovery curve method. The optimal volume of reagent for 21 production wells was calculated. Using the example of 13 wells, the efficiency of the injected volume of reagent was determined and an overestimated volume of reagent injected into the formation was demonstrated. The authors assessed the subsoil user's costs taking into account the excess consumption of the reagent. The factors influencing the success of the method application depending on the operating conditions of the wells were identified. Criteria inappropriateness of acid treatment were identified.

Establishing minimal clinically important differences for the quality of life scale QLICD-SLE for patients with systemic lupus erythematosus based on ROC curve

The minimal clinically important difference (MCID) is an important concept with big appeal in a field struggling to interpret quality of life (QOL) and other patient-reported outcomes (PRO), is also a bridge between statistics and clinical medicine. This study uses the ROC curve to formulate the MCID value of the Quality of Life Instruments for Chronic Diseases of Systemic lupus erythematosus (QLICD-SLE V2.0) scale. Using the representative item “In general, would you say your health is” of the MOS item short form health survey(SF-36) as an anchor, the questionnaire of QLICD-SLE V2.0 and the anchor item were used to investigate the patients on the first day of hospitalization, and the day before the patient was discharged. 279 patients with lupus erythematosus were participated in this longitudinal follow-up study. The ROC curve was constructed by using the classification based on the anchor item as the gold standard and the difference score of the scale as the test variable. The cut-off point corresponding to the maximum value of the Youden index in the ROC curve is taken as the minimum clinical importance difference (MCID) value of the QLICD-SLE (V2.0) scale. The Results showed that the MCID of physical domain, psychological domain, social domain, general module, specific module and QLICD-SLE (V2.0) total scale are 8.3, 2.3, 2.5, 2.7, 9.2 and 3.2, respectively. Area under the ROC curve of QLICD-SLE (V2.0) is 0.898, P (Area = 0.5) < 0.001, the sensitivity is 100%, the specificity is 66.9%. It concluded that if the total scores after treatments changes at least 3.2 points positively, the treatment intervention can be considered as clinically significant. It is more convincing to use the corresponding cut-off point as the MCID for ROC curve method can visualize the sensitivity and specificity.

A Secure Fusion: Elliptic Curve Encryption Integrated with LSB Steganography for Hidden Communication

In today's digital age, ensuring secure communication is essential. This article presents a novel approach for hidden communication by integrating Elliptic Curve Encryption (ECE) with Least Significant Bit (LSB) Steganography. Our proposed fusion offers a robust solution, Stegno Curve for concealing sensitive information within innocuous cover media while encrypting it using elliptic curve cryptography. By leveraging the strengths of both techniques, we achieve enhanced security and confidentiality in data transmission. Through a comprehensive literature review, methodology explanation, security analysis, and implementation details, we demonstrate the feasibility and effectiveness of the Stegno Curve Method. The findings of this study not only contribute to advancing the field of secure communication but also open avenues for practical applications in various domains, such as secure cloud transitions, smart home technologies, and data encryption.

FIB-4 Reliability in Patients With Severe Obesity: Lower Cutoffs Needed?

Liver biopsy is the gold standard to evaluate hepatic fibrosis; however, it has many drawbacks, especially in patients with severe obesity. Noninvasive testing such as the FIB-4 score is increasingly being used as the initial screening tool to identify patients at risk for advanced fibrosis. The broader applicability of FIB-4 and the precision of its cutoff values remain uncertain in metabolic dysfunction-associated steatotic liver disease and patients with severe obesity. Our study explored the correlation between FIB-4 scores and intraoperative liver biopsy in patients with severe obesity undergoing bariatric surgery. A total of 632 patients with severe obesity underwent preoperative vibration-controlled transient elastography and intraoperative liver biopsy during bariatric surgery from January 2020 to August 2021. Variables collected included patient demographics, laboratory values, abdominal ultrasound, vibration-controlled transient elastography, and liver biopsy results. ANOVA 1-way test, χ 2 tests, and Fisher exact tests were used for quantitative and qualitative variables, respectively. The 95% CIs for the mean FIB-4 scores were used to generate surrogate cutoff values. The proposed FIB-4 cutoffs for F0-1, F2, F3, and F4 were 0.62 (CI: 0.59, 0.64), 0.88 (0.74, 1.01), 1.24 (0.94, 1.54), and 1.53 (0.82, 2.24), respectively. Area under the curve (AUC) methods were used to compare traditional to proposed cutoff values. Applying the traditional FIB-4 cutoffs to approximate advanced fibrosis yielded an AUC of 0.5748. Use of the proposed FIB-4 cutoffs increased the AUC to 0.6899. The proposed FIB-4 cutoffs correctly identified 40 patients with biopsy-proven advanced fibrosis (F3-F4), all of which would have been missed using traditional cutoffs. Our study revealed that the use of the currently accepted FIB-4 cutoffs as the screening modality for identifying patients with advanced fibrosis due to metabolic dysfunction-associated steatotic liver disease is insufficient and will result in missing patients with histologically confirmed advanced fibrosis. Use of the revised FIB-4 scores should be considered to diagnose patients with severe obesity at high risk of liver disease progression.

Inhibitory Mechanism of the Oregano Essential Oil on the Growth and Biofilm Formation of Streptococcus mutans

Objective: The objective was to determine the in vitro antibacterial effect of the Oregano essential oil (OEO) on Streptococcus mutans ( S mutans) and to explore the anti-biofilm effect and mechanism of OEO. Methods: The in vitro antibacterial susceptibility of OEO was detected by the growth curve and colony-forming unit (CFU) counting method. Confocal laser scanning microscope (CLSM) and crystal violet assay were used to explore the anti-biofilm activity of OEO, and the anti-biofilm mechanism was explored from the aspects of extracellular polysaccharides (EPS) synthesis, acidoid, and extracellular DNA changes. OEO was characterized using a gas chromatography-mass spectrometer and cytotoxicity was tested using a cell counting Kit-8 assay. Results: The minimum inhibitory concentration of OEO was 0.25 mg/mL, and the CFU showed the ability of OEO to kill planktonic bacteria. Scanning electron microscopy and CLSM showed that OEO could hinder the development of biofilms, harm bacteria, and eliminate mature biofilms by changing EPS synthesis and pH value. Carvacrol in OEO played a major role in biological antibacterial activity. OEO had low cytotoxicity and good biocompatibility. Conclusions: OEO had excellent antibacterial and anti-biofilm effects on the key virulence traits of S mutans, indicating potential prospects in preventing dental caries.

The predictive value of albumin to alkaline phosphatase ratio for vertebral refractures in postmenopausal women.

To investigate the clinical value of serum albumin to alkaline phosphatase ratio (AAPR) in predicting the risk of osteoporotic vertebral refractures group (OVRFs) after percutaneous vertebral augmentation (PVA) in postmenopausal women. This is a retrospective case-control study including a series of postmenopausal women patients with osteoporotic vertebral fracture (OVF) and underwent PVA. Patients were divided into OVRFs and non-OVRFs. COX model was used to evaluate the correlation between preoperative AAPR and OVRFs after PVA. The receiver operating characteristic (ROC) curve and Kaplan-Meier method were used to analyze the predictive value of AAPR for the incidence of OVRFs. A total of 305 patients were included in the final study, and the incidence of postoperative OVRFs was 28.9%. Multivariate COX analysis showed that advanced age (HRs = 1.062, p = 0.002), low BMI (HRs = 0.923, p = 0.036), low AAPR (HRs = 0.019, p = 0.001), previous fall history (HRs = 3.503, p = 0.001), denosumab treatment (HRs = 0.409, p = 0.007), low L3 BMD (HRs = 0.977, p = 0.001) and low L3 paravertebral muscle density (PMD)value (HRs = 0.929, p = 0.001)) were closely related to the incidence of OVRFs. The area under the curve (AUC) of AAPR for predicting OVRFs was 0.740 (p < 0.001), and the optimal diagnostic cut-off value was 0.49. Kaplan-Meier curve analysis showed that low AAPR group (< 0.49) was significantly associated with lower OVRFs-free survival (p = 0.001; log-rank test). AAPR is an independent risk factor for OVRFs after PVA in postmenopausal women, and it can be used as an effective index to predict OVRFs.

O102 RELATIONSHIP BETWEEN AGTR1 (c.1166 A&gt;C) POLYMORPHISMS AND KIDNEY INJURY IN HYPERTENSION

Background: High blood pressure is the main cause of cardiovascular diseases. Kidney damage is one of the most common organ secondary damage to hypertension. The study of hypertension gene polymorphisms is an important means of precision treatment of primary hypertension. Objectives: The objective of this study was to explore the relationship between AGTR1 (c.1166 A&gt;C) gene polymorphisms and hypertension combined with kidney damage, while exploring the relationship between codominant, dominant and recessive gene model and hypertension with kidney injury and the susceptibility of different genotypes to hypertension with kidney injury. Methods: The distribution of AGTR1 polymorphism in the AGTR1 in hypertensive patients (hypertension group, 292 patients) and hypertension with kidney injury patients (44 patients) were detected and compared by PCR-melting curve method. Results: The genotype distribution of hypertension and combined groups met Hardy-Weinberg equilibrium (p &gt; 0.05); the distribution difference between the three genotypes was statistically significant (p &lt; 0.05), the codominant, dominant and recessive distribution frequency of genotypes (p &lt; 0.05), and no difference between A allele and C allele (p &gt; 0.05). Conclusions: Our study identified the relationship of AGTRA (c.1166 A&gt;C) with hypertension combined with renal injury, and compared the susceptibility of different genetic models, which may provide novel targets for precision gene therapy of hypertension.

Predictors of Medical and Dental Clinic Closure by Machine Learning Methods: Cross-Sectional Study Using Empirical Data.

Small clinics are important in providing health care in local communities. Accurately predicting their closure would help manage health care resource allocation. There have been few studies on the prediction of clinic closure using machine learning techniques. This study aims to test the feasibility of predicting the closure of medical and dental clinics (MCs and DCs, respectively) and investigate important factors associated with their closure using machine running techniques. The units of analysis were MCs and DCs. This study used health insurance administrative data. The participants of this study ran and closed clinics between January 1, 2020, and December 31, 2021. Using all closed clinics, closed and run clinics were selected at a ratio of 1:2 based on the locality of study participants using the propensity matching score of logistic regression. This study used 23 and 19 variables to predict the closure of MCs and DCs, respectively. Key variables were extracted using permutation importance and the sequential feature selection technique. Finally, this study used 5 and 6 variables of MCs and DCs, respectively, for model learning. Furthermore, four machine learning techniques were used: (1) logistic regression, (2) support vector machine, (3) random forest (RF), and (4) Extreme Gradient Boost. This study evaluated the modeling accuracy using the area under curve (AUC) method and presented important factors critically affecting closures. This study used SAS (version 9.4; SAS Institute Inc) and Python (version 3.7.9; Python Software Foundation). The best-fit model for the closure of MCs with cross-validation was the support vector machine (AUC 0.762, 95% CI 0.746-0.777; P<.001) followed by RF (AUC 0.736, 95% CI 0.720-0.752; P<.001). The best-fit model for DCs was Extreme Gradient Boost (AUC 0.700, 95% CI 0.675-0.725; P<.001) followed by RF (AUC 0.687, 95% CI 0.661-0.712; P<.001). The most significant factor associated with the closure of MCs was years of operation, followed by population growth, population, and percentage of medical specialties. In contrast, the main factor affecting the closure of DCs was the number of patients, followed by annual variation in the number of patients, year of operation, and percentage of dental specialists. This study showed that machine running methods are useful tools for predicting the closure of small medical facilities with a moderate level of accuracy. Essential factors affecting medical facility closure also differed between MCs and DCs. Developing good models would prevent unnecessary medical facility closures at the national level.

Population dynamics of the flathead grey mullet (Mugil cephalus Linnaeus 1758) in the Narmada estuary on the west coast of India

The population dynamics of flathead grey mullet, Mugil cephalus, were evaluated using length-frequency data collected from the Narmada estuary monthly between January 2018 and December 2019. The population parameters were assessed and calculated using the FiSAT-II software tool (FAO-ICLARM Stock Assessment Tools) after the estimation data were divided into 10 mm class intervals. A total of 419 specimens were collected, with an average length range of 171.14±58.15 mm and an average weight of 58.15±45.65 g, respectively. The length-weight relationships were established as W = 0.0105 L2.979. Length-frequency data revealed that length groups 140–149 (15.75 %) and 130–139 mm (13.37 %) dominated the commercial catches of M. cephalus at the Narmada estuary. Different growth parameters were estimated as L∞ = 309.75 mm, K = 0.41 yr−1 and t0 = −0.0013 years. The estimated values of mortality coefficients Z, M, and F were 1.06 yr−1, 0.52 yr−1 and 0.54 yr−1, respectively. The value of exploitation ratio (E) by using the length-converted catch curve method was established as 0.51, which was found to be a little high from the optimum value (0.50). The recruitment was found to be continuous almost throughout the year, with two peaks, once during February to May and another during August to October. The maximum sustainable yield (MSY) was estimated at 970.218 t if the suggested length at first capture (Lc = 123.44 mm TL) is maintained throughout the capture periods. The fishing pressure was found to be slightly excessive for the current stocks, which should be considered for proper management of the fishery in the Narmada estuary.

PVC membrane bulk optode incorporating 4-nitrobenzo-15-crown-5 and sodium tetrakis(1-imidazolyl) borate for the pico-molar determination of silver ion in pharmaceutical formulation

Silver ion (Ag+) is of harmful effects to both environment and human health. Ag+ soluble compounds and salts is used in treating mental illness, epilepsy, nicotine addiction, gastroenteritis, and infectious diseases, including syphilis and gonorrhea, and as anti-infective dermatological agent for controlling nose bleeding. However, high Ag+ doses cause several harmful effects to human health such as irreversible pigmentation of skin and eye, and problems to liver and kidney. A bulk membrane Optode is proposed in this work to measure the Ag+ concentration in the pharmaceutical formulations. The membrane optode is prepared from the ionophore 4-nitobenzo-15-crown-5, the ion-exchanger sodium tetrakis (imidazolyl) borate, the plasticizer o-nitrophenyl octyl ether, and the chromoionophore ETH 5294; these components are dissolved in the PVC/THF slurry to form the membrane. The optode is studied by atomic force microscope and UV–visible spectrophotometer, and its spectrum exhibits two maximum wavelengths of 550 and 665 nm, and response for Ag+ at these maximum wavelengths is reproducible in the concentration range of 10–11 to 10–8 M using acetate buffer of pH 5.0, with very low detection limit of 8.8 × 10–12 M. The most important feature in this work is the selectivity improvement for Ag+ over all interfering ions; the selectivity coefficient logarithm logKAg+,cationopt\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${logK}_{Ag+, cation}^{opt}$$\\end{document} is found to be − 4.3 for Cu2+, − 5.6 for Ni2+ and − 5.0 for Cd2+. The response mechanism is studied by FTIR, and it depends on ion-exchange of Ag+ and sodium imidazolyl borate, followed by the host–guest complexation between Ag+ and the crown ionophore, which is accompanied by concomitant deprotonation of the chromoionphore. The optode has a response time of 2–3 min within lifetime of 10 days with the same response. The optode can be applied successfully for Ag+ determination in the pharmaceutical formulation, PinkEye Relief® eye drop, which is used for treating inflammation, redness and water discharge of the eye; the high recovery and low standard deviation of the results using calibration curve method confirm the accuracy and precision of the proposed optode for its application in real samples.

Influence of electron and hole doping on structural, Magnetic, and magnetocaloric properties of Ba2FeMoO6 double perovskite

The impact of Sm3+ and Ag+ doping at the Ba2+ site on the structural, magnetic, and magnetocaloric properties of Ba2FeMoO6 (BFMO) double perovskite was compared. Samples were synthesized using the sol–gel method. Rietveld refinement patterns of samples Ba2-xAxFeMoO6 (A=Sm, Ag, x = 0.0, 0.025) showed all samples had cubic structures with Fm-3 m space group and no impurity. The lattice parameters and unit cell of the Ba1.975Sm0.025FeMoO6 (BSFMO), and Ba1.975Ag0.025FeMoO6 (BAFMO) samples decreased compared to the parent sample. X-ray photoelectron spectroscopy confirmed that Fe and Mo ions were mixed valence for all samples. The results of magnetization versus temperature (M−T) showed an increase for BSFMO and a decrease for BAFMO samples under an external magnetic field of 0.05 T. The magnetic study indicated a decrease in the transition temperature for BSFMO (∼303 K) and an increase for BAFMO (∼321 K) to compare with the parent sample (∼310 K). The maximum value of magnetic entropy changes (ΔSMmax)of the BFMO, BSFMO, and BAFMO samples at H=3 T obtained 0.92 Jkg-1K−1, 0.75 Jkg-1K−1, and 0.39 Jkg-1K−1, respectively, and the second-order magnetic phase occurred around the transition temperature. For BFMO, BSFMO, and BAFMO, the relative cooling power (RCP) is 34.48 J/kg, 32.25 J/kg, and 21.97 J/kg, respectively. The second-order magnetic phase transition occurred around the transition temperature for all samples using the energy criterion as well as the universal curve method. In addition, we used Widom’s law to determine the critical exponent of the samples, which provides a new thermodynamic method to determine the magnetic phase transition. The results of the magnetocaloric effect indicate that although the maximum entropy changes and relative cooling decrease with doping Ag and Sm ions, they have a wide temperature range of magnetic entropy changes compared to the pristine sample, which can be candidates for magnetic cooling.

Fatigue assessment of structural components through the Effective Critical Plane factor

The integrity assessment of structural components under complex loading conditions relies on the evaluation of the fatigue damage typically arising from stress concentrations, such as geometric irregularities, notches, weld beads, grooves etc.. Various methodologies, including the Notch Stress Approach (NSA), the Theory of Critical Distances (TCD), the Strain Energy Density (SED), and the Critical Plane (CP) concept, have been pivotal in assessing fatigue strength for notched and welded components. Recent works combine some of the above mentioned methodologies, while other works propose to vary the embedded parameters accounting for the loading type or the fatigue lives, trying to improve the accuracy of the fatigue assessment process. This paper introduces a novel approach, the Effective Critical Plane (ECP), which is founded on the critical plane concept. The CP factor is, however, calculated starting from an averaged, over a small volume, stress–strain field. The size of the averaging volume is assumed to be a material parameter and is determined by a best fitting procedure over different experimental data sets. The novel approach is illustrated by means of the Fatemi-Socie and the Smith-Watson-Topper CP damage factors. Its potential application to other CP formulations is straightforward, as well. Literature experimental data for low carbon steel specimens possessing different notches and loading conditions are used to validate the method’s capability in accurately determining the fatigue life and to set the radius of the averaging volume for the given material and CP parameter. A spherical volume or circular area are used in case of fully 3D or 2D numerical models, respectively. Results are compared to those of some of already existing methods, namely SED, TCD and the Modified Wöhler Curve Method.

Multiplex methylation detection assays using a blocking FRET probe with machine learning-assisted quantitative melting curve method targeting early-stage breast cancer

Breast cancer (BC) is the second most prevalent form of cancer, and poses a significant threat to public health. DNA methylation is an ideal marker for the early detection of BC. Fluorescence quantitative polymerase chain reaction (PCR)-based DNA methylation detection is simpler and faster but is constrained by its multiplexing capability and specificity. To address this, we developed a multiplex quantitative methylation PCR assay for the simultaneous analysis of methylation status at multiple sites specific to BC (cg11754974, cg13828440, cg18637238, and cg16652347). The machine learning model was trained using 1200 cases of multipeak data to enhance the melting curve resolution. Performance testing demonstrated the method’s ability to selectively amplify methylated genes at a DNA concentration of 1 × 105 copies μL−1, with high replicability (coefficient of variation <5 %) and mutation detection capabilities as low as 10 %. When applied to 80 clinical BC samples, the assay effectively distinguished patients with early-stage BC from normal controls, achieving an area under the curve of 0.8938, sensitivity of 83.33 %, and specificity of 84.62 %. Our essay exhibits superior clinical performance when compared to the quantitative methylation-specific PCR assays for noninvasive detection of early-stage BC, which is poised to become a favorable clinical diagnostic method for early-stage BC owing to its simplicity, speed, and capacity to improve diagnostic accuracy.

A novel evaluation mode of Nao An Capsules using multi-wavelength fusion fingerprint combined with quantitative analysis of multi-components by a single marker method and antioxidant activity

Nao An Capsules (NAC) are utilized in the acute phase of cerebral thrombosis and are appropriate for patients in the recovery stage exhibiting symptoms of qi deficiency and blood stasis. Nevertheless, there has been a lack of recent research on the overall quality control of NAC. The objective of this study is to establish a comprehensive quality control strategy for NAC. This article presents a methodology based on the average linear quantitative fingerprinting method (ALQFM) in conjunction with multi-wavelength high performance liquid chromatography (HPLC) fusion fingerprinting, quantized Fourier transform infrared (FT-IR) spectroscopy and ultraviolet (UV) spectral techniques to comprehensively evaluate NAC from both qualitative and quantitative perspectives. Subsequently, quantitative analysis of multi-components by a single marker (QAMS) method and the Standard Curve Method (SCM) were used to quantitatively determine 10 quality markers (Q-markers) in 22 batches of samples, with the results indicating that QAMS is a reliable method for quantifying active ingredients. Chemometrics methods such as principal component analysis (PCA) and principal component analysis (HCA) were also used to analyze the quality of samples. To achieve a thorough and methodical evaluation, a combined assessment of the three fingerprints was executed. Subsequently, an in vitro antioxidant activity experiment was performed utilizing the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical-scavenging technique. By employing a partial least squares (PLS) model, the correlation between HPLC fingerprint chromatography and antioxidant activity was investigated. The study found that out of the 59 common peaks in the five-wavelength fusion fingerprint spectra of NAC, 33 peaks exhibit antioxidant activity. In this study, multi-wavelength fusion HPLC, quantized FT-IR and UV were jointly used to effectively identify functional groups and fingerprint information in compounds. It can fully and quickly obtain the fingerprint information of the compounds in the sample. NAC multi-components quantification and overall quality evaluation were performed using ALQFM and QAMS and chemometrics methods. We have developed a new approach for comprehensive, rapid, and cost-effective quality control of traditional Chinese medicine (TCM) compound preparations.

Renormalized Internally Contracted Multireference Coupled Cluster with Perturbative Triples.

In this work, we combine the many-body formulation of the internally contracted multireference coupled cluster (ic-MRCC) method with Evangelista's multireference formulation of the driven similarity renormalization group (DSRG). The DSRG method can be viewed as a unitary multireference coupled cluster theory, which renormalizes the amplitudes based on a flow equation approach to eliminate numerical instabilities. We extend this approach by demonstrating that the unitary flow equation approach can be adapted for nonunitary transformations, rationalizing the renormalization of ic-MRCC amplitudes. We denote the new approach, the renormalized ic-MRCC (ric-MRCC) method. To achieve high accuracy with a reasonable computational cost, we introduce a new approximation to the Baker-Campbell-Hausdorff expansion. We fully consider the linear commutator while approximating the quadratic commutator, for which we neglect specific contractions involving amplitudes with active indices. Moreover, we introduce approximate perturbative triples to obtain the ric-MRCCSD[T] method. We demonstrate the accuracy of our approaches in comparison to advanced multireference methods for the potential energy curves of H8, F2, H2O, N2, and Cr2. Additionally, we show that ric-MRCCSD and ric-MRCSSD[T] match the accuracy of CCSD(T) for evaluating spectroscopic constants and of full configuration interaction energies for a set of small molecules.

Infrared spectral library of tooth enamel from African ungulates for accurate electron spin resonance dating

Electron spin resonance coupled with uranium-series dating (ESR/U-series) of carbonate hydroxyapatite in tooth enamel is the main technique used to obtain age determinations from Pleistocene fossils beyond the range of radiocarbon dating. This chronological information allows to better understand diachronic change in the palaeontological record, especially with regard to the evolution of the genus Homo. Given the relative paucity of human teeth at palaeontological and archaeological localities, ESR/U-series is widely applied to the teeth of ungulate species. However, the accuracy of ESR/U-series ages is greatly affected by the incorporation of uranium in the enamel during burial in sediments. It has been shown that uranium content is positively correlated with an increased degree of atomic order in carbonate hydroxyapatite crystals, the latter determined using infrared spectroscopy. Here we present a reference infrared spectral library of tooth enamel from African ungulates, based on the grinding curve method, which serves as baseline to track the diagenetic history of carbonate hydroxyapatite in different species and thus select the best-preserved specimens for dating.