Method For Simultaneous Identification Research Articles

Machine Learning-Assisted Eu(III)-Functionalized HOF-on-HOF Composite-Based Sensor Platform for Precise and Visual Identification of Multiple Pesticides.

Precise and rapid identification of pesticides is crucial to ensure a green environment, food safety, and human health. However, complex sample environments often hinder precise identification, especially for simultaneous differentiation of multiple pesticides. Herein, we first synthesize a Eu(III)-functionalized HOF-on-HOF composite (Eu@PFC-1@MA-TPA) and then utilize principal component analysis (PCA) and a machine learning (ML) algorithm to achieve simultaneous identification of the pesticides 2,6-dichloro-4-nitroaniline (DCN) and thiabendazole (TBZ) and their mixtures. Eu@PFC-1@MA-TPA displays high quantitative identification ability, which can distinguish single DCN and TBZ as low as 1 μM and their mixtures at 5 μM through PCA. In addition, the hydrogel film Eu@PFC-1@MA-TPA/AG is fabricated to monitor DCN and TBZ in drinking water, tap water, river water, and apple juice with high sensitivity. Furthermore, based on the obvious fluorescence color variance of pesticides, Eu@PFC-1@MA-TPA/AG achieves visual and in situ imaging detection of single DCN and TBZ and their mixtures. More importantly, we construct an intelligent artificial vision platform integrating Eu@PFC-1@MA-TPA/AG with a DenseNet algorithm, which can identify the concentrations and types of DCN and TBZ and their mixtures within 1 s with over 98% accuracy. This work develops a precise and rapid analysis method for simultaneous identification of multiple pesticides through combining a visualized fluorescence sensor and an ML algorithm.

HPLC Method for Simultaneous Identification and Quantification of Enrofloxacin, Bromhexine*HCl and Their Related Substances/Degradation Products, in Veterinary Pharmaceutical Product, Bromflovet

HPLC Method for Simultaneous Identification and Quantification of Enrofloxacin, Bromhexine*HCl and Their Related Substances/Degradation Products, in Veterinary Pharmaceutical Product, Bromflovet

Development and validation of a multiclass method for the determination of veterinary drug residues in honey

ABSTRACT This study developed and validated an analytical method for simultaneous identification and quantification of 41 veterinary drugs in honey using liquid liquid extraction (LLE) and liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry (LC-Q-Orbitrap HRMS). The method was validated in accordance with Commission Implementing Regulation (CIR) EU 2021/808 at five different concentrations ranging from 0.075 to 50 μg/kg. The mean recoveries ranged from 70 to 105, while repeatability values were all below 17%. The linearity, as correlation coefficients (R2) ranged from 0.994 to 1. The limits of detection (LOD) and limits of quantification (LOQ) were in the range of 0.006–3.92 μg/kg and 0.011–6.54 μg/kg, respectively. The decision limit (CCα) and detection capability (CCβ) ranges were 0.0759–5.33 µg/kg and 0.0804–6.08 µg/kg, respectively. Of the 263 honey samples that were collected from local markets in Egypt, 47.5% had antibiotic residues. The mean concentration (µg/kg) and detection frequency (%) of the five most frequently detected antibiotics in the honey samples were as follows: trimethoprim (143.25 µg/kg and 39.9%), sulfamethoxazole (136.69 µg/kg and 30.7%), sulphadiazine (77.19 µg/kg and 18.6%), tylosin (184.37 µg/kg and 18.2%), and ciprofloxacin (185.33 µg/kg and 7.60%). The applicability of the developed method was proven through successful three proficiency testing (PT). The proposed method was demonstrated to be reliable for the simultaneous analysis of multi-class veterinary drugs in honey.

A multiplex DNA probe-based method for simultaneous identification of adulteration in meat samples

Meat adulteration and admixing are prevalent malpractices observed in processed and raw meat samples, where the consumption of adulterated meat has been associated with food allergies, financial losses, and consumer distrust. Meat authentication is pivotal to address these concerns. The meat authenticity can be determined through genetic, protein, and immunological markers and advanced detection methods. However, these methods often target a single species and lack the specificity to distinguish closely related species. Here, in the present study, we have developed a multiplex detection method based on the species-specific primers and probes, that can target four meat species in one reaction. The developed method amplifies the mitochondrial genomic regions of chicken, pork, sheep and goat using TaqMan multiplex probe-based RT-qPCR assay. Unique pairs of species-specific primers and probes that target specific mitochondrial DNA (mtDNA) regions of each species were designed and screened for specificity and sensitivity. The detection limit for species identification using the designed primers in real-time qPCR assays was 0.1 picogram per microliter (pg/μL) DNA detected in singleplex reaction and facilitates the simultaneous detection of closely related species, such as goat and sheep. Further, DNA-based probes were utilized in a multiplex real-time qPCR assay to identify chicken, pork, sheep and goat DNA in a single tube reaction. The multiplex assay was validated for raw and processed meat products, demonstrating its applications in ensuring the quality of meat products and safeguarding consumer interests.

Deep multi-task learning structure for segmentation and classification of supratentorial brain tumors in MR images

Identification of brain tumors border and determination of their possible pathology in MR images is an important step in pre-operation analyzing of this serious medical condition. Manual segmentation and classification of brain tumors could be challenge full in neurosurgical practice because of vast differences between brain tumors characteristic such as shape, border irregularity, consistency and etc. as well as interobserver variations. To solve this problem, some automatic methods have been proposed for brain tumors segmentation or classification during recent years, but an intelligence-based method for simultaneous identification of tumor type and tumor border in MR images has not proposed till now. Here, we have planned a unique automatic model includes a common encoder for feature representation, one decoder for segmentation and a multi-layer perceptron for classification of three common primary brain tumors (meningiomas, gliomas and pituitary adenomas) in brain MR images. The proposed model was examined on a brain tumor images dataset and the output were evaluated in both multi-task and single-task learning model. The multi-task learning model gains significant improvement in simultaneous classification and segmentation of brain tumors with promising accuracy of 97% for each task. So, this model could serve as a primary screening tool for early diagnosis of common primary brain tumors in general practice with a high success rate.

Application of a modified tetra-primer ARMS–PCR assay for rapid Panax species identity authentication in ginseng products

Panax ginseng products can be adulterated with materials from other Panax species. The purpose of this study is to provide a rapid P. ginseng authentication method for simultaneous identification of P. ginseng and detection of adulteration in ginseng products at different processing stages. First, a tetra-primer ARMS–PCR assay was designed based on a single-nucleotide polymorphism (SNP) within the trnL-trnF region and was tested at 28 PCR cycles with DNA extracted from Botanical Reference Materials (BRMs). Next, 5′ end random nucleotide and 3′ terminus phosphorothioates linkage modifications were incorporated into the inner primers to improve sensitivity and specificity at 40 PCR cycles. Finally, the modified assay was validated using characterized market ginseng materials and the detection limit was determined. The modified tetra-primer ARMS–PCR assay can achieve the desired sensitivity and specificity using one set of reaction conditions in ginseng materials at different stages. In validation, it was able to correctly identify target species P. ginseng and differentiate it from closely related species. This study suggests that the modified tetra-primer ARMS–PCR assay can be used for the rapid, species identity authentication of P. ginseng material in ginseng products. This assay can be used to complement chemical analytical methods in quality control, so both species identity and processing attributes of ginseng products can be efficiently addressed.

A Smoothing EKF-UI-WDF Method for Simultaneous Identification of Structural Systems and Unknown Seismic Inputs without Direct Feedthrough

It is of great significance to identify structural state-parameters and the unknown seismic inputs using partial measurements of structural acceleration responses for the rapid evaluation of structures after unknown seismic excitations. However, unknown seismic inputs do not directly appear in the observation equations of measured absolute floor accelerations of building structures, i.e., there is no direct feedthrough of unknown seismic inputs in the observation equations. Current methods for the identification of joint structural systems and unknown inputs are either inapplicable or greatly influenced by measurement noises. In this paper, a method so-called smoothing extended Kalman filter with unknown input without direct feedthrough (smoothing EKF-UI-WDF) is proposed. The identification algorithm is derived in the framework of minimum-variance unbiased estimation (MVUE), and the smoothing technique is adopted to introduce subsequent observation steps in the current identification step. Then, structural states, parameters, and unknown seismic excitations without direct feedthrough are simultaneously identified recursively with only a few steps delay, and the identification results are tolerant to measurement noises. The proposed method is verified by a numerical simulation model and a practical engineering case study. Both identification results validate the effectiveness of the proposed method for the simultaneous identification of structural systems and seismic inputs without direct feedthrough.

Development of qualitative GC MS method for simultaneous identification of PM-CCM a modified illicit drugs preparation and its modern-day application in drug-facilitated crimes

Prescriptions for psychoactive substances such as Pregabalin, Methamphetamine, Caffeine, Clonazepam and Mirtazapine (PM-CCM) are common in the treatment of a variety of disorders. Indeed, the PM-CCM has been used in different therapeutic areas, including insomnia, anxiety, seizure disorders, etc. Unfortunately, these psychoactive substances are present in the illegal street market, leading to a lot of drug abuse among some addicted users, road insecurity and suicide. Hence, it has become essential to validate and develop a rapid and effective method to analyze the PM-CCM, a modified illicit drug, for drug abuse in the forensic sciences. A simple, rapid, specific and sensitive Gas Chromatography-Mass Spectrometry(GC-MS) method has been developed for the identification of Pregabalin, Methamphetamine, Caffeine, Clonazepam and Mirtazapine (PM-CCM) in forensic exhibits. At room temperature, the sample was ultrasonicated for 5 minutes before being extracted with methanol. A highly precise auto-injector is used to inject a very small quantity of samples for analysis. Helium is used as a carrier gas with a flow rate of 1 ml/min. The separation of PM-CCM was performed on SH-RXi-5 MS, ID.25 mm, film thickness. 25 µm, length of 30 m column. The constituents of PM-CCM were identified by the mass-to-charge ratio (m/z ratio) of fragments of the parent compound by comparing them with the NIST-17 MS Library. Separation and identification of PM-CCM were achieved within a 15-minute run. The proposed method has been successfully used for the routine analysis of PM-CCM in complex illicit drug preparations and in forensic exhibits as well. The application of above discussed qualitative analysis method and screening of PM-CCM, modified illicit drug samples demonstrates the potential and applicability of the technique to the fast chemical profiling of illicit samples.

Method development for simultaneous estimation of Amlodipine Besylate and Perindopril Tertbutyl amine in fixed-dose

The fixed-dose combination of Amlodipine Besylate (ADB) with Perindopril Tertbutylamine (PTBA) drug is used to treat patients with mild-to-moderate hypertension. In recent times researchers are interested to find the efficient analytical method development and validation for the simultaneous determination of ADB and PTBA in a fixed-dose, film-coated tablet. Therefore, the current study was performed with a reverse-phase liquid chromatography method developed to simultaneously analyze ADB and PTBA in film-coated tablets as fixed-dose combinations. The linearity of the proposed method was calculated by preparing six different mixtures of both ADB and PTBA in the mobile phase. The concentration of both the analytes was analyzed at 56mg/100 mL to 84mg/100 mL and 32mg/100 mL to 48mg/100 mL, respectively. The ratio of acetonitrile and phosphate buffer was 35:65. The flow rate was adjusted to 1.5 ml per minute to reduce the retention time. The validation study was performed for the parameters specificity, linearity, precision, range, limit of detection, limit of quantification, accuracy/biasness, and robustness. The relative percentage standard deviation for Perindopril Tertbutyl amine was 0.148%, and for Amlodipine is 0.312%. These results show that the advanced analysis method for simultaneous analysis of fixed-dose is precise. The theoretical IR spectra were also calculated by Gaussian 9.2 by employing the B3LYP functional at density functional theory (DFT) level study. All these parameters studied in this work authenticate the effectiveness of the developed validation method and ensure its repeatability/reproducibility accordingly. To the best of our knowledge, this is the first time to develop a new fast, and easy method for simultaneous identification and quantification of ADB and PTBA by high-performance liquid chromatography (HPLC) with a time-efficient and cost-effective approach.

Optimization of HPLC-MS/MS method for determination of antimalarial adulterants in herbal products.

The use of herbal products is booming all over the world because of being believed as safer than conventional drugs and free of side effects. However, there are untrustworthy manufacturers who adulterate herbal products by adding conventional drugs which might eventually lead to microbial resistance and herb-to-drug interactions. There is a need to develop methods for detecting adulterants in herbal products. A high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method for simultaneous identification and determination of conventional antimalarials (chloroquine, quinine, sulfadoxine, pyrimethamine, mefloquine, lumefantrine, amodiaquine, artemisinin, dihydroartemisinin, artesunate and artemether) in herbal products was developed. Stable isotopically labelled compounds (artemether-d3, quindine-d3, and sulfadoxine-d3) were used as internal standards (ISs) for quantitative analysis. Extraction of analytes was performed using methanol: water: formic acid (90:10:0.1, v/v) and chromatographic separation was done in a gradient mode using mobile phase A: Ultrapure water containing 0.1% formic acid and 1mM ammonium formate and mobile phase B: Acetonitrile/methanol (50:50) containing 0.1% formic acid and 1mM ammonium formate. The calibration curves were linear (r2 ≥ 0.991) over the range of 0.001-0.3µgmL-1 for all compounds. The limit of detection (LOD) ranged from 0.002 to 0.02μgmL-1 while the limit of quantification (LOQ) ranged from 0.006 to 0.08μgmL-1. Accuracy, expressed as recovery of spiked herbal products ranged from 52 to 128%. The precision, expressed as percent relative standard deviation (%RSD) at two concentration levels, ranged from 1.0 to 13.8%. The matrix effect expressed as the matrix factor (MF) ranged from 0.77 to 0.97. The developed method was used to identify and quantify conventional antimalarials in herbal product samples from Tanzania. Ten out of 50 herbal products were found to contain amodiaquine, sulfadoxine, pyrimethamine, mefloquine, dihydroartemisinin, artemether and lumefantrine. The developed method is considered a valuable tool for getting a better understanding of the adulteration of conventional antimalarials in herbal products.

Generation of Friction Coefficient Function for Hot Forging with Autopilot FEA and Simultaneous Identification of Friction and Heat Transfer Coefficients

An automatic simultaneous identification method for the friction coefficient and heat transfer coefficient is proposed for accurate hot forging process simulation. We established an autopilot finite element analysis system (autopilot FEA; APFEA) that repeats the FEA of the hot ring compression test, minimizing the errors, defined by the compression load and minimum inner diameter reduction ratio, between results of the experiment and the FEA with a machine-learningbased optimization algorithm. The automatic generation of a surface-pressure-dependent friction coefficient function, the selection of the friction law from Coulomb’s and shear friction lows, and the automatic simultaneous identification of the sigmoid curve friction and heat transfer coefficient functions are performed using the APFEA system and the results of a hot ring compression test performed with a quasi-air-suspended heating tester designed by us. As a result, the optimized friction and heat transfer parameters are identified, and the reasonableness of the friction law is evaluated.

Development and optimization of a method based on dispersive solid phase extraction followed by ultra-high-performance liquid chromatography-quadrupole/orbitrap high-resolution mass spectrometry for simultaneous determination of 30 mycotoxins in Citrus products.

Citrus, a raw material widely used in food and medicine, is susceptible to fungal infection and its metabolites during growth, transportation, and storage. Thus, monitoring the residual levels of various mycotoxins in Citrus traditional Chinese medicines and related products is crucial. This study described a simple, reliable, and sensitive method for simultaneous identification and quantification of 30 mycotoxins in Citrus products. The method is based on modified quick, easy, cheap, effective, rugged, and safe extraction and purification followed by ultra-high-performance liquid chromatography-quadrupole/orbitrap high-resolution mass spectrometry. The limit of detection ranged from 0.10 to 1.50μg/kg, and the quantification ranged from 0.25 to 5.00μg/kg. The recoveries at three spiked levels were 64.90-99.72% and the relative standard deviation was less than 12%. The method was applied to 55 Citrus samples. The detection rates of tentoxin and mycophenolic acid were the highest, reaching 22.7% and with concentration ranges of 0.33-1.03 and 0.57-2.09μg/kg, respectively. All contamination levels were below the maximum residue limits recommended by the European Commission and China. These results could be used to establish guidelines for screening mycotoxins in Citrus products and the limits of acceptable levels.

Establishment of the thin-layer chromatography-surface-enhanced Raman spectroscopy and chemometrics method for simultaneous identification of eleven illegal drugs in anti-rheumatic health food

The risk of the illegal addition of anti-inflammatory and analgesic chemical drugs in anti-rheumatic health foods should not be ignored. Market supervision and rapid on-site detection technology need to be strengthened. Thin-layer chromatography-surface-enhanced Raman spectroscopy (TLC-SERS), which has the advantages of simple operation, fast separation, and qualitative and quantitative detection, was used in this study. And these eleven chemical drugs (acetaminophen, acetylsalicylic acid, aminophenazone, dexamethasone, diclofenac sodium, hydrocortisone, indometacin, naproxen, phenylbutazone, piroxicam, prednisone 21-acetate) that may be added to anti-rheumatic health foods have been simultaneously identified by TLC-SERS combined with chemometrics method. The characteristic signals of the separated drug spots were collected by SERS, which were optimized by the gold colloidal nanoparticles' volume and integration time. Then SERS was subjected to principal component analysis (PCA) to reduce dimensionality and combined with the pattern recognition methods in chemometrics, such as PCA-Linear Discriminant Analysis (LDA), PCA-K Nearest Neighbor and PCA-Support Vector Machine, and eleven drug components were judged and identified. Moreover, the predictive performances of different models were also analyzed and compared. The results showed that the TLC plate and four organic solvents of petroleum ether, chloroform, ethyl acetate and acetic acid were selected as the developing agent. The dropping amount of gold colloidal nanoparticles and the integration time were set and optimized. The limit of detection of the simultaneous detection method of SERS was 10–100 mg/L. Furthermore, SERS was preprocessed by Gap-Segment 2nd Derivative, and then the PCA-LDA model was established, and the model's prediction accuracy can reach 100%. The method is simple, rapid, sensitive and accurate, and has low experimental instruments and equipment requirements. It is suitable for the on-site simultaneous detection of various anti-inflammatory and analgesic chemical drugs in health foods. It can also provide guarantee and support for the establishment of appropriate rapid detection methods and the development of supervision technology.

Simultaneous Load Identification Method Based on Hybrid Features and Genetic Algorithm for Nonintrusive Load Monitoring

Nonintrusive load monitoring (NILM) is a widely accepted technology to conduct load monitoring. Many effective methods have been established to make NILM more practical. However, the focus of current methods is mainly on the identification accuracy and efficiency of single load under the individual appliance operated independently, which have limited support for the identification problem under multiple appliances operated simultaneously. Therefore, a simultaneous identification method is proposed to efficiently identify the total load under multiple appliances operated simultaneously in this paper. The proposed identification method mainly consists of three parts: hybrid features extraction, simultaneous identification optimization model construction, and frequency-weighting-factor-based genetic algorithm (FWF-GA). Firstly, the hybrid feature model, which integrates the features of active power, reactive power, and harmonic magnitude, is constructed by hybrid features extraction. Secondly, the simultaneous identification optimization model is constructed by employing the features of active and reactive power. Thirdly, the developed FWF-GA is used to solve the simultaneous identification optimization problem. In FWF-GA, the relative errors of active power, reactive power, and the frequency-weighting factor of harmonic magnitude are used to evaluate the fitness of an individual. Finally, a NILM practice to identify household appliances is used to demonstrate the validity of the proposed method.

Multiplex PCR method for simultaneous identification of Xanthii Fructus and its adulterants

The purpose of this study is to establish a molecular method to identify Xanthii Fructus and two adulterants, the fruits of Xanthium mongolicum and X. italicum. Xanthii Fructus is the fruit of X. sibiricum, which is a Chinese herbal medicine used clinically to treat allergic rhinitis. The fruits of X. mongolicum and X. italicum have strong morphological similarities with Xanthii Fructus, while their safety of medication cannot be guaranteed. The genomes of X. sibiricum, X. mongolicum, and X. italicum were sequenced, which generated sequences of 2.21, 2.24, and 2.54 Gb, respectively. Based on the 76 specific contigs screened out by BLASTN and Bowtie 2, the corresponding primers were designed by Primer 5.0. Three pairs of primers with stable amplification efficiency and good reproducibility were screened out to establish a multiplex PCR method based on the PCR amplification results. Further, the annealing temperature, the amount of DNA template, the number of cycles, different DNA polymerases, and different PCR thermal cyclers were optimized. Fragments of 262 bp and 458 bp from X. sibiricum, 260, 454, and 927 bp from X. mongolicum, and 260 bp and 926 bp from X. italicum were amplified under the following conditions: the annealing temperature of 52 ℃, 35 cycles, 30 ng template DNA. Then, the established method was used to detect 18 samples of X. sibiricum, 17 samples of X. mongolicum, and 12 samples of X. italicum. The results showed that all the samples had positive results, which were consistent with the morphological identification results, thus proving the stability and reliability of the established method. Combining genome sequencing technology and multiplex PCR method to identify Xanthii Fructus and its adulterants can not only obtain the difference in genetic background but also facilitate the design of reliable primers. The multiplex PCR have high specificity and repeatability, providing a new method for the molecular identification of Xanthii Fructus.

Identification of Multiple Mechanical Properties of Laminates from a Single Compressive Test.

In-plane elastic and interlaminar properties of composite laminates are commonly obtained through separate experiments. In this paper, a simultaneous identification method for both properties using a single experiment is proposed. The mechanical properties of laminates were treated as uncertainties and Bayesian inference was employed with measured strain-load curves in compression tests of laminates with embedded delamination. The strain–load curves were separated into two stages: the pre-delamination stage and the post-delamination stage. Sensitivity analysis was carried out to determine the critical properties at different stages, in order to alleviate the ill-posed problem in inference. Results showed that the in-plane Young’s modulus and shear modulus in elastic properties are dominant in the pre-delamination stage, and the interlaminar strength and type I fracture toughness in interlaminar properties are dominant in the post-delamination stage. Five times of property identification were carried out; the maximum coefficient of variation of identified properties was less than 1.11%, and the maximum error between the mean values of the identified properties and the ones from standard experiments was less than 5.44%. The proposed method can reduce time and cost in obtaining multiple mechanical properties of laminates.

A novel multiplex PCR method for simultaneous identification of hypervirulent Listeria monocytogenes clonal complex 87 and CC88 strains in China

Listeria monocytogenes is an important foodborne pathogen worldwide, with 20–30% fatality rate in vulnerable persons. The hypervirulent L. monocytogenes clonal complex (CC) 87 strains have emerging both in food production environments and clinic cases. The objective of this study was to develop a multiplex PCR to simultaneously detect L. monocytogenes CC87 and CC88 strains based on pan-genome analysis. A novel multiplex PCR comprised of genes A6K41_13255 (specific for CC87 and 88), BCW_4260_01987 group_8135 (specific for CC88) and 02-1103_01073 group_5869 (specific for L. monocytogenes) were designed. The specificity of this multiplex PCR was robust verified with other CCs of L. monocytogenes and other species strains. The detection limit of this multiplex PCR for CC87 and CC88 were 1.7 × 104 cfu/mL and 2.1 × 104 cfu/mL, respectively. This multiplex PCR could accurately detect CC87 and CC88 strains with the interference of different ratios of L. monocytogenes CC8, CC9, CC121, CC155, and L. innocua strains. Furthermore, this multiplex PCR method could successfully detect 1.9 × 104 cfu/mL of L. monocytogenes CC87 and 1.7 × 104 cfu/mL CC88 strains in artificially contaminated milk after 9 h enrichment, respectively. In addition, this multiplex PCR could accurately detect CC87 isolates in food samples within 48 h, which was faster than the routine MLST analysis. In conclusion, this novel multiplex PCR offers a promising approach for accurate, inexpensive, and rapid detection of L. monocytogenes CC87 and CC88 strains simultaneously, which could apply to surveillance the prevalence of CC87 and CC88 strains in both food and food production environments and to evaluate the effect of disinfection measures for controlling the persistent L. monocytogenes contamination.

Stability-Indicating New RP-UPLC Method for Simultaneous Determination of a Quaternary Mixture of Paracetamol, Pseudoephedrine, Chlorpheniramine, and Sodium Benzoate in (Cold-Flu) Syrup Dosage Form.

A combination of paracetamol, pseudoephedrine, chlorpheniramine, and sodium benzoate in (Cold-Flu) 1,2,3 Syrup dosage form is specified for the treatment of common cold and flu symptoms. The functional role of this study is to develop a novel, reliable, and selective stability-indicating reversed-phase ultra-performance liquid chromatography (RP-UPLC) method for simultaneous identification of a quaternary mixture of paracetamol, pseudoephedrine, chlorpheniramine, and sodium benzoate in (Cold-Flu) 1,2,3 Syrup dosage form. The specific method is accomplished using an Acquity UPLC HSS T3 C18 column (2.1 mm × 100 mm), 1.8 µm particle size with pore size 100 Å, utilizing a mixture of purified water-methanol-trifluoroacetic acid (72.5:27.5:1.5, v/v) as the mobile phase at a flow rate of 0.3 mL/min. The column void volume is 1.15 min. UPLC detection is adjusted at 205 nm using a photodiode array detector. Calibration curves are obtained in the linearity ranges: 25-500 µg/mL for paracetamol, 10-50 µg/mL for pseudoephedrine, 0.5-5 µg/mL for chlorpheniramine, and 3-30 µg/mL for sodium benzoate with a correlation coefficient > 0.9992. The mean recovery of the developed method is tested and shows good recovery results between 99-101%; selectivity and forced degradation studies are investigated as per the International Council for Harmonisation Guidelines and no interference is detected due to degradation peaks. The proposed stability-indicating UPLC method for simultaneous determination of the three drugs, paracetamol, pseudoephedrine, and chlorpheniramine, with a preservative sodium benzoate in (Cold-Flu) 1,2,3 Syrup dosage form is successfully accomplished, developed, and validated, and can be easily used in the analysis of drugs in pure or dosage form. The novelty of the current research work lies in the development of the UPLC method for simultaneous determination of a quaternary mixture of paracetamol, pseudoephedrine, chlorpheniramine, and sodium benzoate in (Cold-Flu) 1,2,3 Syrup dosage form.

Conjugate gradient method for simultaneous identification of the source term and initial data in a time-fractional diffusion equation

In this paper, we consider the simultaneous inversion of the source term and the initial data for a time-fractional diffusion equation based on the additional temperatures at two fixed times and . The inverse problem is formulated on the basis of the Fourier method as an operator equation of the first kind. For the overdetermined system of linear equations, we apply the conjugate gradient method with an appropriate stopping criterion to solve the least-squares problems. The method is not only able to converge quickly, but also it can solve large-scale linear equations. Based on the proposed results, it can be seen that the iteration numbers play a role of a regularization parameter. Four numerical examples are provided to demonstrate the effectiveness of the proposed method.

Improved Vibration Analysis Model for 3D Printed CFRTP Plate

With the development of 3D printers, it has become possible to 3D print materials containing carbon fibers. In this study, FE model that can reproduce the vibration characteristics of a test plate made with the 3D printer Mark Two. This study aims to create FE model that can reproduce the vibration characteristics of a test plate made with the Mark Two 3D printer when it is subjected to central excitation. Currently, the model can reproduce the vibration modes but is not able to reproduce the natural frequencies. One possible reason for this is that the value of the material constants used in the material constants used in the analysis may differ from the actual ones. To ensure the accuracy of the material constants used, the output of the material constant by the simultaneous identification method using the differential evolution method with APDL were applied to improve the reproducibility of the natural frequencies.