Analysis Method Research Articles

Unsteady MHD Walter’s-B Viscoelastic Flow Past a Vertical Porous Plate

The present paper intended to analyse an unsteady MHD Walter’s-B viscoelastic flow past a vertical porous plate embedded in a porous medium in the presence of the radiation and chemical reaction effects. The dimensionless partial differential equations of governing equations of the flow field are solved numerically using closed analytical method. The velocity, temperature and concentration profiles are discussed graphically and discussed qualitatively

Analytical Method Development and Validation for Quantitative Estimation of Tebentafusp Bulk Dosage by RP-HPLC

Analytical Method Development and Validation for Quantitative Estimation of Tebentafusp Bulk Dosage by RP-HPLC

Relationships Among the Bryophytes and Vascular Plants: A Case Study in Deep-Time Reconstruction

Relationships of the three bryophyte lineages (liverworts, mosses, and hornworts) to vascular plants is a pivotal question in the study of the origin and evolution of land plants. In recent decades, this question has been subjected to intense phylogenetic analyses using morphological characters, multigene DNA sequences, and genome structural characters. A tentative consensus, reached ten years ago, suggested that bryophytes are a paraphyletic group, with liverworts being sister to all other land plants and hornworts being sister to vascular plants. However, several more recent nuclear phylogenomic studies have concluded that bryophytes represent a monophyletic group that is sister to vascular plants. A discussion is presented here on strengths and weaknesses of different types of characters (morphological traits, nucleotide sequences, and genome structural arrangements) and their suitability for resolving deep phylogenetic relationships. Moreover, several criteria for credible phylogenetic reconstruction are proposed. Strong statistical support for reconstructed relationships should be derived from high-quality, independent characters selected for suitability to the particular question being addressed. The relationships inferred in a study should be congruent with those from as many other lines of phylogenetic evidence as possible. Any incongruities should be explicable by well-understood biological mechanisms. It is concluded that the relationships of the three bryophyte lineages to vascular plants should currently be viewed as unresolved. This is a difficult phylogenetic problem; the land plants underwent a rapid radiation a long time ago. Yet, further exploration of analytical methods and careful choice of characters should lead to the eventual elucidation of diversification patterns among early land plants.

Comparative Study of Analytical and Numerical Methods for Stress Analysis in Screw Thread Fillets

Comparative Study of Analytical and Numerical Methods for Stress Analysis in Screw Thread Fillets

Deciphering the degradation mechanisms of nano-Si and micro-SiO anodes in lithium-ion battery full-cells using distribution relaxation times analysis

Silicon (Si) and silicon monoxide (SiO) have attracted great interest as next-generation anode materials for lithium-ion batteries (LiBs) due to their high energy density. However, their commercialization has been hindered by rapid capacity fading, which stems from mechanical degradation (e.g., cracking and delamination) and the aggressive formation of solid electrolyte interphase (SEI) layer. While understanding these degradation mechanisms in batteries necessitates in-operando measurement techniques, very few non-destructive analytical methods have been documented in literature. This paper highlights the effectiveness of combined electrochemical impedance spectroscopy (EIS) and distribution of relaxation times (DRT) techniques in performing systematic characterization of LiNi0.6Mn0.2Co0.2O2 (NMC)/nano-Si and NMC/micro-SiO full-cells. The systematic design of experiments enabled the separate deconvolution of anode and cathode aging using symmetrical cells. This approach offered a clear understanding of the overall degradation mechanisms in the full-cells. The major impedance sources in the NMC/nano-Si full-cell were anode contact impedance, resulting from mechanical degradation of Si, and cathode charge transfer impedance, due to significant lithium loss and consequently deeper extraction of lithium ions in NMC. In contrast, micro-SiO anodes exhibited less electrode-level degradation, as evidenced by SEM images and relatively stable impedance behaviors during extended cycling, which strongly corroborate its superior capacity retention (66 % at 300th cycle) compared to that of nano-Si anode in full-cells (26.5 % at 300th cycle).

Remote Sensing Technologies for Mapping Ecosystem Services: An Analytical Approach for Urban Green Infrastructure

Urban Green Infrastructures (UGIs) have gained increasing relevance in the field of climate adaptive design because of their capacity to provide regulating ecosystem services apt to respond to the impacts of global warming with short-term strategies. The effectiveness of UGIs in reducing climate risks depends on both the state of natural resources and the understanding of urban ecosystem processes over time. The implementation of analytic methods to better understand urban ecosystem dynamics, as well as the local effective potential of ESs, is crucial for addressing climate impacts in cities. The advances in remote sensing methodologies for mapping and monitoring urban ecosystems represent a key opportunity to deepen the ecological features of existing urban green areas as a potential planning asset to respond to climate impacts. Indeed, remote sensing technologies implement a new data-driven planning approach that enables models and simulations of different project scenarios by supporting planning decisions and reducing the risk of failures. According to these assumptions, this paper discusses the results of a literature review aimed at providing the current state of the art in applying remote sensing technologies for mapping and monitoring ecosystem services, focusing on operational opportunities in urban environments. It examines how remote sensing can depict ESs and ensure data quality and reliability for UGI design. The emphasis is on the potential of ESs to mitigate and adapt to heat wave risks which will be more frequent in the next decade, particularly in cities, as highlighted by the IPCC Report 2023. Therefore, UGIs are strategic tools for addressing heat wave impacts, necessitating a shift from empirical approaches to analytical, data-driven planning methods.

In-house validation of a visible and near infrared spectroscopy non-targeted method to support panel test of virgin olive oils

In this study, an in-house validation of Visible and Near Infrared Spectroscopy was performed to distinguish between extra virgin olive oil (EVOO) and virgin olive oil (VOO). A total of 161 samples of olive oil of three different categories (EVOO, VOO and lampante (LOO)) were analysed by transflectance using a monochromator instrument. One-class models were initially developed using Partial Least Squares (PLS) Density Modelling to characterize EVOO and VOO category. Once the LOO samples were discriminated, linear and non-linear discriminant models were built to classify EVOO and VOO. Different data pre-treatments and variable selection algorithms were evaluated to establish the best models in terms of Correct Classification Rate (CCR). The best model, obtained after variable selection using PLS Discriminant Analysis, yielded CCR values of 82.35 % for EVOO and 66.67 % for VOO in external validation. These results confirmed that VIS + NIRS technology may be used to provide rapid, non-destructive preliminary screening of olive oil samples for categorization; suspect samples may then be analysed by official analytical methods.

Out of the blue: Hyperaccumulation of molybdenum in the Indo-Pacific sponge Theonella conica.

Molybdenum is an essential micronutrient, but because of its toxicity at high concentrations, its accumulation in living organisms has not been widely demonstrated. In this study, we report that the marine sponge Theonella conica accumulates exceptionally high levels of molybdenum (46,793 micrograms per gram of dry weight) in a wide geographic distribution from the northern Red Sea to the reefs of Zanzibar, Indian Ocean. The element is found in various sponge body fractions and correlates to selenium. We further investigated the microbial composition of the sponge and compared it to its more studied congener, Theonella swinhoei. Our analysis illuminates the symbiotic bacterium Entotheonella sp. and its role in molybdenum accumulation. Through microscopic and analytical methods, we provide evidence of intracellular spheres within Entotheonella sp. that exhibit high molybdenum content, further unraveling the intricate mechanisms behind molybdenum accumulation in this sponge species and its significance in the broader context of molybdenum biogeochemical cycling.

Gut microbiota and epigenetic choreography: Implications for human health: A review.

The interwoven relationship between gut microbiota and the epigenetic landscape constitutes a pivotal axis in understanding human health and disease. Governed by a myriad of dietary, genetic, and environmental influences, the gut microbiota orchestrates a sophisticated metabolic interplay, shaping nutrient utilization, immune responses, and defenses against pathogens. Recent strides in genomics and metabolomics have shed light on the intricate connections between these microbial influencers and the host's physiological dynamics, presenting a dynamic panorama across diverse disease spectra. DNA methylation and histone modifications, as key players in epigenetics, intricately align with the dynamic orchestration of the gut microbiota. This seamless collaboration, notably evident in conditions like inflammatory bowel disease and obesity, has captured the attention of researchers, prompting an exploration of its nuanced choreography. Nevertheless, challenges abound. Analyzing data is intricate due to the multifaceted nature of the gut microbiota and the limitations of current analytical methods. This underscores the need for a multidisciplinary approach, where diverse disciplines converge to pave innovative research pathways. The integration of insights from microbiome and epigenome studies assumes paramount importance in unraveling the complexities of this intricate partnership. Deciphering the synchronized interactions within this collaboration offers a deeper understanding of these delicate interplays, potentially heralding revolutionary strides in treatment modalities and strategies for enhancing public health.

Development of LC–MS/MS Method for the Simultaneous Detection of Emerging Contaminants in Aquatic Matrices

Emerging contaminants (ECs) are substances that have no defined environmental quality standards or regulations, and have the potential to pose major adverse impacts on the environment and human health. The detection of contaminants in the natural environment is the key step for establishing precise environmental risk assessment approach for ECs. However, ECs come from different origins with various physicochemical properties, making their detection a complicated process. Moreover, their presence in the aquatic environment at trace concentration range (ng/L-µg/L), requires an accurate detection at low concentration levels. This study aims to develop an efficient analytical method for simultaneous determination of 5 different ECs in aqueous solution based on solid phase extraction technique (SPE) followed by liquid chromatography-mass spectrometry (LC–MS/MS). High recovery rates (72% to 114%) were achieved for all targeted compounds. Ciprofloxacin (CIP), diuron (DIU), terbutryn (TER) and diclofenac (DIC) had a limit of detection (LOD) of 5 µg/L and a limit of quantification (LOQ) of 10 ng/L, while LOD and LOQ for EE2 were 25 µg/L and 50 ng/L, respectively. These results confirm that the optimized method can be applied for extraction and analysis of ECs from different classes in the aquatic environment.

واقع إلمام معلمات الدراسات الإسلامية بأساليب مكافحة الأفكار الهدامة بالمرحلة الثانوية بالعاصمة المقدسة

The study aims to evaluate the level of female Islamic Studies teachers familiarity with methods of combating destructive ideas in high school education in the Holy Capital of Makkah. To achieve this, the study used the descriptive analytical survey method, the study sample included (86) female Islamic Studies teachers, and used a questionnaire consisting of 12 items. The study had come to several conclusions, most importantly being: That female Islamic Studies teachers are highly familiar with destructive ideas combating methods, the study scored an arithmetic mean of (3.59), a standard deviation of (.86), and a high level of familiarity. In light of these results, the study made several recommendations.

Enhancing Supplier Selection for Sustainable Raw Materials: A Comprehensive Analysis Using Analytical Network Process (ANP) and TOPSIS Methods

Enhancing Supplier Selection for Sustainable Raw Materials: A Comprehensive Analysis Using Analytical Network Process (ANP) and TOPSIS Methods

Jacobi polynomials and the numerical solution of ray tracing through the crystalline lens

The human eye is a fascinating optical system, with the crystalline lens playing a significant role in focusing light onto the retina of the eye. The ray tracing through the crystalline lens problem is a challenging problem in optics. In this paper, the case of a non-homogeneous optical medium is investigated, and the ray equation is numerically solved to get the ray paths. The governing equation is an ODE with a fractional derivative given in the Caputo sense. A novel numerical scheme is based on the Jacobi polynomial collocation technique to tackle this problem. A fast and accurate Broyden’s Quasi-Newton algorithm is applied to solve the nonlinear system of equations obtained from the collocation process. Numerical results are stated in detail to show the efficiency of our technique and are compared with other analytical and numerical methods using tables and illustrated figures, which will be useful to corroborate the clinical and physical data. Ray tracing through the crystalline lens is not only fascinating from a scientific perspective but also has practical implications across various domains, and the proposed scheme is considered a promising and practically reliable method to address such types of applications.

Frailty Modeling using Machine Learning Methodologies: A Systematic Review with Discussions on Outstanding Questions.

Studying frailty is crucial for enhancing the health and quality of life among older adults, refining healthcare delivery methods, and tackling the obstacles linked to an aging demographic. Approaches to frailty modeling often utilise simple analytic techniques rather than available advanced machine learning methods, which may be sub-optimal. There is no large-scale systematic review on applications of machine learning methods on frailty modeling. In this study we explore the use of machine learning methods to predict or classify frailty in older persons in routinely collected data. We reviewed 181 research articles, and categorised analytic methods into three categories: generalised linear models, survival models, and non-linear models. These methods have a moderate agreement with existing frailty scores and predictive validity for adverse outcomes. Limited evidence suggests that non-linear methods outperform generalised linear methods. The top-three predictor/input variables are specific diagnosis or groups of diagnoses, functional performance (e.g., ADLs), and impaired cognition. Mortality, hospital admissions and prolonged hospital stay are the mainly predicted outcomes. Most studies utilise classical machine learning methods with cross-sectional data. Longitudinal data collected by wearable sensors have been used for frailty modeling. We also discuss the opportunities to use more advanced machine learning methods with high dimensional longitudinal data for more personalised and accessible frailty tools.

Penalization and Color Code-Technical Approaches for Methods' Greenness and Whiteness Appraisal in Veterinary Medication: Assay of Toltrazuril Suspension.

Intestinal coccidiosis is a debilitating disease in poultry and livestock, leading to economic impact worldwide. Coccidiosis is prevented and treated in broilers by the inclusion of anticoccidials in feed. Toltrazuril is administered in potable water to treat coccidiosis. Three robust analytical methods for quantitation of toltrazuril in pure and pharmaceutical formulations are developed. Furthermore, ecological metrics; either penalization- or color-code-based techniques are applied for the appraisal of assays. Firstly, Second-Derivative (Δλ; 5 nm) spectrophotometric method; Toltrazuril is measured from peak to peak at 244-260 nm within a linearity range of 5-25 μg/mL. The second one is a high-performance thin-layer chromatography (HPTLC) analysis performed on an aluminum sheet of silica gel using ethyl acetate, methanol, ammonium chloride buffer, and water (8:1:0.5:0.5) (%V/V) as the elution phase. Toltrazuril, at a retardation factor of 0.66 ± 0.01, is linearly determined in the range of 1-9 μg/spot at 243 nm. The third one is Reversed Phase-HPLC-diode array detection, using Agilent column C18 (5 μm, 4.6 x 150 mm) in isocratic elution mode with a mobile phase of acetonitrile and water in a ratio of 80:20 (v/v), respectively, at 1 mL/min flow rate. Toltrazuril elutes at a retention time of 2.58 ± 0.1 min and is linearly determined at 243 nm in the range of 0.25-25 μg/mL. Calculated 2D-values and peak areas are highly correlated to their corresponding drug concentrations at coefficients; r > 0.999. All methods were ICH validated and applied to dosage form with satisfactory % recoveries (97-103%). Statistical comparisons reported one using t-test and F-test disclose insignificant variation. Examining greenness and whiteness norms, proposed methods were evaluated and ranked alongside four different reported methods. The proposed methods are green, accurate, and can be applied in routine quality control for the determination of toltrazuril in pharmaceutical formulations.

Node-layer duality in networked systems

Real-world networks typically exhibit several aspects, or layers, of interactions among their nodes. By permuting the role of the nodes and the layers, we establish a new criterion to construct the dual of a network. This approach allows to examine connectivity from either a node-centric or layer-centric viewpoint. Through rigorous analytical methods and extensive simulations, we demonstrate that nodewise and layerwise connectivity measure different but related aspects of the same system. Leveraging node-layer duality provides complementary insights, enabling a deeper comprehension of diverse networks across social science, technology and biology. Taken together, these findings reveal previously unappreciated features of complex systems and provide a fresh tool for delving into their structure and dynamics.

Application of untargeted liquid chromatography-mass spectrometry to routine analysis of food using three-dimensional bucketing and machine learning

For the detection of food adulteration, sensitive and reproducible analytical methods are required. Liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) is a highly sensitive method that can be used to obtain analytical fingerprints consisting of a variety of different components. Since the comparability of measurements carried out with different devices and at different times is not given, specific adulterants are usually detected in targeted analyses instead of analyzing the entire fingerprint. However, this comprehensive analysis is desirable in order to stay ahead in the race against food fraudsters, who are constantly adapting their adulterations to the latest state of the art in analytics. We have developed and optimized an approach that enables the separate processing of untargeted LC‑HRMS data obtained from different devices and at different times. We demonstrate this by the successful determination of the geographical origin of honey samples using a random forest model. We then show that this approach can be applied to develop a continuously learning classification model and our final model, based on data from 835 samples, achieves a classification accuracy of 94% for 126 test samples from 6 different countries.

PdRuO2/PVP nanomaterial as a highly selective, stable, and applicable potentiometric sensor for the detection of Cr3+

PdRuO2/PVP nanomaterial was synthesized using a straightforward method and characterized using advanced analytical methods such as TEM, XRD, XPS, elemental mapping and SEM. The synthesized PdRuO2/PVP nanomaterial was used as an ionophore in potentiometric sensor electrodes and successfully adapted to Cr3+ ion detection in a large number of aqueous samples. Several experimental parameters of the PdRuO2/PVP sensor such as potentiometric behavior, selectivity, repeatability, response time, pH, titration, and recovery in real samples were investigated. Potentiometric behavioral characteristics were performed in the concentration range 1 × 10−6–1.0 × 10−1 M. The repeated experiments performed six times showed that there was no deviation in the measurements. The limit of detection of the PdRuO2/PVP potentiometric sensor was very low with a value of 8.6 × 10−8 M. The potentiometric measurements showed that the synthesized PdRuO2/PVP ionophore was highly effective in detecting Cr3+ in a wide pH range of 2.0–8.0 and was found to have a shelf life of over 1 year. As a result, the synthesized PdRuO2/PVP electrode material was found to be highly selective, stable, and applicable for Cr3+ detection.Graphical

Extraction and characterization of phenolic compounds from mandarin peels using conventional and green techniques: a comparative study

The exploration of citrus waste valorization extends beyond its environmental benefits to encompass potential health implications, particularly in cancer prevention. The bioactive compounds extracted from citrus waste, notably polyphenols like quercetin, gallic acid, hesperidin, and ferulic acid, hold promising anti-cancer properties. Research suggests that these compounds exhibit potent antioxidant and anti-inflammatory effects, which are integral in combating carcinogenesis. Quercetin, a flavonoid abundantly found in citrus extracts, has garnered attention for its ability to inhibit cancer cell proliferation and induce apoptosis, thereby impeding tumor growth. Gallic acid, another prevalent compound, demonstrates anticancer potential through its modulation of signaling pathways associated with cell survival and proliferation. Hesperidin, known for its antioxidative properties, has shown promise in suppressing tumor growth and metastasis by targeting various molecular pathways involved in cancer progression. Ferulic acid, renowned for its anti-inflammatory and antioxidant activities, exhibits chemopreventive effects by inhibiting carcinogen activation and promoting detoxification processes within the body. The present study compares conventional (soxhlet, maceration) and non-conventional (ultrasound, microwave) techniques to obtain these polyphenols from mandarin peels. The maximum total phenolic content of 3.78 mg GAE/ g dry peels and DPPH activity of 69.89% was observed using 80% methanol and ultrasound assisted extraction. The presence of these compounds was confirmed using advanced analytical methods such as FT-IR and HPLC. The phenolic compounds (mg/g dry peels) such as gallic acid (0.29 ± 1.08), p-coumaric acid (0.17 ± 0.52), chlorogenic acid (0.30 ± 0.56), ferulic acid (1.49 ± 1.36), hesperidin (1.34 ± 0.51), naringenin (0.56 ± 0.94), and quercetin (0.33 ± 1.02), observed during UAE were 25–35% higher values compared to other techniques. By harnessing the bioactive potential of citrus waste-derived compounds, particularly for cancer prevention, this study contributes to both environmental sustainability and human health enhancement, paving the way for innovative strategies in functional food development and nutraceutical applications.

Liquid chromatography-mass spectrometry quantification of phytochemicals in Withania somnifera using data-dependent acquisition, multiple-reaction-monitoring, and parallel-reaction-monitoring with an inclusion list

Characterization of botanical extracts by mass spectrometry-based metabolomics analysis helps in determining the phytochemical composition that underlies their bioactivity and potential health benefits, while also supporting reproducibility of effects in clinical trials. The quantification of seven withanolides in Withania somnifera using three mass-spectrometry methods was evaluated using Deming regression. Two high-resolution time-of-flight mass spectrometry methods were used, one operating in data-dependent acquisition mode and the other in parallel-reaction-monitoring mode with an inclusion list. The two high-resolution time-of-flight mass spectrometry methods were compared to a multiple-reaction-monitoring method. We evaluated in-source fragmentation of steroidal glycosides and optimized the methods accordingly. A novel software approach to integrating parallel-reaction-monitoring data acquired with an inclusion list was developed. Combining and comparing quantitative results allowed for quantitative specificity, good precision, and adjustment of instrument source conditions for optimal quantification by multiple-reaction-monitoring mass spectrometry, an analytical method that is widely accessible in analytical and phytochemical laboratories.