Classes Of Analytes Research Articles

Application of the Neutrosophic Poisson Distribution Series on the Harmonic Subclass of Analytic Functions using the Salagean Derivative Operator

The authors explore the innovative application of the Neutrosophic series, particularly the Neutrosophic Poisson Distribution Series (NPDS), to investigate various indeterminacy or uncertainties inherent in the classical univalent harmonic function class. The Neutrosophic Poisson Distribution Series is equipped with a Salangean derivative operator and convoluted with analytic univalent harmonic function class to derive new properties, such as inclusion relation, and coefficient inequalities for star-likeness. The results obtained demonstrate the effectiveness of this approach in capturing the inherent uncertainties and complexities associated with harmonic functions. There are several other areas of importance of our results that can be unlocked by computer engineers, scientists, and other experts. In this investigation, some of these indeterminacy and complexities are revealed using graphs by employing Python software tools. This novel integration enhances the analytical techniques available and opens a new stairway for future research in neutrosophic series and geometric function theory.

The Role of Mechanical Mixing and Biologically Active Additives in Enhancing Cutlet Quality

The research relevance is determined by the need to understand the effect of mechanical mixing and the use of biologically active additives on the quality of cutlet mass, which will optimize food technologies and create products with improved texture and nutritional value. This need stems from the fact that the quality and characteristics of culinary products are important criteria for consumers. The research aims to investigate the relationship between mechanical mixing parameters and the use of biologically active additives with structural and mechanical quality parameters of cutlet mass, to improve production processes and develop higher quality food products. Analytical methods, classification methods, functional methods, statistical methods, and synthesis methods were used to determine the quality of the cutlet mass. In the course of the study, a comprehensive analysis of the effect of various parameters of mechanical mixing and the use of various biologically active additives on the structural and mechanical characteristics of the cutlet mass was carried out. It was found that optimal mixing conditions and types of additional components can significantly improve the textural properties of the product. It was found that the use of certain biologically active additives helps to increase the resistance of the mass to mechanical stress and preserve its juiciness. These conclusions allow us to develop more effective strategies for the production of cutlet mass with improved quality and nutritional value. The practical significance of this study is to provide scientifically based recommendations for optimizing food production processes aimed at improving the quality and nutritional value of cutlet mass by studying the effect of mechanical mixing and biologically active additives on its structural and mechanical properties.

Regularity, synthesis, rigidity and analytic classification for linear ordinary differential equations of second order

We study second order linear homogeneous differential equations a(x)y'' + b(x)y' + c(x)y = 0 with analytic coefficients in a neighborhood of a regular singularity in the sense of Frobenius. These equations are model for a number of natural phenomena in sciences and applications in engineering. We address questions which can be divided in the following groups: (i) Regularity of solutions. (ii) Analytic classification of the differential equation. (iii) Formal and differentiable rigidity. (iv) Synthesis and uniqueness of ODEs with a prescribed solution. Our approach is inspired by elements from analytic theory of singularities and complex foliations, adapted to this framework. Our results also reinforce the connection between classical methods in second order analytic ODEs and (geometric) theory of singularities. Our results, though of a clear theoretical content, are important in justifying many procedures in the solution of such equations.

Enantioselective Molecular Detection by Surface Enhanced Raman Scattering at Chiral Gold Helicoids on Grating Surfaces.

Distinct advantages of surface enhanced Raman scattering (SERS) in molecular detection can benefit the enantioselective discrimination of specific molecular configurations. However, many of the recent methods still lack versatility and require customized anchors to chemically interact with the studied analyte. In this work, we propose the utilization of helicoid-shaped chiral gold nanoparticles arranged in an ordered array on a gold grating surface for enantioselective SERS recognition. This arrangement ensured a homogeneous distribution of chiral plasmonic hot spots and facilitated the enhancement of the SERS response of targeted analytes through plasmon coupling between gold helicoid multimers (formed in the grating valleys) and adjacent regions of the gold grating. Naproxen enantiomers (R(+) and S(-)) were employed as model compounds, revealing a clear dependence of their SERS response on the chirality of the gold helicoids. Additionally, propranolol and penicillamine enantiomers were used to validate the universality of the proposed approach. Finally, numerical simulations were conducted to elucidate the roles of intensified local electric field and optical helicity density on the SERS signal intensity and on the chirality of the nanoparticles and enantiomers. Unlike previously reported methods, our approach relies on the excitation of a chiral plasmonic near-field and its interaction with the chiral environment of analyte molecules, obviating the need for the enantioselective entrapment of targeted molecules. Moreover, our method is not limited to specific analyte classes and can be applied to a broad range of chiral molecules.

(Invited) Non-Invasive Injectable Nanotube-Hydrogel Formulations for Local Analyte Detection

Rapid, minimally-invasive in situ detection of analytes in vivo remains a goal to study inflammatory signaling molecules, disease biomarkers, and pharmacology of therapeutics. To achieve this, we are using the near-infrared fluorescent properties of single-walled carbon nanotubes (SWCNT) to design sensors for use in live mice. SWCNT fluorescence is responsive to the local environment, in the tissue-transparent window, and does not photobleach, allowing for long-term signal monitoring. In this work, we are exploring several formulations of SWCNT embedded within hydrogels which gel in situ. We have investigated the kinetics of penetration of several classes of analytes—proteins, small molecules, and ions—through the hydrogel and their interaction with SWCNT sensors in vitro. Then, we explored the long-term stability of these nanotube-hydrogel formulations in live mice prior to detection of the chemotherapeutic doxorubicin. In ongoing work, we are exploring disease biomarker-specific sensing and monitoring of inflammatory cytokines in mouse models of disease using this nanotube-hydrogel system. We anticipate long-term applications of this work may include minimally-invasive and rapid clinical diagnostic development.

Analytic and Gevrey Class Regularity for Parametric Elliptic Eigenvalue Problems and Applications

Analytic and Gevrey Class Regularity for Parametric Elliptic Eigenvalue Problems and Applications

Classification of unimodal parametric plane curve singularities in positive characteristic

In 2011 Hefez and Hernandes completed Zariski's analytic classification of plane branches belonging to a given equisingularity class by creating “very short” parameterizations over the complex numbers. Their results were used by Mehmood and Pfister to classify unimodal plane branches in characteristic 0 by giving lists of normal forms. The aim of this paper is to give a complete classification of unimodal plane branches over an algebraically closed field of positive characteristic. Since the methods of Hefez and Hernandes cannot be used in positive characteristic, we use a different approach and, for some sporadic singularities in small characteristic, computations with Singular. Our methods are characteristic-independent and provide a different proof of the classification in characteristic 0 showing at the same time that this classification holds also in large characteristic. The main theoretical ingredients are the semicontinuity of the semigroup and of the modality, which we prove and which may be of independent interest.

Human biomonitoring of PCDDs, PCDFs, and PCBs in women living in a Northern Italy industrial area.

In Brescia, a highly industrialized city in the Lombardy Region (Northern Italy) classified as a SIN (Contaminated Site of National Interest), a human biomonitoring study was carried out on breast milk of two groups of women residing in areas with presumably different levels of exposure to polychlorodibenzo-p-dioxins, polychlorodibenzofurans, and polychlorobiphenyls. This study was aimed at evaluating the possible difference between women living in Brescia and women living far from it but in the same Region. Between 2016 and 2018, 82 women were enrolled (41 "exposed" subjects and 41 "not exposed"), breast milk samples were collected, and a specific questionnaire was administered to the donors. Data obtained were processed by robust regression and Principal Component Factor Analysis. The differences in concentration between the two groups were significant for all the classes of analytes (except for PCDDs). The concentration increase rates from the not exposed to the exposed group resulted highly significant: some PCB congeners showed increase rates more than 1000 ng/g lb per one-unit change of the independent variable. Among the variables significantly associated with the observed concentrations, age showed the greatest influence, while BMI showed a counteracting effect. Consumption of vegetable oil and fruit resulted to possibly influence the chemicals body burden. For the not exposed group, the levels appear to be in line with the decreasing trend (2001-2018) observed for these contaminants in Italy.

Delineation of groundwater potential zones in coastal alluvial region using remote sensing, geographic information system and analytical hierarchy process techniques

Delineation of groundwater potential zone in coastal region is a challenging task. One of the reasons for that is lack of understanding of the geogenic factors in the coastal alluvial areas such as geomorphology, lithology etc. These factors can influence the locations of the groundwater potential zones over the coastal alluvial terrains. The present study is an attempt to analyse the multiple factors to delineate groundwater potential zones in the coastal region of Contai Sub-division, West Bengal, India. In this study, remote sensing, geographic information system (GIS) and multi-criteria decision analysis (MCDA) techniques have been utilized to delineate the groundwater potential zones. Weights were assigned to the parameters using the analytical hierarchical process (AHP) and different classes within each parameter have been ranked on the basis of their relative importance regarding groundwater potentiality. The results of the study were validated by water yield data, water level fluctuation data and geophysical survey. The outcome of validation reveals that a strong correlation (80%) exists between water yield data and groundwater potential zones. Similarly, a good relation occurs for the water level fluctuation data and groundwater potential zones, where the overall accuracy and kappa coefficients are 84.2% and 0.76 respectively. The output of the study reveals that geomorphologically older deltaic plain, older alluvial plain and older coastal plain are good indicators of high groundwater potential regions. Furthermore, the outcome of the study also unveils that lithologically the well sorted medium grained sand is important feature to delineate high groundwater potential regions in coastal alluvial areas. The findings, thus, could establish that present methodology using GIS and AHP techniques has a better potential to identify and map the groundwater potential zones more realistically and can be applied for future planning of groundwater resource management and groundwater exploration in wider coastal alluvial terrain.

Mechanics of surface deformations in rigid bodies

Studying surface deformations in solids is crucial for advancing science and technology, informing material development, structural design and process enhancement. The purpose of study is to review and analyse the mechanics of surface deformations in rigid bodies in order to identify their features and develop new methods for describing and predicting such deformations. The study analysed theoretical models and experimental approaches to study surface deformation; among the methods used, the analytical method, classification method and synthesis method should be noted. In the study, the following parameters and aspects related to surface deformation in rigid bodies were investigated: material response to plastic deformation, mechanical properties, surface deformation characteristics, extent of deformation and behaviour under small deformations. The study investigates the impact of plastic deformation on the crystal structure of materials, focusing on grain boundary structure, dislocation motion and stacking faults. The main results of the study are the identification of the relationship between mechanical stress and surface deformation in rigid bodies. It was found that high mechanical stress leads to a change in the crystal structure of the material on the surface, which, in turn, affects its mechanical properties. Also, the results of the study are the establishment of relationships between the parameters of materials and the amount of surface deformation, as well as the identification of physical laws governing this process.

Surface-Engineered Graphene surface-enhanced Raman scattering Platform with Machine-learning Enabled Classification of Mixed Analytes

Surface-Engineered Graphene surface-enhanced Raman scattering Platform with Machine-learning Enabled Classification of Mixed Analytes

Sufficient Conditions for Linear Operators Related to Confluent Hypergeometric Function and Generalized Bessel Function of the First Kind to Belong to a Certain Class of Analytic Functions

Geometric function theory has extensively explored the geometric characteristics of analytic functions within symmetric domains. This study analyzes the geometric properties of a specific class of analytic functions employing confluent hypergeometric functions and generalized Bessel functions of the first kind. Specific constraints are imposed on the parameters to ensure the inclusion of the confluent hypergeometric function within the analytic function class. The coefficient bound of the class is used to determine the inclusion properties of integral operators involving generalized Bessel functions of the first kind. Different results are observed for these operators, depending on the specific values of the parameters. The results presented here include some previously published findings as special cases.

Practice-oriented approach to teaching Python programming to university students

Relevance. The study on this topic is relevant due to the growing need for practical skills to enhance graduate competitiveness, advances in technology, and demands for real-world problem-solving. Purpose. The purpose of this study was to evaluate the effectiveness of a practice-oriented approach to teaching Python programming in higher education institutions to optimise curricula and make students better prepared for the demands of modern industry. Methodology. The methods used include an analytical method, experimental method, comparative method, synthesis method, modelling method, classification method, and statistical method. Results. The study found a considerable increase in academic performance, an increase in interest in the subject and the development of practical skills, which emphasises the significance of the practice-oriented approach in university education. Conclusions. The study concluded that the practice-oriented approach significantly improved the quality of learning, student satisfaction, and practical skills. This educational approach not only enhanced learning efficiency but also better-prepared students for successful careers in programming. The practical value lies in providing students with real software development skills, boosting their competitiveness in the job market, and ensuring successful adaptation to the information technology industry. Keywords: curricula; innovations in education; modern technologies; assessment of educational results

A screening method for heavy metals in consumer goods using reactive desorption electrospray ionization mass spectrometry.

Contamination of everyday goods with heavy metals such as nickel, cadmium, and lead known to be hazardous to the health of customers is an ongoing problem. Here, a mass spectrometric screening method based on reactive desorption electrospray ionization (DESI) is presented for the analysis of metals in consumer goods such as jewelry, tableware, and paintings. The method detects oxidized species of lead, nickel, cadmium, copper, and iron from the surface of objects without sample preparation. Positively charged metal ions form singly and doubly negatively charged complexes with ethylenediaminetetraacetic acid added to the DESI solvent, which are analyzed by a mass spectrometer. Qualitative and quantitative performance of the method was elucidated with metal salt standards. Subsequently, authentic samples were analyzed qualitatively. Reactive DESI-MS was able to detect lead and cadmium in eight out of nine consumer goods. For tableware, these heavy metals were found to be localized in the print as determined by reactive DESI imaging. In addition, mockup paintings generated from modern and historical pigments of Pb, Cu, Cd, and Fe in various media (acrylic binder, egg tempera, and linseed oil) were measured to show the suitability of the method for art authentication and conservation. The developed method expands the range of analytes accessible by DESI-MS to metal ions. Hence, DESI becomes a suitable ionization technique for an increasing number of analyte classes, which are of interest in chemical screening of consumer goods.

Analytic and Gevrey class regularity for parametric semilinear reaction-diffusion problems and applications in uncertainty quantification

We investigate a class of parametric elliptic semilinear partial differential equations of second order with homogeneous essential boundary conditions, where the coefficients and the right-hand side (and hence the solution) may depend on a parameter. This model can be seen as a reaction-diffusion problem with a polynomial nonlinearity in the reaction term. The efficiency of various numerical approximations across the entire parameter space is closely related to the regularity of the solution with respect to the parameter. We show that if the coefficients and the right-hand side are analytic or Gevrey class regular with respect to the parameter, the same type of parametric regularity is valid for the solution. The key ingredient of the proof is the combination of the alternative-to-factorial technique from our previous work [1] with a novel argument for the treatment of the power-type nonlinearity in the reaction term. As an application of this abstract result, we obtain rigorous convergence estimates for numerical integration of semilinear reaction-diffusion problems with random coefficients using Gaussian and Quasi-Monte Carlo quadrature. Our theoretical findings are confirmed in numerical experiments.

Supersymmetric Wormholes in String Theory.

We construct a large family of Euclidean supersymmetric wormhole solutions of type IIB supergravity which are asymptotically AdS_{5}×S^{5}. The solutions are constructed using consistent truncation to maximally gauged supergravity in five dimensions which is further truncated to a four scalar model. Within this model we perform a full analytic classification of supersymmetric domain wall solutions with flat Euclidean domain wall slices. On each side of the wormhole, the solution asymptotes to AdS_{5} dual to N=4 supersymmetric Yang-Mills deformed by a supersymmetric mass term.

Coming of age: governance challenges in updated AMR national action plans in the EU.

National action plans (NAPs) are key instruments for governing antimicrobial resistance (AMR). In Europe, we can now observe many countries updating their NAPs which raise two key research questions; what substantial modifications are states opting for, and how do they wish to address challenges related to AMR governance in a comparative perspective? Building on a previous analytical classification, we address these two questions by examining data of updated versions of NAPs in 13 European Union member states covering seventeen elements related to AMR governance. Our results substantiate the large variation with regard to both substantive issues and governance-related matters. Most tellingly, they highlight the growing importance of the One Health approach in updated versions of NAPs. Our analysis also shows that while substantive issues remain important, One Health and the coordination and collaboration issues it entails are becoming more salient in the second or third generation of NAPs. Updated NAPs suggest that EU member states are becoming increasingly knowledgeable on the causes and consequences of AMR and how it needs to be addressed. The enhanced level of knowledge also leads these countries to address the next set of issues and challenges; to improve domestic and international coordination and collaboration. Thus, the revised NAPs present a noticeable development from substantive issues towards governance issues.

Systematic evaluation of benzoylation for liquid chromatography-mass spectrometry analysis of different analyte classes

LC-MS is an indispensable tool for small molecule analysis in many fields; however, many small molecules require chemical derivatization to improve retention on commonly used reversed-phase columns and increase ionization. Benzoyl chloride (BzCl) derivatization is commonly used for derivatization of primary and secondary amines and phenolic alcohols, though evidence exists that with proper reaction conditions (i.e., specific bases), other hydroxyl groups may be derivatized too. Previous studies have examined BzCl concentration, reaction times, and reaction temperatures for derivatization of amines and phenols for LC-MS analysis; however, use of different bases, base concentration, and extending to conditions to hydroxyl groups for LC-MS analysis has not been well-studied. To address this understudied area and identify reaction conditions for both amino and hydroxyl groups, we performed a systematic study of reaction conditions on multiple classes of potential targets. For selected derivatization methods, detection limits and performance in a variety of biological matrices were assessed. Results highlight the importance of tailoring derivatization methods for a given application as they varied by molecule and/or molecule class. Compared to the standard BzCl method commonly used, alternative methods were identified to better derivatize challenging analytes (glucosamine, choline, cortisol, uridine, cytidine) with detection limits reaching 1100, 9, 38, 170, and 67 nM compared to undetectable, 170, 86, 1000, and 86 nM respectively. Sub-nanomolar detection limits were achieved for norepinephrine with alternative derivatization approaches. Improved derivatization methods for several classes and molecules including nucleosides, steroids, and molecules containing hydroxyl groups were also identified.

Copper Oxide Anchored Carbon Nanofibers: A Versatile Platform for Multiplex Detection of Antibiotics, Heavy Metals and Pesticides.

Electrochemical sensors offer promising prospects for real-time pollutant monitoring. In this study, copper oxide-dispersed graphitic carbon nanofibers (CuO-CNFs) grown via chemical vapour deposition were employed as a robust platform for detecting a variety of environmental pollutants. This array-based sensor adeptly identifies three different classes of analytes, i. e., antibiotics (chloramphenicol (CP) and tylosin tartrate (TT)), heavy metals (cadmium (Cd) and lead (Pb)), and pesticides (quinalphos (QP) and imidacloprid (IP)). Electron collection is facilitated by a glassy carbon electrode, while various physico-electrochemical methods delve into the properties of CuO-CNFs. The CuO-CNF-modified GCE array rapidly discerns (<15 sec) a broad linear range: 1-20 ppm for CP, 1-13.33 ppm for TT, 0.66-11.66 ppm for Cd, 20-33.33 ppm for Pb, 1.6-11.6 ppm for QP, and 5-25 ppm for IP, boasting quantification limits of 1.0, 1.0, 0.66, 20.0, 1.6, and 5.0 ppm for CP, TT, Cd, Pb, QP, and IP, respectively. Notably, this sensor achieves simultaneous identification of mixed analytes, including CP and TT, Cd and Pb, and QP and IP, within real tap water. Furthermore, the electrochemical sensor exhibits robustness; heightened sensitivity, selectivity, and stability; a swift response; and impressive reproducibility in detecting CP, TT, Cd, Pb, QP, and IP within aqueous samples. Consequently, this array-based electrochemical sensor has emerged as a rapid and simultaneous detection tool for diverse pollutant residues in surface and groundwater samples.

The analytic classification of plane curves

In this paper, we present a solution to the problem of the analytic classification of germs of plane curves with several irreducible components. Our algebraic approach follows precursive ideas of Oscar Zariski and as a subproduct allows us to recover some particular cases found in the literature.