Classes Of Analytes Research Articles

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.

Analytical solutions and classification of vesicle motion and deformation in shear flow: Uncovering new tank-treading modes.

Using a small deformation approach, a fractional ordinary differential system is proposed to investigate the motion and deformation of a vesicle in shear flow. Closed analytical expressions of the orientation angle and the ellipticity of the vesicle contour (shape deformation) are provided. Three different motions are identified, the classical tank-treading state, and two new types of motions, namely, the over-damped tank-treading mode, in which the vesicle's orientation angle ψ and its shape deformation R tend more slowly toward equilibrium, and the under-damped tank-treading mode, in which ψ oscillates all the time along the flow direction with decreasing amplitude, while R starts making a breathing motion and then tends to an attractive amplitude. The implications of our findings extend widely within the field of fluid dynamics, revealing the potential for further advancements and applications in understanding complex fluid systems.

Features and Advantages of the Recurrent Approximation of Retention Times in Reversed-Phase High-Performance Liquid Chromatography

Background: Recurrent approximation of retention parameters in reversed-phase HPLC is effective for revealing anomalies that are otherwise difficult to detect, namely, the reversible hydration of analytes. This was demonstrated previously for restricted sets of analytes with acetonitrile–water eluents. Expanding the number of analytes and eluents seems to be a topical problem. Two kinds of derivatives of aromatic carbonyl compounds were characterized: unsubstituted hydrazones and oximes. Methods: If analyte demonstrates no anomalies in dependences of retention times vs. concentration of organic modifier, the recurrent approximations of these dependences are linear. To explain the features of recurrent approximations, the numerical experiments were proposed and considered. The artificial shifting of one, two, or more points allows for the modeling the different kinds of deviations of approximations from linearity. Results: It was shown that hydrazones are the class of analytes having no anomalies of retention parameters. On the contrary, several anomalies were detected for oximes. Downward deviations of points in the plots of recurrent approximations of retention times are the signs of reversible hydration. This effect for methanol–water eluents was detected for the first time. Some of oximes underwent hydrolysis. Conclusions: Recurrent approximation of retention times allows detecting chemical transformations of analytes during RP HPLC analysis.

A simultaneous dispersive liquid-liquid microextraction and GC-MS determination of PCBs and PAHs in nature waters

The subject of this study is polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs) – super ecotoxicants and widely distributed organic pollutants in natural waters. Their danger lies in acute toxicity, cumulative action, and long-term effects on living organisms. The degree of water ecosystem pollution is assessed based on the levels of indicator compounds, with 16 PAHs and 7 PCBs. Assessing the levels of these super ecotoxicants when they are simultaneously present in natural waters is an urgent task of ecological monitoring in order to obtain reliable information about the pollution level of the water body. The aim of this study is to evaluate the possibility of dispersive liquid-liquid microextraction (DLLME) of PCBs and PAHs and GC-MS determination in natural waters in their simultaneous presence. To achieve the set goal, the peculiarities of simultaneous extraction and determination of PAHs and PCBs from natural waters were studied. The selected range of analyte concentrations was determined based on literature data on environmental monitoring and the maximum allowable concentrations (MAC) of the investigated components in natural waters. The similarity of the applied methods for extraction and detection of PAHs and PCBs allowed for the justification of the approach to selecting a universal sample preparation scheme for simultaneous extraction and GC-MS determination of both classes of analytes. The possibilities of modifications of DLLME extraction of PAHs and PCBs, differing in dispersion method and nature of the extractor, were studied in combination with chromatographic-mass spectrometric determination of the analytes. Simultaneous extraction of super-toxicants was achieved by applying DLLME with a binary dispersant – 500 μl acetone + 500 μl acetonitrile and 150 μl chloroform as the extractor. The chloroform extract after DLLME extraction of the analytes without re-dissolution was used for GC-MS determination of 16 PAHs and 7 PCBs on a specific 60 m long capillary column with a 5% polyarylene + 95% dimethylpolysiloxane stationary phase with gradual heating of the thermostat from 60 to 290°C. Using the selected ion monitoring (SIM) mode increased the reliability of component identification in matrices of natural waters. The possibility of mutual influence of ecotoxicants on their extraction in the presence of each other was studied. Dispersive liquid-liquid microextraction with a binary dispersant provided simultaneous extraction of analytes at a level of 80-97%. The proposed analysis scheme allowed for GC-MS determination of 16 PAHs and 7 PCBs in the presence of each other in natural waters over a wide range of concentrations (0.02-40 μg/L) with an accuracy of 7-18% (PAHs) and 11-18% (PCBs). The relative standard deviations of repeatability and reproducibility for PAHs were in the ranges of 3.1-6.5% and 4.3-7.7%, respectively, and for PCBs 2.8-5.3% and 3.4-6.0%.

Smart agriculture for urban regions: Digital transformation strategies in the agro-industrial sector for enhanced compliance and economic growth

Research on this topic is becoming relevant due to the growing pressure on agriculture in urbanized regions due to population growth, climate change and the need for sustainable production, which requires the introduction of smart technologies to increase productivity and sustainability. The purpose of this paper is to investigate the impact of growing pressures on agriculture in urbanized regions due to population growth, climate change and sustainable production needs. The methods used include the analytical method, classification method, functional method, statistical method, synthesis method, and others. The study found that modern digital transformation technologies have great potential to improve agricultural productivity and sustainability in urbanized regions, particularly in Latvia and the European Union. The use of data analytics allowed identifying key trends and patterns, which contributed to informed decision-making in the agricultural sector. The study results confirmed the need to implement comprehensive strategies to achieve compliance with sustainable development standards and ensure economic growth. The introduction of modern agricultural technologies, such as aeroponics and hydroponics, has focused on innovative methods to increase productivity and ensure sustainability. The use of the Internet of Things (IoT), data analytics, and modern agricultural technologies has led to an increase in the efficiency of urbanized agriculture. The practical significance of the work lies in the development of specific recommendations aimed at optimizing the functioning of agriculture, which will increase the efficiency of resource use and ensure sustainable economic growth in urbanized regions

Application of the regression neural network for the analysis of the results of ultrasonic testing

Conducting a study on this topic becomes relevant due to the great importance of the safety of critical infrastructure facilities and the presence of operational defects in equipment elements and pipelines, which poses serious threats, including the possibility of equipment destruction and negative environmental impact. The purpose of this work is to study the possibility of using the diffraction-time technique of ultrasonic non-destructive testing together with a deep convolutional neural network to accurately determine the numerical value of the height of an operational crack. The methods used include the analytical method, classification method, functional method, statistical method, synthesis method, and others. The study found that an automated approach to measuring crack height, based on diffraction signals and the use of neural networks, significantly improved the quality and accuracy of non-destructive testing. Ultrasonic testing is one of the most common inspection methods for detecting service cracks and is considered to be the most effective. It allows for reliable detection of defects and determination of their size without destroying the product. The results of the study emphasize the high potential and efficiency of the method in analysing the data obtained and provide confirmation of its applicability for determining the condition of objects during ultrasonic inspection. The paper emphasizes that these technologies are particularly important and effective. It is noted that their widespread use in various industries, such as medicine, aviation, and machine learning, demonstrates their power in solving complex problems. The practical significance of the work lies in the development of advanced approaches that provide new insights and methods to improve the efficiency of analysing the results, which can be applied in industry to improve the quality of control and reliability of technical facilities

Innovative approaches to improving the agricultural sector in the era of digitalization of the economy

Conducting a study on this topic is becoming relevant due to the rapid introduction of digital technologies in the agricultural sector, which requires urgent study to effectively address current challenges in agriculture. The purpose of this paper is to analyse innovative approaches to improving the efficiency of economic activity in the agri-food sector. The methods used include the analytical method, classification method, functional method, statistical method, synthesis method, and others. The study found that the use of innovative approaches has significantly improved the productivity and sustainability of the agricultural sector. The use of blockchain technologies has increased trust in the supply chain by providing verified and transparent information on product quality. The analysis of large volumes of data has made it possible to develop specialized solutions and strategies tailored to specific business conditions in different regions. The results show an increase in the resilience of the agricultural sector to changes in economic and climate conditions. The findings of the study highlight the potential of digital transformation as a strategic tool for innovative and sustainable development of the agricultural sector. The study identified key strategies for the future implementation of digital technologies, taking into account the needs of the agricultural sector. The conclusion emphasizes the importance of introducing digital technologies to increase efficiency, improve management and ensure the sustainability of the industry in today’s digital economy. The practical significance of the paper is to analyse and highlight the factors that affect productivity and resource management in agriculture, which serves as a basis for further research and development of specific strategies and recommendations to improve the efficiency of the sector

Technical solutions to prevent blackouts in order to provide the population with electricity: The case of Ukraine

Due to the deteriorating condition of the power grids and the increasing number of power outages, research on technical solutions to prevent blackouts in the Ukrainian energy system is becoming an extremely relevant and necessary task. This study aims to analyse technical solutions aimed at increasing the resilience of Ukraine’s energy system to prevent blackouts and ensure reliable electricity supply to the population. The methods used include the analytical method, classification method, functional method, statistical method, synthesis method, and others. The study analysed modern technical solutions to improve the resilience of the Ukrainian energy system. The study included a detailed analysis of innovative approaches to modernizing the energy infrastructure. The primary objective was to study and evaluate modern technologies for designing new power lines with improved transmission characteristics. The study emphasized the importance of expanding automation systems to effectively monitor and control the state of the power grid. The study also identified the importance of using energy storage, developing renewable energy sources and improving electricity consumption forecasting systems. Flexible load management measures and improved cybersecurity systems were identified as critical. It is noted that the implementation of the project to provide electricity to the conditional area will be a key step in improving the lives of the local population and providing the necessary conditions for the development of the area’s infrastructure and economy. In addition, the operation of generators for electricity supply will help to reduce the feeling of lack of electricity among residents and ensure reliability in the use of electricity for all sectors of the district’s economy. The overall conclusion is that the implementation of such technical solutions will significantly increase the resilience of Ukraine’s energy system. The results obtained make it possible to effectively avoid blackouts and ensure a sustainable electricity supply to the population. This allows energy companies, government agencies and other stakeholders to optimize energy resource management and make informed decisions to ensure the sustainable and efficient operation of Ukraine’s energy system in the face of a possible blackout risk

Nanopore Fabrication Made Easy: A Portable, Affordable Microcontroller-Assisted Approach for Tailored Pore Formation via Controlled Breakdown.

With growing interest in solid-state nanopore sensing─a single-molecule technique capable of profiling a host of analyte classes─establishing facile and scalable approaches for fabricating molecular-size pores is becoming increasingly important. The introduction of nanopore fabrication by controlled breakdown (CBD) has transformed the economics and accessibility of nanopore fabrication. Here, we introduce the design of an Arduino-based, portable USB-powered CBD device, with an estimated cost of <150 USD, which is ≈10-100× cheaper than most commercial solutions, capable of fabricating single nanopores conducive for single molecule sensing experiments. We demonstrate the facile fabrication of 60 tailored nanopores (∼2.6-12.6 nm) with ∼80% of the pores within 1 nm of the target diameter. Selected pores were then tested with double-stranded DNA, the canonical molecular ruler, demonstrating their performance for single-molecule sensing applications. The device is constructed with off-the-shelf readily available components and controlled using a highly customizable MATLAB application, which has capabilities encompassing pore fabrication, pore enlargement, and current-voltage acquisition for pore size estimation. When combined with a portable amplifier, this device also provides a fully portable sensing platform, an important step toward portable solid-state nanopore sensing applications.

Analysis and optimization of torsion shafts in the context of improving the strength and durability of a light armoured vehicle

In the context of the continuous development of armoured vehicles and the increasing requirements for the strength and efficiency of armoured vehicles, the study and improvement of torsion shafts becomes relevant to ensure high service life and optimal functioning. The aim of this study is to analyse the torsion shafts of light armoured vehicles to identify possible areas of optimization to increase the strength and durability of these vehicle elements. The methods used include the analytical method, classification method, functional method, statistical method, synthesis method, and others. As a result of the study, a comprehensive analysis and optimization of torsion shafts for light armoured vehicles was carried out to increase their strength and durability. The choice of high-strength material and weight consideration helped to reduce the weight of the vehicle, increasing its efficiency. Geometric design included the use of advanced techniques to optimize the shaft shape, and stress and strain analysis helped determine the optimum parameters. The use of computer modelling and simulation simplified the analysis of the shaft’s behaviour under load. The use of safety factors and consideration of impact loads during operation helped to improve the reliability and durability of the structure. The use of the latest materials and manufacturing technologies allowed achieving the optimum parameters of the transmission element. Testing of the prototypes in real conditions confirmed their efficiency and durability. The optimization of weight and weight distribution was aimed at improving the stability of the armoured vehicle, taking into account the requirements of a particular application and manufacturer. The results indicate the potential for improving the design of torsion shafts to increase the performance and stability of light armoured vehicles. This study makes an important contribution to science, as the identified optimizations and improvements in the design of torsion shafts of light armoured vehicles contribute not only to increasing their strength and durability, but also to the rational use of resources and increasing the overall performance of the vehicle

Cross-curricular project-based laboratory learning enables hands-on interdisciplinary education for chemical engineering students

To enhance students’ interdisciplinary awareness and understanding of (i) high-pressure reactors, (ii) zeolites as catalysts and (iii) analysis of complex reactor effluents with unknown compounds, the laboratory exercises of two courses are coupled into a cross-curricular Project-Based laboratory Learning trajectory. The alkylation of anisole with 1-hexene proves to be an excellent case study for students to learn new objectives and strengthen the skills acquired in prior courses, emulating the work of expert engineers and analytical chemists. The time-efficient cross-curricular project proves effective in fostering teamwork and addressing complex engineering and analytical challenges. Student testimonials highlight the integrated project's success in providing new insights and cultivating advanced decision-making skills during experimentation. This approach also encourages future interdisciplinary collaborations between chemical engineering and analytical practice classes.

Nitro Indole Derivatives as Novel Dual-Polarity Matrices for MALDI Mass Spectrometry and Imaging with Broad Applications.

A new matrix framework is presented in this study for the improved ionization efficiency of complex mixtures by matrix-assisted laser desorption ionization (MALDI) mass spectrometry/imaging. Five nitro indole (NI) derivatives [3-methyl-4-nitro-1H-indole (3,4-MNI), 3-methyl-6-nitro-1H-indole (3,6-MNI), 2,3-dimethyl-4-nitro-1H-indole (2,3,4-DMNI), 2,3-dimethyl-6-nitro-1H-indole (2,3,6-DMNI), and 4-nitro-1H-indole (4-NI)] were synthesized and shown to produce both positive and negative ions with a broad class of analytes as MALDI matrices. NI matrices were compared to several common matrices, such as 2,5-dihydroxybenzoic acid (DHB), alpha-cyano-4-hydroxylcinnamic acid (CHCA), sinapinic acid (SA), 1,5-diaminonaphthelene (1,5-DAN), and 9-aminoacridine (9-AA), for the analysis of lipid, peptide, protein, glycan, and perfluorooctanesulfonic acid (PFOS) compounds. 3,4-MNI demonstrated the best performance among the NI matrices. This matrix resulted in reduced ion suppression and better detection sensitivity for complex mixtures, for example, egg lipids/milk proteins/PFOS in tap water, while 2,3,6-DMNI was the best matrix for blueberry tissue imaging. Several important aspects of this work are reported: (1) dual-polarity ion production with NI matrices and complex mixtures; (2) quantitative analysis of PFOS with a LOQ of 0.5 ppb in tap water and 0.05 ppb in MQ water (without solid phase extraction enrichment), with accuracy and precision within 5%; (3) MALDI imaging with 2,3,6-DMNI as a matrix for plant metabolite/lipid identification with ionization enhancement in the negative ion mode m/z 600-900 region; and (4) development of a thin film deposition under/above tissue method for MALDI imaging with a vacuum sublimation matrix on a high-vacuum MALDI instrument.

Investigation and optimisation of a lithium-drift silicon detector using Si–Li structure and bidirectional diffusion and drift techniques

Abstract The research relevance is predefined by the continuous development and improvement of radiation analysis methods and the need for more efficient and accurate detectors for various applications. This research may improve the sensitivity and resolution of Si(Li) detectors, which is important for scientific and industrial research as well as radiation safety monitoring. The research aims to analyse and improve the performance of a Si(Li) lithium-drift silicon detector. The methods used include an analytical method, classification method, functional method, statistical method, synthesis method and others. The results of the two-sided observation of lithium diffusion in silicon monocrystals provided valuable information about the characteristics of the process and its dependence on the method of silicon production. A large-diameter detector detection mode was found to be important for optimising the production of such detectors. The diffusion process in monocrystalline silicon produced by the shadowless zone melting method is relatively fast. This means that lithium ions penetrate the material rapidly and spread evenly throughout its volume. This fast diffusion process can be useful for detectors that need to respond quickly to incoming signals. It was found that in monocrystalline silicon produced by the Czochralski method, there is a delayed penetration of lithium ions.

Converting the energy of sea waves into electrical energy

AbstractThe study is highly relevant as ocean waves hold significant potential for producing electricity. Improvements in production, usage and rectification of research errors are crucial for meeting the energy demands of diverse consumers. The aim of this work is to put forward recommendations for eliminating design and implementation errors in wave energy conversion systems, specifically for offshore power plants, and to analyze their performance. Various methods were employed, including the analytical method, classification method, functional method, statistical method, synthesis method, and others. During the study, the characteristics and differences of ocean waves were observed, along with an analysis of the errors that can occur during the operation of offshore power plants designed for wave energy production and their associated causes. Uncertainties affecting the development of these power stations were identified, and the potential of sea waves as an energy resource was examined. Recommendations for enhanced regulation were put forward. The practicality lies in applying the identified findings to rectify errors in offshore power stations that use sea waves. This guarantees reliable operation by considering various factors and assists in recommending the optimal use of energy resources.

THE IMPORTANCE OF MULTIPLE ANALYTICAL STRUCTURES IN THE EVALUATION OF RISK EXPOSURES OF CONSTRUCTION PROJECTS

Construction projects are complex, multifaceted operations that involve multiple perspectives and different resources and activities. The success of a project depends on its ability to balance the resources and activities that comprise it in a way consistent with all of its stakeholders' needs. Construction projects must be evaluated from different perspectives to assess risk exposures. Each view will render a different financial impact depending on which resources and activities are included in a particular perspective. A separate analysis of a single project mandates a computer-assisted framework to define multiple analytical classes. Multiple analysis of a single project implies comparing various projects by the same analytical structure. This paper discusses a framework that enables an arbitrary number of analytical classes for a particular project.

Oil and global politics after 24 February 2022

A study of the impact of oil on global politics at this time is necessary to understand the relationship between energy security, geopolitical conflicts, and economic relations, which could substantially affect the future of the global energy landscape and international relations. The purpose of this study was to analyse the impact of the oil market on geopolitical relations and develop strategies to ensure energy security and stability in the international arena. The meth- ods employed include the analytical method, classification method, functional method, statistical method, and synthesis method. The study found that the rise in oil and other energy prices after the outbreak of geopolitical conflicts led to a considerable increase in economic pressure on importing countries. It was emphasised that the development of alterna- tive energy sources has become a vital strategic step to reduce dependence on oil. For instance, expanding the use of solar and wind power can help to balance the energy mix and reduce risks from geopolitical turbulence. The study analysed the possibilities of international cooperation in the energy sector to ensure energy security and stability in the global market. It was found that synergy between countries can help reduce the impact of geopolitical conflicts on the energy market and ensure sustainable energy supplies. It was established that the transition to alternative energy sources and the de- velopment of effective energy security strategies are key factors in supporting the sustainable development of national economies in a changing geopolitical environment. The conclusion is that there is a need to intensify efforts to develop and implement a comprehensive approach to energy regulation to ensure energy stability and maintain international peace and security. The authorities, business, and other stakeholders can use the findings of this study to make strategic decisions in the field of energy and global economic relations

Methods and technical means of reducing power losses in 0.38 kV networks with a symmetering device

The relevance of this paper is due to the need to solve a specific problem, which is the reduction of power losses in asymmetrical electric receivers. The purpose of this paper is to develop methodological prerequisites for analyzing ways to reduce power losses caused by asymmetry of currents in a 0.38 kV network and to study the influence of current asymmetry on the increase of electrical losses, as well as to determine the effectiveness of symmetrical devices in reducing these losses. Among the methods used, we should mention the analytical method, classification method, functional method, statistical method, synthesis method and others. This paper highlights the issue of developing a methodology and theoretical studies, as well as conducting experimental studies on additional power losses caused by asymmetry of currents and voltages in 0.38 kV networks using symmetrical devices. The solution of problems of power supply and improvement of electric power quality in such low-voltage networks is closely connected with the problem of current asymmetry reduction. This study is of practical importance as it contributes new scientific knowledge and offers practical recommendations for effective improvement of low-voltage power networks.

FÁRMACOS NA PANDEMIA DA COVID-19: UMA TEMÁTICA PARA A EDUCAÇÃO AMBIENTAL CRÍTICA NO ENSINO DE QUÍMICA ANALÍTICA

PHARMACEUTICALS IN THE COVID-19 PANDEMIC: A THEME TO CRITICAL ENVIRONMENTAL EDUCATION ON ANALYTICAL CHEMISTRY TEACHING. During the COVID-19 pandemic, the pursuit of a cure for the disease resulted in an excessive consumption of various pharmaceuticals, even after their inefficacy had been scientifically demonstrated. This scenario highlights the urgency of educational initiatives that improve students’ critical thinking and promote awareness of indiscriminate use of pharmaceuticals and its environmental and social implications. This research described the educational initiative “Pharmaceuticals in the COVID-19 pandemic” based on the study case method, implemented at an analytical chemistry class, and analyzed its potential on promoting Critical Environmental Education through a content analysis guided by the indicators proposed by Luz and Tonso. Students were divided into groups and studied different cases about pharmaceuticals featured in the media during the pandemic. They were expected to gather relevant data regarding the case scenario; to take a position on a socio-environmental dilemma; propose an analytical chromatographic methodology for the pharmaceutical in the case and present their results in a final report. The educational initiative was considered aligned with Critical Environmental Education principals due to the presence of six out of the seven indicators. As a future perspective, we aim to optimize the educational initiative in order to include all the indicators and students’ suggestions.

Searching for global equilibrium: How new economic statecraft undermines international institutions

The rise of “new economic statecraft”—intervention in trade and investment for foreign policy reasons—is increasingly threatening the stability of the global economic system. Building on previous work, we consider the types of intervention we have seen, classifying state measures as behind the border, at the border, and beyond the border. In addition, in the past, we have focused on understanding variation in new forms of economic statecraft through a five-factor model. This paper's central goal is to evaluate alternatives for constraining economic statecraft via institutional approaches. To this end, we draw on an analytical classification framework to theoretically and empirically analyze both sectoral and overall bilateral, minilateral, and multilateral institutional approaches to glean lessons for the management of new economic statecraft.

Certain Results on Subclasses of Analytic and Bi-Univalent Functions Associated with Coefficient Estimates and Quasi-Subordination

The purpose of the present paper is to introduce and investigate new subclasses of analytic function class of bi-univalent functions defined in open unit disks connected with a linear q-convolution operator, which are associated with quasi-subordination. We find coefficient estimates of h2, h3 for functions in these subclasses. Several known and new consequences of these results are also pointed out. There is symmetry between the results of the subclass fq,∑ μ(ζ,n,ρ,σ,ϑ,γ,δ,φ) and the results of the subclass ℵ∑q,δλ,ζ,n,ρ,σ,ϑ,φ.