Minimization Method Research Articles

Thin-layer chromatography quantification of ibuprofen using digital imaging

Ibuprofen is a pharmaceutical that is commonly used to reduce inflammation and to treat headaches. A thin-layer chromatographic method combined with simple and inexpensive digital imaging is proposed for the determination and quantification of ibuprofen. The recommendations of the standard pharmacopoeia were followed with the addition of a minimal spotting method as a local calibration curve (n = 3) and comparison with a spotted sample. Images were acquired using a smartphone and then converted to greyscale using Fiji, an open-source image analysis software. The peak area and density of each spot was then calculated using a densitometric principle. To analyse the present image data, several images were taken with different filters. Using a calibration curve ranging in the range of 3 to 5 mg/mL, linearity could be determined across the subjected images (R2 ranging from 0.984 to 0.996), with a mean accuracy of 99.9 ± 2.20% and RSD of 2.20%. The method studied, using smartphone imaging and open-source software (Fiji), offered a simple and inexpensive application for the quantification of ibuprofen in pharmaceuticals, applicable to preliminary studies and curricula.Graphical abstractMethod proposal for ibuprofen quantification using digital image processing software (Fiji)

Thermodynamic analysis of the corrosion of high alumina cement by carbon dioxide

The integrity of the wellbore cement sheath plays a crucial role in the geological utilization and sequestration of carbon dioxide. Although high alumina cement (HAC) is a specialized cement with exceptional performance, additional research is required to assess its capability for long-term carbon dioxide sequestration. In this study, the effects of various corrosion conditions and pozzolanic materials on the corrosion of HAC were investigated by using the Gibbs energy minimization method. And the corrosion resistance of minerals was analyzed based on the multiphase chemical equilibrium theory. The results indicate that C3AH6 in HAC is the most susceptible to corrosion. As the temperature increases, more carbon dioxide is consumed for the complete reaction of the primary minerals in HAC. However, the corrosion of HAC is largely unaffected by system pressure. The high concentration of carbon dioxide in formation water accelerates mineral corrosion rates. In addition, the presence of Mg2+ and SO42− increases the formation of intermediate products during the corrosion of HAC, whereas the rate of mineral corrosion decreases as salinity increases. Fly ash can enhance the corrosion resistance of HAC during the initial stage of carbonization. Increasing the replacement ratio of fly ash to HAC reduces the generation of C3AH6 and increases the formation of C2ASH8. The corrosion resistance of each mineral is different, following the order: Al(OH)3 > C2ASH8 > C4AcH11 > C4Ac0.5H12 > C3AH6.

Failure diagnosis for time-modulated arrays based on compressed sensing

Time-modulated arrays (TMAs) have a high design degrees of freedom (DoFs) to improve radiation performance, while they are prone to failure due to their hardware characteristics. In this article, we propose a novel technique to diagnose impaired TMAs based on compressed sensing (CS). The TMA diagnosis problem is reformulated as a sparse signal recovery problem at the center frequency and sidebands. Then, a method based on the difference of convex sets theory and sequential convex programming (DCS-SCP) is developed to implement diagnosis for impaired TMAs. Using a small number of far-field measurements at the same position but different frequencies, the joint recovery of the equivalent excitations at the center frequency and sidebands is realized by a mixed l 0 / l 2 -norm minimization method. The numerical simulation and the successful comparison with the state-of-the-art algorithms demonstrate the superiority of the proposed methods in terms of noise robustness and diagnosis accuracy.

Minimal residual methods in negative or fractional Sobolev norms

For numerical approximation the reformulation of a PDE as a residual minimisation problem has the advantages that the resulting linear system is symmetric positive definite, and that the norm of the residual provides an a posteriori error estimator. Furthermore, it allows for the treatment of general inhomogeneous boundary conditions. In many minimal residual formulations, however, one or more terms of the residual are measured in negative or fractional Sobolev norms. In this work, we provide a general approach to replace those norms by efficiently evaluable expressions without sacrificing quasi-optimality of the resulting numerical solution. We exemplify our approach by verifying the necessary inf-sup conditions for four formulations of a model second order elliptic equation with inhomogeneous Dirichlet and/or Neumann boundary conditions. We report on numerical experiments for the Poisson problem with mixed inhomogeneous Dirichlet and Neumann boundary conditions in an ultra-weak first order system formulation.

DAMAGE TO THE HEAT EXCHANGE SURFACE OF STEAM GENERATOR PGV-1000

A comprehensive analysis of the damaged heat exchange surface of the PGV-1000 steam generator during long-term operation, their relationship with hydrodynamic, water-chemical regimes and surface properties was conducted. The methods of minimization of damages during the operation of Ukraine's NPP are considered.

Experimental investigation on the thermal and flow performance of a thermodynamically-balanced packed bed humidification system

In this paper, a packed bed humidification system filled with corrugated wire mesh was experimentally investigated to obtain a better humidification performance. To thermodynamically balance the simultaneous heat and mass transfer process, multiple water injection bypasses were fabricated at different packing heights based on the entropy generation minimization method. In addition to the inlet water temperature, the influences of the liquid–gas ratio and injection ratio on the humidification capacity, energy effectiveness, and pressure drop were respectively studied and discussed. The experimental and comparison results demonstrated that the established humidification device was robust and superior. It was summarized that raising the number of injections can significantly elevate the humidification capacity, and synchronously magnify the pressure drop for all the cases, while the effectiveness behaved a reverse trend. Additionally, a higher value of the inlet water temperature could increase the humidification capacity and effectiveness, as well as the pressure drop. And, an elevation amplitude of the humidification capacity emerged as 35.51% for the double water injections with a maximum value of 1.48 × 10−2 kgs−1 once the liquid–gas ratio increased from 1 to 1.36, while the value was 39.13% as the injection ratio raised from 0.33 to 0.7. Furthermore, it was illustrated that increasing the mass flow rate of the liquid will reduce the effectiveness when the heat capacity rate ratio is larger than 1, and the effectiveness can reach 0.97 at Twi = 70 °C. In the process of thermodynamic balancing, the increase in the pressure drop of humid air should receive more attention for the designer and researcher related to the packed bed humidifier.

RELIABILITY OF HYDROPNEUMODRIVES FOR METAL CUTTING EQUIPMENT

The reliability of hydropneumodrives largely determines the safety of machine tools, metal cutting equipment, the movement of transport vehicles, and the flight of modern passenger aircraft, and their failures can in some cases lead to accidents. The design stage is crucial in ensuring reliability. The main tasks of reliability research and calculation at this stage can be divided into three groups. First, it is a justification of reliability requirements for the main elements of the hydraulic pneumatic actuator (the task of reliability norming). This task is solved at an early stage of design and involves the preliminary development of the unit structure and justification of design principles. Secondly, it is to ensure the reliability of the elements and the unit as a whole. This group of tasks includes research and quantitative assessment of the efficiency of possible ways to ensure reliability; selection of basic design characteristics, statistical reserves of durability and longevity, stability reserves and other indicators; comparative analysis of options and selection of optimal designs. Thirdly, these are control calculations of the unit's reliability according to the design documentation. Algorithms for the distribution of normalised reliability indices at the design stage for hydropneumodrives implemented by the standard positional structure method and the minimisation method are obtained. Algorithms allow already at the early stages of hydropneumodrive design to normalise reliability indices, which makes it possible to obtain optimal solutions of reliability issues at the subsequent stages of development of the drive life cycle. The methods of calculation and determination of design relations for finding quantitative characteristics of failure-free indices of designed hydropneumodrives, implemented by the method of standard positional structure and the method of minimisation, are selected, which allows designing highly reliable hydropneumodrives for new metal cutting equipment. Evaluation of reliability indicators of hydropneumodrives at the stage of preliminary design allows to make a rational choice of structural scheme and parameters, to select appropriate materials and elements of scheme realisations.

Autothermal Reforming of Methane: A Thermodynamic Study on the Use of Air and Pure Oxygen as Oxidizing Agents in Isothermal and Adiabatic Systems

In this paper, we analyze the autothermal reforming (ATR) of methane through Gibbs energy minimization and entropy maximization methods to analyze isothermic and adiabatic systems, respectively. The software GAMS® 23.9 and the CONOPT3 solver were used to conduct the simulations and thermodynamic analyses in order to determine the equilibrium compositions and equilibrium temperatures of this system. Simulations were performed covering different pressures in the range of 1 to 10 atm, temperatures between 873 and 1073 K, steam/methane ratio was varied in the range of 1.0/1.0 and 2.0/1.0 and oxygen/methane ratios in the feed stream, in the range of 0.5/1.0 to 2.0/1.0. The effect of using pure oxygen or air as oxidizer agent to perform the reaction was also studied. The simulations were carried out in order to maintain the same molar proportions of oxygen as in the simulated cases considering pure oxygen in the reactor feed. The results showed that the formation of hydrogen and synthesis gas increased with temperature, average composition of 71.9% and 56.0% using air and O2, respectively. These results are observed at low molar oxygen ratios (O2/CH4 = 0.5) in the feed. Higher pressures reduced the production of hydrogen and synthesis gas produced during ATR of methane. In general, reductions on the order of 19.7% using O2 and 14.0% using air were observed. It was also verified that the process has autothermicity in all conditions tested and the use of air in relation to pure oxygen favored the compounds of interest, mainly in conditions of higher pressure (10 atm). The mean reductions with increasing temperature in the percentage increase of H2 and syngas using air under 1.5 and 10 atm, at the different O2/CH4 ratios, were 5.3%, 13.8% and 16.5%, respectively. In the same order, these values with the increase of oxygen were 3.6%, 6.4% and 9.1%. The better conditions for the reaction include high temperatures, low pressures and low O2/CH4 ratios, a region in which there is no swelling in terms of the oxygen source used. In addition, with the introduction of air, the final temperature of the system was reduced by 5%, which can help to reduce the negative impacts of high temperatures in reactors during ATR reactions.

Techno-economic modelling for energy cost minimisation of a university campus to support electric vehicle charging with photovoltaic capacity optimisation

Workplace charging of Electric Vehicles (EV) is a promising approach for transport decarbonization while addressing issues emerging from renewable energy growth. For workplaces, the decision to invest in EV charging infrastructure depends on the overall cost of providing this service. This study proposes a novel modelling approach to minimize the net annual energy cost of a university campus providing EV charging service using optimum capacity solar photovoltaic (PV) systems. The research includes an innovative approach to determine the campus EV charging demand and a novel net annual energy cost minimisation method combining PV size optimisation and EV charging control. A comprehensive analysis is presented to illustrate the influence of EV penetration, charging strategy, charging fees, charger cost and PV generation cost on the campus net annual energy cost. The influence of these parameters are also analysed on the optimal PV capacity, power and energy demand, and PV self-utilisation. Results show that, by using the proposed method, for 25 % EV penetration, the campus's peak demand is reduced by around 12 % and net annual energy cost is reduced by up to 9.2 % while providing free EV charging. The net annual energy cost reduction increases to over 20 % for 100 % EV penetration.

3D reconstruction of the scapula from biplanar X-rays for pose estimation and morphological analysis.

Patient-specific scapular shape in functional posture can be highly relevant to clinical research. Biplanar radiography is a relevant modality for that purpose with already two existing assessment methods. However, they are either time-consuming or lack accuracy. The aim of this study was to propose a new, more user-friendly and accurate method to determine scapular shape. The proposed method relied on simplified manual inputs and an upgraded version of the first 3D estimate based on statistical inferences and Moving-Least Square (MLS) deformation of a template. Then, manual adjustments, with real-time MLS algorithm and contour matching adjustments with an adapted minimal path method, were added to improve the match between the projected 3D model and the radiographic contours. The accuracy and reproducibility of the method were assessed (with 6 and 12 subjects, respectively). The shape accuracy was in average under 2mm (1.3mm in the glenoid region). The reproducibility study on the clinical parameters found intra-observer 95% confidence intervals under 3mm or 3° for all parameters, except for glenoid inclination and Critical Shoulder Angle, ranging between 3° and 6°. This method is a first step towards an accurate reconstruction of the scapula to assess clinical parameters in a functional posture. This can already be used in clinical research on non-pathologic bones to investigate the scapulothoracic joint in functional position.

Rethinking Logic Minimization for Tabular Machine Learning

Tabular datasets can be viewed as logic functions that can be simplified using two-level logic minimization to produce minimal logic formulas in disjunctive normal form (DNF), which in turn can be readily viewed as an explainable decision rule set for binary classification. However, there are two problems with using logic minimization for tabular machine learning. First, tabular datasets often contain overlapping examples that have different class labels, which have to be resolved before logic minimization can be applied since logic minimization assumes <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">consistent</i> logic functions. Second, even without inconsistencies, logic minimization alone generally produces complex models with poor generalization because it exactly fits all data points, which leads to detrimental <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">overfitting</i> . How best to remove training instances to eliminate inconsistencies and overfitting is highly non-trivial. In this paper, we propose a novel statistical framework for removing these training samples so that logic minimization can become an effective approach to tabular machine learning. Using the proposed approach, we are able to obtain comparable performance as gradient boosted and ensemble decision trees, which have been the winning hypothesis classes in tabular learning competitions, but with human-understandable explanations in the form of decision rules. To our knowledge, neither logic minimization nor explainable decision rule methods have been able to achieve state-of-the-art performance before in tabular learning problems.

Discontinuous PWM Technique With Reduced Low-Order Harmonic Distortion for High-Power Applications

The modulation techniques used in high power applications have to generate high quality waveforms with reduced switching losses. As an attractive alternative, Discontinuous PWM (DPWM) techniques present lower device switching frequencies than conventional continuous PWM methods lowering the converter switching loss. Considering the same cooling system, this allows to increase the carrier frequency of DPWM methods displacing the main switching harmonics to higher frequencies. As a main drawback, when low carrier to fundamental ratios are used, DPWM methods present some undesired low-order harmonics that are required to be filtered. This paper presents a low-order harmonic minimization method for synchronous DPWM methods by modifying the conventional modulating reference to limit low order harmonics amplitude, while keeping the same effective switching frequency and thus limited switching losses.

Back-Azimuth Estimation of Air-to-Ground Coupled Infrasound from Transverse Coherence Minimization

AbstractWe present the transverse coherence minimization method (TCM)—an approach to estimate the back-azimuth of infrasound signals that are recorded on an infrasound microphone and a colocated three-component seismometer. Accurate back-azimuth information is important for a variety of monitoring efforts, but it is currently only available for infrasound arrays and for seismoacoustic sensor pairs separated by 10 s of meters. Our TCM method allows for the analysis of colocated sensor pairs, sensors located within a few meters of each other, which may extend the capabilities of existing seismoacoustic networks and supplement operating infrasound arrays. This approach minimizes the coherence of the transverse component of seismic displacement with the infrasound wave to estimate the infrasound back-azimuth. After developing an analytical model, we investigate seismoacoustic signals from the August 2012 Humming Roadrunner experiment and the 26 May 2021 eruption of Great Sitkin Volcano, Alaska, U.S.A., at the ranges of 6.5–185 km from the source. We discuss back-azimuth estimates and potential sources of deviation (1°–15°), such as local terrain effects or deviation from common analytical models. This practical method complements existing seismoacoustic tools and may be suitable for routine application to signals of interest.

Stabilized isogeometric formulation of the Stokes problem on overlapping patches

We present a novel stabilized isogeometric formulation for the Stokes problem, where the geometry of interest is obtained via overlapping NURBS (non-uniform rational B-spline) patches, i.e., one patch on top of another in an arbitrary but predefined hierarchical order. All the visible regions constitute the computational domain, whereas independent patches are coupled through visible interfaces using Nitsche’s formulation. Such a geometric representation inevitably involves trimming, which may yield trimmed elements of extremely small measures (referred to as bad elements) and thus lead to the instability issue. Motivated by the minimal stabilization method that rigorously guarantees stability for trimmed geometries (Buffa et al., 2020), in this work we generalize it to the Stokes problem on overlapping patches. Central to our method is the distinct treatments for the pressure and velocity spaces: Stabilization for velocity is carried out for the flux terms on interfaces, whereas pressure is stabilized in all the bad elements. We provide a priori error estimates with a comprehensive theoretical study. Through a suite of numerical tests, we first show that optimal convergence rates are achieved, which consistently agrees with our theoretical findings. Second, we show that the accuracy of pressure is significantly improved by several orders using the proposed stabilization method, compared to the results without stabilization. Finally, we also demonstrate the flexibility and efficiency of the proposed method in capturing local features in the solution field. This contribution is dedicated to Thomas J.R. Hughes, as a tribute to his remarkable lifetime achievements.

Psycho-images of Language Units in the Consciousness of the Individual - the Basis of Bilingual and Intercultural Communication

The contact of languages and cultures forms bilingualism and biculturalism at different levels of their functioning. The purpose of the article is to analyze and describe the dual simultaneous formation and functioning of bilingual and bicultural communication based on the material of contact between the Kazakh and Russian languages. Language is the basis of bilingualism and biculturalism, since both bilingual and intercultural processes in an individual and society are carried out through the use of language units. Psycho-images of linguistic units and cultural symbols are formed in the consciousness of an individual of society, which are the basis of monolingual and monocultural communication within an ethnos. These national-linguistic-cultural psycho-images contribute to the formation of foreign, foreign-cultural psycho-images in the minds of the future bilingual, bicultural individual and society. The materials of the study were Kazakh (In general, Turkic), Russian linguistic and speech units, universal and national-specific cultural concepts and symbols, which, on the one hand, give rise to interference, on the other hand, facilitation, the latter facilitates the assimilation of non-native languages and cultures. Therefore, teaching a second language will be more effective if it is carried out when teaching and language material is presented in a harmonious combination of the language, which, in content, are logically closely interconnected with the cultural values of the foreign people. In the course of the study, methods of comparative analysis, opposition of minimal pairs, methods and techniques of inductive and deductive nature were used. The results of the scientific research are of theoretical and practical importance in the aspect of the formation of bilingualism of knowledge, skills and abilities of intercultural communication in the conditions of active Turkic-foreign (Kazakh-Russian) bilingualism and biculturalism.

Targeted quantitative metabolic profiling of brain-derived cell cultures by semi-automated MEPS and LC-MS/MS

The accurate characterisation of metabolic profiles is an important prerequisite to determine the rate and the efficiency of the metabolic pathways taking place in the cells. Changes in the balance of metabolites involved in vital processes such as glycolysis, tricarboxylic acid (TCA) cycle, oxidative phosphorylation (OXPHOS), as well as in the biochemical pathways related to amino acids, lipids, nucleotides, and their precursors reflect the physiological condition of the cells and may contribute to the development of various human diseases. The feasible and reliable measurement of a wide array of metabolites and biomarkers possesses great potential to elucidate physiological and pathological mechanisms, aid preclinical drug development and highlight potential therapeutic targets. An effective, straightforward, sensitive, and selective liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach was developed for the simultaneous quali-quantitative analysis of 41 compounds in both cell pellet and cell growth medium obtained from brain-derived cell cultures. Sample pretreatment miniaturisation was achieved thanks to the development and optimisation of an original extraction/purification approach based on digitally programmed microextraction by packed sorbent (eVol®-MEPS). MEPS allows satisfactory and reproducible clean-up and preconcentration of both low-volume homogenate cell pellet lysate and cell growth medium with advantages including, but not limited to, minimal sample handling and method sustainability in terms of sample, solvents, and energy consumption. The MEPS-LC-MS/MS method showed good sensitivity, selectivity, linearity, and precision. As a proof of concept, the developed method was successfully applied to the analysis of both cell pellet and cell growth medium obtained from a line of mouse immortalised oligodendrocyte precursor cells (OPCs; Oli-neu cell line), leading to the unambiguous determination of all the considered target analytes. This method is thus expected to be suitable for targeted, quantitative metabolic profiling in most brain cell models, thus allowing accurate investigations on the biochemical pathways that can be altered in central nervous system (CNS) neuropathologies, including e.g., mitochondrial respiration and glycolysis, or use of specific nutrients for growth and proliferation, or lipid, amino acid and nucleotide metabolism.

Adaptive stabilized finite elements via residual minimization onto bubble enrichments

The Adaptive Stabilized Finite Element method (AS-FEM) developed in [16] combines the idea of the residual minimization method with the inf-sup stability offered by the discontinuous Galerkin (DG) frameworks. As a result, the discretizations deliver stabilized conforming approximations and residual representatives in a DG space that can drive automatic adaptivity. In this work, we extend AS-FEM by considering continuous enriched test spaces. Thus, we propose a residual minimization method on a stable Continuous Interior Penalty (CIP) formulation, which considers a C0-conforming trial FEM space and a test space based on the bubble enrichment of that trial space. In our numerical experiments, the test space choice significantly reduces the total degrees of freedom compared to the DG test spaces of [16], while recovering the expected convergence rate for the error in the corresponding trial space norm.

Bivariate retrieval from intensity of cross-correlation

Pulse characterization in ultra-fast optics presents a powerful motivation to study phase retrieval problems of high order. Frequency- and time-resolved techniques for pulse characterization both construct measurements that depend on the intensity of the cross-correlation between two unknown signals undergoing known modulations. The problem of recovering these signals has been traditionally studied and solved with alternating minimization, but recently Wirtinger gradient techniques were demonstrated to invert frequency-resolved measurements on a symmetric signal pair (Pinilla et al., 2019). In this paper, we construct a generalized Wirtinger gradient and Hessian to solve a wide breadth of problems including signal recovery from time- and frequency-resolved measurements. We further demonstrate that both measurement paradigms are special cases of low-rank phase retrieval but with a special structure that disrupts spectral initializers. To combat this problem, we present a tensor-based iterative hard thresholding initializer that, when paired with a Wirtinger gradient descent, is capable of recovering unknown signals with fewer measurements than matrix-based alternating minimization or spectral initialization methods. Finally, we employ Wirtinger gradient descent to recover signals from real-world DSCAN (Wilhelm et al., 2021) measurements and compare results with the existing state-of-the-art.

Proximal variable smoothing method for three-composite nonconvex nonsmooth minimization with a linear operator

Proximal variable smoothing method for three-composite nonconvex nonsmooth minimization with a linear operator

An Enhancement of the Accuracy of the BiCGStab Method for Solving Linear Systems with Single or Multiple Right-Hand Sides

In this paper, we present a technique to improve the convergence of the biconjugate gradient stabilized (BiCGStab) method. This method was developed by Van der Vorst for solving nonsymmetric linear systems with a single right-hand side. The global and block versions of the BiCGStab method have been proposed for solving nonsymmetric linear systems with multiple right-hand sides. Using orthogonal projectors to minimize the residual norm in each step, we get an enhancement of the convergence of each version of the BiCGStab method. The considered methods are BiCGStab, global BiCGStab, and block BiCGStab methods, noted, respectively, as Gl-BiCGStab and Bl-BiCGStab. To show the performance of our enhanced algorithms, we compare them with the standard, global, and block versions of the well-known generalized minimal residual method (GMRES).