Analytical Matrices Research Articles

Update stiffness matrix using the displacement output feedback technique

The analytical matrices of a finite element model are generally symmetric and positive definite (semidefinite). How to ensure that the coefficient matrices of the adjusted model have such properties is an important yet challenging task in the process of model updating. In this paper, we put forward a direct method to update the stiffness matrix of the undamped structural systems by means of the displacement output feedback technique. Utilizing the QR-decomposition and the singular value decomposition, the required displacement output feedback gain matrix is found, and the explicit representation of the optimal adjusted stiffness matrix is achieved. The introduced method can ensure that the updated stiffness matrix is symmetric and positive semidefinite. Finally, two numerical examples verify the accuracy of the results obtained.

Competencias investigativas en docentes de ciencias de la salud

Teaching is a task that usually requires scientific research because, from it, knowledge is strengthened not only in the area of teaching performance but also in the development of pedagogical strategies. Considering these ideas, this article has proposed as a general objective, to characterize the research competencies of Health Sciences teachers in universities in Ecuador. In its methodological orientation, it is descriptive research with a documentary design that uses known databases, including Dialnet, Google Academic, and Scielo. Thus, authors and research are selected concerning the dimensions of teaching research competencies, that is, research, publications, methodological expertise, and digital literacy. Subsequently, the results are presented in categorical tables or analytical matrices that contrast the theoretical elements with some realities of universities in the country, specifically in the health area. Among the study findings, the need to strengthen teachers' research skills is specified based on their scientific production, the number of publications, and their task in terms of forging the student profiles they are in charge of in the classroom. It concludes with the projection of the desired teaching profile, in terms of skills for research in the field of health, which is pertinent to promote in higher education centers in Ecuador.

An iterative method for updating finite element models with connectivity constraints

It is well known that the analytical matrices arising from the discretization of distributed parameter systems using the finite element technique are usually symmetric and banded. How to preserve the coefficient matrices of the updated model being of the same band structure is an important yet difficult challenge for model updating in structural dynamics. In this paper, an iterative method for updating mass, damping and stiffness matrices simultaneously based on partial modal measured data is provided. By the method, the optimal updated matrices can be obtained within finite iteration steps by choosing a special kind of initial matrix triplet. The proposed approach not only preserves the physical connectivity of the original model, but also the updated model reproduces the measured modal data, which can be utilized for various finite element model updating problems. Numerical examples confirm the effectiveness of the introduced method.

Navigating the realm of noncommutative probability: Historical perspectives and future directionsstorical perspectives and future directions

This review article provides a comprehensive overview of the fascinating field of noncommutative probability theory, tracing its evolution from its inception in the early 1980s by Romanian-American mathematician Dan Voiculescu to its current state of prominence in mathematics. Through a meticulous examination of seminal works and recent advancements, we explore the key concepts, methodologies, and significant developments in this field, emphasizing the combinatorial aspects of noncommutative probability spaces, including non-crossing partitions and linked partitions. This exploration encompasses various aspects, including analytical methods, operator algebras, random matrices, and combinatorial structures. Additionally, it concludes with the current understanding and potential directions for future research.

Sparse structure preserving finite element model updating problem for gyroscopic systems

An important yet difficult aspect of the finite element model updating problem is to preserve the original inherent structures in the updated model. The analytical matrices resulting from the discretization of distributed parameter systems using finite element techniques are often symmetric and sparse. In this paper, an iterative method is proposed for solving the constrained optimization problem (COP) of gyroscopic systems, that is, finding the optimal updated matrices M̂,Ĝ and K̂ that satisfy the constraints of the characteristic equation, symmetry (or skew-symmetry) and sparsity. The proposed method is proved to be convergent and numerical examples verify the effectiveness of the method.

Physical activity and mental health experiences of people living with long term conditions during COVID-19 pandemic: A qualitative study.

Regular physical activity is a strategy that is effective in the physical management of long term conditions. The COVID-19 pandemic, led to disruption of physical activity routines for many people with long term conditions. It is important, to understand the experiences of people with long term conditions regarding physical activity during COVID-19 to enable future identification of strategies to mitigate the impact of restrictions on health. To explore perceptions and experiences of people with long term conditions of the impact of the UK Government physical distancing restrictions on their physical activity participation during the COVID-19 pandemic. A qualitative study, with in depth videoconference semi-structured interviews were conducted between January and April 2022, with 26 adults living with at least one long term condition in the UK. Data were managed in analytical matrices within Excel and data analysis was conducted using thematic analysis. Two main themes were developed, explaining how participants managed their physical activity during COVID19 lockdowns, and based on those experiences, what they considered should be in place should another lockdown occur:1) COVID-19 and physical activity: Losses, opportunities and adapting to new formats; and 2) Micro, meso, and macro contexts: creating the right conditions for physical activity support in future pandemics. This study provides information on how people with long term conditions managed their condition during the COVID-19 pandemic and generates new understanding of how physical activity routines changed. These findings will be used to inform stakeholder engagement meetings with individuals with long term conditions and local, regional, and national policy makers, to co-produce recommendations that will help people living with long term conditions remain active during and after COVID-19 and other pandemics.

Strategic analysis for Imbocar enterprise, Valledupar branch - Colombia

The critical challenge of contemporary management involves making effective, efficient, and accurate decisions that drive the effectiveness of internal processes and, consequently, achieve organizational goals. Such decision-making must consider internal and external factors to optimize organizational outcomes. In line with this, a strategic analysis was carried out at the Imbocar branch in Valledupar, with the explicit aim of identifying strategies that promote internal improvement and growth in various market sectors. The analysis was based on a study designed with an interpretivist methodology and a qualitative approach. It included an interview with the coordinator of the organization under study and the development of analytical matrices, including Porter's Five Forces, EFE, EFI, IE, SWOT, PESTEL, CPME, and MICMAC. As a primary outcome of this strategic analysis, various strategies were identified, focusing on market growth, product/service development, and market penetration. These strategies are presented as significant contributions to internal improvement and the sustained growth of the aforementioned branch.

Ordered Mesoporous Electrodes for Sensing Applications.

Electrochemical sensors have become increasingly relevant in fields such as medicine, environmental monitoring, and industrial process control. Selectivity, specificity, sensitivity, signal reproducibility, and robustness are among the most important challenges for their development, especially when the target compound is present in low concentrations or in complex analytical matrices. In this context, electrode modification with Mesoporous Thin Films (MTFs) has aroused great interest in the past years. MTFs present high surface area, uniform pore distribution, and tunable pore size. Furthermore, they offer a wide variety of electrochemical signal modulation possibilities through molecular sieving, electrostatic or steric exclusion, and preconcentration effects which are due to mesopore confinement and surface functionalization. In order to fully exploit these advantages, it is central to develop reproducible routes for sensitive, selective, and robust MTF-modified electrodes. In addition, it is necessary to understand the complex mass and charge transport processes that take place through the film (particularly in the mesopores, pore surfaces, and interfaces) and on the electrode in order to design future intelligent and adaptive sensors. We present here an overview of MTFs applied to electrochemical sensing, in which we address their fabrication methods and the transport processes that are critical to the electrode response. We also summarize the current applications in biosensing and electroanalysis, as well as the challenges and opportunities brought by integrating MTF synthesis with electrode microfabrication, which is critical when moving from laboratory work to in situ sensing in the field of interest.

On an improved PDE-based elliptic parameterization method for isogeometric analysis using preconditioned Anderson acceleration

Constructing an analysis-suitable parameterization for the computational domain from its boundary representation plays a crucial role in the isogeometric design-through-analysis pipeline. PDE-based elliptic grid generation is an effective method for generating high-quality parameterizations with rapid convergence properties for the planar case. However, it may generate non-uniform grid lines, especially near the concave/convex parts of the boundary. In the present work, we introduce a novel scaled discretization of harmonic mappings in the Sobolev space H1 to remit it. Analytical Jacobian matrices for the involved nonlinear equations are derived to accelerate the computation. To enhance the numerical stability and the speed of convergence, we propose a simple and yet effective preconditioned Anderson acceleration framework instead of using computationally expensive Newton-type iteration. Three preconditioning strategies are suggested, namely diagonal Jacobian, block-diagonal Jacobian, and full Jacobian. Furthermore, we discuss a delayed update strategy of the preconditioner, i.e., the preconditioner is updated every few steps to reduce the computational cost per iteration. Numerical experiments demonstrate the effectiveness and efficiency of our improved parameterization approach and the computational efficiency of our preconditioned Anderson acceleration scheme.

Fictitious finite integration method for solving high order partial differential equations

In this paper, we combine the finite integration method (FIM) with the technique of fictitious points to solve high order partial differential equations (HOPDEs). Two type of fictitious finite integration method (FFIM) are proposed and analyzed. The first type FFIM (FFIM-I) constructs the first order integration matrices by shifted Chebyshev polynomials so that the analytical high order integration matrices can be recursively obtained. Compared with the classical FIM, whose high order integration matrices are approximated directly through low order integration matrices, this FFIM-I leads to higher accuracy. Based on FFIM-I, the second type FFIM (FFIM-II) is proposed in which the fictitious points are located freely either inside or outside the problem domain. The FFIM-II can further improve the performance of FFIM-I in solving HOPDEs. The advantage of this fictitious finite integration method will be demonstrated by making comparisons among FIM, FFIM-I and FFIM-II through several 2D and 3D numerical experiments.

SILENCING INDIGENOUS CULTURE IN HIGHER EDUCATION IN ECUADOR: A VIEW FROM SOCIAL WORK EDUCATION

This article arises from ongoing mixed methods research called “Intercultural Processes in Social Work Training: A Reflection on the Silencing of Indigenous Culture in Higher Education”. It is part of a line of research of the doctoral program of the University of Granada. The article presents an epistemological, theoretical and conceptual reflection on intercultural training in Social Work and the silencing of indigenous culture in higher education. For this purpose, a categorical scheme was built, and a documentary review carried out, the findings of which were processed through analytical matrices. The findings present an approach to the subject with specific references that will allow us to understand the reality of indigenous students. As well as the challenges faced by the educational system and Social Work, to reach a truly intercultural higher education in Ecuador.

Building of mid-infrared spectral signature of pesticides using functionally-enhanced derivative spectroscopy (FEDS)

Pesticides are synthetic substances widely used in several processes related to agriculture-based food production. Their monitoring is important to evaluate their impact on environment, ensure the food quality, and for the developing of new methods and strategies that help to understand their dynamics from the moment they are released until their end disposal. In this way, the use of mid-infrared spectroscopy (mid-IR spectroscopy) and chemometric methods have been widely explored. However, the strong overlap of spectral signals in complex analytical matrices is recognized as the main limitation of reflectance-based methods for monitoring of this kind of pollutant. In this work, the use of MID-IR spectroscopy by attenuated total reflectance (ATR), in conjunction with functionally-enhanced derivative spectroscopy (FEDS), is proposed as non-destructive technique for fast and simple monitoring of pesticides. Thus, high-resolution dynamic spectral signature (HDSS) for six pesticides commonly used in tropical crops were used as model substances; as analytical matrix was used the peel of banana (e.g., Musa paradisiaca). In addition, concentration effect was evaluated to mimic real conditions. Data recording was obtained by mid-IR spectroscopy (from 4000 to 600 cm−1) and HDSS were evaluated by Pearson’s correlation coefficient and spectral similarity FEDS index between the spectra and the reference signals. Based on these correlation parameters, some selection criteria are proposed to estimate the spectral zones where the pesticide signature persists even at relative low concentrations. For the six pesticides, the spectral region considered coincide with those bands of high polarity bonds in the pesticide molecules. Additionally, a good linear prediction models that correlate the relative absorbance intensity and the peak area of the mid signal with the pesticide concentration level are obtained in the spectral ranges of interest. The model performance is defined by Pearson’s coefficients rf greater than 0.97, residual prediction deviation RPDs (root mean square errors - RMSEs) greater (lower) than 5 (3), and limits of detection (LODs) lower than 1 g/kg. Furthermore, this methodology and results are successfully employed to detect Chlorpyrifos residues in banana peel.

Modelling of acoustic metamaterial sound insulator using a transfer matrix method for aircraft cabin applications

The incorporation of acoustic metamaterials in the design of aircraft fuselage panels in order to reduce the low frequency noise inside the cabin is nowadays a major research subject in order to offer passengers a comfortable cabin environment. In this study, acoustic metamaterial made of Helmholtz resonators periodically embedded into a porous material is investigated using a transfer matrix approach combined with finite element calculations. This transfer matrix method is based on the two-load methods where the two loads in the numerical simulations are two different termination conditions (plane wave radiation and rigid wall) in order to retrieve the equivalent transfer matrix of the porous layer with embedded periodic Helmholtz resonators. The equivalent matrix is then coupled analytically in series with others analytical matrices to model complex multilayer metamaterials. The results of the transmission loss obtained exclusively using finite element method for single and double wall configurations are compared with the results of the proposed transfer matrix method and good agreements are obtained. It is observed that the frequency band of the transmission loss of the double wall configuration is larger than the one of the single wall configuration with higher transmission loss peak value. The investigated metamaterial can potentially be used in the design of aircraft cabin panels for low frequency noise reduction.

Develop and prioritize domestic wastewater use scenarios with SWOT and QSPM analytical matrices — case study: Sabzevar City treatment plant

Develop and prioritize domestic wastewater use scenarios with SWOT and QSPM analytical matrices — case study: Sabzevar City treatment plant

Urban Crises and the Covid-19 Pandemic: An Analytical Framework for Metropolitan Resiliency

Social scientists of the urban condition have long been interested in the causes and consequences of the phenomena that shape the growth and decline of cities and their suburbs. Such interests have become increasingly relevant in light of the Covid-19 pandemic. Over the course of the pandemic, many academic and popular analyses have confronted two essential questions: How has the pandemic changed the city? And given these changes, are they permanent? This current scholarly and popular dialogue generally lacks comparative analysis. In this article, we attempt to further the analysis and discussion about the pandemic and the city by reframing the debate through three comparative lenses: temporal, scalar, and dimensional. Drawing on the debate and experience of urban areas in the United States, we present an analytical framework to apply a comparative analytical approach. Three temporal analytical matrices are presented: (a) pre-pandemic, (b) current-pandemic, and (c) post-pandemic. These matrices articulate the relationships between a city’s developmental patterns and their related dimensions of urbanization. We pay special attention to the nature of scale within and among the cities and suburbs of regions. Each matrix is tested and contextualized using relevant narratives from cities in the United States before, during, and after the pandemic on various issues, including housing, transportation, and economic development. This framework will serve as an analytical tool for future research on the pandemic and how cities can become more resilient to such shocks.

A Sensor Array for the Ultrasensitive Discrimination of Heavy Metal Pollutants in Seawater

AbstractMetal cations are potent environmental pollutants that negatively impact human health and the environment. Despite advancements in sensor design, the simultaneous detection and discrimination of multiple heavy metals at sub‐nanomolar concentrations in complex analytical matrices remain a major technological challenge. Here, the design, synthesis, and analytical performance of three highly emissive conjugated polyelectrolytes (CPEs) functionalized with strong iminodiacetate and iminodipropionate metal chelates that operate in challenging environmental samples such as seawater are demonstrated. When coupled with array‐based sensing methods, these polymeric sensors discriminate among nine divalent metal cations (CuII, CoII, NiII, MnII, FeII, ZnII, CdII, HgII, and PbII). The unusually high and robust luminescence of these CPEs enables unprecedented sensitivity at picomolar concentrations in water. Unlike previous array‐based sensors for heavy metals using CPEs, the incorporation of distinct π‐spacer units within the polymer backbone affords more pronounced differences in each polymer's spectroscopic behavior upon interaction with each metal, ultimately producing better analytical information and improved differentiation. To demonstrate the environmental and biological utility, a simple two‐component sensing array is showcased that can differentiate nine metal cation species down to 500 × 10−12 m in aqueous media and to 100 × 10−9 m in seawater samples collected from the Gulf of Mexico.

An analytical framework for broadband dynamic analysis of plate built-up structures with uncertain viscoelastic boundary or connection conditions

This paper proposes an analytical stochastic spectral dynamic stiffness method (SSDSM) for free and forced vibration analysis of plate built-up structures subject to uncertain viscoelastic boundary or connection conditions (BCs or CCs). First, a recently developed spectral dynamic stiffness (SDS) theory for broadband vibration analysis of plate built-up structure with arbitrary spatially-varying viscoelastic BCs or CCs is extended to model deterministic viscoelastic BCs or CCs. Then, uncertain viscoelastic BCs or CCs are described by random fields in stiffness and damping, which are discretized by Karhunen–Loève expansion. By using the modified Fourier series as the shape functions for the BCs or CCs, the analytical SSDS matrices of the uncertain viscoelastic BCs or CCs are developed. Then, those SSDS matrices are superposed directly to the SDS matrix of the plate built-up structure. For the solution technique, the extended Wittrick–Williams algorithm is used for stochastic eigenvalue analysis, whereas two different methods are proposed for stochastic response analysis. Representative examples are chosen to validate and demonstrate the superiorities of the proposed method. The proposed method retains all the advantages of the SDS method which is highly efficient and accurate within the whole frequency range. Meanwhile, the proposed method also provides a feasible technique for stochastic broadband dynamic analysis of plate-like structures subject to uncertain boundary or connection conditions.

A Novel Approach for Monitoring the Volatile Metabolome in Biological Samples from Ruminants through Miniaturized Liquid-Liquid Extraction and Multiclass Gas Chromatography Analysis.

A straightforward and versatile methodology for the extraction of volatile metabolites in biological samples from ruminants for gas chromatography analysis is proposed. The methodology was applied in the determination of multiclass metabolites (short-chain fatty acids, aldehydes, alcohols, ketones, esters, phenols, and sulfides) in different analytical matrices (rumen fluid, urine, and feces) collected from Holstein cows. The 24 multiclass volatile metabolites reported in the different biological samples and their respective concentrations were critically discussed in the context of digestive physiology. Most detected compounds are derived from the rumen and lower gut fermentation of carbohydrates, proteins, and lipids or their metabolism, being consistent with the prior state of the art. The proposed method also takes advantage of the already existing tools in animal nutrition laboratories, providing a novel methodological ground that can generate relevant bioanalytical information with a significant impact on ruminant's nutritional studies.

A methodology for the identification of physical parameters of soil-foundation-bridge pier systems from identified state-space models

A methodology for the identification of the physical parameters of a model describing the transverse dynamics of soil-foundation-pier systems founded on piles is presented in this paper, starting from identified state-space models of the systems obtained from results of dynamic experimental tests and identification techniques available in the literature. By assuming the order of the model to be compliant with that of a numerical one suitably developed to capture the dynamics of the bridge pier, the procedure allows the identification of the stiffness, mass and damping matrices of the analytical model from which the physical parameters of the real system (e.g. masses, pier stiffness matrix and soil-foundation impedance) can be extracted by directly comparing the components of the identified and analytical matrices. The procedure allows the direct definition of the numerical model that best fits the experimental data without the need of any model calibration, and permits the identification of the soil-foundation compliance taking into account its intrinsic frequency-dependent behaviour. Firstly, the dynamics of the analytical model is formulated adopting the continuous-time first-order state-space form. The model includes the frequency-dependent behaviour of the soil-foundation system through the introduction of a lumped parameter model able to reproduce the typical soil-foundation impedances of pile foundations. Then, an identification strategy of the physical parameters of a generic realistic soil-foundation-pier system is proposed starting from the discrete-time state-space model identified from dynamic tests. The procedure is illustrated with some applications, simulating results of forced vibration and ambient vibration tests executed on a known system whose parameters are then identified according to the proposed approach. The procedure revealed to be effective to identify the stiffness, mass and damping matrixes of the known system, and consequently its physical parameters.

Chromatographic estimation of a novel triple-therapy combination targeting Helicobacter pylori eradication in different matrices.

Aim: Helicobacter pyloriinfection is a prevalent global bacterial infection that can potentially exaggerate symptoms of other serious infections like SARS-CoV-2 (COVID-19). Methodology: Herein, an efficient, accurate and cost-effectivehigh-performance liquid chromatography-diode array detectormethod was developed and validated for determination of the novel triple therapy combination of tinidazole (TD), clarithromycin (CLR) and lansoprazole (LAN) in different analytical matrices (pharmaceutical formulation, dissolution media and spiked human plasma). Results: Successful chromatographic separation was achieved using Agilent Microsorb-MV 100-5 CN column (250×4.6mm, 5μm) and a mobile phase consisted of acetonitrile and 10.0mM phosphate buffer, pH 7.5±0.1 at flow rate of 1ml/min via gradient elution. UV-detection was accomplished at 210.0nm for CLR and 290.0nm for TD and LAN. Conclusion: The developed method clearly provides a reliable, beneficial and cost-effective tool for quality control, dissolution testing and biological applications of the mentioned drugs.