Matrix Model Research Articles

Heart rate variability as a digital biomarker for frailty in cardiovascular patients.

Frailty is a syndrome associated with age-related impairments in multiple organ systems, of which the autonomic nervous system plays a fundamental role. Measurement of heart rate variability (HRV) is a non-invasive method to evaluate the autonomic activity and gain insights into cardiovascular health and potentially, frailty. A few small studies have explored the relationship between HRV and frailty, with promising but conflicting results. To investigate the relationship between HRV and frailty among adult patients with cardiovascular disease. A cross-sectional study was conducted using clinical data. Data were collected from an ambulatory cardiology clinic. The cohort comprised 155 patients with a mean age of 67 years (44 % female). HRV was assessed seated at rest for 2.5 min using a finger-based photoplethysmography (PPG) device. Frailty was assessed using the Clinical Frailty Scale (CFS), with a score ≥5 considered frail. Associations between HRV and frailty were examined using a Spearman correlation matrix and multivariable ordinal regression model. The LF/HF ratio (a frequency-domain measure reflecting imbalances between sympathetic and parasympathetic activity) was the primary HRV measure analyzed. The prevalence of frailty was 15 %. Among all HRV measures, the LF/HF ratio was most closely correlated with frailty (p < 0.001). In the multivariable model, each 1 standard deviation decrease in LF/HF ratio was associated with a 1.1-point increase in CFS (95 % CI 0.7-1.6, p < 0.001). The optimal ROC cutoff at which the LF/HF ratio was associated with frailty is ≤ 0.37. The LF/HF ratio is inversely correlated with the CFS and independently associated with frailty. Measurement of HRV is a promising technique to enrich existing frailty scales and assist in frailty assessments in an ambulatory cardiology clinic.

Dual effect of targeting LSD1 on the invasiveness and the mechanical response of acute lymphoblastic leukemia cells.

Epigenetic alterations are hallmarks of cancer, with histone modifiers playing critical roles in gene transcription, DNA homeostasis, and other nuclear functions. Lysine-specific demethylase 1 (LSD1), a key regulator of H3K4 methylation, has emerged as a promising pharmacological target in cancer treatment, including leukemia. Acute lymphoblastic leukemia (ALL), the most common pediatric cancer, remains a significant therapeutic challenge due to limited understanding of how epigenetic therapy impacts leukemia dissemination. In this study, we demonstrate that targeting LSD1 enhances the invasive capacity of ALL cells, inducing an elongated, invasive phenotype and increasing nuclear deformability. Using a 3D matrix model, LSD1 inhibition promoted ALL cell invasion without significantly affecting the cell cycle progression or apoptosis under the tested conditions. Interestingly, LSD1 targeting reduced ALL cell spreading and tissue colonization in vivo, suggesting differential effects depending on the cellular context. Our findings indicate that LSD1 inhibition impairs chemotactic responses and transendothelial migration, key processes for extravasation and in vivo invasiveness. These results reveal a dual role for LSD1 in leukemia cell migration: promoting invasiveness in 3D environments while reducing extravasation and chemotaxis in vivo. This dual effect underscores the importance of cellular context in determining therapeutic outcomes and the development of strategies targeting specific stages of leukemia dissemination.

Memory-corrected quantum repeaters with adaptive syndrome identification

We address the challenge of incorporating encoded quantum memories into an exact secret key rate analysis for small and intermediate-scale quantum repeaters. To this end, we introduce the check matrix model and quantify the resilience of stabilizer codes of up to eleven qubits against Pauli noise, obtaining analytical expressions for effective logical error probabilities. Generally, we find that the five-qubit and Steane codes either outperform more complex, larger codes in the experimentally relevant parameter regimes or have a lower resource overhead. Subsequently, we apply our results to calculate lower bounds on the asymptotic secret key rate in memory-corrected quantum repeaters when using the five-qubit or Steane codes on the memory qubits. The five-qubit code drastically increases the effective memory coherence time, reducing a phase flip probability of 1% to 0.001% when employing an error syndrome identification adapted to the quantum noise channel. Furthermore, it mitigates the impact of faulty Bell state measurements and imperfect state preparation, lowering the minimally required depolarization parameter for nonzero secret key rates in an eight-segment repeater from 98.4% to 96.4%. As a result, the memory-corrected quantum repeater can often generate secret keys in experimental parameter regimes where the unencoded repeater fails to produce a secret key. In an eight-segment repeater, one can even achieve nonvanishing secret key rates up to distances of 2000 km for memory coherence times of tc=10 s or less using multiplexing. Assuming a zero-distance link-coupling efficiency p0=0.7, a depolarization parameter μ=0.99, tc=10 s, and an 800 km total repeater length, we obtain a secret key rate of 4.85 Hz, beating both the unencoded repeater that provides 1.25 Hz and ideal twin-field quantum key distribution with 0.71 Hz at GHz clock rates. Published by the American Physical Society 2025

Random matrix ensemble for the covariance matrix of Ornstein-Uhlenbeck processes with heterogeneous temperatures

We introduce a random matrix model for the stationary covariance of multivariate Ornstein-Uhlenbeck processes with heterogeneous temperatures, where the covariance is constrained by the Sylvester-Lyapunov equation. Using the replica method, we compute the spectral density of the equal-time covariance matrix characterizing the stationary states, demonstrating that this model undergoes a transition between stable and unstable states. In the stable regime, the spectral density has finite and positive support, whereas negative eigenvalues emerge in the unstable regime. We determine the critical line separating these regimes and show that the spectral density exhibits a power-law tail at marginal stability, with an exponent independent of the temperature distribution. Additionally, we compute the spectral density of the lagged covariance matrix characterizing the stationary states of linear transformations of the original dynamical variables. Our random-matrix model is potentially interesting to understand the spectral properties of empirical correlation matrices appearing in the study of complex systems. Published by the American Physical Society 2025

Providing Security of Banking in View of New Factors of Fast Changing Environment

The goal of the research is to classify sources of hazard and threats for banking, to identify key functional targets, whose attainment could provide security of banking in fast changing environment. In the research the authors used methods of comparative analysis, formal-logical, inductive ones, as well as mathematic methods – matrix, graphic and fuzzy modeling. As a result goals were defined and steps proposed that could foster shaping of complex security of banking. However, the mentioned goals cannot be reached at once and finally, thus provision of security is a continuous succession of steps of cyclic nature. Dynamically changing conditions of the external environment of the bank raises the importance of estimating external threats by the top management, including foreign-policy and even global ones. To prevent those threats activities of a single bank will not be enough, however, top management of the organization is responsible for finding the level of their hazard and working-out steps of response, which gives rise to the necessity to change the structure of managerial bodies, the scheme of subordination and responsibility of bank divisions in order to raise involvement of management in operation of security bodies. Practical classification of sources of hazard and threats for banking is conducted by matrix of threats, whose elaboration could help characterize key sources of threats and objects of infringement. An example of such a matrix was given and on its basis a mathematic model was put forward, which combines fuzzy estimations and accurate values that provide coordinated decisions. The result of modeling shows which steps aimed at providing banking security are now the most important and in what order they shall be taken.

Research on the Spiral Rolling Gait of High-Voltage Power Line Serpentine Robots Based on Improved Hopf-CPGs Model

The efficiency of helical locomotion in snake-like robots along high-voltage transmission lines is often hindered by low motion efficiency, high joint signal noise, and challenges in traversing obstacles. This study aims to address these issues by proposing a gait generation method that leverages a standardized Central Pattern Generator (CPG). We modify the traditional Hopf-CPG model by incorporating constraint functions and a frequency-tuning mechanism to regulate the oscillator, which allows for the generation of asymmetric waveform signals for deflection joints and facilitates rapid convergence. The method begins by determining initial and obstacle-crossing state parameters, such as deflection angles and helical radii of the snake-like robot, using the backbone curve method and the Frenet–Serret framework. Subsequently, a CPG neural network is constructed based on Hopf oscillators, with a limit cycle convergent speed adjustment factor and amplitude bias signals to establish a fully connected matrix model for calculating multi-joint output signals. Simulation analysis using Simulink–CoppeliaSim evaluates the robot’s obstacle-crossing ability and the optimization of deflection joint signal noise. The results indicate a 55.70% increase in the robot’s average speed during cable traversal, a 57.53% reduction in deflection joint noise disturbance, and successful crossing of the vibration damper. This gait generation method significantly enhances locomotion efficiency and noise suppression in snake-like robots, offering substantial advantages over traditional approaches.

The Role of Environmental Management Systems (EMS) in Driving Organizational Development and Environmental Sustainability

An Environmental Management System (EMS) is a framework that helps in assessing the risks a business has on its environment while providing organizations with mitigation strategies to minimize the risks. This study aims to analyze the importance and impact of EMS on organizations and global sustainability goals. This review study uses a descriptive and analytical approach by including 67 studies for the review that were published in the last 5 years. The findings from this review suggest that the integration of EMS along with tools and techniques like ISO 14031, Cross-Functional Team (CFT), Matrix model, and Life Cycle Inventory (LCI) can be very useful in attaining global sustainability goals and maximizing the environmental efficiency of organizations. The study concludes that the integration of EMS in industries not only helps in minimizing environmental pollution but it also helps in managing the overall growth of the organizations.

Defects vibrations engineering for enhancing interfacial thermal transport in polymer composites.

To push upper boundaries of thermal conductivity in polymer composites, understanding of thermal transport mechanisms is crucial. Despite extensive simulations, systematic experimental investigation on thermal transport in polymer composites is limited. To better understand thermal transport processes, we design polymer composites with perfect fillers (graphite) and defective fillers (graphite oxide), using polyvinyl alcohol (PVA) as a matrix model. Measured thermal conductivities of ~1.38 ± 0.22 W m-1 K-1 in PVA/defective filler composites is higher than those of ~0.86 ± 0.21 W m-1 K-1 in PVA/perfect filler composites, while measured thermal conductivities in defective fillers are lower than those of perfect fillers. We identify how thermal transport occurs across heterogeneous interfaces. Thermal transport measurements, neutron scattering, quantum mechanical modeling, and molecular dynamics simulations reveal that vibrational coupling between PVA and defective fillers at PVA/filler interfaces enhances thermal conductivity, suggesting that defects in polymer composites improve thermal transport by promoting this vibrational coupling.

Glenoid Preparation in Reverse Shoulder Arthroplasty: Robotic-Arm Assisted Preparation Compared to Manual Preparation and Patient-specific Guides.

Precise and accurate glenoid preparation is important for the success of shoulder arthroplasty. Despite advancements in preoperative planning software and enabling technologies, most surgeons execute the procedure manually. Patient-specific instrumentation (PSI) facilitates accurate glenoid guide pin placement for cannulated reaming; however, few commercially available systems offer depth of reaming control. Robotic-arm assisted bone preparation has gained popularity in knee and hip arthroplasty, but at the present time there is limited information available on the use of robotics for shoulder arthroplasty. The purpose of this study was to compare glenoid preparation and final implant position using three techniques: manual, manual assisted with PSI, and robotic arm assisted bone preparation. Six shoulder surgeons participated in this study utilizing three preparation techniques: (1) manual reaming, (2) manual reaming over a pin inserted using PSI, and (3) preparation using a robotic arm assist with an end-effector burr and haptic boundaries. Each surgeon randomly conducted each technique on 2 separate Bone Matrix glenoid models, for a total of 36 glenoid models tested. To compare the techniques, the final prepared Bone Matrix models underwent a CT scan with 3D virtual model generation. The prepared 3D virtual glenoid models were then compared to the preoperatively planned models. Parameters compared included deviations in version, inclination, anterior-posterior (AP) translation, superior-inferior (SI) translation, and depth of reaming. Regarding glenoid version with values reported as mean deviations from the preoperative plan, the robotic-assisted technique (1°) was significantly better than manual (9°, p<0.001) and PSI (4°, p<0.001) techniques at executing the preoperative plan. Regarding inclination, the robotic-assisted technique (2°) was significantly better than manual (9°, p=0.003) but not significantly different than PSI (3°, p=0.211). The robotic-arm technique, with AP translation, resulted in significantly lower mean displacements (0.3mm) than the manual technique (2mm, p=0.001) and the PSI technique (2mm, p=0.002). With SI translation, the robotic-arm assisted technique (0.7mm) resulted in significantly lower mean displacements as compared to the manual (2mm, p=0.007) and PSI (1mm, p=0.011). The robotic-arm assisted technique (0.4 mm) did not result in significantly lower mean depth of reaming displacements compared to the manual technique (0.8 mm, p=0.051) but did when compared to PSI (0.8 mm, p=0.036). Glenoid preparation using a robotic arm with an end-effector burr and haptic boundaries was significantly better in its ability to execute a preoperatively planned implant position than manual preparation in 4 of 5 glenoid metrics examined and was significantly better than PSI in 4 of 5 glenoid metrics.

Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise

We consider a prototypical problem of Bayesian inference for a structured spiked model: a low-rank signal is corrupted by additive noise. While both information-theoretic and algorithmic limits are well understood when the noise is a Gaussian Wigner matrix, the more realistic case of structured noise still remains challenging. To capture the structure while maintaining mathematical tractability, a line of work has focused on rotationally invariant noise. However, existing studies either provide suboptimal algorithms or are limited to a special class of noise ensembles. In this paper, using tools from statistical physics (replica method) and random matrix theory (generalized spherical integrals) we establish the characterization of the information-theoretic limits for a noise matrix drawn from a general trace ensemble. Remarkably, our analysis unveils the asymptotic equivalence between the rotationally invariant model and a surrogate Gaussian one. Finally, we show how to saturate the predicted statistical limits using an efficient algorithm inspired by the theory of adaptive Thouless-Anderson-Palmer (TAP) equations. Published by the American Physical Society 2025

The Galician entrepreneurship internationalization matrix: A regulatory framework

This study examines the internationalization strategies of Galician entrepreneurs and SMEs, focusing on early internationalization trends. The main objective is to develop a regulatory framework that enables entrepreneurs and established SMEs to approach foreign markets effectively. From a qualitative approach, the research analyzed data from Galician firms to construct the Galician Entrepreneurship Internationalization (GEI) matrix. Data were collected through surveys and supplemented from the Vigo Free Trade Zone database, covering exporting companies founded between 1999 and 2021. Qualitative analysis and matrix modeling were applied to categorize firms into distinct internationalization stages, considering factors such as market breadth, export intensity, and speed of entry. Four company profiles emerged from the analysis. The findings reveal that newer companies, influenced by technological advances and favorable public policies, tend to internationalize within a year of inception. The GEI Matrix offers valuable insights for public policymakers and business managers aiming to promote early internationalization.

FORMATION OF INSTITUTIONAL SUPPORT FOR INNOVATIVE DEVELOPMENT OF WEAPONS AND MILITARY EQUIPMENT IN UKRAINE

Innovations and the scale of their implementation in the sphere of defense and security, including the defense industry sector, are the fundamental basis for the development of national Armed Forces. This is especially relevant in the context of a full-scale war in the center of Europe and the general aggravation of military confrontation between the leading centers of power, which in turn has led to the transformation of national security strategies and military doctrines. From the perspective of ensuring the high-tech nature of the defense industry sector, this is also a prerequisite for the accelerated innovative modernization of the national economy, which is implemented in particular through mechanisms for the commercialization of military technologies and ensuring their wider application in civilian developments as dual-purpose innovations. The article is devoted to the study of the state of institutional support for the development of high-tech weapons and military equipment in Ukraine. The features of an effective institutional environment for the development of defense innovations are formulated. A cross-country analysis of the institutional transformation of defense and security sphere, including the development of high-tech weapons and military equipment, is carried out. The defining features of the world's leading countries in stimulating innovations in the field of defense and security are highlighted. The institutional environment of the European Union and Ukraine in the field of defense innovations is presented in the form of a matrix model. It is substantiated that the innovative development of the defense sector is characterized by a dual nature. On the one hand, the defense sector is a material embodiment of the state's monopoly obligation to protect the sovereignty and territorial integrity of the country, which determines its certain isolation, including due to the need to comply with state secret norms. On the other hand, it is the defense-industrial complex that is a significant driver of economic development and innovative progress in general, since it is this industry that is capable of creating additional closed cycles of expanded reproduction at the level of the national economy. It is proven that currently the capabilities of the domestic defense industry significantly exceed the state's purchasing capabilities. The factors of the influence of the institutional environment on the field of defense innovations are systematized. The factors hindering the progressive development of the defense innovation sector include: the lack of long-term planning for weapons procurement, as this blocks development, leads to higher product prices and a decrease in production volumes; limited financial resources of the state for the purchase of domestic weapons and military equipment and a narrow list of financial instruments applied to private defense enterprises; personnel shortage in the industry, which limits the possibilities for growth and implementation of high- tech projects in the defense innovation sector.

A Piecewise Linearization Based Method for Crossed Frequency Admittance Matrix Model Calculation of Harmonic Sources.

The integration of large-scale power electronic equipment has intensified harmonic issues in power systems. Accurate harmonic models are fundamental for evaluating and mitigating harmonic problems, but existing models still exhibit deficiencies in harmonic mechanism, model complexity and accuracy. This work proposes a calculation method of crossed frequency admittance matrix (CFAM) analytical model based on piecewise linearization, aiming to achieve accurate modeling of phase-controlled power electronic harmonic sources. Firstly, the traditional CFAM model construction methods are introduced, and the shortcomings in harmonic modeling are discussed. Subsequently, the parameter-solving process of the CFAM analytical model based on piecewise linearization is proposed. This method improves the accuracy of harmonic modeling and simplifies the construction process of the analytical model. Furthermore, taking single-phase and three-phase bridge rectifiers as examples, CFAM analytical models under intermittent and continuous load current conditions are established, respectively, and the unified harmonic models for both conditions are summarized. Finally, case studies of rectifier harmonic sources under varying circuit control parameters and supply voltage distortions are conducted through Matlab/Simulink and experiments. The results demonstrate that the proposed method provides higher accuracy and more stable performance for harmonic current estimation compared with the traditional CFAM model and constant current source model.

Frankenstein matrices: Among-population life history variation affects the reliability and predictions of demographic models.

Population matrix models are routinely used to study the demography of wild populations and to guide management choices. When vital rates are unknown for a specific population or life history stage, researchers often replace them with estimates from other populations of the same species. Such 'hybrid' matrices might ignore among-population life history variation and lead to incorrect inferences. In this study, we examined the real-world effect of using hybrid matrices on demographic inference and management decisions, using a large dataset on yellow-bellied toad (Bombina variegata) populations, an amphibian species whose life history depends on human land use. We estimated stage-specific survival and recruitment for 18 populations across different habitat types. We then assessed how estimated population growth rates and elasticities changed when population-specific vital rates were replaced by estimates from other populations, chosen randomly or based on habitat, demographic or geographic proximity. The use of hybrid matrices mixing demographic estimates from different populations and habitats biased predictions. The mean bias was relatively minor even when sampling randomly across all populations, because our large dataset represented the whole range of life histories and errors cancelled out on average. However, borrowing estimates from geographically close or demographically similar populations substantially reduced the risk of extreme errors. Borrowing from populations from similar habitat types could also reduce bias, but results varied depending on the exact habitat types concerned. Our study illustrates how habitat-specific among-population variation in life history affects the reliability of population matrices commonly used in evolutionary demography, ecology and conservation. When the use of hybrid population matrices cannot be avoided, their creation can be informed by additional information about ecological or demographic patterns, helping reduce bias. When such information is not available, we recommend that studies should consider the whole space of parameter estimates (the complete range of estimates available), thus transparently describing the true uncertainty surrounding demographic estimates.

Source-oriented health risk assessment of soil potentially toxic elements based on Monte Carlo simulation in the upper reaches of Wei River Basin, China.

The natural environment and public health are gravely threatened by the enrichment of soil potentially toxic elements (PTEs). To explore the contamination level, sources and human health risks posed by PTEs, high-density soil sampling was carried out in the upper Wei River region (UWRR). The results demonstrated that the pollution risk and ecological risk in UWRR as a whole were at a low level, but there were moderate or higher ecological risks of Hg and Cd in some areas. Source analysis of soil PTEs was conducted via absolute principal component score multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) receptor models. APCS-MLR identified three potential sources, while the source division of PMF model was more detailed, which identified four potential sources: mining, coal combustion, machinery manufacturing and agricultural sources, with contribution percentages of 31%, 3%, 37% and 29% respectively. According to the probabilistic human health risk assessment (HHRA), the non-carcinogenic risk for adults was negligible, while that for children cannot be negligible. There were total carcinogenic risks for all populations, but the risk level was acceptable. The total cancer risk for children surpassed 1E-04 by 31.29%, implying a significant carcinogenic risk. Machinery manufacturing was found to be the most significant anthropogenic source of health concerns. This study offers an illustration of probabilistic risk assessment based on sources. The results of the study are favorable to provide new perspectives and scientific reference for soil PTE risk assessment and pollution control.

Optimisation of performance and emission parameters of a CI engine fuelled with kapok oil methyl ester–turpentine oil blends and diethyl ether additive

The article aims to investigate the characteristics of compression ignition (CI) engines fuelled with blends of kapok oil methyl ester (KME) and turpentine oil (TO) with the inclusion of diethyl ether (DEE) as a fuel additive and the RSM has been used to analyse the engine characteristics. The design matrix is created for 50% to 100% loading and 30% to 70% blending in TO with kapok methyl ester. The experiment was conducted on a water-cooled 5.2 kW CI engine and 30%, 50%, and 70% of KME and TO blend. According to the test results, 50–50 KME and TO have a brake thermal efficiency of 29.13%. Another design matrix was designed for a load range of 50% to 100% and DEE of 0% to 20% in a 50 KT blend. The 50 KT blend with 20% DEE has the highest brake thermal efficiency (30.30%) and the lowest brake-specific energy consumption. The emissions of carbon monoxide, hydrocarbons, and smoke decrease to 8.25 g/kWh, 0.13 g/kWh, and 57%, respectively. The combustion process leads to the highest peak pressure and net heat release rate, which are 72 bar and 74.93 kJ/OCA, respectively. The outcome is 50–50% turpentine and kapok oil methyl ester blends, with 20% DEE have improved the performance and reduced the emissions.

Brazilian Road Bridge Management Based On Probabilistic Markov Process Deterioration Models

Objective: The objective of this study is to investigate the feasibility of applying the Markov chain method, with the aim of obtaining deterioration models for road bridges in Brazil. Theoretical Framework: The concept of Condition Index (CI), the determination of the probability transition matrix and deterioration models based on Markov chains are presented. Method: The methodology is based on inspection records of highway bridges inspected by the Agência Nacional de Transporte Terrestre (ANTT) in three sections of different federal highways, based on annual records of condition indexes from 2010 to 2016. Results and Discussion: The deterioration models indicate that in the bridges of the analyzed highway sections, BR-040/MG/RJ, BR-101/RJ and BR-116/BA, the transition from CI=4 to CI=3 is observed in 10 years. The bridges on the BR-040/MG/RJ highway also drop from maximum CI=5 to CI=3 in just 10 years. Research Implications: The results obtained can be applied or influence practices in the field of Transportation Engineering in Brazil. The implications cover the passenger and cargo transportation sectors. Originality/Value: The study uses real data from inspections of highway bridges from a specific period of time. The relevance and value of this research are evidenced by the achievement of bridge deterioration models, which constitute fundamental tools for planning, managing and preparing public works concession notices.

A matrix model of a non-Hermitian β-ensemble

We introduce the first random matrix model of a complex [Formula: see text]-ensemble. The matrices are tridiagonal and can be thought of as the non-Hermitian analogue of the Hermite [Formula: see text]-ensembles discovered by [I. Dumitriu and A. Edelman, Matrix models for beta ensembles, J. Math. Phys. 43 (2002) 5830–5847]. The main feature of the model is that the exponent [Formula: see text] of the Vandermonde determinant in the joint probability density function (j.p.d.f.) of the eigenvalues can take any value in [Formula: see text] However, when [Formula: see text], the j.p.d.f. does not reduce to that of the Ginibre ensemble, but it contains an extra factor expressed as a multidimensional integral over the space of the eigenvectors.

Optimization of pyrolysis process parameters for optimal high heating value of biochar produced from rice straw

The harvest of rice leaves abundant biowaste and its utilization is being researched. Hence, this paper targets the conversion of rice straw into biochar. In this study, the vacuum-assisted intermediate pyrolysis process is used to convert the rice straw biowaste into biochar, which can be used as a fuel. The produced biochar is studied for the biochar yield and energy yield. It is further analyzed for the high heating value (HHV). This experimental investigation optimizes the processing parameters such as time and temperature to obtain the optimal HHV. The response of HHV is maximized using response surface modeling (RSM) based on a central composite design (CCD) matrix. This technique systematically investigated the influence of continuous parameters on the dependent variable. As a result, the time and temperature and their interaction have the most significant effect on the HHV of the biochar obtained from two different amounts of feedstocks. The optimal response obtained for HHV1 is 21.45 MJ/kg at time 47 min and temperature 397 °C, whereas HHV2 is 19.43 MJ/kg at time 51 min and temperature 405 °C. The Fourier transform infrared (FTIR) analysis is further used to characterize the biochar obtained at optimized parameters.

Novel multi-physics simulation of transient dynamics in functionally graded porous multiferroic cylindrical shells under moving heat flux: A magneto-electro-thermoelastic analysis

Cylindrical structures, such as pipelines in power plants and novel energy-harvesting devices that combine flexible piezoelectric/piezomagnetic layers with other materials, are frequently exposed to moving heat fluxes. Understanding the physics of these structures can provide potential solutions for stress management and energy harvesting. This study investigates, for the first time, the effect of thermal wave propagation on the transient fully coupled magneto-electro-thermoelastic (METE) response of functionally graded porous (FGP) multiferroic cylindrical shells subjected to a partially distributed moving heat flux. The structure is supported by a distributed viscoelastic Winkler-Pasternak foundation, and its mechanical and electromagnetic boundary conditions are considered to be simply supported and suitably grounded. This approach is innovative as it represents the first extension of the three-dimensional (3D) Lord-Shulman coupled thermoelasticity theory to specifically address multiphysics materials. In this updated framework, the governing equations for the motion of each layer are derived following an orthotropic laminated model. To solve the problem, the state-space technique and the mathematical model of the transfer matrix are employed. The study evaluates the structure's vibrational behavior by examining four models of porosity distributions within the thermoelastic layer: symmetric, stiff non-symmetric, soft non-symmetric, and uniform. The key parameters of the dynamic response are calculated using Durbin’s numerical Laplace inversion algorithm. Subsequently, to validate the proposed model, the results are compared with the findings obtained by other researchers. Comprehensive numerical results concerning temporal and spatial variations of temperature, transverse displacement, and stress components are presented for various influencing parameters such as volume fraction index, open or closed-circuit conditions, heat flux speed, porosity, and smart layer thickness.