Stability Of Method Research Articles

Sampled-data observer design for sensorless control of wind energy conversion system with PMSG

This paper presents a nonlinear observer for a variable-speed wind energy conversion system (WECS) utilizing a permanent magnet synchronous generator (PMSG). The study addresses the design of high-gain sampled-data observers based on the nonlinear WECS model, supported by formal convergence analysis. An essential aspect of this observer design is the incorporation of a time-varying gain, significantly enhancing system performance. Convergence of estimation errors is demonstrated using the input-to-state stability method. Simulation of the proposed observer is conducted using the MATLAB-Simulink tool. The obtained results are presented and analyzed to showcase the overall effectiveness of the proposed system.

Unilateral modified radical mastectomy with thoracic epidural anesthesia and serratus anterior plane block under dexmedetomidine sedation in a patient with multiple comorbidities: a case report

Anesthesia management in patients with multiple comorbidities is extremely challenging for the anesthesiologist. We aimed to present anesthesia management with dexmedetomidine sedation accompanied by thoracic epidural anesthesia and serratus anterior plane block in a 59-year-old high-risk patient with multiple comorbidities who was planned for modified radical mastectomy. We suggest that serratus anterior plane block can be used combined with thoracic epidural anesthesia as an effective, safe, and feasible method for hemodynamic stability in intraoperative and postoperative pain control in patients undergoing modified radical mastectomy surgery and in reducing the need for postoperative analgesic use and postoperative complications.

Self-nano-emulsifying Drug Delivery Systems of Atorvastatin Calcium Liquid Filled in Hard Shell Capsules for Improved Oral Bioavailability in Rabbits

Aims and Objectives: Atorvastatin calcium (ATR) is a BCS class II drug showing poor bioavailability due to limited aqueous solubility. In the present study, a self-nano-emulsifying drug delivery system (SNEDDS) was developed and formulated as a liquid filled in a hard shell capsule to improve the bioavailability of ATR. Methods: Different oils were screened through the saturated stability method, and the amount of ATR solubilized in the respective oils was analysed through HPLC at 245nm. A ternary phase diagram was plotted to obtain the optimized ratio of oil, surfactant, and co-surfactant to formulate SNEDDS. The prepared ATR SNEDDS was filled into hard shell capsules, band sealed, and subjected to various evaluations like disintegration time, self-emulsification time, precipitation time assessment, globule size analysis and zeta potential. Then the in vitro dissolution studies were carried out. The optimized SNEDDS formulation was filled in a hard shell capsule, and in vivo studies were performed on rabbits to compare the pharmacokinetic parameters with the marketed formulation and pure ATR. Results: Capmul MCM as the oil component showed five-fold solubility of ATR and was selected for the preparation of ATR-SNEDDS. The SNEDDS formulation showed an entrapment efficiency of 89.76±4.1% ATR with a globule size of 385±1.9 nm and an emulsification time of 5 seconds. It was established from the study that liquid ATR-SNEDDS had relative bioavailability enhanced by 1.7 times in comparison to the marketed formulations (Lipvas) and 4.8 times with respect to pure ATR. Conclusion: From the study, it was concluded that the bioavailability of ATR was enhanced by formulating ATR as Liquid SNEDDS filled in hard shell capsules.

Numerical and experimental investigations of swirl-stabilized partially premixed flames using natural gas-hydrogen-air mixtures

This study uses experimental and numerical techniques to examine natural gas and hydrogen mixtures as fuel with a partially premixed swirl-stabilized burner. Variations in the fuel mixture composition were investigated throughout the course of the study. In the experiments, hydrogen was gradually added to the fuel combination, initially made only of natural gas. Chemiluminescence imaging was used to examine how the addition of hydrogen affected the stability and overall structure of the flame. Throughout the experiments, the overall volumetric fuel flow rate remained constant. The change to the flame stabilization mode from a detached flame to a burner attached flame only happened once a certain volumetric hydrogen ratio (H2VOL%) in the fuel was attained. Numerical simulations also evaluated how the lifted flame dimensions and stabilization method changed. The simulations are performed using a commercial compressible, finite volume Large Eddy Simulation software and include the Thickened Flame Model (TFM) for turbulence-chemistry interactions, the Flamelet Generated Manifold (FGM) combustion model, and the Large Eddy Simulation (LES) turbulence model. Experimental and numerical results show that the flame lowers and becomes more compact as the H2VOL% increases. Additionally, experimental and numerical data showed that the flame stabilization mode changes for H2VOL% approaching the value of 70%.

Positivity-preserving discontinuous spectral element methods for compressible multi-species flows

We introduce a novel positivity-preserving numerical stabilisation approach for high-order discontinuous spectral element approximations of compressible multi-species flows. The underlying stabilisation method is the adaptive entropy filtering approach (Dzanic and Witherden, J. Comput. Phys., 468, 2022), which is extended to the conservative formulation of the multi-species flow equations. We show that the straightforward enforcement of entropy constraints in the filter yields poor results around species interfaces and propose an adaptive switch for the entropy bounds based on the convergence properties of the pressure field which drastically improves its performance for multi-species flows. The proposed approach is shown in a variety of numerical experiments applied to the multi-species Euler and Navier–Stokes equations computed on unstructured grids, ranging from shock-fluid interaction problems to three-dimensional viscous flow instabilities. We demonstrate that the approach can retain the high-order accuracy of the underlying numerical scheme even at smooth extrema, ensure the positivity of the species density and pressure in the vicinity of shocks and contact discontinuities, and accurately predict small-scale flow features with minimal numerical dissipation.

Stability of Protein Pharmaceuticals: Recent Advances.

There have been significant advances in the formulation and stabilization of proteins in the liquid state over the past years since our previous review. Our mechanistic understanding of protein-excipient interactions has increased, allowing one to develop formulations in a more rational fashion. The field has moved towards more complex and challenging formulations, such as high concentration formulations to allow for subcutaneous administration and co-formulation. While much of the published work has focused on mAbs, the principles appear to apply to any therapeutic protein, although mAbs clearly have some distinctive features. In this review, we first discuss chemical degradation reactions. This is followed by a section on physical instability issues. Then, more specific topics are addressed: instability induced by interactions with interfaces, predictive methods for physical stability and interplay between chemical and physical instability. The final parts are devoted to discussions how all the above impacts (co-)formulation strategies, in particular for high protein concentration solutions.'

Estimation method for geometric stability during shoe-type centerless grinding of rolling bearing parts

Estimation method for geometric stability during shoe-type centerless grinding of rolling bearing parts

Investigating Stability in Subgroup Identification for Stratified Medicine.

Subgroup analysis may be used to investigate treatment effect heterogeneity among subsets of the study population defined by baseline characteristics. Several methodologies have been proposed in recent years and with these, statistical issues such as multiplicity, complexity, and selection bias have been widely discussed. Some methods adjust for one or more of these issues; however, few of them discuss or consider the stability of the subgroup assignments. We propose exploring the stability of subgroups as a sensitivity analysis step for stratified medicine to assess the robustness of the identified subgroups besides identifying possible factors that may drive this instability. After applying Bayesian credible subgroups, a nonparametric bootstrap can be used to assess stability at subgroup-level and patient-level. Our findings illustrate that when the treatment effect is small or not so evident, patients are more likely to switch to different subgroups (jumpers) across bootstrap resamples. In contrast, when the treatment effect is large or extremely convincing, patients generally remain in the same subgroup. While the proposed subgroup stability method is illustrated through Bayesian credible subgroups method on time-to-event data, this general approach can be used with other subgroup identification methods and endpoints.

Comparative study on the effect of SRB and Sporosarcina pasteurii on the MICP cementation and solidification of lead–zinc tailings

The production of tailings sand due to mining and smelting activities is one of the reasons for the accelerated environmental pollution caused by heavy metals, drawing social attention to the management of tailings sand. Microbially induced carbonate precipitation (MICP) is an environmentally friendly soil remediation technique that is gradually becoming the preferred method for soil stabilisation and heavy metal pollution control. To address the issues of heavy metal pollution release and the loose particle structure of lead–zinc tailings sand (LZTS), this study employs a layered MICP approach. The solidification effects of two typical mineralising bacteria, sulfate-reducing bacteria (SRB) and Sporosarcina pasteurii, on LZTS, were compared for the first time. The results show that the maximum unconfined compressive strength (UCS) of SRB cemented solidified lead–zinc tailings sand (SRB-CS-LZTS) specimens is 0.22 MPa, while that of S. pasteurii cemented solidified lead–zinc tailings sand (SP-CS-LZTS) specimens is 0.95 MPa. Compared with the UCS of SRB-CS-LZTS, the UCS of SP-CS-LZTS increased by 3.32 times. The effect of S. pasteurii on the improvement of UCS and immobilisation of heavy metal ions was greater than that of SRB. The immobilisation effect of SRB on SO42- in the LZTS was better than that of S. pasteurii. Compared with SRB, the biological CaCO3 formed by S. pasteurii exhibited stronger adhesion and was more suitable for the cementation and solidification of LZTS. This study uses MICP technology to treat LZTS, aligning with the green environmental concept and providing a reference for the bioremediation of multiple heavy metals in tailing areas.

A phase-field fracture model in thermo-poro-elastic media with micromechanical strain energy degradation

This work extends the hydro-mechanical phase-field fracture model to non-isothermal conditions with micromechanics based poroelasticity, which degrades Biot’s coefficient not only with the phase-field variable (damage) but also with the energy decomposition scheme. Furthermore, we propose a new approach to update porosity solely determined by the strain change rather than damage evolution as in the existing models. As such, these poroelastic behaviors of Biot’s coefficient and the porosity dictate Biot’s modulus and the thermal expansion coefficient. For numerical implementation, we employ an isotropic diffusion method to stabilize the advection-dominated heat flux and adapt the fixed stress split method to account for the thermal stress. We verify our model against a series of analytical solutions such as Terzaghi’s consolidation, thermal consolidation, and the plane strain hydraulic fracture propagation, known as the KGD fracture. Finally, numerical experiments demonstrate the effectiveness of the stabilization method and intricate thermo-hydro-mechanical interactions during hydraulic fracturing with and without a pre-existing weak interface.

Stabilization of Fibrous Peat Soils with Addition Palm Shell Ash Waste

South Sumatra Province has a peat area of 1.4 million Ha. The distribution of peat soil in Ogan Ilir is 23,687.91 Ha. Peat soil has a low bearing capacity. This research aims to explain the effect of stabilization on peat soil characteristics. Peat soil samples were taken using the Block Sampling method. The research locations are Parit Village and Lorok Village, Ogan Ilir Regency. Peat soil needs better properties and is unsuitable for foundation soil for civil construction. To overcome this, one method of soil improvement is required, namely the chemical stabilization method: changing the chemical properties of the soil by adding a mixture. The mixture used is palm shell ash waste with variations of 0%, 10%, 15%, 20%, 25%. Soil properties (physical and chemical), SEM, EDS, PTS, and CBR tests were carried out to determine the effect of this mixture. Soil properties test results: water content () in Parit Village 226.39%, and Lorok Village 252.39%. The fiber content (FC) test results for Parit Village were 25.18% and for Lorok Village 28.01%. Peat soil is classified as fibrous peat soil. The CBR value for Parit Village was 4.60%, and Lorok Village was 4.16%. The results of the immersion CBR test showed that Parit Village had a curing period of 7 days, a variation of 5%, namely 4.68%. Look Village obtained the most outstanding results: a curing period of 14 days, a variation of 25%, and 4.76%. The CBR value obtained in this study is 3%-5% (average) when used for subgrade strength with compaction conditions depending on the road category.

Stability of Dexamethasone during Hot-Melt Extrusion of Filaments based on Eudragit® RS, Ethyl Cellulose and Polyethylene Oxide

Hot-melt extrusion (HME) potentially coupled with 3D printing is a promising technique for the manufacturing of dosage forms such as drug-eluting implants which might even be individually adapted to patient-specific anatomy. However, these manufacturing methods involve the risk of thermal degradation of incorporated drugs during processing. In this work, the stability of the anti-inflammatory drug dexamethasone (DEX) was studied during HME using the polymers Eudragit® RS, ethyl cellulose and polyethylene oxide. The extrusion process was performed at different temperatures. Furthermore, the influence of accelerated screw speed, the addition of the plasticizers triethyl citrate and polyethylene glycol 6000 or the addition of the antioxidants butylated hydroxytoluene and tocopherol in two concentrations were studied. The DEX recovery was analyzed by a high performance liquid chromatography method suitable for the detection of thermal degradation products. The strongest impact on the drug stability was found for the processing temperature, which was found to reduce the DEX recovery to <20% for certain processing conditions. In addition, differences between tested polymers were observed, whereas the use of additives did not result in remarkable changes in drug stability. In conclusion, suitable extrusion parameters were identified for the processing of DEX with high drug recovery rates for the tested polymers. Moreover, the importance of a suitable analysis method for drug stability during HME that is influenced by several parameters was highlighted.

Effect of Slope Gradient on The Application of Vetiver Grass for Slope Stabilization

Slope failure has been a common disaster that occurred all over the world and causes infrastructure damage or/and causalities. The application of vegetation as part of slope stability and to control erosion has proven to be cost-effective for stabilizing the surface of the slope. This research describes the unique characteristics of Vetiver Grass as a bioengineering technique to use for stabilizing slopes. The objectives of this research are to measure the mechanical properties and tensile shear strength of roots in soil with different slope gradients (45°, 50°, and 60°). The methodologies of this study were carried out through physical modeling and lab work to analyze the objective. Shear boxes were applied to measure the mechanical properties and tensile strength of roots in soil with different slope gradients. For 21 days, the greatest soil and root shear stress for 45°, 50°, and 60° slope gradients is 13.73 kN/m2,13.70 kN/m2, and 13.25 kN/m2, respectively. Meanwhile, for 30 days, the greatest shear stress of soil with roots at 45°, 50°, and 60° slope gradients is 32.93 kN/m2, 27.71 kN/m2, and 27.22 kN/m2 respectively. Therefore, the 45° slope gradient has the largest shear stress for a period of 21 days and 30 days. According to this research, among slope gradients of 50° and 45°, the Vetiver root for the 60° slope gradient has the greatest value for tensile strength, which is 0.025 kN for 30 days, while for a period of 21 days it is 0.024 kN. However, to have better approach its appropriate if the Vetiver grass planted with slope gradient 450 since obtained great Vetiver root strength compared to others slope gradient. This study can be used as a reference to produce a slope stabilization method by using Vetiver Grass as its medium of bioengineering technique in the future.

An improved evolutionary structure optimization method considering stress minimization and smooth design

AbstractThe design of continuum structures often presents challenges related to stress concentration, which can cause significant structural damage. To address this issue, the current study presents a new stress minimization method that utilizes the Windowed Evolutionary Structural Optimization (WESO) framework. The method aims to improve algorithm stability by optimizing design variables with an intermediate density. The use of a P‐norm stress aggregation method improves the assessment of global stress levels and enhances computational efficiency. Furthermore, a stable element sensitivity formulation, derived from the adjoint sensitivity analysis of the global stress measure, effectively handles the nonlinear stress behavior. Mesh filtering techniques are utilized to convert sensitivity from elements to nodes, and the structural topological solution is represented using the level set function (LSF) based on element‐node sensitivity. This method addresses the singularity issue commonly found in density‐based optimization methods and facilitates the achievement of smooth topological solutions. Through 2D and 3D benchmark designs, the proposed method's feasibility, stability, and superiority are thoroughly demonstrated. A parametric study is conducted to identify the optimal parameter range for the algorithm, leading to the development of a rational method for parameter selection. The optimized topology, with its smooth boundaries, can guide the design of structures without the need for redesign or post‐processing, helping to drive innovation and development in engineering.

Efficiency of Alginic Acid, Sodium Carboxymethylcellulose, and Potassium Polyaspartate as Calcium Tartrate Stabilizers in Wines.

The instability of calcium tartrate (CaT) in wines occurs when the effective concentration of ions surpasses the solubility product, leading to the formation of CaT crystals. Unlike potassium hydrogen tartrate (KHT), temperature has little effect on the rate of CaT precipitation, making cold stabilization ineffective. Additives like metatartaric acid and carboxymethylcellulose (CMC) have been used to mitigate this problem, but metatartaric acid's effectiveness is limited due to hydrolysis. Additionally, potassium polyaspartate (KPA), commonly used as a KHT stabilizer, has been reported to reduce wine stability regarding CaT instability. Therefore, exploring alternative stabilization methods is crucial. Alginic acid, permitted as a processing aid in winemaking, can be an alternative to CMC and metatartaric acid due to its strong negative charge and ability to bind calcium ions. This study aimed to assess alginic acid's efficacy as a CaT stabilizer compared to CMC and investigate the impact of KPA on CaT instability. The results showed that KPA did not increase CaT instability and even improved its stability in some wines. Alginic acid outperformed both CMC and KPA in mitigating CaT instability, possibly due to its higher zeta potential and calcium ion complexation ability. This study is the first to investigate the use of alginic acid for CaT stability in wine.

Reinforcement learning for encouraging cooperation in a multiagent system

Success in cooperative tasks may be compromised if cooperative stagnation and failure from information sharing occur. However, information sharing may require excessive memory. Other methods must be developed to encourage agents to take actions in accordance with the needs of the team. In this study, a method called the cooperative tendency model using Q-learning (CTM-Q) is proposed for a partial-communication multiagent team. Each agent maintains and records its tendency values (encouraging cooperation) and Q-values (encouraging goal-seeking) as input for a payoff function that is used to select actions. Each agent selects the action with the highest payoff value for the current state. The method improves learning performance, enabling agents to rapidly reach a consensus. In simulations, the proposed method accelerated learning for multiagent cooperative applications and outperformed competing methods in solution speed, convergence time, and stability.

A Thermodynamically Consistent Anisotropic Continuum Damage Mechanics Model With Damage-Dependent Equivalent Strain

Abstract This paper proposes a new thermodynamically consistent anisotropic continuum damage mechanics model that the degradation of material is described by a set of damage variables. We adopt a set of novel equivalent strains which are functions of both the strain and the damage state variables as well. A viscous stabilization method is considered to improve the convergence during the material softening. The evolution of damage state variables is updated through a Newton–Raphson iterative process. The expression of the consistent tangent stiffness matrix is also derived. A smoothed exponential damage evolution shape function with rescaling regularization method is proposed to describe the material softening process and the mesh dependency phenomenon is relieved. Several sets of numerical examples including three-point-bending of a notched beam, uniaxial tension of unnotched and notched plate of composite material with multiple layups are presented to verify the anisotropic damage models.

Practical stabilisation of discrete-time switched nonlinear systems without a common equilibrium and using hybrid switching functions

This paper presents a new practical stabilization method for discrete-time switched nonlinear systems without a common equilibrium point among all modes. The proposed method has two main features. First, the number of nonlinear terms in the stability conditions is independent of the number of switched system modes. The result is that the computational cost is reduced, and it can be applied to switched systems with a large number of subsystems. Second, using switched Lyapunov functions, hybrid switching laws are designed to preserve the practical stability property in both the closed-loop state-dependent switching function and the open-loop time-dependent one. As a result, when the state data is lost during sensor or communication failures, the controller can change the control scheme from a closed-loop state-dependent switching function to an open-loop time-dependent one without loss of stability property. Numerical examples are presented to illustrate the validity and efficiency of the proposed method.

Medicinal Chemistry of Antisense Oligonucleotides for Therapeutic Use in SARS-CoV-2: Design Strategies and Challenges for Targeted Delivery

Background: The evolution of novel Severe Acute Respiratory Syndrome-related Coronavirus 2 (SARS-CoV-2) strains with greater degrees of infectivity, resistance to vaccine-induced acquired immunity, and more severe morbidity have contributed to the recent spread of COVID-19. In light of this, novel therapeutic alternatives with improved effectiveness and fewer side effects have become a necessity. Despite many new or repurposed antiviral agents recommended for Coronavirus disease (COVID-19) therapy, this objective remains unfulfilled. Under these circumstances, the scientific community holds the significant responsibility to develop classes of novel therapeutic modalities to combat SARS-CoV-2 with the least harmful side effects. Objective: Antisense Oligonucleotides (ASOs) are short single-stranded oligonucleotides that allow the specific targeting of RNA, leading to its degradation. They may also prevent cellular factors or machinery from binding to the target RNA. It is possible to improve the pharmacokinetics and pharmacodynamics of ASOs by chemical modification or bioconjugation, which may provide conditions for customization of a particular clinical target. This study aimed to outline the potential use of ASOs in the treatment of COVID-19 disease, along with the use of antisense stabilization and transfer methods, as well as future challenges and limitations. Methods: We have reviewed the structure and properties of ASOs containing nucleobase, sugar, or backbone modifications, and provided an overview of the therapeutic potential, delivery challenges, and strategies of ASOs in the treatment of COVID-19. Results: The first-line therapy for COVID-19-infected individuals, as well as the development of oligonucleotide-based drugs, warrants further investigation. Chemical changes in the oligonucleotide structure can affect the biological processes. These chemical alterations may lead to enhanced potency, while changing the pharmacokinetics and pharmacodynamics. Conclusion: ASOs can be designed to target both coding and non-coding regions of the viral genome to disrupt or completely degrade the genomic RNA and thereby eliminate SARS-CoV-2. They may be very effective in areas, where vaccine distribution is challenging, and they may be helpful for future coronavirus pandemics.

Comparison of Physics Informed Neural Networks and Finite Element Method Solvers for advection-dominated diffusion problems

We present a comparison of Physics Informed Neural Networks (PINN) and Variational Physics Informed Neural Networks (VPINN) with higher-order and continuity Finite Element Method (FEM). We focus on the one-dimensional advection-dominated diffusion problem and the two-dimensional Eriksson–Johnson model problem. We show that the standard Galerkin method for FEM cannot solve this problem on uniform grid. We discuss the stabilization of the advection-dominated diffusion problem with the Petrov–Galerkin (PG) formulation and present the FEM solution obtained with the PG method. The main benefit of using a stabilization method is that it can deliver a good-quality approximation to the solution on a mesh that is not fully refined towards the singularity. We employ PINN and VPINN methods, defining several strong and weak loss functions. We compare the training and solutions of PINN and VPINN methods with higher-order FEM methods. We consider a case with uniform FEM and uniform distribution of points for PINN, as well as uniform distribution of test functions for VPINN. We also consider adaptive FEM, refined towards edge singularity, and non-uniform distribution of points for PINN, as well as non-uniform distribution of test functions for VPINN.