Stability Parameters Research Articles

GA and PSO Techniques Based Optimal Tuning of Power System Stabilizers in a PV Integrated Power Network

This paper involves the employment of Genetic Algorithm (GA) and Particle Swam Optimization (PSO) methods for the optimal tuning of gain and time constant parameters of power system stabilizers in a power network with integrated Photovoltaic (PV) energy conversion systems. To examine the critical modes of the PV integrated system and the impact of the PV integration on various modes of oscillations, eigenvalue analysis is carried out under various PV penetration levels. The investigations indicate that the rotor angle oscillations following a disturbance have less damping as the PV penetration level increases. To enhance the small signal stability, the excitation systems are provided with the signal from power system stabilizers (PSS). The gain and time constant parameters of the PSS are tuned utilizing the GA and PSO methods and compared with the conventional proportional-integral (PI) PSS. The preliminary investigations on the PV integrated standard IEEE power system reveal that the PSO and GA-based PSS are significantly better than the PI-PSS, and further, PSO-PSS is marginally more effective than the GA-PSS in damping the rotor angle oscillations.

Palliative Subcutaneous Needle Drainage for a Rare Cause of Refractory Lymphedema: Yellow Nail Syndrome.

Yellow nail syndrome (YNS) presents a therapeutic challenge due to its elusive etiology and lack of effective treatments. We present a case of a 77-year-old female with YNS-associated lymphedema who experienced significant symptomatic relief with subcutaneous drainage therapy, a novel intervention not previously described in YNS. Despite prior failed conventional therapies, she achieved remarkable weight loss, improved mobility, and stable biochemical parameters. Subcutaneous drainage therapy, though traditionally utilized in cancer-associated lymphedema, demonstrates promise as an alternative palliative treatment for refractory cases of lymphedema to improve quality of life.

Non-smooth self-excited vibration of a novel dynamical model for a disc brake

This paper proposes a new dynamic model for the study of friction-induced self-excited vibration of a disc brake system, where the pad’s motions in both radial and circumferential/tangential directions are included, which is in stark contrast to the previous studies that normally consider the pad’s motion in the tangential/circumferential direction only. The non-smooth dynamics of the system including three different states of motion, i.e., stick, slip and separation, is investigated. Both the linear stability analysis and the transient dynamic analysis are performed. The numerical results in the linear stability analysis indicate that the inclusion of pad’s radial motion in the present brake model significantly expands the ranges of operating parameters for dynamic instability than the brake model with only circumferential/tangential motion for the pad. For the transient dynamic analysis, two different methods, i.e., the time integration method and the shooting method, are employed for the calculation of steady-state response. The accuracy and efficiency of the shooting method are subsequently examined. The numerical results show rich bifurcation behaviours of the steady-state response in the present brake model with the variations of brake pressure and disc speed , and (the stiffness of the inclined spring in the radial direction) is a key parameter for controlling the occurrence of chaotic vibration in the system. Conflict of Interest Statement The authors declare no conflicts of interest.

Priority radiomic parameters for computed tomography of head and neck malignancies: A systematic review

BACKGROUND: Radiomics is the newest and most promising direction in modern radiographic diagnostics. The number of head and neck cancer studies employing radiomics is increasing annually. A systematic review of recent publications (2021–2023) on computed tomography (CT) of head and neck malignancies was performed. AIM: To present systematized data on parameters for radiomic analysis for head and neck malignancies identified by CT data. MATERIALS AND METHODS: The literature search was carried out in PubMed. The basic characteristics of the selected articles were extracted, and their quality was assessed using RQS 2.0 and the modified QUADAS-CAD questionnaire. The reproducibility level of radiomic parameters selected for predictive models in different studies was assessed. Eleven articles were selected for the review. In most cases, a high risk of systematic error associated with data imbalance in terms of demographic parameters and level of pathologies was noted. RESULTS: The range of RQS 2.0 scores for the included articles varied from 19.44% to 50.00% of the maximum possible score. The decreasing research quality was mainly caused by the lack of external result validation (73% of the analyzed articles) and data accessibility and transparency (82%). Inter-study reproducibility of radiomic parameters was low owing to the wide variety of techniques used for image acquisition, image post-processing, extraction, and statistical processing of radiomic parameters. CONCLUSION: A set of stable radiomic parameters must be successfully introduced into clinical practice. The standardization of radiomics method and creation of an open radiomics database are necessary for this purpose.

Shifting shapes: Density variations and physicochemical characteristics from spheres to rods

This work extensively explores purifying cetyltrimethylammonium bromide (CTAB)-stabilized gold nanorods, focusing on efficiently separating spheres and rods to achieve a rod-rich suspension in one cycle. Utilizing UV–vis spectroscopy and Helium ion microscopy, the study delves into nanorods' spectral traits across different aspect ratios (AR 3–6). Results show centrifugation greatly influences gold nanorods' spectral features, indicating a link between CTAB-coated nanorod density and absorbance levels post-centrifugation. This quantitative evaluation enhances understanding of purification dynamics, highlighting effects on purity and density while offering insights for future refinements. Emphasizing centrifugation's role in reducing byproducts, nanoparticle density changes, and absorbance variations, the study's consistent spectral profiles affirm the effectiveness of purification parameters for stability and nanoparticle density maintenance. By quantitatively analyzing centrifugation duration's impact on spectral properties and shape separation dynamics, the research provides an empirical foundation for optimizing gold nanorod suspension purification processes. Additionally, a clear correlation between AR and absorbance-to-density ratios pre- and post-centrifugation underscores AR's relevance in comprehending nanorods' optical traits amidst centrifugation, benefiting purification strategies.

Horizon picking algorithm using global optimization and coherence measurement in poststacked seismic data

Accurate horizon recognition within poststack seismic sections is important in seismic interpretation. Horizon picking techniques influence diverse seismic structural analyses and inversion methodologies. Despite encountering challenges such as computational demands and time constraints, the past few years have witnessed the development of numerous 2D and 3D methods. With the progress of modern computing, more robust and efficient techniques, harnessing artificial intelligence, have come to the fore. In this context, we develop an innovative cost-effective algorithm grounded in a global optimization framework. This algorithm combines the very fast simulated annealing method with a set of stability parameters and coherence measurements between neighboring seismic traces, which is used as the objective function. The search is executed on continuous and sequential clusters of seismic traces, with a focus on maximizing coherence amidst the presented events. We evaluate the algorithm’s efficacy by applying it to two distinct input data sets — enveloped and nonenveloped seismic traces. The initial application is to the time-migrated Marmousi data set, a synthetic marine data set originated from a complex geologic sedimentary basin situated in Angola, Africa. Subsequently, we apply the algorithm to depth-migrated land data extracted from a past survey conducted in the Tacutu Basin in northern Brazil. Outcomes arising from the application to 2D synthetic and field data sets underscore the method’s viability as a compelling alternative for seismic horizon picking within the time or depth domain.

Performance and Stability for Grain Yield and Its Components of Some Rice Cultivars under Various Environments

Refine current agricultural practices considering environmental changes are crucial for finding tolerant rice varieties that can meet the demands of human consumption. To this end, stability analysis assesses a crop genotype’s ability to adapt to various conditions. Therefore, the objective of this study was to (1) examine the interaction between rice genotypes and environmental conditions; (2) evaluate the stability of twelve rice genotypes using various stability methods; (3) identify representative environments for multi-environment testing; and (4) determine superior genotypes for specific environments. The evaluated rice cultivars were Sakha 101, Sakha 104, Sakha 105, Sakha 106, Sakha 107, Sakha 108, Giza 177, Giza 178, Giza 179, Giza 182, Egyptian Yasmine, and Sakha super 300. The experiment followed a strip-plot design, with three replications. The findings revealed significant differences among the rice varieties across various environments for the majority of the assessed characteristics. The joint regression analysis of variance demonstrated highly significant differences among rice cultivars for all the studied traits in terms of genotype-by-environment interaction (G × E). The statistical significance of the interaction between genetic and environmental factors was evident for all variables demonstrating heritable variation among the rice cultivars, specifically Sakha 108, Sakha 104, Giza 177, and Giza 178, concerning grain yield per feddan. These rice cultivars exhibited stability parameters that were not significantly different from unity for the regression coefficient (bi) and from zero for the deviations from regression (S2di) for those traits. Overall, stability criteria are essential for ensuring reliable rice production, meeting human consumption, advancing genetic improvement, and promoting environmental sustainability in agriculture.

Landslide Analysis with Incomplete Data: A Framework for Critical Parameter Estimation

Landslides are one of the most common geohazards, posing significant risks to infrastructure, recreation, and human life. Slope stability analyses rely on detailed data, accurate materials testing, and careful model parameter selection. These factors are not always readily available, and estimations must be made, introducing uncertainty and error to the final slope stability analysis results. The most critical slope stability parameters that are often missing or incompletely constrained include slope topography, depth to water table, depth to failure plane, and material property parameters. Though estimation of these values is common practice, there is limited guidance or best practice instruction for this important step in the analysis. Guidance is provided for the estimation of: original and/or post-failure slope topography via traditional methods as well as the use of open-source digital elevation models, water table depth across variable hydrologic settings, and the iterative estimation of depth to failure plane and slope material properties. Workflows are proposed for the systematic estimation of critical parameters based primarily on slide type and scale. The efficacy of the proposed estimation techniques, uncertainty quantification, and final parameter estimation protocol for data-sparse landslide analysis is demonstrated via application at a landslide in Colorado, USA.

Towards sharper excess risk bounds for differentially private pairwise learning

Pairwise learning is a vital part of machine learning. It depends on pairs of training instances, and is naturally fit for modeling relationships between samples. However, as a data driven paradigm, it faces huge privacy issues. Differential privacy (DP) is a useful tool to protect the privacy of machine learning, but corresponding excess population risk bounds are loose in existing DP pairwise learning analysis. In this paper, we propose a gradient perturbation algorithm for pairwise learning to get better risk bounds under Polyak–Łojasiewicz condition, including both convex and non-convex cases. Specifically, for the theoretical risk bound in expectation, previous best results are of rates O(pn2ϵ2+1n) and O(pnϵ+1n) under strongly convex condition and convex conditions, respectively. In this paper, we use the on-average stability and achieve an O(min{pn1.5ϵ+p1.5n2.5ϵ3,pn2ϵ2+1n}) bound, significantly improving previous bounds. For the high probability risk bound, previous best results are analyzed by the uniform stability, and O(βnU+pnϵ) excess population risk bounds are achieved under strongly convex or convex conditions, where βnU is the traditional pairwise uniform stability parameter, it is large since it considers the worst case of the loss sensitivity. In this paper, we propose the pairwise locally elastic stability and improve the high probability bound to O(βEn+pnϵ), in which the pairwise locally elastic stability parameter βE≪βnU because it considers the average sensitivity of the pairwise loss function.

Clinical experience on switching trientine tetrahydrochloride to trientine dihydrochloride in Wilson disease patients.

This study evaluates the effectiveness and safety of trientine dihydrochloride (TETA 2-HCl) in patients with Wilson disease (WD) following a switch from trientine tetrahydrochloride (TETA 4-HCl). A total of 30 WD patients with stable copper metabolism were identified for treatment with TETA 2-HCl (Cufence™) after prior use of TETA 4-HCl (Cuprior™). Biochemical markers including urinary copper, non-ceruloplasmin bound copper (NCC) and liver function were analyzed at baseline and followed up over 12 months. Safety was assessed based on reported adverse events (AEs). Urinary copper levels and NCC remained stable across all follow-ups, indicating adequate copper metabolism control. Reported AEs during TETA 2-HCl treatment were mostly gastrointestinal discomfort (n = 6). In two patients, progressive elevation of transaminases occurred (despite stable copper metabolism). AEs led to discontinuation of treatment in five cases. Median baseline dose per day was 10.2 mg TETA 4-HCl/kg bodyweight, whereas median baseline dose after therapeutic switch to TETA 2-HCl was 12.8 mg/kg bodyweight. Median daily dose at 12 months did not differ significantly from TETA 2-HCl dose at switching timepoint, with stable biochemical markers and markers of copper metabolism in most (25/30) of the patients. Transitioning from TETA 4-HCl to TETA 2-HCl maintained stable copper parameters and liver function in most of analyzed patients. TETA 2-HCl treatment was generally well tolerated, suggesting that switching medications is safe and effective. In our real-life cohort, adjustment factor of ~1.25× for the switch of TETA 4-HCl to TETA 2-HCl resulted in adequate copper metabolism control.

Cardiac tamponade in a patient with chagas disease and pericardiocentesis. Case report

Introduction: Cardiac tamponade is considered a medical emergency, which is characterized by the accumulation of fluid, pus, blood or clots in the pericardial space. Chagas disease is considered one of the potential causes of cardiac tamponade due to the myocarditis and pericarditis it can produce.Clinical case: 58-year-old male patient who went to the emergency department, with a condition characterized by: dizziness, fatigue, productive cough with whitish expectoration, moderate dyspnea, general and mild chest discomfort. With a history of Chronic Chagas, smoker. A P-A chest x-ray, electrocardiogram and transthoracic echocardiogram were performed, confirming the diagnosis of cardiac tamponade. Discussion: Although Beck's triad can guide the diagnosis, it occurs in a small percentage of cases. In our case, after diagnosis, ultrasound-guided pericardiocentesis was performed and allowed the evacuation of blood content, improving the hemodynamic condition after performing the procedure and stable vital parameters. Conclusions: Chronic Chagas and some associated risk factors triggered the development of plugging. The pericardiocentesis was successful, allowing the evacuation of blood content, improving the hemodynamic condition and avoiding complications. Atypical presentation requires multidisciplinary management, early diagnosis related to clinical and ultrasound findings are essential for management, these will be determining factors in the evolution and prognosis of our patients

Improving UASS pesticide application: optimizing and validating drift and deposition simulations.

As unmanned aerial spraying systems (UASS) usage grows rapidly worldwide, a critical research study was conducted to optimize the simulation of UASS applications, aiming to enhance pesticide delivery efficiency and reduce environmental impact. The study examined several key aspects for accurate simulation of UASS application with lattice Boltzmann method (LBM). Based on these discussions, the most suitable grid size and simulation parameters were selected to create a robust model for optimizing UASS performance in various pest management scenarios, potentially leading to more targeted and sustainable pest control practices. The effect of stability parameter, grid size around the rotor and near ground, and parameters at wake flow were carefully analyzed to improve the precision of pesticide drift predictions and deposition patterns. Optimal grid sizes were identified as 0.2 m generally, 0.025 m near rotors, and a 0.1 + 0.2 m scheme for ground proximity, with finer grids improving accuracy but increasing computation time. Wake resolution and threshold significantly influenced simulation results, while wake distance had minimal impact beyond a certain point. The LBM's accuracy was validated by comparing simulated downwash flow and droplet deposition with field test data. This study optimized UASS simulation parameters, balancing computational efficiency with accuracy. The validated model enhances our ability to design more effective UASS for pest management, potentially leading to more precise and targeted pesticide applications. These advancements contribute to the development of sustainable pest control strategies, aiming to reduce pesticide usage and environmental impact while maintaining crop protection efficacy. © 2024 Society of Chemical Industry.

Dynamic stability and response of morphing wing structure with time-varying stiffness

Abstract Morphing, adaptable or smart structures are being used in mechanical and aerospace applications in recent years. These structures often have the property of time-varying stiffness or inertial properties, which can cause parametric instability issues that are not well understood. This paper examines the dynamic stability and response of a morphing aircraft wing with periodically time-varying structural stiffness. The wing is modeled as a beam with coupled bending-torsion motion, and parametrically excited stiffness. Aerodynamic loads introduce aerodynamic damping and aerodynamic stiffness to the wing structure. The dynamic and aeroelastic equation of motion resembles a coupled, damped Mathieu-type equation but differs with asymmetric damping and stiffness matrices, and symmetric inertial matrix. Further, these equations are functions of airspeed, magnitude and frequency of parametric excitation. Initially, dynamic stability of the wing is analyzed using Floquet theory, and the instability regions are numerically quantified by stability charts. Subsequently, dynamic responses in the stable and unstable regions are investigated with a Floquet-based Harmonic balance method. The findings reveal that, at zero airspeed, the combination instabilities are eliminated by varying the bending and torsional stiffness with equal magnitudes and frequency. However, as airspeed increases, instability regions shift unevenly, leading to the emergence of new instabilities. Furthermore, the response analysis within stable regions uncovers several unfavorable zones for operating the variable stiffness, where response decay is slower. The results clearly show that parametric excitation can cause unusual phenomena that significantly impact the operation of morphing wings with variable stiffness, which needs to be thoroughly investigated for successful implementation.

Research on Active Trailer Steering Control Strategy of Tractor Semitrailer under Medium-/High-Speed Conditions

Abstract: The study proposes an active trailer steering control method for tractor semitrailers to promote the path tracking effect of the trailer portion as well as lateral stability during lane changing. Firstly, a simplified model of a tractor semitrailer is constructed, and the MAP map is formed based on the genetic algorithm for the identification of the key parameters, which improves the model’s accuracy. Then the tractor and trailer’s yaw rate and sideslip angle at CG are tracked as the control objective and the trailer angle distribution strategy is given. Then the LQR-based corner controller is designed to control the steering actuators of each axle of the trailer. Finally, the effectiveness of the designed control strategy is verified based on the Trucksim/Simulink joint simulation platform and the semi-physical HiL test platform. The simulation results show that the designed controller can effectively improve the path tracking effect of the tractor and the trailer, and at the same time, the lateral stability parameters of the tractor and the trailer are also significantly improved, which improves the driving stability of the tractor semitrailer.

Research on image segmentation processing of coal particle flocs combined with clarity detection

ABSTRACT In the image analysis of the hydrophobic flocculation process of coal particles, the recognition accuracy of floc characteristic parameters is affected by bubbles, floc superposition, and floc morphology. An image processing method was studied and designed based on the PyCharm Community platform for clarity recognition and floc segmentation of coal particle floc characteristics. Firstly, the critical value of image clarity was determined to be 1.31 by using the Laplace convolution accounting method after the average gray level correction, and the fuzzy flocs whose clarity was less than the critical value were eliminated. Then, by comparing the segmentation effect of the threshold, edge, and region segmentation algorithm on the flocs, the histogram bimodal method was determined to be the best image processing segmentation method for fine coal floc collection. The fractal theory was used to verify the effect of image processing. The results showed that the surface fractal dimension of the floc image after deblurring and segmentation was maintained near 2.05, indicating that the processed image can obtain more stable and reliable floc characteristic parameters.

A linear second order unconditionally maximum bound principle-preserving scheme for the Allen-Cahn equation with general mobility

In this work, we investigate a linear second-order numerical method for the Allen-Cahn equation with general mobility. The proposed scheme is a combination of the two-step first- and second-order backward differentiation formulas for time approximation and the central finite difference for spatial discretization, two additional stabilizing terms are also included. The discrete maximum bound principle of the numerical scheme is rigorously proved under mild constraints on the adjacent time-step ratio and the two stabilization parameters. Furthermore, the error estimates in H1-norm for the case of constant mobility and L∞-norm for the general mobility case, as well as the energy stability for both cases are obtained. Finally, we present extensive numerical experiments to validate the theoretical results, and develop an adaptive time-stepping strategy to demonstrate the performance of the proposed method.

Behavioral state and stimulus strength regulate the role of somatostatin interneurons in stabilizing network activity.

Inhibition stabilization enables cortical circuits to encode sensory signals across diverse contexts. Somatostatin-expressing (SST) interneurons are well-suited for this role through their strong recurrent connectivity with excitatory pyramidal cells. We developed a cortical circuit model predicting that SST cells become increasingly important for stabilization as sensory input strengthens. We tested this prediction in mouse primary visual cortex by manipulating excitatory input to SST cells, a key parameter for inhibition stabilization, with a novel cell-type specific pharmacological method to selectively block glutamatergic receptors on SST cells. Consistent with our model predictions, we find antagonizing glutamatergic receptors drives a paradoxical facilitation of SST cells with increasing stimulus contrast. In addition, we find even stronger engagement of SST-dependent stabilization when the mice are aroused. Thus, we reveal that the role of SST cells in cortical processing gradually switches as a function of both input strength and behavioral state.

Increasing the Thermal Resistance of Water-Based Mud for Drilling Geothermal Wells

Energy demand and growing environmental concerns have fueled increased interest in geothermal drilling in recent decades. The high temperature and pressure in the boreholes present significant challenges to drilling, particularly in terms of the selection of suitable drilling mud, cement slurry, and drilling equipment. Drilling mud is regarded as one of the primary factors that affect the cost and success of geothermal drilling. This paper presents experimental studies aimed at assessing the thermal stability of drilling muds for geothermal drilling. Research on the antidegradation of polymers contained in drilling muds is presented. The thermal stability of drilling fluids was evaluated on the basis of changes in rheological and filtration parameters under the influence of a temperature of 160 °C. Attempts were made to increase the thermal resistance of drilling fluids by using antioxidants and glycol compounds. The effectiveness of increasing the thermal resistance of muds by adding synthetic polymers, nanomaterials, and graphite was tested. A new way of increasing the thermal resistance of drilling muds by using fatty amine compounds in combination with the amine agent ‘TEA’ was proposed. Tests showed that the addition of polyglycol and the antioxidant agent sodium ascorbate to the mud did not protect the polymers from decomposition at 160 °C. There was no effect of increasing the thermal conductivity on improving the thermal resistance of the scrubber. Based on the analysis of results from laboratory tests, a composition of a water-based drilling mud without bentonite was developed for drilling geothermal wells. The developed drilling mud is characterized by thermal resistance up to 160 °C, stable rheological parameters, low filtration, and appropriate thermal conductivity characteristics.

Large‐signal stability analysis for hybridized vehicular power supply systems of rolling stocks

AbstractHybridized vehicular power supply (HVPS) are acquiring widespread adoption in various applications such as providing power for passenger or heavy‐duty electric vehicles, more‐electric ships, electrified rolling stocks, and more. Stability analysis is a critical issue for HVPS, but it presents significant challenges due to their prominent high‐dimensional and nonlinear characteristics. This paper presents a large‐signal stability analysis scheme for HVPS of rolling stocks, enabling the assessment of system stability under sudden load changes. Based on the state‐space averaging method, a mathematical model for the large‐signal behavior of the system is established. Subsequently, the small‐signal stability parameter range of the system is determined by analyzing the eigenvalues of the Jacobian matrix. To further analyze the stability of the system during large‐signal disturbances, a nonlinear decoupling transformation approach is employed to decompose the original high‐order state equations into multiple lower‐order equations. For the decoupled lower‐order subsystems, their stability is analyzed using phase portrait, and the region of attraction (ROA) is determined using the inverse trajectory method. Based on the stability analysis results, the controller is enhanced to bring the points outside the ROA back within it, thereby mitigating the transient instability phenomenon of the system. The effectiveness of the proposed method was demonstrated using two case studies.

Stability of the Ionic Parameters of a Nonlocal FitzHugh-Nagumo Model of Cardiac Electrophysiology

Stability of the Ionic Parameters of a Nonlocal FitzHugh-Nagumo Model of Cardiac Electrophysiology