Global Stability Research Articles

Pre- and Post-Operative Cognitive Assessment in Patients Undergoing Surgical Aortic Valve Replacement: Insights from the PEARL Project

Background: Aortic valve stenosis (AVS) is a common valvular heart disease affecting millions of people worldwide. It leads to significant neurocognitive and neuropsychological impairments, impacting patients’ quality of life. Objective: The objective of this article is to identify and discuss the potential neurocognitive effects on patients with aortic stenosis before and after undergoing surgical aortic valve replacement (SAVR). Method: Our study involved the assessment of 64 patients undergoing aortic valve replacement (SAVR) using a neurocognitive evaluation comprising a battery of 11 different cognitive tests. These tests were designed to analyze the patients’ overall cognitive functioning, executive abilities, short- and long-term memory, and attentional performance. The tests were administered to patients before the aortic valve surgery (T0) and after the surgery (T1). From a statistical perspective, numerical variables are presented as means (±standard deviation) and medians (IQR), while categorical variables are presented as counts and percentages. Normality was assessed using the Shapiro–Wilk test. T0 and T1 scores were compared with the Wilcoxon signed rank test, with p < 0.05 considered significant. Analyses were performed using SAS version 9.4. Results: Conducted as part of a fully financed Italian Ministry of Health project (RF-2016-02361069), the study found that most patients showed normal cognitive functioning at baseline. Cognitive assessments showed that executive functions, attention, language, and semantic knowledge were within the normal range for the majority of participants. After SAVR, cognitive outcomes remained stable or improved, particularly in executive functions and language. Notably, verbal episodic memory demonstrated significant improvement, with the percentage of patients scoring within the normal range on the BSRT increasing from 73.4% at T0 to 92.2% at T1 (p < 0.0001). However, visuospatial and visuoconstructive abilities showed stability or slight decline, while attentional skills remained relatively stable. The Clock Drawing Test indicated the maintenance of cognitive functions. Conclusions: The findings of our study indicate a global stability in cognitive status among patients after undergoing SAVR, with significant improvement noted in verbal episodic memory. While other cognitive domains did not demonstrate statistically significant changes, these insights are valuable for understanding the cognitive effects of SAVR and can guide future research and clinical practice in selecting the most effective surgical and rehabilitative options for patients. Monitoring cognitive outcomes in patients undergoing aortic valve replacement surgery remains crucial.

Investigation of an optimal control strategy for a cholera disease transmission model with programs

Cholera is a disease of poverty affecting people with inadequate access to safe water and basic sanitation. Conflict, unplanned urbanization and climate change all increase the risk of cholera. In this article, an optimal control deterministic mathematical model of cholera disease with cost-effectiveness analysis is developed and analyzed considering both direct and indirect contact transmission pathways. The model qualitative behaviors, such as the invariant region, the existence of a positive invariant solution, the two equilibrium points (disease-free and endemic equilibrium), and their stabilities (local as well as global stability) of the model are studied. Moreover, the basic reproduction number of the model is obtained. We also performed sensitivity analysis of the basic parameters of the model. Then an optimal control problem is designed with a control functional having five controls: vaccination, treatment, environment sanitation and personal hygiene, and water quality improvement program. We examined the existence and uniqueness of the optimal controls of the system. Through the implementation of Pontryagin's maximum principle, the characterization of the optimal controls optimality system is established. The numerical simulation results the integrated control strategies demonstrated that strategy 2, 7, and 12 are effective programs to combat cholera disease from the community. Based on the local circumstances, available funds, and resources, it is recommended to the government stakeholders and policymakers to execute any one of the three integrated intervention programs.

Containerized Freight Index Prediction Integrating Deep Learning and Time Series Analysis

In the context of globalization, the shipping industry, as a core pillar of international trade, is crucial for global economic stability. This study focuses on the China Containerized Freight Index (CCFI) and proposes a composite deep learning model combining CEEMDAN, CNN, LSTM, and SENet for CCFI analysis and prediction. Initially, the CEEMDAN algorithm is used to decompose the CCFI time series, extracting useful signals from noise. Then, CNN extracts features, LSTM model sequences, and SENet enhances feature representation. The CEEMDAN-CNN-LSTM-SENet model achieves superior predictive performance with MAE of 29.5171, RMSE of 33.7638, and MAPE of 1.56%. Compared to other models like ECL (MAE 77.0951, RMSE 57.3559, MAPE 3.25%), our model shows approximately 61.7% improvement in MAE. This research offers a robust tool for shipping market analysis and policy-making, providing new perspectives for handling complex economic data.

Global Analysis of Meningitis Disease With Optimal Control

The meningitis epidemic has impacted lives negatively, especially in Sub-Sahara Africa, dubbed the ‘Meningitis Belt’. The epidemic has been a public health concern due to an improper understanding of the disease’s dynamics. To implement a control measure that will help minimize the epidemic, we introduce a non-linear Meningitis model that describes the dynamic behaviour of the disease and explains the transmission trend. The model explores the condition that leads to local or global asymptomatic stability of the equilibria. The model is subjected to a sensitivity analysis to find the parameters that influence the R0. The model is modified into an optimal control by adding timedependent controls. The control model is solved qualitatively using Pontryagin’s maximum principle and numerically using MATLAB and the fourth-order Runge-Kutta method. We provide a control strategy that can be relied on for management decision-making based on the results.

A conformable fractional finite difference method for modified mathematical modeling of SAR-CoV-2 (COVID-19) disease.

In this research, the ongoing COVID-19 disease by considering the vaccination strategies into mathematical models is discussed. A modified and comprehensive mathematical model that captures the complex relationships between various population compartments, including susceptible (Sα), exposed (Eα), infected (Uα), quarantined (Qα), vaccinated (Vα), and recovered (Rα) individuals. Using conformable derivatives, a system of equations that precisely captures the complex interconnections inside the COVID-19 transmission. The basic reproduction number (R0), which is an essential indicator of disease transmission, is the subject of investigation calculating using the next-generation matrix approach. We also compute the R0 sensitivity indices, which offer important information about the relative influence of various factors on the overall dynamics. Local stability and global stability of R0 have been proved at a disease-free equilibrium point. By designing the finite difference approach of the conformable fractional derivative using the Taylor series. The present methodology provides us highly accurate convergence of the obtained solution. Present research fills research addresses the understanding gap between conceptual frameworks and real-world implementations, demonstrating the vaccination therapy's significant possibilities in the struggle against the COVID-19 pandemic.

Reflections of Economic Shocks and Price of Crude Oil on Gold Price Volatility within Asian Nations

The focus of this study is to examine the effects of economic shocks along with the crude oil price on gold prices in Asian countries. This study utilizes a regression analysis to measure the relationship between the macroeconomic indicators, crude oil price, and gold price in six selected nations from 1990 until 2022. The validity of the data was diagnostically checked by performing a VIF procedure, autocorrelation test, and normality test on residual, and data were analyzed via EViews software. The analysis showed mixed findings, however, a major variable that positively affects the fluctuation of the gold price is “the crude oil price” and it reflects global economic stability in the six countries. A sudden rise in crude oil prices might trigger conflicts in oil-exporting countries and limit access to material sources. This situation may force investors to move their funds into a safe-haven commodity like gold. The fluctuations in crude oil prices are not only a response to current market conditions but also alarming a lot more fundamental problems in an economy, which include approaching economic recessions, currency devaluation and a major financial crisis. For practical implications, this study suggests that policymakers pay extra attention to this commodity besides other economic indicators like inflation, interest and currency rates, and a GDP rate to ensure a sustainable economic condition. To the best of the authors’ knowledge, this study is the first that examines the economic shocks along with crude oil prices pre-and-post COVID-19 pandemic focusing on a few Asian countries.

Rich dynamics of a hepatitis C virus infection model with logistic proliferation and time delays

AbstractIn this paper, we study a dynamic model of hepatitis C virus (HCV) infection with density‐dependent proliferation of uninfected and infected hepatocytes and two time delays, which is derived from a three‐dimensional model by the quasi‐steady‐state approximation. The model can exhibit forward bifurcation or backward bifurcation, and an explicit control threshold parameter is obtained for the case of backward bifurcation. It is shown that if the proliferation rate of infected hepatocytes is greater than the proliferation rate of uninfected hepatocytes by a certain amount, it becomes more difficult for the virus to be removed. The model has rich dynamical properties: (i) In some parameter regions, bistability can occur; (ii) both time delays (virus‐to‐cell delay) and (cell‐to‐cell delay) can lead to Hopf bifurcations; (iii) same length of time delays and can lead to at most one stability switch, but different time delays can lead to multiple stability switches. Several sufficient conditions for the global stability of the disease‐free equilibrium and the endemic equilibrium are obtained for both forward and backward bifurcation scenarios. In particular, several sharp results on global stability are obtained. Theoretical and numerical results portray the complexity of viral evolutionary dynamics in chronic HCV‐infected patients.

The Impact of the Russia-Ukraine Conflict on Global Economic Stability and Political Security

The conflict between Russia and Ukraine has emerged as a significant geopolitical tension, with far-reaching implications for global stability and security. This paper intends to study the impact of the war on the worlds and regional economic development and political stability, and achieve some findings that may trigger further policy considerations in mitigating challenges and issues imposed by the war. Through literature reviews and comparison analysis, the findings reveal economic, political, and security consequences of the conflict. The disruption of trade flows, economic sanctions, and uncertainty have impacted both Russia and Ukraine, as well as the wider region and the world. Energy security concerns and shifts in military alliances have added to the complexity of the conflict. The expansion of NATO and increased rivalries between Russia and Western countries have further heightened tensions. Based on the findings, the paper concludes that the Russia-Ukraine conflict poses a significant threat to global economic stability and political security. It emphasizes the need for a multilateral approach to address the conflict and promote peace and stability in the region. Ceasefire agreements, humanitarian assistance, and reconstruction efforts are crucial steps towards long-term peace and development. The paper highlights the importance of prioritizing diplomatic solutions over short-term gains from the conflict. In summary, this paper intends to explore the implications of the Russia-Ukraine conflict on global stability and security, with findings that underscore the need for international cooperation and concerted efforts to mitigate the consequences of the conflict and foster a peaceful resolution.

Evaluation of the spatial responses in vegetation phenology to drought and the analysis of their driving factors in China

The warming and drying trend accompanying climate change challenges global ecosystem stability. Vegetation phenology, which can serve as a sensitive indicator of climate change, is crucial in understanding ecosystem carbon cycling and climate-carbon cycle feedback. Therefore, assessing the phenological responses to drought is essential for addressing climate change. In this study, vegetation phenology data [including the start and end of season (SOS, EOS) and length of growing season (LOS)] and the Palmer drought severity index (PDSI) were employed to analyze the impacts of drought on plant phenology in China by maximum Pearson correlation coefficients and partial least squares regression. The findings showed that drought significantly affected the timing of phenology, delaying senescence in approximately 62% of China and extending the growing season in about 53% of the country, indicating the critical role of water availability in vegetation biomass. Preseason nocturnal warming was found to advance SOS, delay EOS, and extend LOS across China, with significant effects observed in approximately 60% of the country. Meanwhile, daytime warming delayed SOS, delayed EOS and extended LOS in 50∼60% of the regions. Moreover, preseason precipitation is conducive to advanced SOS, delayed EOS and extended LOS in northern China and areas susceptible to drought. It is suggested that vegetation management should be strengthened to mitigate the impact of climate change in temperate and drought-prone regions in China since climate warming will lead to frequent droughts.

Rapid and Environmentally-Friendly Synthesis of Thiazolidinone Analogues in Deep Eutectic Solvent Complemented with Computational Studies.

A greener, safer, and more efficient methodology for the synthesis of (Z)-5-benzylidene-2-thioxothiazolidin-4-ones (3 a-u) and (Z)-5-benzylidenethiazolidine-2,4-diones (4 a-i) has been developed. The deep eutectic solvent (DES) ZnCl2/urea used as a greener solvent as well as a catalyst in this study accelerated the condensation of rhodanine and thiazolidine-2,4-dione with different aldehydes to afford the target scaffolds in excellent yields (88-98 %). The reaction methodology adopted offered significant advantages such as mild reaction conditions, functional group tolerance, quick reaction time, column-free isolation, catalytic recyclability, and applicability to gram-scale production. Moreover, density function theory calculations were carried out to investigate the global reactivity and stability profiles of these compounds. Finally, the green metrics analysis supported the greener nature of the present methodology.

Chaos and feasibility analysis of a healthy lifestyle’s sustainability using fractional-order polycystic ovarian syndrome’s effect on infertility

In this study, we developed a fractional-order model for polycystic ovarian syndrome issue transmission in women through four compartments with the Mittag-Leffler kernel. For biological feasibility, we discussed the positivity and boundedness of solutions with fixed point mappings in Banach spaces. Sensitivity analysis is performed using different variables as response functions each time, employing Latin Hyper-cube Sampling (LHS) and Partial Rank Correlation Coefficient (PRCC) with 200 iterations. Further, the reproductive number is determined for the model’s biological feasibility with an analysis of parameter impact through Matlab software. The solutions are examined for global stability using the Lyapunov function with a first derivative. Chaos Control will use the regulate for linear responses approach to bring the system to stabilize according to its points of equilibrium. Numerical solutions are derived by using a Newton polynomial in the generalized form of the Mittag-Leffler kernel, which illustrates the effect of the fractional operator and parameters involved in the system. Results are also analyzed with different assumptions of parameter values and initial conditions to observe the different impacts of treatment to overcome the risk of infertility in women. Such type of investigation will be useful to investigate the spread of disease as well as helpful in developing control strategies to overcome the risk of problems and best management care pre-detection of the issue and for treatment.

Stability and qualitative dynamics of a class of three‐dimensional difference equation system of exponential type

In this paper, we study the boundedness, persistence, and global stability of the equilibrium point and rate of convergence of positive solutions of the exponential form of a system of difference equations where are constants and are initial values. Furthermore, some numerical examples are also given, which support our theoretical results.

Effect of geogrid spacing on the global stability of reinforced slope: a finite element approach

Effect of geogrid spacing on the global stability of reinforced slope: a finite element approach

The impact of weather patterns on inter-annual crop yield variability

Inter-annual variations in crop production have significant implications for global food security, economic stability, and environmental sustainability. Existing crop yield prediction models primarily using meteorological variables may not adequately encapsulate the full breadth of weather influences on crop development processes, such as compound or extreme events. Incorporating weather patterns into crop models could provide a more comprehensive understanding of the environmental conditions affecting growth, enabling more accurate and earlier yield predictions.Our study examines 30 distinct UK Met Office weather patterns (MO30) based on mean sea level pressure. We investigate their association with weather conditions that limit winter wheat yield in the UK (1990–2020). Blocked, negative North Atlantic Oscillation (NAO) patterns create the highest risk of temperatures that are below optimal for crop yield. However, the connection between weather patterns and yield is complex, with differing effects at a regional scale and even at which point in the growth cycle they appear. It was found that anticyclonic weather patterns during sowing, emergence, vernalisation, anthesis, and grain filling exhibit a relationship with good crop yields with a Spearman correlation coefficient of up to 0.55 for a single weather pattern (WP3 during vernalisation in South East England), whilst cyclonic patterns can help during the terminal spikelet phenological phase. The strongest positive correlations were during sowing, emergence, and vernalisation, whilst the largest negatives were observed in anthesis and grain filling.The potential of combining weather patterns with existing crop simulation models to produce earlier and more accurate yield predictions is shown. This would enable effective crop management and climate mitigation strategies, critical to strengthening food security. Projected changes in weather pattern occurrences in the late 21st century will likely reduce crop yields. This is due to increased cyclonic weather patterns, which bring warmer, wetter conditions during the wheat's vernalisation stage, followed by warmer, drier conditions during the anthesis and grain-filling phases.

Sustainable biomass derived natural surfactant of soybean seeds in fly ash industrial waste utilization for carbon storage: Evaluation of environmental impact

The rising carbon emissions challenge global environmental sustainability and climate stability. This study aims to advance climate change mitigation by integrating fly ash and natural surfactant into CO2 sequestration strategies. Fly ash, a by-product of industrial processes, presents an opportunity for innovative reuse. By combining fly ash with a natural surfactant extracted from soybean seeds, both industrial waste management and greenhouse gas reduction can be addressed. The surfactant was characterized using Fourier transform infrared spectroscopy, scanning electron microscopy, surface tension, and electrical conductivity measurements, confirming saponin presence with a critical micelle concentration of 0.3 wt%. Pressure decay studies revealed that a (5 wt% fly ash + NS) demonstrated the highest CO2 absorption, supported by microscopic analysis. Further research on optimizing reaction conditions and kinetics of mineralization could enhance this method’s efficiency and scalability for broader application.

Advanced optimal control approaches for immune boosting and clinical treatment to enhance dengue viremia models using ABC fractional-order analysis.

This work focuses on the Dengue-viremia ABC (Atangana-Baleanu Caputo) fractional-order differential equations, accounting for both symptomatic and asymptomatic infected cases. Symptomatic cases are characterized by higher viremia levels, whereas asymptomatic cases exhibit lower viremia levels. The fractional-order model highlights memory effects and other advantages over traditional models, offering a more comprehensive representation of dengue dynamics. The total population is divided into four compartments: susceptible, asymptomatic infected, symptomatic infected, and recovered. The model incorporates an immune-boosting factor for asymptomatic infected individuals and clinical treatment for symptomatic cases. Positivity and boundedness of the model are validated, and both local and global stability analyses are performed. The novel Adams-Bash numerical scheme is utilized for simulations to rigorously assess the impact of optimal control interventions. The results demonstrate the effectiveness of the proposed control strategies. The reproduction numbers must be reduced based on specific optimal control conditions to effectively mitigate disease outbreaks. Numerical simulations confirm that the optimal control measures can significantly reduce the spread of the disease. This research advances the understanding of Dengue-viremia dynamics and provides valuable insights into the application of ABC fractional-order analysis. By incorporating immune-boosting and clinical treatment into the model, the study offers practical guidelines for implementing successful disease control strategies. The findings highlight the potential of using optimal control techniques in public health interventions to manage disease outbreaks more effectively.

Study on dynamic post-buckling stability of fast reactor vessels subjected to vertical vibration

Abstract As a lesson learned from the Fukushima nuclear accident, the importance of accident mitigation for Beyond Design Basis Events (BDBEs) is recognized. Excessive earthquake is a typical BDBE. During such events, the Fast Reactor Vessel (FRV) is vulnerable to buckling. The safety goal of FRV under excessive earthquake is to achieve a stable post-buckling state. Our previous study on bending buckling confirmed a global response stability under horizontal vibration. As a parallel study, this paper focuses on axial compression buckling under vertical vibration. Shaking table experiments using thin-walled cylindrical models (R/t=260) are carried out. Similar methodology is applied to investigate the buckling and post-buckling behavior. It is found that axial compression buckling shares an extensive similarity with bending buckling in both buckling mode and post-buckling behavior. Similar global response stability is confirmed due to phase-inverse phenomenon. After buckling, buckling failure becomes stable and does not progress further even when an intense input amplitude is continuously applied. The vibrational load acts as a displacement-controlled load in the out-of-phase domain such that immediate collapse is prevented. Most input energy is dissipated in hysteresis loops rather than being carried by the mass. These mechanisms are independent of input waveform and can be applied to an arbitrary seismic input. In addition, a conservative limit displacement for global response stability is identified. Moreover, the effect of the input frequency ratio, the initial geometrical imperfection and the gravitational force on the post-buckling behavior are clarified.

Green Solutions: The Impact of Agroforestry on Climate Change Resilience- A Review

The effect of agroforestry systems on resilience to climate change, highlighting their function in improving biodiversity and reducing environmental degradation. Agroforestry offers creative ways to enhance soil health, trap carbon, and boost agricultural output while benefiting communities socioeconomically by incorporating trees into agricultural settings. Stakeholders may improve food security, rebuild ecosystems, and support the livelihoods of marginalized communities by supporting agroforestry techniques. This assessment promotes greater funding for agroforestry implementation and research, which may encourage international cooperation. Adopting eco-friendly solutions, such as agroforestry, will be essential to accomplishing sustainable development objectives and building a resilient future for the world community as climate threats worsen. Additionally, by maximising the use of natural resources, agroforestry practices lessen the burden on forests and aid in the restoration of damaged regions. Climate change poses tremendous difficulties to global agriculture, affecting livelihoods, food security, and ecosystem stability. Agroforestry is a promising integrated land management technique that combines agricultural and forestry practices to lessen the effects of climate change. This summary provides an overview of the vital roles that agroforestry plays in mitigating and adapting to climate change. In order to adapt to climate change, agroforestry offers several benefits, including increased agricultural productivity, improved soil fertility, and improved water retention

Synthesis of 6-dialkylaminopyrimidine carboxamide analogues and their anti-tubercular properties

AbstractTuberculosis (TB) continues to be a threat to global health stability. Pyrimidine carboxamides have demonstrated potent anti-tubercular properties against clinical Mycobacterium tuberculosis, the causative agent of TB. Herein, we report a follow-up study on the synthesis of pyrimidine carboxamide molecular analogues and their anti-TB evaluation. In total, a library consisting of 37 new compounds is reported. Seven compounds (7b, 7d, 7m, 7p, 7q, 7aa, and 7ah) demonstrated excellent in vitro activities with MIC90 values below 1.00 µM. Apart from compound 7ah, compounds with improved aqueous solubility properties had lower anti-TB potency. Preliminary mode of action studies using bioluminescence assays indicate that the active compounds do not affect the integrity of mycobacterial DNA or the cell wall. The active compounds were also found to be bactericidal against replicating H37Rv Mtb strain.

Distributed driving electric vehicle lateral stability control method considering time delay

This paper introduces a novel control method to address lateral stability challenge in distributed driving electric vehicles. By considering inherent time delay and unknown sensor measurement error generated from design, manufacturing, and external disturbances, the proposed approach achieves better robustness. Firstly, we establish a two-degree-of-freedom (2-DOF) dynamic model for lateral motion of an electric vehicle driven by in-wheel motors (EV-DIM). Based on this model, a control system considering time delay and unknown sensor measurement error is constructed. The control system incorporates a controller based on a dual domination gains observer, and its global asymptotic stability is rigorously proved by the Lyapunov method. Numerical simulations and co-simulations via CarSim and Simulink verify the method’s effectiveness. Compared to the sliding mode control, the proposed method shows better performance which indicates this approach promising for enhancing lateral stability of an electric vehicle.