Changes In Dynamic Behavior Research Articles

On the variability of the site-response parameters of the active rock slope in Brienz/Brinzauls (Switzerland)

Summary Unstable rock slopes, prone to collapse, pose an increasingly severe threat to both people and infrastructures, necessitating effective monitoring for risk mitigation. While many techniques rely on surface displacements to assess slope stability, seismic indicators such as resonant frequency, variations in seismic shear wave velocity, and site amplification offer valuable insights into the structural integrity of the slope, aspects not captured by surface deformation alone. Research has demonstrated that these site-response parameters can serve as monitoring tools to detect precursory signs of failure, such as a drop in resonant frequency and relative seismic velocity prior to collapse. Still, environmental factors like temperature, precipitation, snow melt, earthquakes, and freeze-thaw cycles transiently influence the seismic response. Our main objective is to understand the correlations and drivers between environmental parameters and seismic response, distinguishing between reversible and irreversible changes in dynamic behaviour. Over a five-year monitoring period, we continuously recorded ambient vibration data at the Brienz/Brinzauls landslide and monitored three different site-response parameters (resonant frequency, site amplification, relative seismic wave velocity variation) using enhanced frequency domain decomposition, site-to-reference spectral ratio, and single station ambient vibrations correlation techniques. Our results highlight a long-term increase in site amplification and a long-term decrease in first and second resonant frequencies, indicating ongoing structural weakening. Temperature was found to correlate with seasonal variations of seismic wave velocity with a few day’s time lag. Snow melting and rainfalls exerted a secondary influence, temporarily reducing relative seismic wave velocity during snowmelt and rainfall. Our findings suggest that single-station relative seismic velocity variations are mainly influenced by the shallow sub-surface (depth of about 30 m), limiting its application to study the stability of deep structures.

A multi-faceted view of the X-ray spectral variability in Seyfert galaxy Ark 120

Abstract Utilizing a range of techniques including multi-band light curves, softness ratio analysis, structure functions, rms spectra, cross-correlation functions, and ratios of spectra from different intervals, we present a comprehensive study of the complex X-ray spectral variability in Seyfert 1 galaxy Ark 120, through re-analyzing its six XMM-Newton observations taken between 2003 and 2014. We find a clear ``softer-when-brighter" trend in the 2--10 keV power-law component over long timescales, with this trend being timescale dependent, as it is much weaker on shorter timescales, similar to that previously detected in NGC 4051. Notably, a rare ``harder-when-brighter" trend is observed during one exposure, indicating dynamic changes in the spectral variability behavior of the power-law component. This exceptional exposure, with the spectral variability indeed marked by a power-law pivoting at an unusually low energy of $\sim$ 2 keV, suggests intricate variations in the thermal Comptonization processes within the corona. Furthermore, when the data below 2 keV are included, we identify that the soft excess component adds significant complexity to the spectral variability, such as evidenced by a transition from ``harder-when-brighter” to ``softer-when-brighter” during another single exposure.Such extra complexity arises because the variability of the soft excess sometimes follows and sometimes does not follow the changes in the power-law component.Our findings underscore the necessity of applying multiple analytic techniques to fully capture the multifaceted spectral variability of AGNs.

Vehicle-To-Grid (V2G) Charging and Discharging Strategies of an Integrated Supply–Demand Mechanism and User Behavior: A Recurrent Proximal Policy Optimization Approach

With the increasing global demand for renewable energy and heightened environmental awareness, electric vehicles (EVs) are rapidly becoming a popular clean and efficient mode of transportation. However, the widespread adoption of EVs has presented several challenges, such as the lagging development of charging infrastructure, the impact on the power grid, and the dynamic changes in user charging behavior. To address these issues, this paper first proposes a vehicle-to-grid (V2G) optimization framework that responds to regional dynamic pricing. It also considers power balancing in charging and discharging stations when a large number of EVs are involved in scheduling, with the aim of maximizing the benefits for EV owners. Next, by leveraging the interaction between environmental states and the dynamic behavior of EVs, we design an optimization algorithm that combines the recurrent proximal policy optimization (RPPO) algorithm and long short-term memory (LSTM) networks. This approach enhances system convergence and improves grid stability while maximizing benefits for EV owners. Finally, a simulation platform is used to validate the practical application of the RPPO algorithm in optimizing V2G and grid-to-vehicle (G2V) charging strategies, providing significant theoretical foundations and technical support for the development of smart grids and sustainable transportation systems.

The Evaluation of Rainfall Warning Thresholds for Shallow Slope Stability Based on the Local Safety Factor Theory

Rainfall-induced shallow slope instability is a significant global hazard, often triggered by water infiltration that affects soil stability and involves dynamic changes in the hydraulic behavior of unsaturated soils. This study employs a hydro-mechanical coupled analysis model to assess the impact of rainfall on slope stability, focusing on the dynamic hydraulic behavior of unsaturated soils. By simulating the soil water content and slope stability under four different rainfall scenarios based on observational data and historical thresholds, this study reveals that higher rainfall intensity significantly increases the soil water content, leading to reduced slope stability. The results show a strong correlation between the soil water content and slope stability, with a 20 mm/h rainfall intensity threshold emerging as a reliable predictor of potential slope instability. This study contributes to a deeper understanding of slope stability dynamics and emphasizes the importance of proactive risk management in response to changing rainfall patterns while also validating current management practices and providing essential insight for improving early warning systems to effectively mitigate landslide risk.

Characterizing the adult zebrafish model of Parkinson's disease: a systematic review of dynamic changes in behavior and physiology post-MPTP administration.

Adult zebrafish are increasingly used in Parkinson's disease (PD) research due to their well-characterized dopaminergic system. Among the toxin-based models, the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is widely utilized to induce parkinsonism in adult zebrafish. Therefore, this review presents an overview of the procedures and the dynamic changes in behavior and physiology observed in the adult zebrafish PD model following a single intraperitoneal injection of MPTP. A systematic literature search in the PubMed and Google Scholar databases was conducted to identify relevant articles. Of the 165 articles identified, 9 were included in this review. These chosen articles are original works published before March 2024, all of which utilized adult zebrafish induced with MPTP as the model for PD. Other articles were excluded based on factors such as limited relevance, utilization of zebrafish embryos or larvae instead of adults, and variations in MPTP deliveries. Studies indicated that the ideal model entails the utilization of mixed gender zebrafish aged between 4 and 6 months from the wild-type strain. The acceptable MPTP doses ranges between 20 μg/g (lowest) and 225 μg/g (highest) and doses above 292 μg/g are lethal. Furthermore, noticeable parkinsonian symptoms appear 1 day after administration and persist for more than 1 week. Mitochondrial dysfunction precedes dopaminergic neurodegeneration within this experimental regime. A single administration of MPTP effectively induces PD in adult zebrafish. This study aids in crafting the adult zebrafish PD model, outlining the progressive behavioral and physiological changes ensuing from MPTP administration.

Mechanism of Pressure-Modulated Self-Trapped Exciton Emission in Cs2TeCl6 Double Perovskite.

Pressure-modulated self-trapped exciton (STE) emission mechanism in all-inorganic lead-free metal halide double perovskites characterized by large Stokes-shifted broadband emission, has attracted much attention across various fields such as optics, optoelectronics, and biomedical sciences. Here, by employing the all-inorganic lead-free metal halide double perovskite Cs2TeCl6 as a paradigm, the authors elucidate that the performance of STE emission can be modulated by pressure, attributable to the pressure-induced evolution of the electronic state (ES). Two ES transitions happen at pressures of 1.6 and 5.8GPa, sequentially. The electronic behaviors of Cs2TeCl6 can be jointly modulated by both pressure and ES transitions. When the pressure reaches 1.6GPa, the Huang-Rhys factor S, indicative of the strength of electron-phonon coupling, attains an optimum value of ≈12.0, correlating with the pressure-induced photoluminescence (PL) intensity of Cs2TeCl6 is 4.8-fold that of its PL intensity under ambient pressure. Through analyzing the pressure-dependent STE dynamic behavioral changes, the authors have revealed the microphysical mechanism underlying the pressure-modulated enhancement and quenching of STE emission in Cs2TeCl6.

Study on dynamic behavior of atomic diffusion at interface between TiAlN coating and WC matrix

The molecular dynamics method was used to simulate the dynamic behavior change of atomic diffusion at interface between TiAlN coating and WC matrix in the carbide tool with TiAlN coating. It was determined that the one-way diffusion of C atom to TiAlN coating resulted in serious lattice distortion on the surface. Meanwhile, the whole diffusion process was accompanied by the continuous increase of stress, resulting in gradual deformation of the material. The interface bonding performance also decreases. Then, the surface energy and atomic layer convergence are calculated by the first-principles method. The TiAlN crystal surface is stable at 8 atomic layers, and the WC crystal surface is stable at 6 atomic layers, and then a stable microinterface model can be built. The relaxation processing for the established model was performed to determine the diffusion path of C atom. Then, the energy barrier, adhesion work, interface energy and fracture toughness of different transition state structures in the diffusion path of C atom are calculated, and it is determined that with the deepening of the diffusion of C atom in the coating, the binding ability of the interface of the coating base and the performance of the coating tool are more and more serious damage. Finally, the cutting experiment of TiAlN coated tool is designed. According to the surface topography of TiAlN coated tool in different periods, the simulation and theoretical analysis mentioned above are verified, which provides a theoretical basis for the subsequent research on improving the performance of coated tool.

Evaluation of Pain-Associated Behavioral Changes in Monoiodoacetate-Induced Osteoarthritic Rats Using Dynamic Weight Bearing Analysis.

Pain is the primary clinical indication of osteoarthritis (OA), and behavioral assessments in rodent pain models are widely used to understand pain patterns. These preclinical pain assessments can also help us to understand the effectiveness of emerging therapeutics for prolonged OA pain management. Along with evoked methods like mechanical allodynia and thermal hyperalgesia, non-evoked methods such as dynamic weight bearing (DWB) analysis are valuable tools for behavioral assessments of pain. Both these methods were utilized to study pain-induced behavioral changes in a monoiodoacetate (MIA)-induced osteoarthritic pain model, which is a well-established preclinical OA pain model. However, the utility of DWB analysis as an indicator of long-term pain sensitivity (more than 4 weeks) remains largely unexplored. Understanding the long-term sensitivity of DWB is valuable to study the effectiveness of novel prolonged pain-relieving therapeutics. Here, we studied the dynamic behavioral changes in MIA-induced OA rats over a period of 16 weeks using DWB measurements. Female Sprague Dawley rats were injected in the right knee joint with MIA (3 mg) using X-ray guidance. Multiple dynamic postural evaluations such as ipsilateral weight percentage, paw area, contralateral/ipsilateral weight ratio and area ratio were assessed to understand the behavioral changes. The data showed that the ipsilateral weight bearing percentage alone is not sufficient to assess pain-related behavior beyond 6 weeks. This study shows the advantages and limitations of dynamic weight bearing as an assessment tool for the long-term progression of pain behavior in MIA-induced OA rats.

Investigation of Arc Dynamic Behavior Change Induced by Various Parameter Configurations for C4F7N/CO2 Gas Mixture

This study investigates the feasibility of using a mixture of C4F7N/CO2 gases as an eco-friendly arcing medium for high-voltage circuit breakers, comparing its performance to that of conventional SF6 gas. An existing magnetohydrodynamic (MHD)-based arc model is modified to incorporate the non-recombination characteristics of C4F7N. The temperature, pressure, and velocity distributions of the arc throughout the whole arcing process are systematically analyzed. First, the differences in multi-physical fields induced by the C4F7N non-recombination feature are highlighted. The effects of varying the C4F7N concentration from 4% to 10% in the C4F7N/CO2 gas mixture on the arc behavior are also computationally studied. The results indicate significant differences in the arc-extinguishing performance between C4F7N/CO2 and SF6 under identical operating conditions. The potential of using C4F7N/CO2 as a viable alternative to SF6 in circuit breaker applications may need further design efforts to optimize key components such as the driving mechanism and nozzle. Moreover, as the concentration of C4F7N increases, the gas mixture exhibits improved flow field characteristics, suggesting that a higher volume concentration of C4F7N enhances the gas’s short-circuit current interruption capabilities.

Self-calibrated transit service monitoring using automated collected data

This paper proposes a self-calibrated transit service monitoring framework that aims to obtain the performance of a transit system using automated collected data. We first introduce an event-based transit simulation model, which allows the detailed simulation of passenger travel behavior in a transit system, including boarding, alighting, and transfer walking. To estimate passenger path choices, we assume the path choices can be modeled using a C-logit model, and propose a simulation-based optimization model to estimate the path choice parameters based on automated fare collection and automated vehicle location data. The path choices can be estimated on a daily basis, which enables the simulation model to adapt to dynamic passenger behavior changes, and output more accurate network performance indicators for regular service monitoring such as train load, passenger travel time, and crowding at platforms. The proposed system eliminates the need for conventional monitoring equipment such as cameras at platforms and scaling/weighing systems on trains. The Hong Kong Mass Transit Railway (MTR) system is used as the case study. Results show that the model can well estimate the path choice behavior of passengers in the system. The output passenger exit flows are closer to the actual one compared to the two benchmark models (shortest path and uniform path choice).

Dynamic modulation of the processing of unpredicted technical errors by the posterior cingulate and the default mode network

The pervasive use of information technologies (IT) has tremendously benefited our daily lives. However, unpredicted technical breakdowns and errors can lead to the experience of stress, which has been termed technostress. It remains poorly understood how people dynamically respond to unpredicted system runtime errors occurring while interacting with the IT systems on a behavioral and neuronal level. To elucidate the mechanisms underlying such processes, we conducted a functional magnetic resonance imaging (fMRI) study in which 15 young adults solved arithmetic problems of three difficulty levels (easy, medium and hard) while two types of system runtime errors (problem errors and feedback errors) occurred in an unexpected manner. The problem error condition consisted of apparently defective displays of the arithmetic problem and the feedback error condition involved erroneous feedback. We found that the problem errors positively influenced participants’ problem-solving performance at the high difficulty level (i.e., hard tasks) at the initial stage of the session, while feedback errors disturbed their performance. These dynamic behavioral changes are mainly associated with brain activation changes in the posterior cingulate and the default mode network, including the posterior cingulate cortex, the mPFC, the retrosplenial cortex and the parahippocampal gyrus. Our study illustrates the regulatory role of the posterior cingulate in coping with unpredicted errors as well as with dynamic changes in the environment.

Closing the Gap: How Psychological Distance Influences Willingness to Engage in Risky COVID Behavior.

Pandemics, and other risk-related contexts, require dynamic changes in behavior as situations develop. Human behavior is influenced by both explicit (cognitive) and implicit (intuitive) factors. In this study, we used psychological distance as a lens to understand what influences our decision-making with regard to risk in the context of COVID-19. This study was based on the rationale that our relational needs are more concrete to us than the risk of the virus. First, we explored the impact of social-psychological distance on participants' risk perceptions and behavioral willingness. As hypothesized, we found that close social relationships of agents promoted willingness to engage in risky behavior. In the second phase, we tested an intervention designed to increase the concreteness of information about virus transmission as a mechanism to mitigate the bias of social influence. We found that the concreteness intervention resulted in significantly reduced willingness to engage in risky behavior. As such, communications aimed at changing the behavior of citizens during times of increased risk or danger should consider conceptually concrete messaging when communicating complex risk, and hence may provide a valuable tool in promoting health-related behavior.

Simultaneous determination of Young's modulus and residual stress via dynamic analysis of nanobridge exhibiting beam-to-string behaviors using a genetic algorithm

The mechanical properties of nanostructures, particularly Young's modulus and residual stress, exert significant influence on the performance and reliability of nanomechanical devices. However, conventional methods prove inadequate for evaluating these properties due to the impact of fabrication processes on nanostructures. This study addresses this challenge by proposing a dynamic model that considers the transition between “beam-like” and “string-like” characteristics under residual stress, a factor overlooked in previous research. Through analysis of nanobridge vibration modes and utilization of genetic algorithms (GAs) to reverse-engineer Young's modulus and residual stress from resonant frequencies, we introduce a novel and precise methodology. In contrast to the conventional Euler-Bernoulli beam theory, our proposed model integrates the system's kinetic and potential energies for resonant frequency calculation. This energy-based approach, grounded in physical principles, excels at capturing dynamic changes in structural behavior. Particularly in the critical “transition region” where the resonator shifts from “beam-like” to “string-like” behavior, our method adeptly accounts for energy conversion processes, resulting in more accurate resonant frequency estimations. By comparing with existing published data, our proposed method achieves a maximum error of 5.87 % in the determination of Young's modulus and residual stress of nanostructures.

Dynamic changes in the aggregation-depolymerization behavior of Ovomucin-Complex and its binding to urease during in vitro simulated gastric digestion

Ovomucin-Complex extracted from egg white is expected to have a barrier function similar to gastric mucin. In this study, the dynamic changes in structure, rheological properties and binding ability of Ovomucin-Complex during in vitro simulated gastric digestion were investigated. The results from HPLC and CLSM showed that extremely acidic pH (pH = 2.0) promoted Ovomucin-Complex to form aggregation. Acid-induced aggregation may hinder its binding to pepsin, thus rendering Ovomucin-Complex resistant to pepsin. Consequently, most of the polymer structure and weak gel properties of Ovomucin-Complex retained after simulated gastric digestion as verified by HPLC, CLSM and rheological measurement, although there was a small breakdown of the glycosidic bond as confirmed by the increased content of reducing sugar. The significantly reduced hydrophobic interactions of Ovomucin-Complex were observed under extremely acidic conditions and simulated gastric digestion compared with the native. Noticeably, the undigested Ovomucin-Complex after simulated gastric digestion showed a higher affinity (KD = 5.0 ± 3.2 nm) for urease - the key surface antigen of Helicobacter pylori. The interaction mechanism between Ovomucin-Complex and urease during gastric digestion deserves further studies. This finding provides a new insight to develop an artificial physical mucus barrier to reduce Helicobacter pylori infection.

Estimating hydrogen demand function: A structural time series model

This paper utilizes a Structural Time Series Model (STM) with an underlying component to estimate the global hydrogen demand function. This approach allows for the discernment of the ongoing impact of technology and the dynamic changes in consumer behavior that affect hydrogen demand over time. To estimate the hydrogen demand function, the analysis incorporates key variables, including hydrogen price, natural gas price, oil price, and GDP (Gross Domestic Product) per capita. The study utilizes quarterly global data from the first quarter of 2009 to the fourth quarter of 2021. In comparing the underlying components influencing hydrogen demand, the study suggests that advancements in production technology, organizational technology, and changes in consumer behavior collectively contribute to a gradual leftward shift in the global hydrogen demand curve over time. The study uncovered that, in the short term, global hydrogen demand demonstrates high inelasticity. Furthermore, the results reveal.a complementary relationship between natural gas and hydrogen, although this complementarity diminishes significantly over time. Additionally, the findings suggest that oil.can function as a substitute for hydrogen, with the substitution effect intensifying in the long term. Interestingly, hydrogen is initially perceived as a luxury commodity, yet over the long term, it transitions to behaving as a normal commodity.

Design and synthesis of phenoxy methyl-oxadiazole compounds against Alzheimer's disease.

This study examines the synthesis and evaluation of 11 newly developed compounds as potential anti-Alzheimer's agents that occur via cholinesterase and β-secretase inhibition. The compounds were tested for their inhibitory activity against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) using the modified Ellman method. The results showed that several compounds exhibited significant inhibition of AChE, particularly compounds 6d, 7a, and 7e, which demonstrated high inhibitory activity at lower concentrations, with IC50 values of 0.120, 0.039, and 0.063 µM, respectively. However, the compounds showed limited effectiveness against BChE, with only a few compounds exhibiting moderate inhibition. Compound 7e showed an inhibitory effect against BACE-1 close to that of the standard drug. Structural analysis revealed that the compounds with substituted benzothiazole and thiazole moieties exhibited the most promising inhibitory activity. This study provides valuable insights into the potential of these synthesized derivatives as a treatment against Alzheimer's disease. Moreover, the structure, stability, and properties of the active compounds were further investigated using density functional theory calculations. As a final note, the utilization of molecular docking and molecular dynamics simulation studies allowed us to elucidate the action mechanism of the active compounds and gain insights into the structure-activity relationship against AChE and β-secretase proteins. These computational techniques provide valuable information on the binding modes, interactions with target enzymes, dynamic behavior, and conformational changes of the compounds, enabling a comprehensive understanding of their biological activity.

Study on mechanical properties of shotcrete lattice girder in a tunnel considering the excavation effect at early-age

The lattice girder (LG) and shotcrete work together to provide support in tunnel engineering, being influenced by the hardening process of concrete and the excavation process. To elucidate the dynamic changes in the mechanical behavior of the LG during this process, the present study conducted indoor experiments using a self-developed loading system suitable for early age flow-plastic state shotcrete LG. Through the secondary development of the ABAQUS concrete hardening process constitutive model, an analysis of parameters such as curvature and load values was conducted to understand the evolution of the load patterns on the LG. Subsequently, relying on the background of the construction of an underground excavation station in Qingdao Metro, refined numerical simulations of the construction process were carried out. Combining the analysis with measured data, the following conclusions were drawn: 1. In the first three days after concrete casting, the LG specimen experiences relatively low stress, and after seven days, the LG specimen and concrete form a cohesive synergy; 2. The initial load caused the deterioration of the supporting performance of the unhardened grid concrete specimens, and the bearing capacity of the test group was reduced by 25% compared with the control group; 3. In the early stages of tunnel excavation and support, due to the low hardening process of shotcrete, the ability to transfer the surrounding rock load to the LG is limited, and the layout of the LG has no significant impact on the stability of the surrounding rock; 4. The collaborative support effect between the rebar bent frame (RBF) and concrete is greater than that of the LG, and it coordinates better with prestressed anchor bolts, presenting advantages in hard rock tunnels.

Discovery of Novel Noncovalent KRAS G12D Inhibitors through Structure-Based Virtual Screening and Molecular Dynamics Simulations.

The development of effective inhibitors targeting the Kirsten rat sarcoma viral proto-oncogene (KRASG12D) mutation, a prevalent oncogenic driver in cancer, represents a significant unmet need in precision medicine. In this study, an integrated computational approach combining structure-based virtual screening and molecular dynamics simulation was employed to identify novel noncovalent inhibitors targeting the KRASG12D variant. Through virtual screening of over 1.7 million diverse compounds, potential lead compounds with high binding affinity and specificity were identified using molecular docking and scoring techniques. Subsequently, 200 ns molecular dynamics simulations provided critical insights into the dynamic behavior, stability, and conformational changes of the inhibitor-KRASG12D complexes, facilitating the selection of lead compounds with robust binding profiles. Additionally, in silico absorption, distribution, metabolism, excretion (ADME) profiling, and toxicity predictions were applied to prioritize the lead compounds for further experimental validation. The discovered noncovalent KRASG12D inhibitors exhibit promises as potential candidates for targeted therapy against KRASG12D-driven cancers. This comprehensive computational framework not only expedites the discovery of novel KRASG12D inhibitors but also provides valuable insights for the development of precision treatments tailored to this oncogenic mutation.

Spatially and Temporally Resolved Dynamic Response of Co-Based Composite Interface during the Oxygen Evolution Reaction.

Interfacial interaction dictates the overall catalytic performance and catalytic behavior rules of the composite catalyst. However, understanding of interfacial active sites at the microscopic scale is still limited. Importantly, identifying the dynamic action mechanism of the "real" active site at the interface necessitates nanoscale, high spatial-time-resolved complementary-operando techniques. In this work, a Co3O4 homojunction with a well-defined interface effect is developed as a model system to explore the spatial-correlation dynamic response of the interface toward oxygen evolution reaction. Quasi in situ scanning transmission electron microscopy-electron energy-loss spectroscopy with high spatial resolution visually confirms the size characteristics of the interface effect in the spatial dimension, showing that the activation of active sites originates from strong interfacial electron interactions at a scale of 3 nm. Multiple time-resolved operando spectroscopy techniques explicitly capture dynamic changes in the adsorption behavior for key reaction intermediates. Combined with density functional theory calculations, we reveal that the dynamic adjustment of multiple adsorption configurations of intermediates by highly activated active sites at the interface facilitates the O-O coupling and *OOH deprotonation processes. The dual dynamic regulation mechanism accelerates the kinetics of oxygen evolution and serves as a pivotal factor in promoting the oxygen evolution activity of the composite structure. The resulting composite catalyst (Co-B@Co3O4/Co3O4 NSs) exhibits an approximately 70-fold turnover frequency and 20-fold mass activity than the monomer structure (Co3O4 NSs) and leads to significant activity (η10 ∼257 mV). The visual complementary analysis of multimodal operando/in situ techniques provides us with a powerful platform to advance our fundamental understanding of interfacial structure-activity relationships in composite structured catalysts.

Navigating Choppy Waters: Interplay between Financial Stress and Commodity Market Indices

Financial stress can have significant implications for individuals, businesses, asset prices and the economy as a whole. This study examines the nonlinear structure and dynamic changes in the multifractal behavior of cross-correlation between the financial stress index (FSI) and four well-known commodity indices, namely Commodity Research Bureau Index (CRBI), Baltic Dry Index (BDI), London Metal Index (LME) and Brent Oil prices (BROIL), using multifractal detrended cross correlation analysis (MFDCCA). For analysis, we utilized daily values of FSI and commodity index prices from 16 June 2016 to 9 July 2023. The following are the most important empirical findings: (I) All of the chosen commodity market indices show cross correlations with the FSI and have notable multifractal characteristics. (II) The presence of power law cross-correlation implies that a noteworthy shift in FSI is likely to coincide with a considerable shift in the commodity indices. (III) The multifractal cross-correlation is highest between FSI and Brent Oil (BROIL) and lowest with LME. (IV) The rolling windows analysis reveals a varying degree of persistency between FSI and commodity markets. The findings of this study have a number of important implications for commodity market investors and policymakers.