Dynamic Approach Research Articles

Market resilience in turbulent times: a proactive approach to predicting stock market responses during geopolitical tensions

PurposeThe Indian stock market can be tricky when there's trouble in the world, like wars or big conflicts. It's like trying to read a secret message. We want to figure out what makes investors nervous or happy, because their feelings often affect how they buy and sell stocks. We're building a tool to make prediction that uses both numbers and people's opinions.Design/methodology/approachHybrid approach leverages Twitter sentiment, market data, volatility index (VIX) and momentum indicators like moving average convergence divergence (MACD) and relative strength index (RSI) to deliver accurate market insights for informed investment decisions during uncertainty.FindingsOur study reveals that geopolitical tensions' impact on stock markets is fleeting and confined to the short term. Capitalizing on this insight, we built a ground-breaking predictive model with an impressive 98.47% accuracy in forecasting stock market values during such events.Originality/valueTo the best of the authors' knowledge, this model's originality lies in its focus on short-term impact, novel data fusion and high accuracy. Focus on short-term impact: Our model uniquely identifies and quantifies the fleeting effects of geopolitical tensions on market behavior, a previously under-researched area. Novel data fusion: Combining sentiment analysis with established market indicators like VIX and momentum offers a comprehensive and dynamic approach to predicting market movements during volatile periods. Advanced predictive accuracy: Achieving the prediction accuracy (98.47%) sets this model apart from existing solutions, making it a valuable tool for informed decision-making.

From disorder to order: A dynamic approach to mesophase formation in soft sphere model.

This study explores the dynamics of self-assembly and mesophase formation through molecular dynamics simulations of hexagonal and lamellar systems using a simplified coarse-grained model. We focus on characterizing the order-disorder transitions driven by temperature variations and emphasize the often overlooked disordered regime, which serves as a precursor to periodic mesoscale ordering. Our findings not only underscore the morphological richness of the disordered regime, comparable to that of its periodic counterparts, but also reveal the presence of clustering regimes within isotropic phases, thus corroborating prior experimental and theoretical observations. By employing the dynamic correlation coefficient, this work introduces a novel approach to understanding the fundamental mechanisms of mesophase formation, providing new insights into the complex dynamics of self-assembly.

The evolution of two‐stage production and order equilibrium in a random yield supply chain with demand information updating

AbstractThe mismatch between production, order, and demand seriously affects supply chain performance. However, most research focus on the mismatch between the retailer's order and customer's demand, which ignores the influence of the supplier's random yield on supply chain members' decision‐making. This paper investigates a two‐stage optimization problem within a two‐echelon supply chain, featuring a supplier with random yield and a retailer updating demand information in real‐time. Faced with a long production lead time, the retailer can either place advance orders at the production season's onset (first‐stage advance order) or opt for instant orders at the beginning of the sales season (second‐stage instant order). To ensure timely order fulfillment, the supplier initially employs a cost‐effective regular production mode with random yield during the production season. If yields are insufficient during sales, a pricier emergency production mode with guaranteed output becomes available. Utilizing a dynamic programming approach, we formulate the two‐stage optimization problem to derive optimal production and order decisions. Our analysis uncovers how realized random yield and stochastic market signals influence emergency production and instant order quantities in the second stage. We compare expected profits in scenarios with perfect and imperfect market signals, probing the members' preferences regarding order strategies. An intriguing finding emerges: as instant wholesale prices rising, the supplier's preferred order strategy diverges from the retailer. By strategic adjustments to the instant wholesale price, we demonstrate the potential for unanimous agreement on preferred order strategies among supply chain members — a quality enhancing the chain's flexibility and performance. Moreover, we extend the model to hybrid order strategies and identify conditions for unanimous preference among the three strategies. To bolster our theoretical findings, we provide numerical examples, lending practical support to our study.

Pore-to-Core Upscaling of Two-Phase Flow in Mixed-Wet Porous Media: Part II-A Dynamic Pore-Network Modeling Approach

Pore-to-Core Upscaling of Two-Phase Flow in Mixed-Wet Porous Media: Part II-A Dynamic Pore-Network Modeling Approach

A dynamic and critical approach to belonging as a dimension of occupation

ABSTRACT Doing, being, becoming, and belonging have been theorized as dimensions of occupation, yet belonging has received comparatively less attention from occupational scientists. The occupation-based literature tends to equate belonging with connectedness and to take a sedentarist approach in which (transnational) mobilities are considered as a challenge for occupational engagement and belonging. This paper critically examines belonging as developed through occupations and considers its constructed, dynamic, and multifaceted nature in the context of migration. Our theoretical framework is informed by transnational approaches, the mobilities paradigm, and transculturality. We draw from a cross-national comparative ethnography including 86 interviews with recent Vietnamese migrants in Vancouver, Canada, and Paris, France, as well as returning migrants in Vietnam. Our findings address participants’ belonging with regards to 1) routines, social ties, and familiarity; 2) mobile and immobile occupations; and 3) (post-)colonial politics of belonging. This study deepens understandings of the dynamic nature of occupation and belonging as well as how both are shaped by and can reproduce power dynamics. First, we contend that occupation and belonging are inherently situated, yet are not necessarily bounded to a single location. Belonging develops through routine occupations involving familiar people, objects, and amenities, which can themselves be mobile or accessible in multiple settings. Second, we emphasize how some occupations can become benchmarks for belonging, particularly in Western immigrant-receiving countries influenced by assimilationist and (post-)colonial dynamics. Lastly, we underscore individuals’ agency in employing occupations in ways to negotiate and claim belonging to their receiving and/or sending countries.

A Resonant Lyapunov Centre Theorem with an Application to Doubly Periodic Travelling Hydroelastic Waves

We present a Lyapunov centre theorem for an antisymplectically reversible Hamiltonian system exhibiting a nondegenerate 1 : 1 or 1:-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$1:-1$$\\end{document} semisimple resonance as a detuning parameter is varied. The system can be finite- or infinite-dimensional (and quasilinear) and have a non-constant symplectic structure. We allow the origin to be a ‘trivial’ eigenvalue arising from a translational symmetry or, in an infinite-dimensional setting, to lie in the continuous spectrum of the linearised Hamiltonian vector field provided a compatibility condition on its range is satisfied. As an application, we show how Kirchgässner’s spatial dynamics approach can be used to construct doubly periodic travelling waves on the surface of a three-dimensional body of water (of finite or infinite depth) beneath a thin ice sheet (‘hydroelastic waves’). The hydrodynamic problem is formulated as a reversible Hamiltonian system in which an arbitrary horizontal spatial direction is the time-like variable, and the infinite-dimensional phase space consists of wave profiles which are periodic (with fixed period) in a second, different horizontal direction. Applying our Lyapunov centre theorem at a point in parameter space associated with a 1 : 1 or 1:-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$1:-1$$\\end{document} semisimple resonance yields a periodic solution of the spatial Hamiltonian system corresponding to a doubly periodic hydroelastic wave.

Remaking urban village through culture: the politics of urban aesthetics in Shenzhen, China

ABSTRACT This paper delves into the evolving governance dynamics of urban villages in China through a case study of the heritage-rich Nantou urban village in Shenzhen. Drawing on the Rancierian politics of aesthetics, the study examines the government’s repositioning of urban villages as cultural and aesthetic assets. The research highlights the state’s emerging approach to urban village redevelopment which combines aesthetics regime and cultural governance. The intricate interplay between consensus construction and dissensus destruction reveals the fluid and porous boundaries between policing and politicization. The findings contribute to a more dynamic approach to analyzing urban village governance in China, expanding the frameworks for understanding the diverse possibilities inherent in urban redevelopment.

Uncovering naringin’s anticancer mechanisms in glioblastoma via molecular docking and network pharmacology approaches

Naringin, a flavonoid, exhibits diverse therapeutic properties and has been proven to exert cytotoxic effects on cancer cells. Nevertheless, the precise mechanism of naringin maintaining its cytotoxic effect on glioblastoma (GBM) remains unknown. Thus, the current study aimed to establish a plausible cellular mechanism for Naringin’s inhibition of GBM. We employed various system biology techniques to forecast the primary targets, including gene ontology and cluster analysis, KEGG enrichment pathway estimation, molecular docking, MD (molecular dynamic) simulation and MMPBSA analysis. Glioblastoma target sequences were obtained via DisGeNet and Therapeutic Target Prediction, aligned with naringin targets, and analyzed for gene enrichment and ontology. Gene enrichment analysis identified the top ten hub genes. Further, molecular docking was conducted on all identified targets. For molecular dynamics modelling, we selected the two complexes that exhibited the most docking affinity and the two most prominent genes of the hub identified through analysis of the enrichment of genes. The PARP1 and ALB1 signalling pathways were found to be the main regulated routes. Naringin exhibited the highest binding potential of − 12.90 kcal/mol with PARP1 (4ZZZ), followed by ABL1 (2ABL), with naringin showing a − 8.4 kcal/mol binding score, as determined by molecular docking. The molecular dynamic approach and MM-PBSA investigation along with PCA study revealed that the complex of Naringin, with 4ZZZ (PARP1) and, 2ABL (ABL1), are highly stable compared to that of imatinib and talazoparib. Analyses of the signalling pathway suggested that naringin may have anticancer effects against GBM by influencing the protein PARP and ALB1 levels. Cytotoxicity assay was performed on two different glioblastoma cell lines C6 and U87MG cells. Naringin demonstrates a higher cytotoxic potency against U87MG human glioblastoma cells compared to C6 rat glioma cells.

Interval efficiency estimation using relational dynamic DEA approach: Case of Indian banks

Interval efficiency estimation using relational dynamic DEA approach: Case of Indian banks

Dynamic path planning fusion algorithm with improved A* algorithm and dynamic window approach

Dynamic path planning fusion algorithm with improved A* algorithm and dynamic window approach

Trust in Automation (TiA): Simulation Model, and Empirical Findings in Supervisory Control of Maritime Autonomous Surface Ships (MASS)

Over the past three decades, Trust in Automation (TiA) has been the subject of extensive research. However, a large portion of the research takes a “static” approach to modeling trust and views trust as a linear unidirectional phenomenon. This view fails to recognize that trust is a dynamic construct that changes over time as an outcome of prolonged interaction with automation. The present study aims to address this gap and explore the nonlinear dynamic nature of trust by developing a simulation model of Trust in Automation (TiA) that can demonstrate trust evolution, deterioration, and recovery within the context of supervisory control of Maritime Autonomous Surface Ships (MASS). Employing System Dynamics (SD) approach, the model captures trust’s non-linear and reciprocal nature through dynamic feedback loops, producing behavioral patterns consistent with empirical observations of trust. The simulation results showcase the crucial role of initial trust conditions and the alignment of expectations with system performance in fostering trust and effective automation use. The study also explores the timing of system malfunctions, revealing that early faults have a greater negative impact on trust compared to later faults of the same magnitude. We tested a segment of the proposed model in an experimental study involving 30 human participants to investigate the effects of automation malfunctions on operators’ trust and behavioral responses during the supervisory control of MASS. Results not only validated the proposed model but demonstrated a significant decline in perceived reliability and trust in automation as well as the monitoring strategy after the automation malfunction.

Factoring in the Micro: A Transaction‐Level Dynamic Factor Approach to the Decomposition of Export Volatility

Factoring in the Micro: A Transaction‐Level Dynamic Factor Approach to the Decomposition of Export Volatility

Investigation of the effect of cefazolin drug on swelling and mechanical and thermal properties of polyacrylamide-hydrogels using molecular dynamics approach

Through molecular dynamics simulations, this study examined the interactions between water and cross-linked hydrogels, with a particular emphasis on the effect of cefazolin drug loading. The swelling percentage, ultimate strength, Young's modulus, heat flux, and thermal conductivity of polyacrylamide-based hydrogels were evaluated in relation to their respective drug concentrations (0 %, 3 %, 5 %, 15 %, and 30 %). The study results show that after 10 ns, the kinetic energy and total energy of atomic specimens stabilized at values of 12,532 and 12,488 kcal/mol, respectively. As the drug ratio increased from 0 to 15 %, the volume of polyacrylamide decreased from 342,722 to 302,583 ų, with further increased from 15 to 30 % reducing the volume to 298,562 ų due to pore and interatomic space closure by the drug. As the drug ratio increased from 0 to 3 %, the ultimate strength of the simulated structure slightly decreased from 0.0333 to 0.0332 MPa, then increased to 0.0333 MPa at a 5 % drug ratio, and remained constant beyond that. The heat flux value decreased from 1583 to 1563 W/m2 with a drug ratio increase from 0 to 3 %, but then increased from 1563 to 1585 W/m2 as the drug ratio further increased to 30 %. Increasing the drug ratio had no effect on the thermal properties of simulated structure, and the thermal conductivity remained constant at 0.57 W/m·K with increasing cefazolin dosage.

The effect of cognitive intervention program on intelligence scores in preschool.

Dynamic assessment is an approach that aims to improve student performance through interventions. One of the important application areas of dynamic assessment is the assessment of intelligence. Within the scope of the study, after a Cognitive intervention program (CIP) was developed, its effects on intelligence scores were examined with a quasi-experimental research method. The CIP was prepared by adopting a dynamic assessment approach to improve the performance of students with expert support. This improvement would be provided by the clues and feedback given during the intervention within the scope of the CIP. The sample of the study included 173 students in the 5-6 age group (83 experimental group, 90 control group). The CIP developed by the researcher consisted of 54 worksheets and was applied to the experimental group for 9weeks. The implementation of the worksheets was supervised by classroom teachers. The digital application of the Anadolu-Sak Intelligence Scale (d-ASIS) and Raven's colored progressive matrices (RCPM) were applied to both the experimental and control groups as pretests and posttests. The increases in the intelligence scores of the experimental and control groups were analyzed by MANOVA. The analysis showed that the intelligence levels of the experimental group increased significantly more than the control group in terms of both d-ASIS and RCPM total gain scores (posttest to pretest). This result indicated that the CIP, which was developed by adopting a dynamic assessment approach, supported cognitive development.

Comprehensive evaluation of interfacial interactions optimization for CF reinforced high-performance thermoplastic composites by electrochemical deposition of conjugated polymers

The mechanical properties of carbon fiber (CF) reinforced high-performance thermoplastic composites are significantly compromised due to inadequate interface bonding between CF and matrix. In this study, electrochemical polymerization techniques were employed to modify CFs with polypyrrole (PPy), poly-aniline (PANI), and poly-o-phenylenediamine (PoPd), to systematically investigate the impact of conjugated polymers on the interfacial properties of CF/copoly (phthalazinone ether sulfone ketone)s (PPESK) composites through a combination of experimental and molecular dynamics (MD) approaches. The findings revealed distinct differences among these conjugated polymers in terms of their effects on both IFSS and ILSS for CF/PPESK composites. Among all tested laminates, PoPd@CF-60s/PPESK exhibited the highest IFSS, ILSS and flexural strength values of 39.8 MPa, 75.6 MPa, and 1494 MPa, respectively, 94.1 %, 20.6 %, and 47.6 % higher than those of CF-desized/PPESK, without compromising CFs strength and thermal resistance of CF/PPESK composites. MD simulations combined with fracture morphology analysis confirmed that compatibility between conjugated polymers and matrix played a pivotal role in enhancing interface properties for CF/PPESK composites. Furthermore, the AFM outcomes demonstrated that the PoPd layer could serve as the modulus transition layer between the CF phase and the PPESK phase, which effectively enhancing the load transfer efficiency between the two phases under external forces. To summarize, this work presents a straightforward yet non-destructive approach that effectively enhances the interface strength within advanced CF reinforced high performance thermoplastic polymer composites (CFRHPTPs).

Quantum dynamics of wave packets in a Morse potential: A dynamical system approach

Quantum dynamics of wave packets in a Morse potential: A dynamical system approach

Potential Advantages of Idarubicin-Loaded Trastuzumab-Coated Liposomes for Combating Head and Neck Squamous Cancer Cells.

Head and neck squamous cell carcinoma (HNSCC) with a high mortality rate is among the most common types of cancer in the world. Human epidermal growth factor receptor 2 (HER2) is expressed higher than normal level in the most HNSCC tumors, making them resistant to chemotherapy and radiotherapy. Therefore, HER2 has been introduced as a suitable target for anticancer drugs. The aim of this study is to examine the efficacy of a treatment protocol involving targeted delivery of idarubicin encapsulated in trastuzumab-decorated liposomes to HNSCC cells. In the current experimental study, efficacies of idarubicin, prepared liposomal idarubicin, and constructed immunoliposomal idarubicin (trastuzumab-decorated) were investigated in killing HN5 cells, a HER2- overexpressing HNSCC-originating cell line. Liposomal content of idarubicin and trastuzumab were qualified by UVVisible spectroscopy and preparations were characterized for shape and size by atomic force microscopy (AFM) and dynamic light scattering (DLS). To clarify role of the missing parts of the available crystal structure (PDB ID: 1n8z) within trastuzumab-HER2 interactions, we used a 40 ns molecular dynamic simulation approach. Based on the obtained results, liposomal idarubicin showed higher toxicity of the encapsulated drug on HN5 cells compared to the traditional free drug formulations. The immunoliposomal form of idarubicin was more effective than the liposomal formulation, in killing of HN5 cells. In addition, simulation of interactions between trastuzumab and HER2 revealed that the missing parts (in the crystal structure) of HER2 have critical interaction with trastuzumab, through salt-bridges and hydrogen bonds. It seems that the prepared immunoliposomes could attach more efficiently to HER2 overexpressing cells, which consequently leads to increasing cellular uptake of idarubicin through a receptor-mediated endocytosis mechanism. Moreover, simulation of the interaction between HER2 and trastuzumab suggested considerable possibilities for increasing trastuzumab affinity to HER2.

Anomalously low-mass core-He-burning star in NGC 6819 as a post-common-envelope phase product

Precise masses of red giant stars enable a robust inference of their ages, but there are cases where these age estimates are very precise but also very inaccurate. Examples are core-helium-burning (CHeB) stars that have lost more mass than predicted by standard single-star evolutionary models. Members of star clusters in the database represent a unique opportunity to identify such stars because they combine exquisite asteroseismic constraints with independent age information (members of a star cluster share a similar age and chemical composition). We focus on the single metal-rich ($Z Li-rich low-mass CHeB star KIC4937011, which is a member of the open cluster NGC 6819 (turn-off mass of $ i.e. an age of $ 2.4$ Gyr). This star has a lower mass by $ than expected for its age and metallicity, which might be explained by binary interactions or mass loss along the red giant branch (RGB). To infer formation scenarios for this object, we performed a Bayesian analysis by combining the binary stellar evolutionary framework binary\_c v2.2.3 with the dynamic nested-sampling approach contained in the dynesty v2.1.1 package. We find that this star probably is the result of a common-envelope evolution (CEE) phase during the RGB stage of the primary star in which the low-mass ($<0.71$ main-sequence companion does not survive. The mass of the primary star at the zero-age main sequence is in the range with a log-orbital period in the range days )$. During the CEE phase, $ of material is ejected from the system, and the final star reaches the CHeB stage after helium flashes as if it were a single star with a mass of $ which is what we observe today. Although the proposed scenario is consistent with photometric and spectroscopic observations, a quantitative comparison with detailed stellar evolution calculations is needed to quantify the systematic skewness of the radius, luminosity, and effective temperature distributions towards higher values than observations.

Unveiling the moderating role of governance mechanism on the nexus between CSR and firm performance in India: A GMM‐based dynamic panel approach

Unveiling the moderating role of governance mechanism on the nexus between CSR and firm performance in India: A GMM‐based dynamic panel approach

Service Selection under Uncertainty

Cloud computing has emerged as a popular computing paradigm, providing scalable and pay-per-use services to execute a variety of tasks. However, selecting the most suitable cloud services for a client can be challenging, as it involves taking into account the service characteristics and a set of client restrictions. In this paper, we formalize the problem of Service Selection under Uncertainty (SSuU) as an optimization problem. Our goal is to allocate tasks to appropriate cloud services while considering the probability of Service Level Agreement (SLA) violations and a set of client restrictions. We introduce an efficient dynamic programming approach to calculate the probability of SLA violations incrementally over time. We prove that the SSuU problem is strongly NP-complete, and propose an Integer Linear Programming (ILP) formulation and an Iterated Local Search-based algorithm for tackling it. To facilitate evaluation, we also introduce a set of benchmark instances for the SSuU problem. We extensively evaluate our proposed solutions on 94 input instances and compare them to the exact method (i.e., which always produces the optimal solution). Our results demonstrate that the metaheuristic approach is significantly faster and leads to exact solutions in the great majority of the evaluation scenarios.