Dynamic Interaction Research Articles

Family-Wide Photoproximity Profiling of Integrin Protein Social Networks in Cancer.

Integrin family transmembrane receptors mediate dynamic interactions between cells and their extracellular microenvironment. The heterogeneous interaction partners of integrins directly regulate cell adhesion, motility, proliferation, and intracellular signaling. Despite the recognized importance of protein-protein interactions and the formation of signaling hubs around integrins, the ability to detect and quantify these dynamic binding partners with high spatial and temporal resolution remains challenging. Here, we developed an integrin-family-directed quantitative photoproximity protein interaction (PhotoPPI) profiling method to detect and quantify native integrin-centered protein social networks on live cells and tissues without the need for genetic manipulation, antibodies, or non-physiologic cell culture conditions. We drafted quantitative maps of integrin-centered protein social networks, highlighting conserved and unique binding partners between different cell types and cellular microenvironments. Comparison of integrin social networks in cancer cell lines of diverse tissue of origin and disease state identified specific AND-gate binding partners involved cell migration, microenvironmental interactions and proliferation that serve as markers of tumor cell metastatic state. Finally, we identified unique combinations - or barcodes - of integrin-proximal proteins on the surface of pre- and post-metastatic triple negative breast cancer (TNBC) cells whose expression strongly correlate with both positive and negative disease progression and outcomes in TNBC patients. Taken together, these data provide the first family-wide high-resolution maps of native protein interactors on live cells and identify dynamic integrin-centered social networks as potential AND-gate markers of cell identity, microenvironmental context and disease state.

Vocal Call Locator Benchmark (VCL) for localizing rodent vocalizations from multi-channel audio.

Understanding the behavioral and neural dynamics of social interactions is a goal of contemporary neuroscience. Many machine learning methods have emerged in recent years to make sense of complex video and neurophysiological data that result from these experiments. Less focus has been placed on understanding how animals process acoustic information, including social vocalizations. A critical step to bridge this gap is determining the senders and receivers of acoustic information in social interactions. While sound source localization (SSL) is a classic problem in signal processing, existing approaches are limited in their ability to localize animal-generated sounds in standard laboratory environments. Advances in deep learning methods for SSL are likely to help address these limitations, however there are currently no publicly available models, datasets, or benchmarks to systematically evaluate SSL algorithms in the domain of bioacoustics. Here, we present the VCL Benchmark: the first large-scale dataset for benchmarking SSL algorithms in rodents. We acquired synchronized video and multi-channel audio recordings of 767,295 sounds with annotated ground truth sources across 9 conditions. The dataset provides benchmarks which evaluate SSL performance on real data, simulated acoustic data, and a mixture of real and simulated data. We intend for this benchmark to facilitate knowledge transfer between the neuroscience and acoustic machine learning communities, which have had limited overlap.

Chemical profiling By LC[sbnd]HRMS, antioxidant potential, enzyme inhibition, molecular docking and molecular dynamics simulations of Acantholimon acerosum

The principal objective of this study is to evaluate phenolic content and biological activity in vitro and silico properties of A. acerosum (Willd.) Boiss. subsp. acerosum's (A. acerosum). The antioxidant activity of A. acerosum was assessed in a variety of bioanalytical methods. Strong antioxidant activity was shown for both water (WEAA) and ethanol (EEAA) extracts of the aerial parts of A. Acerosum. Also, it was shown that hyperoside is the most prevalent phenolic compound in EEAA (12,940.83 mg kg−1) and WEAA (5409.67 mg kg−1) by LCHRMS. The enzyme inhibitory abilities of the EEAA were then realised. The IC50 values of EEAA against acetylcholinesterase (AChE) (E.C.3.1.1.7), α-glycosidase (E.C.3.2.1.20), and α-amylase (E.C.3.2.1.1) were determined as 1.828 μg mL−1, 0.615 μg mL−1, and 1.081 μg mL−1, respectively. Subsequently, the α-amylase, α-glycosidase, and AChE enzymes were subjected to molecular docking and molecular dynamic interactions using major compounds of EEAA as ligands. High enzyme-inhibiting properties of EEAA were also determined in silico. It has been reported that numerous traditional and contemporary medical applications of A. acerosum. It can be said that the effective antioxidant results obtained in our study are the basis of previously performed traditional or contemporary medical practices.

An Optimized Power-Angle and Excitation Dual Loop Virtual Power System Stabilizer for Enhanced MMC-VSG Control and Low-Frequency Oscillation Suppression

Modular Multilevel Converter Virtual Synchronous Generator (MMC-VSG) technology is gaining widespread attention for its ability to enhance the inertia and frequency stability of the power grid integrated with converter-interfaced renewable energy sources. However, the excitation voltage regulation in the MMC-VSG can generate equivalent negative damping torque and cause low-frequency oscillation problems similar to those in synchronous machines. This article aims to improve the system’s damping torque and minimize low-frequency oscillations by introducing a Virtual Power System Stabilizer (VPSS) into the power control loop. Building on the study of dynamic interactions between various control links of the MMC, this research establishes a reduced-order model (ROM) and a Phillips–Heffron state equation for the MMC-VSG single machine infinite bus system, using a hybrid modeling approach and a zero-pole truncation method. It also analyzes the mechanism of low-frequency oscillations in the MMC-VSG system through the damping torque method. The analysis reveals that the negative damping torque produced during the excitation voltage regulation process causes changes in the virtual power angle, which in turn increases the risk of low-frequency oscillation in the MMC-VSG. To address this issue, the article proposes an optimized control method for the MMC-VSG dual power loop architecture (power-angle/excitation) VPSS. This strategy compensates for the inadequate damping torque of a single loop VPSS and effectively suppresses low-frequency oscillations in the system.

Vehicle trajectory prediction based on cross-attention and multilevel spatio-temporal features

Accurately predicting vehicle trajectories is crucial for motion planning in autonomous driving. Some existing trajectory prediction models employ Long Short-Term Memory (LSTM) networks to encode trajectory information, but this approach may lead to information loss. Additionally, the sparsity of the grid representation may limit the model’s ability to extract vehicle interaction features. To address these issues, this paper proposes a vehicle trajectory prediction model based on cross-attention and multilevel spatio-temporal features. The proposed model incorporates a spatio-temporal feature extraction module designed to capture the dynamic evolution of vehicle states across both time and space. Furthermore, it employs a temporal cross-attention module that reuses hidden states to select spatio-temporal features closely related to the target vehicle’s historical state, thus compensating for the temporal information loss during the encoding process. Additionally, a spatial cross-attention module, informed by social context, is deployed to analyze the dynamic interactions among vehicles. This module filters spatio-temporal interaction features with a significant impact on the target vehicle’s trajectory. The model is trained and tested using the NGSIM dataset and the highD dataset. Compared with other models, the model presented in this paper shows higher prediction accuracy in long-term trajectory prediction.

Comparative Study of the Coastal Geomorphology of Kajirbhati Sand-Spit Using Google Earth Pro Images (2005, 2011, 2023) and Landsat Satellite Data (2009, 2016, 2023): An Approach Towards the Impact of the Casuarina Plantation

Coastal geomorphology undergoes constant transformation due to a combination of coastal and fluvial processes and human intervention. Remote sensing and GIS tools are invaluable in identifying and studying these changes. Due to the dynamic interaction between land and sea, the coastline requires careful monitoring to detect hotspots and understand the spatial and temporal impacts of climate change on the coastal environment. Remote sensing data offers a comprehensive means of studying coastal landform changes. In a recent study, the focus was to analyze the impact of the Casuarina plantation on the coastal geomorphology of Kajirbhati spit. This involved studying various depositional features such as sand bars, sand spits, dunes, and beaches. The study utilized Google Earth Pro images from 2005, 2011, and 2023 to digitize 13 classes each year, enabling the identification of changing geomorphic classes. These include agriculture, swash zones, dunes on sand spits, berm lines, Casuarina and coconut plantations, estuary, mangroves, mudflats, open land, sea, settlement, and vegetation. The results revealed dramatic changes in land use and land cover classes from 2005 to 2023. In the years from 2011 to 2023, the area of sandspit covered by Casuarina plants expanded rapidly. To analyze the changes, Landsat 5, 8, and 9 data were used to check the intensity of NDVI (Normalized Difference Vegetation Index) in 2009, 2016, and 2023. NDVI is a critical factor in this research. The mean NDVI values for 2009, 2016, and 2023 were -0.002, 0.02, and 0.04 respectively. The changes in higher NDVI values from 2009 to 2023 were -0.10, 0.27, and 0.28, while the lower values were -0.10, -0.10, and -0.07 for the same years. The correlation calculation between the mean NDVI values and the years indicates a strong positive correlation with an R-value of 0.99. Casuarina plants play a crucial role in protecting the coast from strong winds and dynamic sea waves. They help protect mudflats, mangroves, settlements, and estuary land use and cover classes along the coast of Kajirbhati.

Repurposing Antiviral Drugs as Potential Anti-EGFR Agents in NSCLC: A Structure-Based Screening and Molecular Dynamics Analysis.

One of the problems resulting from recurrent hyperactivated or mutant epidermal growth factor receptors (EGFR) in non-small cell lung cancer (NSCLC) is therapeutic resistance. Consequently, this leads to increased expressionof oncogenicproteins and reduces the efficacy of EGFR tyrosine kinase inhibitors (TKIs). This study assessed antiviral drug efficacy as potential anti-EGFR agentsfor NSCLC. We used structure-based virtual screening to evaluate 66 antiviral drugs thoroughly. The top 6 antiviral drugs exhibiting impressive binding energies (i.e. surpassing a threshold of -8.5 kcalmol-1) were identified. Subsequent bioactivity analysis and ADMET profiling were performed to select the most promising candidates, followed by a molecular dynamic simulation. Among the selected antiviral regimens, dolutegravir demonstrated the highest docking score (-9.8 kcalmol-1), followed by rilpivirine and ensitrelvir, surpassing other candidates and our reference EGFR TKI. Further molecular dynamics simulations revealed promising dynamic interactions of dolutegravir, ensitrelvir, and rilpivirine with the EGFR target as compared with afatinib. Our findings highlight the repositioning potential of antiviral drugs for anti-EGFR drug discovery, supported by their robust docking scores, ADMET profiles, dynamic interactions, and binding free energies. The results open up new avenues for advanced NSCLC therapy. Further in vitro investigations are warranted to evaluate their efficacy and safety.

Combinatorial Wnt signaling landscape during brachiopod anteroposterior patterning

BackgroundWnt signaling pathways play crucial roles in animal development. They establish embryonic axes, specify cell fates, and regulate tissue morphogenesis from the early embryo to organogenesis. It is becoming increasingly recognized that these distinct developmental outcomes depend upon dynamic interactions between multiple ligands, receptors, antagonists, and other pathway modulators, consolidating the view that a combinatorial “code” controls the output of Wnt signaling. However, due to the lack of comprehensive analyses of Wnt components in several animal groups, it remains unclear if specific combinations always give rise to specific outcomes, and if these combinatorial patterns are conserved throughout evolution.ResultsIn this work, we investigate the combinatorial expression of Wnt signaling components during the axial patterning of the brachiopod Terebratalia transversa. We find that T. transversa has a conserved repertoire of ligands, receptors, and antagonists. These genes are expressed throughout embryogenesis but undergo significant upregulation during axial elongation. At this stage, Frizzled domains occupy broad regions across the body while Wnt domains are narrower and distributed in partially overlapping patches; antagonists are mostly restricted to the anterior end. Based on their combinatorial expression, we identify a series of unique transcriptional subregions along the anteroposterior axis that coincide with the different morphological subdivisions of the brachiopod larval body. When comparing these data across the animal phylogeny, we find that the expression of Frizzled genes is relatively conserved, whereas the expression of Wnt genes is more variable.ConclusionsOur results suggest that the differential activation of Wnt signaling pathways may play a role in regionalizing the anteroposterior axis of brachiopod larvae. More generally, our analyses suggest that changes in the receptor context of Wnt ligands may act as a mechanism for the evolution and diversification of the metazoan body axis.

Imidazole derivative for corrosion protection: A comprehensive theoretical and experimental study on mild steel in acidic environments

The inhibition efficiency derivative imidazole, 2-mercapto-5,5-diphenyl-3,5-dihydro-4 H-imidazol-4-one (AM0), against corrosion in a hydrochloric acid (HCl) environment was studied. The research focused on the compound's ability to adsorb onto mild steel surfaces. Various experimental techniques, including potentiodynamic polarization (PDP), electrochemical frequency modulation (EFM), and impedance spectroscopy (EIS), were employed to analyze the inhibitory effects. Results showed that the effectiveness of AM0 increased with concentration, reaching an inhibitory efficiency of 95.1 %. Polarization studies revealed that the inhibitor displayed mixed-type behavior. The adsorption process was modeled using the Langmuir adsorption model. Surface characterization techniques such as scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDS), and X-ray photoelectron spectroscopy (XPS) were utilized to examine the inhibited corrosion surfaces. Theoretical calculations based on density functional theory (DFT) and density functional tight binding (DFTB) suggested that inhibitors with electron-accepting capabilities exhibited strong interactions with the iron surface, shedding light on specific bond formations that contribute to the stability and interaction dynamics at the molecular interface. This study provides valuable information on the corrosion inhibition potential of the new imidazole compound, offering important pointers for the development of effective corrosion inhibitors in acidic environments.

A Review on Molecular Mechanism of Plant Immunity against Fungal Pathogens

The molecular mechanisms of plant immunity, with a particular focus on how plants defend themselves against fungal pathogens. Plant immunity is a complex, multi-layered system involving pattern-triggered immunity (PTI) and effector-triggered immunity (ETI), which together form a robust defense against a wide array of pathogens. Advances in genomics and transcriptomics have significantly enhanced our understanding of these immune mechanisms by identifying key resistance (R) genes and uncovering the transcriptional networks that regulate immune responses. Proteomics and metabolomics further elucidate the functional aspects of immunity, revealing how proteins and metabolites are mobilized during pathogen attack. The advent of gene editing technologies, particularly CRISPR-Cas9, has opened new avenues for enhancing plant immunity by enabling precise modifications of genes associated with disease resistance. The ever-evolving nature of fungal pathogens, driven by genetic diversity and environmental changes, poses ongoing challenges. Emerging pathogens and the breakdown of existing resistance in crops underscore the need for durable resistance strategies, which can be achieved through the pyramiding of multiple R genes, susceptibility gene knockouts, and the harnessing of beneficial plant microbiomes. As climate change exacerbates the spread and virulence of fungal pathogens, developing climate-resilient crops that can withstand both abiotic stresses and pathogen pressures is becoming increasingly important. Future research should prioritize understanding the molecular dynamics of plant-pathogen interactions, leveraging new technologies for crop improvement, and fostering interdisciplinary collaboration to address these challenges. Ultimately, translating these scientific advances into practical applications will be crucial for ensuring global food security and sustainable agricultural systems in the face of mounting environmental and biological threats.

Intraday quantile coherence between oil and European sectors during the Russia-Ukraine war

ABSTRACT This study examines the interconnectedness between crude oil and European sectors during the Russia-Ukraine conflict. Using a quantile coherence approach, we investigate the intraday dynamics of market interactions at different quantiles and frequencies. The findings reveal that in the short-term, oil emerges as a robust hedge for 12 sectors in stable market conditions, transitioning to a weaker hedge during bullish and bearish market conditions. Furthermore, the long-term analysis shows a stronger coherence between oil and stock sector indices. The medium-term and long-term analyses reveal shifts in dependence structures, with oil acting as a safe haven in bullish markets for specific sectors. These findings provide valuable insights for investors and policymakers in managing risks amid geopolitical events, contributing to the existing literature on oil-European sector dynamics.

A fluorescence lifetime-based novel method for accurate lipid quantification of BODIPY vital-stained C. elegans

Lipid droplets (LDs) are organelles associated with lipid storage and energy metabolism; thus, their morphology and quantity are of significant research interest. While commercially available BODIPY dye effectively labels LDs in various cell types, it also labels lysosome-related organelles (LROs) in C. elegans, leading to non-specific LD quantification. Here, we report that the fluorescent signals of BODIPY exhibit distinct fluorescence lifetime patterns for LROs and LDs, which can be captured, visualized, and filtered by fluorescence lifetime imaging microscopy. Furthermore, we proposed and validated a method based on fluorescence lifetime that can improve the accuracy of fat storage quantification in BODIPY vital-staining worms, which holds broad applications, including rapid and accurate LD quantification in forward genetic screening. Additionally, our method enables observing dynamic LD-LRO interactions in living worms, a unique capability of BODIPY vital staining. Our findings highlight distinct BODIPY fluorescence lifetime characteristics of LDs and LROs, providing a valuable tool for future research on LDs, LROs, or their interactions.

Quantifying the impact of rail longitudinal level changes on dynamic load magnitudes through instrumented wheelset measurements

Track geometry significantly influences train-track dynamic interactions, primarily due to irregularities at the wheel-rail interface. These irregularities generate dynamic load excitations, leading to defects and damage. This study evaluates how track surface profile longitudinal level vertical changes affect vertical wheel-to-rail loads, quantified by the dynamic load factor ( ϕ ), due to the importance of ϕ in track design. A limitation of the existing studies is their focus on instrumented sections and numerical modellings without considering different track structures. This study conducted dynamic load measurements using two instrumented wheelsets (IWS) over a 340 km section operated by a North American Class 1 freight railway in the Canadian Prairies under various track structures and train speeds. Rail surface longitudinal level measurements were obtained as routine measurements through a track geometry car. The paper presents statistical distributions of rail longitudinal level across different track structures and evaluates two widely used and recently developed ϕ equations within the context of North American freight railways to quantify the impact of rail longitudinal level (i.e. profile) changes on dynamic load magnitudes. The study also evaluates regulated threshold values by considering observed trends in the measured data, which aims to quantify and compare these values with our current understanding.

Abnormal Dynamic Reconfiguration of Multilayer Temporal Networks in Patients with Bipolar Disorder.

Multilayer networks have been used to identify abnormal dynamic reconfiguration in bipolar disorder (BD). However, these studies ignore the differences in information interactions between adjacent layers when constructing multilayer networks, and the analysis of dynamic reconfiguration is not comprehensive enough; Methods: Resting-state functional magnetic resonance imaging data were collected from 46 BD patients and 54 normal controls. A multilayer temporal network was constructed for each subject, and inter-layer coupling of different nodes was considered using network similarity. The promiscuity, recruitment, and integration coefficients were calculated to quantify the different dynamic reconfigurations between the two groups; Results: The global inter-layer coupling, recruitment, and integration coefficients were significantly lower in BD patients. These results were further observed in the attention network and the limbic/paralimbic and subcortical network, reflecting reduced temporal stability, intra- and inter-subnetwork communication abilities in BD patients. The whole-brain promiscuity was increased in BD patients. The same results were observed in the somatosensory/motor and auditory network, reflecting more functional interactions; Conclusions: This study discovered abnormal dynamic interactions of BD from the perspective of dynamic reconfiguration, which can help to understand the pathological mechanisms of BD.

Exploring the synergy of logistics, finance, and technology on innovation

As global environmental challenges intensify, manufacturing firms face increasing pressure to innovate sustainably. Green innovation, characterized by the development of environmentally friendly products, processes, and technologies, has become essential for firms striving to remain competitive. This study aims to investigate the influence of key factors—green logistics, green finance, and green technology—on green innovation within manufacturing firms, while exploring the mediating role of green technology in these relationships. A multi-method approach was employed, combining partial least squares structural equation modeling, fuzzy-set qualitative comparative analysis, and necessity condition analysis. 447 responses were collected from manufacturing companies in Dhaka city, Bangladesh, using structured questionnaires. The analysis revealed that green logistics and green finance have a significant positive impact on green innovation, while the influence of the green work environment was found to be positive but statistically insignificant. Additionally, green technology was identified as a significant mediator in the relationships between green finance, green logistics, and green innovation. This study offers a comprehensive green innovation model while green technology is a mediator. Furthermore, this study advances the resource-based view theory by integrating green technology as a pivotal resource that enhances a firm's competitive advantage in sustainable markets. By adopting a multi-method approach, this research provides a rigorous examination of the research questions, offering a comprehensive understanding of the dynamic interactions between green finance, green logistics, and green technology in driving innovation. Thus, this research has thought provoking implications to prioritize investments in green finance, logistics, and technology, manufacturing firms can enhance their competitiveness, improve operational efficiency, and meet evolving environmental regulations and consumer preferences.

On-Grid Hybrid PV/WT Renewable Energy System for Green Hydrogen Production

The term "Power-to-X" (PtX) refers to a set of techniques for converting electrical energy into another form of energy, primarily focusing on hydrogen production. Produced hydrogen can be stored, distributed, and then used directly (to regenerate electricity, generate heat, or in transportation, steel, and chemical industries) or indirectly to produce ammonia, fertilizers, methane, methanol, e-fuels, and more. Thus, PtX is a mean of storing intermittent energy and a key contributor to the energy transition and decarbonization. In this article, we examine a grid-connected green hydrogen production system. This 1 MW renewable capacity system consists of a 300 kW wind turbine, a 700 kW photovoltaic field, and a 209 kW electrolyzer. In this system, any excess energy is integrated into the grid, enhancing overall energy sustainability. Conversely, when energy output is insufficient for the electrolyzer, the deficit is sourced from the grid, ensuring continuous and reliable operation. This dynamic interaction with the grid optimizes energy usage and reinforces the stability of the system. The results show an annual hydrogen production of about 16 tons, renewable energy production of approximately 1.9 GWh/year, a 20.85% capacity factor, a shortage of about 144.5 MWh, and an energy excess of about 824 MWh.

Caught in the Crossfire: Anti-Corporate Activism and Non-Market Strategies of Corporate Targets in the Creation of Emissions Controls

The paper explores a unique phenomenon in the context of the strategic interaction of activists and their corporate targets. We explore a unique phenomenon - how less targeted firms leverage activists-focal firm rivalry in the context of instituting emission controls in Japan. We find that less targeted firms employ social value-based strategies against market rivals by capitalizing on the opportunity structure created by the conflicts between activists and their primary targets in non-market environments.We contribute to the literature by developing a more fine-grained argument on how dynamic interactions between multiple players (activists, primary targets, and non-targets) can lead to a different path for movement activists to achieve their goals. We also draw attention to the proactive strategic actions taken by non-target firms when their market rivals are under attack by social activists. We add to the previous arguments by revealing social value-based strategies that can serve as an alternative for corporate targets to exert influence on non-market environments.

Investigation into geometric configurations and electronic properties of CeO2-supported gold clusters

A detailed understanding of the geometric structure and electronic properties of gold nanoparticles on the ceria surface is crucial for comprehending their unique catalytic activity. Using the first-principles method based on density functional theory, the adsorption of Aux (x = 1–4) clusters on the CeO2(111) surface was studied. It was discovered that the standing configurations of Au2 and Au3, as well as the tetrahedral structure of Au4, are the most stable adsorption structures. The stability of these configurations is jointly determined by the number and strength of Au-Au bonds, the Au-O bonding energy, and the interaction dynamics between the clusters and the substrate. The analysis of Bader charge, difference charge density and density of states suggested that lattice relaxation and electronic localization occur in the reduced Ce3+. The reduced amount and location of Ce3+ are significantly influenced by the position and charge transfer amount of Aux cluster. The adsorption of CO on Au4/CeO2(111) indicated that stronger Au-C bonding energy due to the hybridization of Au-5d and C-2p, thereby enhancing the catalytic activity for CO oxidation reactions.

Understanding tropical cyclone persistence over land: A case study of Cyclone Gulab

Abstract Tropical Cyclone (TC) Gulab originated in the Bay of Bengal during the post-monsoon season of 2021. Following an unusual westward trajectory, TC Gulab made landfall on the east coast of India, traversed central India, and reintensified over the Arabian Sea into TC Shaheen. This study employed an online Eulerian water vapor tracer (WVT) tool embedded within the Weather Research and Forecasting (WRF) model to investigate the role of land in terms of soil moisture and Land Use Land Cover (LULC) in persistance of TC Gulab over central India. We quantified the contributions of sub-regions and dominant LULC types within the Indian subcontinent to the precipitation associated with TC Gulab. Our findings indicate that evapotranspiration across the entire Indian subcontinent contributed approximately 30% to the post-landfall precipitation associated with TC Gulab. The highest contribution originated from the northwestern region, followed by the northeast. Croplands, the dominant LULC type, were the primary contributors, followed by forests. Despite changing the dominant land cover from cropland to forest, the low-pressure system persisted over land while altering the spatial patterns of precipitation. Sensitivity experiments demonstrated a linear decrease in precipitation originating from land with decreasing soil moisture (SM). Notably, there is a disproportionate decline in total precipitation with decreasing SM. Further analysis separating atmospheric vapor sources into land and ocean contributions using WVT revealed a compensatory mechanism. The contribution of oceanic vapor to atmospheric vapor over land increased when SM decreased due to increase in the latent heat over ocean. However, the total atmospheric vapor remained low, ultimately leading to a lower total precipitation. Although SM plays a role, our results highlight the importance of oceanic and atmospheric processes in determining TC persistence over land. This study offers valuable insights into the dynamics of land-atmosphere interactions during low-pressure systems of TCs.

Importance of Coping Strategies on Quality of Life in People with Multiple Sclerosis: A Systematic Review.

Multiple sclerosis (MS) is a neurodegenerative disorder of the central nervous system characterized by a variety of symptoms such as fatigue, spasticity, tremors, and cognitive disorders. Individuals with MS may employ different coping strategies to manage these symptoms, which in turn can significantly impact their quality of life (QoL). This review aims to analyze these coping strategies and their impact on QoL. Furthermore, it seeks to identify the key factors that influence the choice and effectiveness of these coping strategies, providing insights into which strategies are most beneficial for enhancing QoL in people with MS. Methods: Systematic searches were performed in Scopus, PubMed, Web of Science, and Scopus databases. This systematic review has been registered in OSF with the number DOI 10.17605/OSF.IO/QY37X. Results: A total of 1192 studies were identified. After reading the full text of the selected studies and applying predefined inclusion criteria, 19 studies were included based on their pertinence and relevance to the topic. The results revealed that emotional variables, demographic factors, personality traits, and family support significantly influence the choice of coping strategies used to manage the symptoms of MS. Problem-solving and task-oriented coping were prevalent among MS patients and associated with better QoL outcomes. Emotional-focused and avoidance strategies were generally linked to poorer QoL, though avoidance provided temporary relief in certain contexts. Social support, emotional health, and cognitive reframing were crucial in enhancing QoL. Conclusions: The findings underscore the importance of tailored psychoeducational and therapeutic interventions focusing on emotional health, social support, and adaptive coping strategies. These interventions can significantly improve the long-term outcomes for individuals with MS. Future research should explore the dynamic interactions between coping strategies and QoL over time, providing a comprehensive understanding of how to best support MS patients in managing their disease.