Rapid Changes Research Articles

TEXTILE MERCHANDISING IN THE FAST FASHION ERA: ADAPTING TO RAPID CHANGE IN CONSUMER DEMANDS

Rapid changes in consumer preferences, technology breakthroughs, and mounting sustainability concerns have all had an impact on the fast fashion sector. This study investigates how textile merchandising is changing in this fast-paced world, with a particular emphasis on how companies are adjusting to meet customer expectations while maintaining speed and cost-effectiveness. By examining how these characteristics affect merchandising tactics, the study hopes to shed light on how fast fashion retailers can effectively negotiate the challenges of contemporary retail. The main goal of this study is to find out how fast fashion companies can handle sustainability issues and quickly adapt to changing consumer preferences by optimizing their merchandising strategies. The goal of the study is to comprehend how consumer behavior, sustainability, and technology interact to shape textile marketing techniques. To find new trends and best practices, this study uses a qualitative methodology to analyze secondary data from document analysis and scholarly literature. According to key results, technology is essential for enabling more individualized and flexible merchandising strategies, which enables firms to react swiftly to changing consumer expectations. Companies must manage this issue because the fast fashion model's emphasis on speed and inexpensive production frequently clashes with environmental objectives. Additionally, inventory management and coordination across many sales platforms are made more difficult by the omnichannel retail environment. The dependence on secondary data, which might not adequately reflect the subtleties of current customer behavior or the internal tactics of certain brands, is one of its limitations. Nonetheless, the results have important ramifications for theory and practice. The study theoretically advances our knowledge of how technology, sustainability, and consumer behavior interact in fast fashion merchandising. Practically speaking, it offers fast fashion companies’ useful information to improve their tactics, especially in the areas of inventory control, sustainability, and technological integration. Businesses can improve their competitiveness and long-term viability in a market that is changing quickly by implementing more adaptable, customer-centric strategies.

Dynamic reorganization of multivesicular bodies and exosome production impacted by sonoporation

Naturally occurring cell-derived extracellular vesicles (EVs) have emerged as attractive nanocarriers for drug delivery. However, production of large quantities of EVs for clinical applications in a scalable manner remains a significant challenge. This study investigated at the single cell level how sonoporation, or membrane poration produced by ultrasound-induced microbubble cavitation, impacts EV production using mouse macrophage RAW 264.7 cells stably expressing CD63-GFP as a model system. Real-time fluorescence videomicroscopy detected rapid changes in CD63-GFP, a tetraspanin family member highly enriched in intraluminal vesicles tagged with GFP, to track changes in multivesicular bodies (MVBs), which are the cellular compartments where exosomes originate within the cells. Our results revealed distinct dynamic changes in CD63-GFP intensity and distribution in RAW 264.7 cells in terms of response time and duration depending on whether the cells were directly or indirectly impacted by sonoporation, suggesting reorganization of MVBs in response to direct and indirect mechanisms resulted from the mechanical impact of ultrasound pulse on the cells. Analysis of the supernatant from sonoporation-treated RAW 264.7 cells expressing CD63-GFP demonstrated a delayed and sustained increase in the production of CD63-GFP-positive EVs. These results show the robust and detailed effect of sonoporation and reveal insights into sonoporation-induced EV release useful for guiding the application of sonoporation to enhance large-scale EV production.

Development and validation of a questionnaire to measure educational agility: a psychometric assessment using exploratory factor analysis

BackgroundTo effectively navigate the growing complexities and rapid changes in today’s environment, universities must cultivate agility among their members. Over the past decade, students have encountered a variety of experiences related to E-Learning and the provision of educational services through electronic platforms. This study aimed to develop and validate a Questionnaire of Educational Agility (QEdu-Agility) to assess the capacity of educational institutions to adapt to these evolving demands.MethodThis survey research aimed to validate QEdu-Agility. The statistical sample consisted of 372 students from Shiraz University of Medical Sciences in Iran, who had completed at least one academic year online during the COVID-19 pandemic in 2022. Participants were selected using the Cochran formula. The initial questionnaire was based on three standard instruments related to organizational agility and adapted for educational contexts. After establishing face and content validity, the preliminary version was validated by a focus group of five educational experts, comprising 30 items across five dimensions: responsiveness, adequacy, flexibility, speed, and integrity, measured on a 5-point Likert scale. To confirm the construct validity, the questionnaire was randomly distributed to students via email. Data analysis was conducted using Exploratory Factor Analysis (EFA) with varimax rotation, employing SPSS 24 software.ResultsThe content validity was confirmed with Content Validity Ratio (CVR) = 0.847, Content Validity Index (CVI) = 0.877, and the reliability with internal consistency was confirmed with R = 0.944. The CVI sub-components for relevance, clarity, and simplicity were obtained as 0.867, 0.853, and 0.847, respectively. According to EFA, the sample adequacy was confirmed with Kaiser-Meyer-Olkin (KMO) index = 0.928 and significant Bartlett’s test (P < 0.001). The total variance explained of the QEdu-Agility was about 60%. The first component of responsiveness accounted for 38.79% of the variance, followed by adequacy (7.99%), flexibility (5.17%), speed (3.91%), and integrity (3.57%) in subsequent components.ConclusionThe findings of the construct validity indicated a good fit of the QEdu-Agility. Given that the concept of agility is highly contingent on the context, this tool could be retested for measuring educational agility in educational organizations, such as universities.

How climate change intensified storm Boris’ extreme rainfall, revealed by near-real-time storylines

Disentangling the impact of climate change on environmental extremes is of key importance for mitigation and adaptation. Here we present an automated system that unveils the climate change signal of the day in near-real-time, employing a set of innovative storyline simulations based on a coupled climate model. Its potential to complement probabilistic assessments is showcased for storm Boris, which brought record-breaking rainfall over Central and Eastern Europe in September 2024, leading to devastating floods. Our near-real-time storylines suggest that storm Boris deposited about 9% more rain due to human-induced warming. The area impacted by the same storm’s extreme rainfall (>100 mm) was 18% larger and would continue expanding in a future warmer climate. Results from our prototype storyline system are disseminated publicly via an online tool. The case of Storm Boris demonstrates the potential of near-real-time storylines for rapid evidence-based climate change communication.

Unequal Power Relations at the Center of Social Vulnerability to Climate Change: Empirical Insights from Coastal Bangladesh

ABSTRACT Climate change is a global phenomenon affecting millions of people. Low-income people and communities are particularly at risk because of limited capacities to cope with climate-related stresses. Differential access to social and economic resources determines the level of adaptive potential; thus, the variations in social vulnerability to climate change. This article explores how unequal power relations influence the level of vulnerability in rural agrarian Bangladesh. Using data from the coastal region, it specifically discusses ethnicity, religion, gender, and farm size as the sources and manifestations of power relations in Bangladeshi rural society. I argue that the deeply rooted institutions of power in the country shape access to important resources that might increase adaptive capacity and thus resilience in the context of rapid climate change.

Mechanisms of rapid plant community change from the Miocene Succor Creek flora, Oregon and Idaho (USA)

The fossil record of the U.S. Pacific Northwest preserves many Middle Miocene floras with potential for revealing long-term climate-vegetation dynamics during the Miocene Climatic Optimum. However, the possibility of strong, eccentricity-paced climate oscillations and concurrent, intense volcanism may obscure the signature of prevailing, long-term Miocene climate change. To test the hypothesis that volcanic disturbance drove Middle Miocene vegetation dynamics, high-resolution, stratigraphic pollen records and other paleobotanical data from nine localities of the Sucker Creek Formation were combined with sedimentological and geochemical evidence of disturbance within an updated chronostratigraphic framework based on new U-Pb zircon ages from tuffs. The new ages establish a refined, minimum temporal extent of the Sucker Creek Formation, ~15.8 to ~14.8 Ma, and greatly revise the local and regional chronostratigraphic correlations of its dispersed outcrop belt. Our paleoecological analysis at one ~15.52 Ma locality reveals two abrupt shifts in pollen spectra coinciding with the deposition of thick ash-flow tuffs, wherein vegetation dominated by Cupressaceae/Taxaceae, probably representing a Glyptostrobus oregonensis swamp, and upland conifers was supplanted by early-successional forests with abundant Alnus and Betula. Another ephemeral shift from Cupressaceae/Taxaceae swamp taxa in favor of upland conifers Pinus and Tsuga correlates with a shift from low-Ti shale to high-Ti claystone, suggesting a link between altered surface hydrology and vegetation. In total, three rapid vegetation shifts coincide with ash-flow tuffs and are attributed to volcanic disturbance. Longer-term variability between localities, spanning ~1 Myr of the Miocene Climatic Optimum, is chiefly attributed to eccentricity-paced climate change. Overall, Succor Creek plant associations changed frequently over ≤105 years timespans, reminiscent of Quaternary vegetation records. Succor Creek stratigraphic palynology suggests that numerous and extensive collection of stratigraphically controlled samples is necessary to understand broader vegetation trends through time.

Application Of Chatgpt in The Field of Preschool Education from The Perspective of Personalized Learning

With the rapid change in science and technology, ChatGPT has become a topic of concern in all walks of life, and ChatGPT's development in education has also received extensive attention. This paper explores the application of ChatGPT in the field of preschool education against the background of John Dewey's child-centered theory in educational practice. ChatGPT's education model is of great significance to the current way of children's education, which is conducive to further optimizing the comprehensive reform of the kindergarten curriculum. Through the conclusions, it is concluded that ChatGPT can better promote the innovation and progress of education in preschool education. Based on this, this paper puts forward the following suggestions: firstly, the new artificial intelligence should be applied in preschool education from many aspects. Secondly, the use of new artificial intelligence in home, school, and social education can better realize the reform and innovation of education. Finally, the use of new learning methods can promote the development of children's abilities and provide a more personalized learning experience.

Examining Immediate and Sustained Effects of Check-In/Check-Out in Finnish Elementary Schools

Check-in/Check-out (CICO) behavioral support has been implemented in Finnish School-Wide Positive Behavior Interventions and Support (SWPBIS) schools to cater to students who require personalized behavior support beyond the universal level. Previous studies have demonstrated the effectiveness of CICO as a behavioral support method. However, further research is needed to investigate its effectiveness in a larger sample and to analyze the timeline for behavioral change. This study focused on 51 elementary school students, assessing their behavior at baseline and during the CICO intervention phase using two data collection methods: the Daily Report Card (DRC) and the School Situation Questionnaire (SSQ). Nonlinear growth modeling was employed to examine the effects of the intervention. The results indicated that CICO yielded significant positive effects on behavior within 1 week of initiating support. After the outcomes stabilized, the behavior change remained stable beyond the first week of the intervention. These effects were detected in both the target behavior measured with DRC and the problem behavior measured with SSQ. These findings suggest that CICO interventions produce rapid and sustained changes in behavior. Further, the effects of CICO were observed in various settings within the school environment, indicating distal outcomes.

Theory of AI-driven scheduling (TAIS): a service-oriented scheduling framework by integrating theory of constraints and AI

This paper introduces the Theory of AI-driven scheduling (TAIS), an innovative framework designed to revolutionise service-oriented scheduling (In the context of this paper, ‘service-oriented’ refers to the design and execution of scheduling processes that are specifically tailored to meet the dynamic and varied needs of service-manufacturing industries. This approach emphasises adaptability, customer-centric scheduling, and the efficient allocation of resources to enhance product and service delivery.) by integrating the theory of constraints (TOC) (see APPENDIX I) with cutting-edge Artificial Intelligence (AI) technologies. TAIS extends the traditional five steps of TOC by introducing three additional layers to enhance adaptability, efficiency, and applicability in service-oriented environments. TAIS incorporates continuous monitoring and adjustment mechanisms across all five TOC steps to improve adaptability, ensuring real-time responsiveness to dynamic scheduling challenges. To enhance efficiency, TAIS integrates lifecycle management and governance into the core framework, which helps in the efficient allocation of resources throughout the scheduling process. Lastly, TAIS includes robust security and compliance measures to bolster applicability. By leveraging AI, TAIS offers a predictive, flexible, and scalable solution capable of addressing the complexities and rapid changes inherent in dynamic scheduling tasks and providing a significant leap forward in scheduling and operations management.

Cholinergic regulation of dendritic Ca2+ spikes controls firing mode of hippocampal CA3 pyramidal neurons

Active dendritic integrative mechanisms such as regenerative dendritic spikes enrich the information processing abilities of neurons and fundamentally contribute to behaviorally relevant computations. Dendritic Ca2+ spikes are generally thought to produce plateau-like dendritic depolarization and somatic complex spike burst (CSB) firing, which can initiate rapid changes in spatial coding properties of hippocampal pyramidal cells (PCs). However, here we reveal that a morpho-topographically distinguishable subpopulation of rat and mouse hippocampal CA3PCs exhibits compound apical dendritic Ca2+ spikes with unusually short duration that do not support the firing of sustained CSBs. These Ca2+ spikes are mediated by L-type Ca2+ channels and their time course is restricted by A- and M-type K+ channels. Cholinergic activation powerfully converts short Ca2+ spikes to long-duration forms, and facilitates and prolongs CSB firing. We propose that cholinergic neuromodulation controls the ability of a CA3PC subtype to generate sustained plateau potentials, providing a state-dependent dendritic mechanism for memory encoding and retrieval.

Analysis of economic crises at enterprises: from classical theories to innovative solutions

The article is devoted to a comprehensive analysis of economic crises at enterprises arising as a result of various internal and external factors that affect their stability and competitiveness. The author examines the polysemantic nature of the concept of «crisis», analyzing it in the context of various scientific disciplines and approaches. Special attention is paid to the dualistic approach to the crisis, where it is considered as a phenomenon that simultaneously carries threats and opportunities for development. The article provides a retrospective review of approaches to the study of crisis phenomena, starting from the cyclical approach, which interprets the crisis as a natural stage of the economic cycle, to modern system-synergistic methodologies, which consider the crisis as a prerequisite for self-organization and development of the enterprise. The conducted analysis of literary sources confirms the need to integrate various approaches for complex anti-crisis management at enterprises. The work also identifies unresolved aspects of the problem, including early diagnosis of crises, integration of anti-crisis tools, and the impact of digitalization on crisis processes. The article emphasizes the importance of flexible and adaptive diagnostic models capable of responding effectively to rapid changes in the business environment. The scientific novelty consists in proposing an action algorithm for diagnosing the crisis state of enterprises, based on the definition and analysis of key parameters that reflect the economic health of the business. The author emphasizes the need for a deep understanding of the specifics of each enterprise for successful anti-crisis management and the potential use of crisis phenomena to achieve new heights of development.The variety of interpretations of this term indicates its complexity and multifacetedness, which requires special attention to specify the meaning of the concept not only in the economic context, but also at the level of enterprises, underlines the relevance of this topic.

Pre-service teachers’ technological pedagogical and content knowledge (TPACK): their readiness for online instruction

ABSTRACT Rapid changes and greater complexities bring new difficulties and place new expectations on our educational system. Teacher education programs must adapt to these changes and train pre-service teachers in various learning modalities. This study determined the readiness of pre-service teachers to teach online based on their technological pedagogical and content knowledge (TPACK) when they are grouped based on their profile. Through proportional random sampling, 400 third-year pre-service teachers were surveyed using comparative research. No significant difference in the readiness of pre-service teachers to online instruction based on their TPACK when grouped according to their sex and specialization. However, it was found that the respondents when grouped according to their specialization were different in terms of their Technological Knowledge and Technological Content Knowledge. This study suggests that as the era of technological changes emerged, the abilities of preservice teachers must be highly targeted to cope with dramatic changes in the educational landscape.

Commentary on ‘the interplay of the innovation cycle, build time, lifetime, and deployment rate of new energy technologies: a case study of nuclear fusion energy’ - designing innovation strategies for rapid feasible technological change

Commentary on ‘the interplay of the innovation cycle, build time, lifetime, and deployment rate of new energy technologies: a case study of nuclear fusion energy’ - designing innovation strategies for rapid feasible technological change

Evolution and morphodynamics of the large braided river Brahmaputra during the last four decades of the Quaternary epoch: a spatio-temporal assessment using geoinformatics

ABSTRACT Spatio-temporal assessment of the evolution and morphodynamics of the Brahmaputra River (BR) can contribute significantly in mitigating challenges offered by rapid urbanisation and climate change. The present remote sensing and geographic information system (RS and GIS) based analysis of the BR revealed an increased Braiding Intensity (BI) from 1976 to 2000, which declined in 2010, and re-emerged in 2020. The average maximum width of the river has generally widened over time and sandbar distribution has exhibited fluctuations. The overall active channel area increased by 1.5 times, and the sandbar area expanded by 1.2 times between 1976 and 2020. The interplay between braiding intensity and width reveals a positive relationship. The sandbar-water ratio reveals a significant prevalence of sandbars in the Brahmaputra River. Furthermore, the study highlights changes in the Bar Development Index (BDI), showing a significant increase in micro-bars and meso-bars but a decrease in macro-bars. With the approach of change detection, key factors observed within the river driving the changes are erosion, channel bifurcations, sandbar formation due to sediment deposition, and sandbar loss due to shifts in channel course. These characteristics are potentially influenced by high water and sediment influx, climate change, and anthropological activities.

A Wushu Leg Gesture Recognition Algorithm Based on Random Forest and Bone Feature Extraction (RF-SFE)

Addressing the challenges of complex movement trajectories and rapid action changes in martial arts performances, this study introduces a novel posture recognition algorithm based on Random Forest and Skeletal Feature Extraction (RF-SFE) for martial arts leg movements. Unlike traditional posture recognition methods that struggle with accuracy, RF-SFE aims to provide intelligent analysis of training postures to assist practitioners in efficient training. The algorithm initially employs advanced skeletal feature extraction techniques to identify and articulate the relative positions and movements specific to martial arts. These extracted spatial features enhance the flexibility in modeling the unique dynamics of martial arts. Subsequently, Random Forest classification is utilized to categorize different leg movements, leveraging its strength in handling high-dimensional data and providing robust classification. Comparative experiments on diverse martial arts posture datasets demonstrate a significant improvement in recognition rates over baseline methods. This validates the effectiveness of the RF-SFE method in recognizing martial arts postures, offering scientific guidance for practitioners’ training regimens.

Evolving road networks and urban landscape transformation in the Himalayan foothills, India.

The amalgamation of Himalayan and Indo-Burmese biodiversity has made the state of Manipur, India, a unique ecosystem. In addition, the region is a strategic place for the country to establish an economic corridor to Southeast Asia. In recent times, the region has witnessed tremendous infrastructural/road development. Subsequently, forest fragmentation related to urbanization and road expansion has emerged in the Himalayan foothills. The development of roads brought rapid changes in land use and land cover (LULC) and thus subsequent environmental degradation. The current study attempts to understand how the development of road networks has impacted the natural cover in Manipur, India. A spatio-temporal analysis was performed to assess the relationship between the development of road networks and LULC changes using the Landsat satellite images over a decade (2012-2022). The results showed significant changes in the area coverage of LULC categories such as agricultural land, built-up areas, forest, and water bodies with the increase in road density. To have a holistic view, the study area was segregated into three functional zones based on their urban land use pattern, i.e., urban center, peri-urban, and urban peripheral fringes. Urban sprawl in the urban center has led to the rapid conversion of forested lands into built-up areas and agricultural lands in the peri-urban and urban peripheral fringes, respectively. The decline of forest areas to urbanization in peri-urban and urban peripheral fringes calls for conservation and restoration initiatives. The study also emphasizes how different stakeholders can be involved and empowered to strengthen public-private partnerships for conservation and restoration in such sensitive ecosystems. Urban planners and developers should be critical in making informed decisions through understanding ecological concerns in tandem with infrastructural development.

Machine learning models for river flow forecasting in small catchments.

In consideration of ongoing climate changes, it has been necessary to provide new tools capable of mitigating hydrogeological risks. These effects will be more marked in small catchments, where the geological and environmental contexts do not require long warning times to implement risk mitigation measures. In this context, deep learning models can be an effective tool for local authorities to have solid forecasts of outflows and to make correct choices during the alarm phase. In this study, we investigate the use of deep learning models able to forecast hydrometric height in very fast hydrographic basins. The errors of the models are very small and about a few centimetres, with several forecasting hours. The models allow a prediction of extreme events with also 4-6h (RMSE of about 10-30cm, with a forecasting time of 6h) in hydrographic basins characterized by rapid changes in the river flow rates. However, to reduce the uncertainties of the predictions with the increase in forecasting time, the system performs better when using a machine learning model able to provide a confidence interval of the prediction based on the last observed river flow rate. By testing models based on different input datasets, the results indicate that a combination of models can provide a set of predictions allowing for a more comprehensive description of the possible future evolutions of river flows. Once the deep learning models have been trained, their application is purely objective and very rapid, permitting the development of simple software that can be used even by lower skilled individuals.

Embryo movement is required for limb tendon maturation

IntroductionFollowing early cell specification and tenocyte differentiation at the sites of future tendons, very little is known about how tendon maturation into robust load-bearing tissue is regulated. Between embryonic day (E)16 and E18 in the chick, there is a rapid change in mechanical properties which is dependent on normal embryo movement. However, the tissue, cellular and molecular changes that contribute to this transition are not well defined.MethodsHere we profiled aspects of late tendon development (collagen fibre alignment, cell organisation and Yap pathway activity), describing changes that coincide with tissue maturation. We compared effects of rigid (constant static loading) and flaccid (no loading) immobilisation to gain insight into developmental steps influenced by mechanical cues.ResultsWe show that YAP signalling is active and responsive to movement in late tendon. Collagen fibre alignment increased over time and under static loading. Cells organise into end-to-end stacked columns with increased distance between adjacent columns, where collagen fibres are deposited; this organisation was lost following both types of immobilisation.DiscussionWe conclude that specific aspects of tendon maturation require controlled levels of dynamic muscle-generated stimulation. Such a developmental approach to understanding how tendons are constructed will inform future work to engineer improved tensile load-bearing tissues.

Accelerating Numerical Simulations of CO2 Geological Storage in Deep Saline Aquifers via Machine-Learning-Driven Grid Block Classification

The accurate prediction of pressure and saturation distribution during the simulation of CO2 injection into saline aquifers is essential for the successful implementation of carbon sequestration projects. Traditional numerical simulations, while reliable, are computationally expensive. Machine learning (ML) has emerged as a promising tool to accelerate these simulations; however, challenges remain in effectively capturing complex reservoir dynamics, particularly in regions experiencing rapid changes in pressure and saturation. This article addresses the challenges by introducing a fully automated, data-driven ML classifier that distinguishes between regions of fast and slow variation within the reservoir. Firstly, we demonstrate the variability in pressure across different reservoir grid blocks using a simple brine injection and production scenario, highlighting the limitations of conventional acceleration approaches. Subsequently, the proposed methodology leverages ML proxies to rapidly and accurately predict the behavior of slow-varying regions in CO2 injection simulations, while traditional iterative methods are reserved for fast-varying areas. The results show that this hybrid approach significantly reduces the computational load without compromising on accuracy. This provides a more efficient and scalable solution for modeling CO2 storage in saline aquifers.

Dynamic fractal organizations—A boundaries based‐view of knowledge

AbstractCollective phronesis is the collection of the best‐distributed phronesis of humans and is also integrated phronesis for all management that combines the collective wisdom of individuals within and even between organizations. In a good organization, rather than only certain heroes with phronesis creating new knowledge, phronesis is organized to realize innovation by bringing together the high‐quality wisdom and practical power of various practitioners at all levels of the organization, as well as in its customers and partners. This makes it possible to build dynamic fractal organizations – tough collectives that can respond creatively and with agility in real‐time, no matter what occurs, including rapid changes in the environment. However, little is known from previous studies regarding the formation mechanisms of collective phronesis and dynamic fractal organizations. In this paper, we present a new theoretical model of the formation mechanism of collective phronesis, and dynamic fractal organizations based on inductive research through field surveys and in‐depth case studies, expanding on the concept of boundaries knowledge, which has been explored in existing research.