Dominant Trend Research Articles

Integrating Multimodal and Generative AI in Design Research: Enhancing Ethnographic Methods with Data-Driven Analysis

This research examines the application of Multimodal and Generative AI in analyzing interior design trends within the South Korean market. The objective is to enhance traditional ethnographic research methods with AI's quantitative capabilities, offering a more comprehensive understanding of design preferences. This methodology uses AI tools to systematically analyze and categorize design elements from a large dataset of interior design images sourced from a relevant online platform. This process involves extracting key visual trends and patterns using AI-driven semantic analysis and clustering techniques. The study identifies and classifies four dominant design trends, providing a structured overview of current market preferences. By integrating AI into design trend analysis, the study demonstrates a novel approach to understanding consumer preferences, potentially influencing future design decisions. This use of AI in design research broadens the scope of traditional ethnographic studies in design and provides practical insights for designers and industry practitioners, suggesting a shift towards more data-driven design practice.

Lithostratigraphy and Sedimentation Models of TMG-C4 Well Offshore Eastern Niger Delta

Analysis was carried out in TMG-C4 well by integrating well logs data that revealed three depositional sequences within the Agbada Formation of about 400ft thick. Three systems tracts identified include highstand systems tract, transgressive systems tract and lowstand systems tracts. The highstand systems tract is majorly stacked regressive shoreface sands that occurred in two parasequence sets, whereas the transgressive systems tract is a transgressive unit with both source rock and sealing potentials. The lowstand systems tract shows a boxcar log motif and is identified to be probably channel or barrier bar sand. Major shale units (maximum flooding surfaces) with regional significance mapped are designated MFS. This division is relevant to identifying genetic depositional units. Three genetic sequences occurred in the well. The transgressive shales represent interruptions in the overall regressive sequence that is related to sea-level rise. Three of these shales have been mapped and two of them correspond to the eleven genetic megasequences that occur delta wide. A predominantly marine and deltaic sequences strongly influenced by clastic output from the continent is inferred from the well logs. Paleo water depth is interpreted to fluctuate considerably and deposition occurred within a variety of littoral and neritic environments ranging from nearshore barrier sand complexes to fully marine outer shelf mudstones. The sediments are rapidly deposited within the shallow marine realm and reworked into longitudinal bars by wave action, strong longshore drift and tidal effects. The dominant depositional trend observed in the well shows progradation

Different Typologies of Multicultural Education in Caldecott Medal Books

The Caldecott Medal is renowned for honoring exceptional children’s literature, with a significant emphasis on multicultural education. These celebrated books play a pivotal role in early multicultural education, influencing children’s understanding of cultural diversity and aiding in language development. This research analyzes 25 multicultural Caldecott Medal recipients from 1938 to 2023, categorizing them according to six multicultural education philosophies: assimilation, amalgamation, pluralism, cross-cultural competence, critical awareness, and social action. The study also identifies dominant trends of these philosophies over time. Key findings are as follows: 1) Pluralism is the most prevalent typology, consistently represented across various decades, even during eras when assimilation and amalgamation were predominant; 2) A comparative analysis of the 20th and 21st centuries indicates a notable shift in multicultural education philosophies, moving from pluralism towards social action. This shift reflects a contemporary focus on proactive measures for societal change, going beyond mere recognition of cultural diversity. This study implies that a detailed understanding of the multicultural aspects of Caldecott Medal-winning books based on their embedded philosophies can significantly enhance their effective utilization in both multicultural and language education settings.

Navigating the Landscape of Telemedicine Research: A Topic Modeling Approach for the Present and Future.

Introduction: Telemedicine, which is the provision of remote clinical services via telecommunication technology, has undergone an upsurge since the COVID-19 pandemic. To capture this paradigm, this study surveyed telemedicine literature, including postpandemic publications, to identify dominant research themes and temporal trends and suggest directions for future research. Methods: A corpus of 56,445 telemedicine studies is sourced from PubMed. Latent Dirichlet allocation (LDA) topic modeling performed using the Konstanz Information Miner platform. The textual data for topic modeling were processed by following standard procedures for natural language processing. Moreover, the term frequency-inverse document frequency approach was used to capture the importance of words within the corpus. We assessed perplexity, coherence, and the elbow method to determine the optimal number of topics for modeling. Results: The findings confirm the surge in telemedicine research after 2020, signifying its prominence. LDA topic modeling reveals seven distinct research themes, with the most prominent topic being "patient satisfaction" (21.38%) followed by "perspectives and challenges" (17.95%), and "smartphone apps" (14.32%). Furthermore, the results demonstrate a noticeable shift in topics from screening to therapeutic applications of telemedicine. Conclusions: This study serves as a guide for a broad range of telemedicine research topics. This synthesis of themes reflects the commitment of scholars to address the changing dynamics and health care needs, such as the COVID-19 pandemic, aging in place, smartphone usage, and technological advancement. The analysis also reveals flexible research responses to policy and contextual shifts, highlighting the collective drive to broaden the application of telemedicine in community health care.

Spatial heterogeneity among different-sized port communities in directed-weighted global liner shipping network

Global liner shipping network (GLSN) serves as the backbone of international commerce. In the context of the COVID-19 pandemic and regional integration, regionalization has become one of the dominant trends of the GLSN's structure. This study detected 27 practical relevant port communities within the directed-weighted GLSN using the Infomap algorithm. Based on the community structure of the GLSN, we identified the provincial, gateway, and connector hubs, considering the balance and intensity of the inbound and outbound shipping routes. To highlight the smaller communities obtained in this study, those practical relevant port communities are further differentiated into 7 large and 20 small port communities. The spatial heterogeneity among different-sized port communities is investigated regarding geographical distribution, topological properties, functional characteristics, etc. The large port community is typically formed in major trading regions with well-developed hub-and-spoke networks. They are the principal market in which most liner operators participate in it. Some small port communities lying along the main lane of seaborne container trades also play pivotal roles in the GLSN with many liner companies involved. While other small port communities located peripherally only connect to a few surrounding port communities. The spatial heterogeneity among different-sized port communities is mainly caused by the unbalanced distribution of seaborne container trades. These findings offer new insights into the community structure and its spatial heterogeneity within the GLSN, which can provide stakeholders with practical implications.

Suitability Analysis of Drinking Water from The Springs of Deumai Watershed Ilam, Nepal

Spring is one of the major sources of drinking water in hilly and Himalayan region. The overall purpose of this study was to analyse the suitability of drinking water by studying the physicochemical properties. Springs of Deumai watershed Ilam, Nepal was investigated for water samples and the physicochemical parameters studied were TDS, pH, temperature, total hardness, alkalinity, total iron and major ion concentrations (Na+, K+, Mg2+, Ca2+, Cl–, SO42–, NO­3–) to describe the water’s chemical characteristics. The physical parameters were determined using pH meter, laboratory thermometer etc. The determination of concentration of chemical parameters was performed by using spectrophotometric method, flame photometric method and titration method. The average pH was found 7.47 and average temperature was found to be 19.4ºC. The dominance trend for major cations was Ca2+ > Na+ > Mg2+ > K+ > Fe and for anions was HCO3– > Cl– > NO3– > SO42–. All the values obtain were within the range specified by WHO and NDWQS guidelines of drinking water. According to the findings and comparison with the guidelines of drinking water given by World Health Organization (WHO) and National Drinking Water Quality Standard (NDWQS), the water quality for drinking water was found within the standards set by them.

Reforming Social Protection under Ideological Influences and Preferences. Social Protection Between Austerity and Other Reforms - The Case of North Macedonia

This research provides an analysis of reforms in the transition period with a special focus on the last decade regarding the social protection system as a crucial social policy domain in North Macedonia. From a methodological point of view, the research is based on a literature review and quantitative methods. It provides empirical evidence in the form of a survey conducted with various interest groups and political parties nationwide. The empirical results in the form of perceptions show a tendency of interest groups and political parties preferring social-democratic ideological values on issues such as social protection financing, social services delivery and the central role of the state in welfare provision. On the other hand, based on the literature review and policy analyses, there is evidence of a tendency of neo-liberalizing social policy in the country, in which principles of conditionality and eligibility, cuts in benefits, marketization of social services, etc., have become dominant trends in the last decade, thus transforming the social protection system in essence. Therefore, two questions should be asked: What kind of social protection system do we have? What kind of social protection do we prefer ideologically?

Discovery Learning Research in Mathematics Learning (1968-2023): A Bibliometric Review

The aim of this research is to identify research developments related to Discovery Learning in mathematics learning. This research uses a bibliometric analysis method by collecting data from the Scopus database. The data is then saved in two formats, namely CSV and RIS. Data in CSV format was analyzed using VOSviewer, while data in RIS format was analyzed using Harzing's Publish or Perish software. This research refers to 72 research sources regarding discovery learning in mathematics learning from 1968 to 2023. The research results show that the number of publications related to discovery learning in mathematics learning continues to increase every year. Publications in 2012 had more than 130 citations, this number exceeds publications in other years. The majority of these publications were found in Q2 category journals, with a total of 28 publications. The focus of this research covers three main areas: 1) learning outcomes, learning environments, and the role of universities; 2) technology and STEM (Science, Technology, Engineering, and Mathematics); 3) problems in teaching mathematics. New themes that emerge in research regarding discovery learning in mathematics learning include STEM, communication, self-confidence, learning activities, creativity, critical thinking, and efficacy. However, the term "Discovery Learning" is not yet directly connected to new concepts such as critical thinking and learning methods. This research provides in-depth insight into the development of Discovery Learning in the context of mathematics learning, as well as a better understanding of the dominant research focus and current trends in this field.

Investigation of iron ore potential in north-central Nigeria, using high-resolution aeromagnetic dataset and remote sensing approach

The instability of fuel prices in the international market has adversely affected the economy of Nigeria, which is a developing country that solely relies on crude oil. This has led the country to consider diversifying its economy into mineral resources. The consideration of iron ore as an important mineral for global infrastructure, steel production, and wealth creation has prompted this study to consider its potential within north-central Nigeria. Additionally, no geophysical reports considering the regional distribution of iron ore potential in both the Basement Complex and the sedimentary basins within north-central Nigeria have been previously carried out. This study employs an analytical hierarchy process (AHP) and weighted overlay to integrate the analyses of the high-resolution aeromagnetic data set (HRAMD) and Landsat 8 OLI/TIRS to assess the iron ore potential of the different geological terrain in north-central Nigeria. The ferrous mineral band ratio technique was adopted in processing the Landsat data, and several signal enhancement techniques were performed on the HRAMD, including the first vertical derivative (1VD), analytical signal, center for exploration targeting (CET) grid analysis, Euler deconvolution, and radially averaged power spectrum (RAPS). The shallowest magnetic sources and the high amplitude zones were delineated, and the dominant structural trend of the area was revealed to be WNW-ESE and NE-SW, and both orientations appeared to be favorable for mineralization. The apparent depth estimates of shallow and deep-seated magnetic structures obtained from Euler deconvolution ranged from 127.65 to 3540.64 m, whereas RAPS delineated a range of 285–3710 m. The analytical signal (AS) categorized the magnetism of the area into low, intermediate, and high magnetic zones. The higher magnetic zones were considered to be favorable for mineralization. The ferrous mineral ratio map reveals areas of higher reflectance, which depict zones of iron ore potential. The iron ore potential map was validated using known iron ore mines and deposits, which showed a perfect correlation, and new sites of probable iron ore mineralization within north-central Nigeria were revealed. This article will serve as a guide for stakeholders in the exploration of iron ore deposits.

Review of discrete fracture network characterization for geothermal energy extraction

Geothermal reservoirs are highly anisotropic and heterogeneous, and thus require a variety of structural geology, geomechanical, remote sensing, geophysical and hydraulic techniques to inform Discrete Fracture Network flow models. Following the Paris Agreement on reduction of carbon emissions, such reservoirs have received more attention and new techniques that support Discrete Fracture Network models were developed. A comprehensive review is therefore needed to merge innovative and traditional technical approaches into a coherent framework to enhance the extraction of geothermal energy from the deep subsurface. Traditionally, statistics extracted from structural scanlines and unmanned aerial vehicle surveys on analogues represent optimum ways to constrain the length of joints, bedding planes, and faults, thereby generating a model of the network of fractures. Combining borehole images with seismic attributes has also proven to be an excellent approach that supports the stochastic generation of Discrete Fracture Network models by detecting the orientation, density, and dominant trends of the fractures in the reservoirs. However, to move forward to flow modelling, computation of transmissivities from pumping tests, and the determination of hydraulically active fractures allow the computation of the hydraulic aperture in permeable sedimentary rocks. The latter parameter is fundamental to simulating flow in a network of discrete fractures. The mechanical aperture can also be estimated based on the characterization of geomechanical parameters (Poisson’s ratio, and Young’s modulus) in Hot Dry Rocks of igneous-metamorphic origin. Compared with previous review studies, this paper will be the first to describe all the geological and hydro-geophysical techniques that inform Discrete Fracture Network development in geothermal frameworks. We therefore envisage that this paper represents a useful and holistic guide for future projects on preparing DFN models.

Coastline changes under natural and anthropogenic drivers in a macro-tidal estuary between 2000-2020

Coastline changes in estuarine areas can result from a combination of natural processes such as erosion, sedimentation, and sea-level rise, as well as human activities, including urbanization and infrastructure development. These changes have the potential to affect the local environment, including submarine groundwater discharge, wetlands, and navigation routes. The Yalu River Estuary (YRE), situated on the border between China and North Korea, has been experiencing significant changes in its coastline over recent years. This study aims to investigate the coastline dynamics in the YRE from 2000 to 2020. The study employs Landsat 5/7/8 satellite data and proposes a modified Normalized Difference Water Index (NDWI) to accurately delineate the coast boundary, particularly in areas with extensive tidal flats like the YRE. The research findings indicate that from 2010 to 2020, significant changes occurred in the YRE shoreline, with erosion being the dominant trend. Human activities and alternations in hydrological conditions are important factors affecting the YRE coastline changes, contributing to the formation of distinctive spatiotemporal patterns. An extreme flooding event in the year 2010 also altered the inner estuarine coastline in the YRE, indicating the impact of strong natural drivers. Findings from this study provide a comprehensive understanding of the evolving coastal environment, considering natural and anthropogenic drivers, and highlight the importance of continuous monitoring in a region of ecological and geopolitical significance.

Personal characteristics of predisposition to destructive behavior

Aim. To identify personal characteristics determining the subject’s destructive behavior.Material and methods. Students from Stavropol State Medical University and North-Caucasus Federal University (n=609) took part in the study. The following diagnostic methods were used: a tendency to abnormal behavior (A. N. Orel), a meaning-life orientation test (D. A. Leontyev), a self-attitude test (S. R. Panteleev), a self-organization of activity questionnaire (E. Yu. Mandrikova).Results. We established that the sample corresponds to the characteristics of age-psychological and socio-professional development. The greatest severity by type of deviant behavior was found among respondents who are prone to overcoming norms and rules, and among those who have a reduced tendency to control emotional reactions. The least pronounced were tendencies to delinquent and addictive behavior, the tendency to aggression and violence. The dominant trends in this context are students’ understanding of the emotional richness of their ives, and the average psychological portrait of the respondent reflects their focus on themselves when implementing life’s tasks. On average, students are open to change, accept and value themselves, focus on their own strengths when planning and implementing future activities. They are focused on the present, understand the need to define the goals in life and activity. The study of individual parameters of personal characteristics and the severity of destructive behavior types made it possible to describe models of the relationship between these phenomena.Conclusion. The study showed that the current situation in the development of society is accompanied by risk factors that cause states of emotional stress and maladaptation, which has a negative impact on mental health and behavior. Diagnosis of personal characteristics and the severity of destructive behavior types in students made it possible to describe models of the relationship between these phenomena through regression analysis. A reflexive analysis of the results obtained made it possible to reveal an invariant part of personal characteristics in models of destructive behavior and the presence of certain personal characteristics that can manifest themselves in the variable part of a model of destructive behavior.

Transformation of the institutional code of economic development of industrialized regions in the context of scientific and technological approach

Aim. To develop a methodological approach to the transformation of the institutional code of economic development of an industrial region, which consists in the introduction of a new institute to stimulate scientific and technological development.Objectives. To reveal the peculiarities of the economic development agency as a source of transformation of the region’s institutional code; to propose schemes of transformation of the institutional code of economic development of the industrial region taking into account the assessment of the level of consistency of the trajectories of its scientific-technological and socioeconomic development; to determine the functions of the economic development agency ensuring the transformation of the Sverdlovsk region’s institutional code.Methods. Modified Frobenius norms are applied, which allow to design trajectories of scientific-technological and socio-economic development, reflecting the dominant trends of changes in the regions, and to determine the degree of consistency of these trajectories.Results. The article reflects the approbation of the author’s methodological approach on the example of the Sverdlovsk Oblast. As a result, a partial consistency of the trajectories of scientific and technological and socio-economic development of the Sverdlovsk region in the time interval 2012–2018 is revealed. Recommendations on strengthening the functions of the Economic Development Agency in the context of its participation in the implementation of the territorial projects “Ural Technopolis” and “Ural Engineering School” have been developed.Conclusions. Transformation of the institutional code of industrial regions is possible in the context of creating economic development agencies that create conditions for the growth of scientific and technological initiatives of economic transformation on the ground, ensuring the growth of consistency of development trajectories of territories as a whole.

PREDICTING THE DEVELOPMENT OF THE TECHNOLOGICAL BASIS FOR THE WARS OF THE FUTURE

Technological progress in the field of military technology is developing rapidly, requiring constant work on the development of new systems and strategies. The article demonstrates that the growing role of artificial intelligence and autonomous systems is defining a new level of efficiency and complexity in military operations. The article assesses the use of biotechnology in the defence sector, which defines a new level of strategic importance for the development and maintenance of military power. Space, hypersonic and quantum technologies will be considered, as well as aspects related to the use of 3D printing in a military context. The possibility of using new materials that can be produced using methods from nanotechnology or synthetic biology will be assessed. The benefits of using “green” hydrogen in the military industry and the challenges of implementing this technology are presented. The concept of digital contact tracking technology is explained, and strategic and tactical applications of hyper-precision positioning technology are presented. The results of the study show that the level of protection and security of future citizens is directly related to the ability to predict dominant technologies and technological trends, to assess their impact on the future and, on this basis, to develop a strategy for the transformation of new technologies.

Sequence-Structure Based Comparison of Structurally Homologous Thermophilic and Mesophilic Polyethylene Terephthalate (PET) Hydrolases

Protein structure has a direct impact on thermostability. Deviations in the primary sequence can affect structural changes, leading to alterations in thermostability properties. However, the molecular basis of protein thermostability is unspecified; thus, elucidation of key factors that role particular protein thermostability is required when engineering proteins to be thermostable. To address this challenge, the amino acid composition, hydrophobicity/hydrophilicity ratio, cysteine bridges, and intrinsic features of two structurally homologous but different thermostability, poly(ethylene terephthalate) hydrolase (PETase) were compared. According to the findings, thermostable and thermolabile PETases have similar folds, compactness, and disulfide bridges. Interestingly, an abundance gap of aromaticity, hydrophobic cluster area, polar amino acid and hydrogen bond network compositions demonstrated dominant trends of variations for both PET hydrolases, indicating a pivotal role of these features in the thermostability of PET hydrolase. Furthermore, increased hydrophobic amino acid frequency in the inner surface of thermostable proteins contributed significantly to thermostability by forming more internal hydrophobic interactions and a less hydrophobic patch. There are no consistent trends in insertions and deletions between both PETases. Taken together, these observations demonstrate that hydrophobicity and hydrogen bond networks are essential factors in thermostability of thermostable PETase.

Dynamic Analysis of the EU Countries Sustainability: Methods, Models, and Case Study

The agenda for sustainable development actualizes sustainability analysis of countries’ social, ecological, and economic conditions, as well as the necessity of designing practical recommendations to realize the sustainable development goals (SDGs). Sustainability analysis is a part of decision making and policy development in a broad environmental, economic, and social context. That is why this analysis goes beyond simple technical assessment. In order to make sustainability a target variable in development strategies, it is necessary to use special methods combining mathematical tools and managerial content. The paper systematizes modern mathematical methods for assessing economic sustainability and proposes a methodology for the integrated assessment of the social, economic, and environmental sustainability of countries, which were tested on data from 24 EU countries over 12 periods. The case study results derived from spatial and temporal samples are consistent with the currently observed processes in the EU. The content basis is the UN concept of sustainable development, the instrumental basis is multivariate comparisons, the Mahalanobis distances method, the correlation and regression analysis, analysis of variance, time series analysis, and trends analysis. Composite indices of social, economic, and environmental sustainability of the EU countries, each of them including five indicators, were developed in this study; the levels of social, economic, and environmental sustainability of EU countries were determined, as well as individual instability indicators. Mahalanobis distances and relative and absolute sustainability indicators were calculated and determined. Cluster analysis of the EU countries by levels of social, economic, and environmental instability and Mahalanobis distances, the diagnosis of the current situation and dominant trends were carried out for testing the hypothesis that there are positive relations between the instability of development and Mahalanobis distances. Hypotheses about the relationship between instability and the level of country development, reflected in the values of socio-economic and environmental indicators, and whether countries with good values of social, environmental, and economic indicators are the most sustainable, were investigated.

Young Females Appearance Anxiety in the Self-presentation of the Social Media Platform Xiaohongshu

This paper aims to investigate how self-presentation on contemporary social media platforms propagates young females appearance anxiety, and takes Xiaohongshu, a social media platform currently very popular among young Chinese females, as an example. This study conducted an open-ended questionnaire survey with 40 young women aged 18-30 years old through qualitative analytical research methods, and further conducted one-on-one structured in-depth interviews with representative KOLs and KOC users on the Xiaohongshu platform. Their responses focused on the strategies for presenting themselves on social media platforms, platform interventions, and social aesthetic convergence influences. The findings demonstrate that self-presentation in social media exacerbates contemporary young female appearance anxiety inextricably linked to individual, platform and social factors. This effect is intensified through the platforms adverse value propaganda and influencer marketing interventions, the individuals reshaping of self-presentation based on socially comparative ideologies that conform to dominant aesthetic trends, and the relatively convergent and deeply ingrained aesthetic trends that prevail in contemporary societies.

Performance Evaluation of Chiller Fault Detection and Diagnosis Using Only Field-Installed Sensors

Owing to the rapid expansion of data science, data-driven methods have emerged as a dominant trend in chiller fault detection and diagnosis (FDD). Most of these methods prioritize feature selection to achieve optimal diagnostic performance. However, on-site research indicates a common installation of a limited number of sensors, coupled with a necessity to minimize diagnostic costs. This discrepancy between existing research’s feature selection principles and the current on-site sensor installation status presents a significant challenge. To facilitate the practical implementation of data-driven methods in real chiller units, this study addresses a critical question: under the constraint of limited on-site sensor installations, what is the optimal performance achievable by data-driven methods and their improved versions? To answer this, only features derived from commonly installed sensors on field chillers are chosen as indicators for typical chiller faults. The FDD performance of six frequently used data-driven methods, namely, back-propagation neural network, convolutional neural network, support vector machine, support vector data description, Bayesian network, and random forest, along with their improved versions, is comprehensively evaluated and validated using experimental data, considering four evaluation metrics. The conclusions drawn in this paper provide valuable insights for users/manufacturers with limited or no budget, detailing the best achievable diagnostic performance for each typical fault and offering guidance for those aiming to further enhance FDD performance.

What Does it Mean to be a Silviculturist?

Abstract Silviculture has been a dynamic discipline for over a century in North America. During that time, silviculture has been closely tied with dominant trends in society, from reforestation in the early nineteenth century to incorporating climate change, invasive species, and shifts in disturbance regimes during the twenty-first century, and the discipline continues to evolve. In this evolution, there have also been shifts to the definition of silviculture, from an art to art and science to recent proposals that it is strictly a science. We offer an alternative viewpoint in support of maintaining the contemporary definition that includes both art and science, supported by the role that silviculture plays in contemporary resource management and that silviculturists play in conducting both the strategic and tactical components of forest management. Despite the desire to recast silviculture as solely science, we argue that silviculturists need to be more artistic than ever, given the current era of rapidly changing social, ecological, and economic conditions. In addition to having a firm basis in science, silviculturists must also understand and practice their very important role as the honest broker between other resource professionals and society at large in the application of management on the ground. Study Implications: Silviculture has been practiced in North America for over 100 years. It is being shaped by remarkable developments in technology, evolving suites of interested parties and landowner objectives, and considerable climatic uncertainty. Silviculturists are being tasked with interpreting and applying science to accomplish increasingly complex objectives, often with scarce resources at large spatial scales; and all of this is being done in anticipation of further change. Silviculturists understand and accept these challenges and embrace the opportunity to be active stewards of the forests of tomorrow.

Global soil moisture trend analysis using microwave remote sensing data and an automated polynomial-based algorithm

The change in Soil Moisture Content (SMC) is one of the most crucial variables for regulating and analyzing basic hydrological processes, including runoff, evaporation, carbon and energy cycles, infiltration of water resources, droughts and floods, and desertification. This study aimed to detect and map the global SMC change using microwave remote sensing observations. Monthly SMC data from the Soil Moisture Ocean Salinity (SMOS) with a spatial resolution of 25 km were used to assess the SMC change from January 2010 to December 2021. Various trend patterns, including linear, quadratic, cubic, and concealed, were examined by applying a parametric polynomial fitting-based algorithm (Polytrend). In particular, approximately 16.93% of global land is subjected to soil moisture dynamics, of which 8.33% has become drier and 8.60% has become wetter. Both linear and nonlinear trends were observed in the global land areas that have experienced statistically significant changes. The concealed and linear trends were however the dominant trend patterns globally. The obtained trend results were further investigated using a well-known non-parametric trend test, Mann-Kendall, which showed 93.20% agreement, demonstrating the robustness and reliability of the observed trends.