Dynamic Transformation Research Articles

Intelligent transport construction solutions in the form of new infrastructure

With the advent of the new infrastructure era, new infrastructures such as 5G, AI, BeiDou Navigation and IOT will bring great changes to the transport industry, driving it towards intelligence and digitalization. As an important part of the development of new infrastructure, the transport industry has become a key factor in driving the country towards ecology, digitalization, intelligence, high speed, transformation of old and new dynamics and symmetrical economic structure. Smart light poles are an important part of smart city construction, combining multiple functions in one, including small base stations, video surveillance, LED information screens, environmental sensors, IP broadcasting sound poles and charging posts. This new type of information infrastructure can provide accurate data services for urban governance through edge-cloud collaboration, and provide low-latency support for multi-scene linkage. In the new situation, the study of how to plan and build intelligent traffic light poles is an important part of the transport industry's contribution to the national information development strategy, and is a new topic of great significance for the transport industry's research.

Epidemiology and Genetic Evolutionary Analysis of Influenza Virus Among Children in Hainan Island, China, 2021–2023

Abstract: Background: During the COVID-19 pandemic, we continuously monitored the epidemiology of influenza virus among pediatric patients from January 2021 to December 2023 in Hainan Island, China. Methods: In this study, we collected 54,974 nasopharyngeal swab samples for influenza A Virus (IAV) testing and 53,151 samples for influenza B Virus (IBV) testing from pediatric outpatients. Additionally, we also collected 19,687 nasopharyngeal swab samples from pediatric inpatients for IAV and IBV testing. Outpatient samples were screened for influenza viruses (IVs) infection by the colloidal gold method. Targeted Next-Generation Sequencing (tNGS) was used to detect influenza virus infections in inpatients. Influenza virus types were identified by analyzing the HA/NA partial regions. Results: The findings revealed a significant decrease in the infection rate of IBV over the specified period, while the infection rate of IAV exhibited a rising trend. Additionally, B/Victoria lineage was the dominant epidemic strain in 2021, while the epidemic strains in 2022 and 2023 underwent a dynamic transformation from A/H3N2 to A/H1N1. Phylogenetic analysis revealed close relationships among the circulating strains. Nonetheless, because the sample size is limited, additional research is required. Conclusions: Our findings suggest that the predominant types of influenza viruses in the pediatric population are undergoing dynamic changes, influenced by the implementation and relaxation of non-pharmaceutical intervention measures. These findings highlight the need for adaptive influenza vaccination and containment strategies, particularly in tropical regions like Hainan, where climate and public health policies significantly impact viral transmission patterns. The insights gained from this study could inform more effective public health strategies in similar regions to mitigate the impact of influenza outbreaks in the future.

Dynamic Navigation-Guided Robotic Placement of Zygomatic Implants

Objectives: To assess the feasibility and accuracy of a new prototype robotic implant system for the placement of zygomatic implants in edentulous maxillary models. Methods: The study was carried out on eight plastic models. Cone beam computed tomographs were captured for each model to plan the positions of zygomatic implants. The hand-eye calibration technique was used to register the dynamic navigation system to the robotic spaces. A total of 16 zygomatic implants were placed, equally distributed between the anterior and the posterior parts of the zygoma. The placement of the implants (ZYGAN®, Southern Implants) was carried out using an active six-jointed robotic arm (UR3e, Universal Robots) guided by the dynamic navigation coordinate transformation matrix. The accuracy of the implant placement was assessed using EvaluNav and GeoMagicDesignX® software based on pre- and post-operative CBCT superimposition. Descriptive statistics for the implant deviations and Pearson's correlation analysis of these deviations to force feedback recorded by the robotic arm were conducted. Results: The 3D deviations at the entry and exit points were 1.80 ± 0.96 mm and 2.80 ± 0.95 mm, respectively. The angular deviation was 1.74 ± 0.92°. The overall registration time was 23.8 ± 7.0 minutes for each side of the model. Operative time excluding registration was 66.8 ± 8.8 minutes for each trajectory.The exit point and angular deviations of the implants were positively correlated with the drilling force perpendicular to the long axis of the handpiece and negatively correlated with the drilling force parallel to the long axis of the handpiece. Conclusion: The errors of the dynamic navigation-guided robotic placement of zygomatic implants were within the clinically acceptable limits. Further refinements are required to facilitate the clinical application of the tested integrated robotic-dynamic navigation system. Clinical Significance: Robotic placement of zygomatic implants has the potential to produce a highly predictable outcome irrespective of the operator's surgical experience or fatigue. The presented study paves the way for clinical applications.

Unveiling the dynamic transformation of Cu species in high entropy oxides during the electrochemical nitrate reduction to ammonia

Unveiling the dynamic transformation of Cu species in high entropy oxides during the electrochemical nitrate reduction to ammonia

TECH TECTONICS: DECODING AND ANALYZING INDIA'S DIGITAL PAYMENT REVOLUTION AND GLOBAL IMPACT

"Tectonics," means typically the movement and deformation of the Earth's crust. In the context of technology or business, "tech tonics" can be interpreted as a metaphorical reference to the dynamic shifts, disruptions, and transformations occurring within the realm of technology or the tech industry. Which means a seismic or groundbreaking change in the technological landscape, signifying significant shifts, innovations, or disruptions that reshape the industry or redefine established norms and practices. Over the past decade, India has undergone a profound metamorphosis in its financial ecosystem, primarily driven by the widespread embrace of digital payment mechanisms. This transformation has been propelled by a combination of factors, including the government's proactive initiatives to promote financial inclusion and the proliferation of innovative financial technologies. Simultaneously, the advent of digital wallets, mobile banking apps, and the introduction of the Unified Payments Interface (UPI) have revolutionized the way transactions are conducted in India. UPI, is a real-time payment system that facilitates instant fund transfers between bank accounts through mobile devices, has emerged as a game-changer in the realm of digital payments. Its seamless and interoperable nature has made it a preferred choice for consumers, merchants, and businesses alike. Furthermore, the COVID-19 pandemic acted as a catalyst for the accelerated adoption of digital payment solutions in India. The need for contactless transactions and the shift towards e-commerce during lockdowns underscored the importance of digital payments in ensuring seamless financial transactions amid disruptions. Looking ahead, the trajectory of India's digital payment revolution appears promising, with ongoing advancements in technology, regulatory support, and consumer acceptance driving further innovation in the financial sector. As the ecosystem continues to evolve, stakeholders across the industry are striving to enhance security, interoperability, and user experience to sustain the momentum of this transformative journey towards a cashless economy. KEYWORDS: Covid-19 Pandemic, Deformation, Innovation, Revolution, Tectonics

Decoding Green Bonds for Sustainable Development: A Hybrid Review and Research Agenda

ABSTRACTThe green bond market and related scholarly research have grown exponentially recently. However, the literature remains scattered. This study addresses the gap by analyzing 744 Scopus‐indexed journal articles using a mix of bibliometric and content analyses to unveil trends, current dynamics, and knowledge structures. The bibliometric analysis shows dynamic transformation and differential development among clusters. It indicates the following three prominent research themes: (a) reducing carbon emissions, (b) premium and financing, and (c) connectedness and portfolio risk effects. From policymakers' perspective, the content analysis reveals positive linkages and channels between green bonds and the environment. Pertinent to issuers and investors, estimates of green bond premiums vary by time, context, and methodology. Future scholarly research should focus on causality, regional variations, and the role of policy design in the impact of green finance. Researchers must further investigate the motives of green bond investors and issuers.

Short-term power load forecasting based on spatial-temporal dynamic graph and multi-scale Transformer

Abstract Short-term power load forecasting is crucial for power system stability and market planning, yet the multi-periodic nature of load data and its complex correlations with external factors pose significant challenges for accurate prediction. To address these, we propose the spatial-temporal dynamic graph Transformer (SDGT). SDGT incorporates a multi-scale Transformer module to capture multiple periodic patterns, with a patch-based multi-scale encoder layer for extracting temporal features. Simultaneously, It leverages a spatial-temporal correlation graph (STCG) integrating shape similarity and semantic relevance, coupled with a graph convolution module, to model dynamic spatial correlations between load data and external factors. Experiments on two public datasets validate that SDGT surpasses state-of-the-art models, demonstrating its effectiveness and robustness in improving power load forecasting accuracy.

"Assessing Urban Transformation and Land-Use Dynamics in Unplanned Settlements: Case Studies of 10 No. Market and Bittan Market

- Unplanned settlement areas, such as '10 No. Market' and 'Bittan Market,' highlight the dynamic transformation of urban zones due to rapid population growth, economic activities, and shifting societal demands. Initially planned as low-density residential neighborhoods, these areas have evolved into bustling commercial hubs, exposing the disconnect between land-use planning and actual urban development. This study examines the key drivers behind these changes, including population growth, economic incentives, cultural shifts, and regulatory gaps. Through surveys, interviews, historical analysis, and geospatial data, the research identifies both the positive impacts—such as enhanced local economies and improved access to goods—and the negative consequences, including traffic congestion, inadequate infrastructure, and environmental degradation. The study reveals a mismatch between planned intentions and reality, emphasizing the importance of adaptive urban planning frameworks. The paper recommends integrated land-use planning, zoning flexibility, infrastructure upgrades, community engagement, and sustainability initiatives as strategies for mitigating the adverse effects of uncontrolled commercialization. The findings underscore the necessity of resilient, flexible urban policies to address the complexities of fringe area development and ensure a balance between economic growth, environmental sustainability, and residents' quality of life. Key Words: urban transformation, mixed-use development, informal zoning, infrastructure strain, fringe areas, adaptive planning

The Concept, Essence and Meaning of Digital Rights as an Object of Hereditary Legal Relations

In this article, the author explores existing problems and offers an author’s understanding of the essence, concept and meaning of digital rights as an object of hereditary legal relations. In the Russian and foreign scientific literature, there are many opinions about the essence, meaning and concept of digital rights, both in general and in relation to civil and inheritance law. The impalpability of this phenomenon is difficult to study. Nevertheless, an attempt has been made in Russian legislation to define the concept of digital rights, which turned out to be not entirely successful, which is confirmed by the opinions of civil scientists. The place assigned by the legislator to digital rights in the system of objects of civil legal relations, namely, their attribution to binding rights rather than other property, is also controversial in the scientific community, which determines the complexity of legal regulation of emerging new types of digital property in the context of dynamic digital transformation of public relations. Based on the results of the study, the author provides a definition of the concept of digital rights.

Deciphering the Impact of Halogen Ions on the Oxidative Dynamics and Halogenated Byproduct Transformation in the Ferrate(VI)-Periodate Combined System

Deciphering the Impact of Halogen Ions on the Oxidative Dynamics and Halogenated Byproduct Transformation in the Ferrate(VI)-Periodate Combined System

Evolutionary characteristics and influencing mechanisms of green development efficiency in Chinese urban agglomerations: Analysis of the Yangtze River Delta urban agglomeration.

Urban agglomerations are central to global economic growth and the shift towards green development, particularly in developing countries. This study examines regional comparisons and variations in green development mechanisms within urban agglomerations to better understand their spatiotemporal patterns. An input-output indicator system was developed, accounting for social benefits and carbon emissions. Using the Yangtze River Delta urban agglomeration (YRDUA) as a case, this study measured green development efficiency (GDE) from 2003 to 2022 with the SBM-Undesirable model. It also employed the coefficient of variation (CV) method and Markov chain model to analyze the spatiotemporal variability and dynamic transformation law of GDE. Additionally, a panel quantile regression model was used to identify the dynamic response of key controlling factors, based on the GDE stages of each city. The findings reveal: (1) Cities in the central YRDUA area have higher GDE levels compared to those in non-central areas, with increasing disparity over time. (2) The green development level of a city influences its neighbors, enhancing or degrading their GDE stability and type. (3) Economic growth, foreign direct investment, industrial structure, and technological innovation significantly impact YRDUA's GDE. (4) In cities with low green development, economic growth strongly promotes GDE, while government regulation most restricts it. In medium-level cities, industrial structure advancements have the largest promotional effect, whereas technological innovation is the most limiting factor. In high-level cities, foreign investment intensity is the main inhibitor, while government regulation supports GDE. Marketization and environmental regulation effects on GDE remain consistent across different city levels. These findings provide targeted guidance for the green transition of urban agglomerations in China and other developing nations.

‘A place for everyone who gets it’:

This article discusses the political potential of sharing comics and cartoons on Instagram when that practice lies in the intersection of autobiographical art, feminist activism, and for-profit influencer work. Through a case study of cartoonist Mary Catherine Starr, aka @momlife_comics, and the 2022 viral campaign against her work known as ‘Peachgate,’ the article discusses whether Starr’s work participates in a juxtapolitical intimate public or whether it holds the potential to incite more radical transformation of the gender dynamics it criticizes. Investigating Starr’s visual style and aesthetic strategies, as well as the platformed visibility labor she engages in, the article argues that Peachgate can be seen as an indication of the potential for this work to transform from an intimate public to an affective public, although only if allowed to circulate beyond the intentions and preferred interpretationsoffered by Starr.

Bioprinted Fibroblast Mediated Heterogeneous Tumor Microenvironment for Studying Tumor-Stroma Interaction and Drug Screening.

Cancer-associated fibroblasts (CAFs) are crucial stromal cells in the tumor microenvironment, affecting cancer growth, angiogenesis, and matrix remodeling. Developing an effective in vitro tumor model that accurately recapitulates the dynamic interplay between tumor and stromal cells remains a challenge. In this study, a 3D bioprinted fibroblast - mediated heterogeneous breast tumor model was created, with tumor cells and fibroblasts in a bionic matrix. The impact of transforming growth factor-β （TGF-β） on the dynamic transformation of normal fibroblasts into CAFs and its subsequent influence on tumor cells is further investigated. These findings reveales a profound correlation between CAFs and several critical biological processes, including epithelial-mesenchymal transition (EMT), extracellular matrix (ECM) remodeling, gene expression profiles, and tumor progression. Furthermore, tumor models incorporating CAFs exhibits reduced drug sensitivity compared to models containing tumor cells alone or models co-cultured with normal fibroblasts. These results underscore the potential of the in vitro fibroblast-mediated heterogeneous tumor model to simulate real-life physiological conditions, thereby offering a more effective drug screening platform for elucidating tumor pathogenesis and facilitating drug design prior to animal and clinical trials. This model's establishment promotes the understanding of tumor-stromal interactions and their therapeutic implications.

Triadic balance and network evolution in predictive models of signed networks

This paper introduces a novel approach for identifying dynamic triadic transformation processes, applied to five networks: three undirected and two directed. Our method significantly enhances the prediction accuracy of network ties. While balance theory offers insights into evolving patterns of triadic structures, its effects on overall network dynamics remain underexplored. Existing research often neglects the interaction between micro-level balancing mechanisms and overall network behavior. To bridge this gap, we develop a method for detecting dynamic triadic structures in signed networks, categorizing triangle transformations over two consecutive periods into formation and breakage. We analyze the impact of these structures on temporal network evolution by incorporating them into exponential random graph models across five networks of varying size, density, and directionality. To address the complexity of multi-layer networks derived from signed networks, we modify the temporal exponential random graph model framework. Our method significantly improves out-of-sample prediction accuracy for network ties, with additional predictive power from incorporating negative network information. These findings highlight the importance of considering the triadic transformation processes of balance triangles in studying temporal networks, validated across diverse datasets, warranting further research.

Secondary Alkylation of Arenes via the Borono-Catellani Strategy.

A modular platform technology for the synthesis of α-aryl carbonyl derivatives via Borono-Catellani-type secondary alkylation of arenes is presented. This practical method features a broad substrate scope regarding aryl boronic acid catechol esters, secondary alkyl bromides, and diversified terminating reagents (e.g., olefins, alkynes, and Zn(CN)2), mild reaction conditions, and good functional-group tolerance. Importantly, the asymmetric version based on a dynamic kinetic asymmetric transformation (DyKAT) has also been realized by introducing the 1:1 diastereomeric mixture of α-bromo carboxamides bearing an Evans chiral auxiliary as the electrophiles, and constantly excellent diastereoselectivities (>20:1 d.r.) are obtained. Notably, the obtained chiral products can be readily transformed into diversified enantioenriched α-aryl propionic acid derivatives, laying a solid foundation for the discovery of new NSAIDs. Through mechanistic studies and DFT calculations, a critical stereoretentive oxidative addition step is revealed in this Borono-Catellani secondary alkylation reaction, and the origins of stereodiscrimination of this DyKAT are well explained.

Guest Segregation in Heteromeric Multicage Systems.

Dynamically interconvertible metallo-supramolecular multicomponent assemblies, coexisting orthogonally in solution, serve as simplified mimics for complex networks found in biological systems. Building on recent advances in controlling the nonstatistical self-assembly of heteroleptic coordination cages and heteromeric completive self-sorting, i.e., the coformation of multiple low-symmetry assemblies, we herein describe the first instance of emerging functionality from a heteromeric multicage system. In particular, one heteroleptic cage coexists in equilibrium with one or two different homoleptic cages, each capable of preferentially encapsulating one out of three guests within their cavities. Guest segregation occurs under thermodynamic control and can be reached following several distinct paths. Each pathway involves different sequential transformations, eventually leading to the same outcome. We found that the most complex mixture of components (three ligands, three guests, plus palladium cations) always yields an ordered, pathway-independent final state of three coexisting host-guest species, thus representing a case of simplexity in self-sorted systems. This study forms a basis for expanding the scope of dynamic transformation processes implemented in multicage host-guest systems. Together with the incorporation of stimuli-responsive elements and other functionality, complex cage populations with bioinspired applications in controllable compound separation schemes, compartmentalized cascade reactions, and multistep (even bifurcated) molecular information processing will become accessible.

Time-resolved spectroscopy uncovers deprotonation-induced reconstruction in oxygen-evolution NiFe-based (oxy)hydroxides

Transition-metal layered double hydroxides are widely utilized as electrocatalysts for the oxygen evolution reaction (OER), undergoing dynamic transformation into active oxyhydroxides during electrochemical operation. Nonetheless, our understanding of the non-equilibrium structural changes that occur during this process remains limited. In this study, utilizing in situ energy-dispersive X-ray absorption spectroscopy and machine learning analysis, we reveal the occurrence of deprotonation and elucidate the role of incorporated iron in facilitating the transition from nickel-iron layered double hydroxide (NiFe LDH) into its active oxyhydroxide. Our findings demonstrate that iron substitution promotes deprotonation process within NiFe LDH, resulting in the preferential removal of protons from the specific bridged hydroxyl group (Ni2+-OH-Fe3+) linked to edge-sharing [NiO6] and [FeO6] octahedron. This deprotonation behavior drives the formation of high-valence Ni3+δ species (0 <δ < 1), which subsequently serve as the active sites, thereby ensuring efficient oxygen evolution activity. This approach offers high-resolution insights of dynamic structural evolution, overcoming the limitations of extended acquisition times and advancing our understanding of OER mechanisms.

Dynamic Recrystallization Modeling Considering Dynamic Transformation and Behavioral Analysis for a High-Temperature Titanium Alloy during Hot Deformation

Dynamic Recrystallization Modeling Considering Dynamic Transformation and Behavioral Analysis for a High-Temperature Titanium Alloy during Hot Deformation

Dynamical quantum phase transitions and quantum thermodynamics: An approach through dynamical transformations

Dynamical quantum phase transitions and quantum thermodynamics: An approach through dynamical transformations

Operando monitoring of the functional role of tetrahedral cobalt centers for the oxygen evolution reaction

The complexity of the intrinsic oxygen evolution reaction (OER) mechanism, particularly the precise relationships between the local coordination geometry of active metal centers and the resulting OER kinetics, remains to be fully understood. Herein, we construct a series of 3 d transition metal-incorporated cobalt hydroxide-based nanobox architectures for the OER which contain tetrahedrally coordinated Co(II) centers. Combination of bulk- and surface-sensitive operando spectroelectrochemical approaches reveals that tetrahedral Co(II) centers undergo a dynamic transformation into highly active Co(IV) intermediates acting as the true OER active species which activate lattice oxygen during the OER. Such a dynamic change in the local coordination geometry of Co centers can be further facilitated by partial Fe incorporation. In comparison, the formation of such active Co(IV) species is found to be hindered in CoOOH and Co-FeOOH, which are predominantly containing [CoIIIO6] and [CoII/FeIIIO6] octahedra, respectively, but no mono-μ-oxo-bridged [CoIIO4] moieties. This study offers a comprehensive view of the dynamic role of local coordination geometry of active metal centers in the OER kinetics.