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The Influence Maximization in Complex Networks: Significant Trends, Leading Contributors, and Prospective Directions
No full textInfuence maximization (IM) is a concept in social network analysis and data science that focuses on fnding the most infuential nodes (people, users, etc.) in a network to maximize the spread of information, behavior, or infuence. IM studies have become more crucial due to the quick uptake of social media and networking technologies, which have revolutionized communication and information sharing. Using information from the Scopus database, this study conducts a thorough bibliometric analysis of the literature on instant messaging from 2006 to 2024 to investigate publishing trends, signifcant contributors, and developing themes. Te three primary issues the study attempts to answer are fnding the most productive journals, nations, and scholars in IM research; assessing the growth and infuence of publications; and predicting future research trends. Te results show that IM research is dominated by China and the US, with signifcant contributions from organizations like the Department of Computer Science and Microsoft Research Asia. Te development of the feld toward scalable algorithms and practical applications is highlighted by highly cited articles, such as Chen’s (2009) work on successful instant messaging. Te investigation also shows the possibility of incorporating AI into future advancements and points out shortcomings in behaviorally informed techniques. This study ofers a valuable summary of information management research for academics and professionals trying to understand this ever-evolving topic
Genome-wide identification, expression, and regulatory network analysis of wheat microRNAs responsive to Bipolaris sorokiniana
No full textSpot blotch, caused by Bipolaris sorokiniana, is an important disease that leads to significant economic losses in wheat globally. Due to the complexity of B. sorokiniana infection, identification of wheat lines with strong resistance to spot blotch is challenging. Hence, the introduction of effective disease management strategies through the manipulation of genes involved in B. sorokiniana–wheat interaction remains essential. MicroRNAs (miRNAs) play a vital role in gene regulation and are increasingly used to predict molecular networks and genes associated with disease development or resistance. In this study, we employed small RNA sequencing to profile miRNAs in a resistant (IC566637) and a susceptible (Agra Local) wheat genotype following B. sorokiniana infection. A total of 726 miRNAs, predominantly 21 to 22 nucleotides in length, were identified. Among these, 140 are differentially expressed (DE) and associated with the modulation of 894 genes. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed these target genes as secondary metabolites, ATB-binding cassette (ABC) transporters, nucleotide-binding leucine-rich repeat (NB-LRR), mitogen-activated protein kinase (MAPK) genes, and hormones associated with plant–pathogen interaction and defense signal transduction. The regulatory network constructed from this data highlights key miRNA–target interactions likely contributing to disease resistance. Quantitative RT-PCR validation of nine selected miRNAs and their corresponding target genes further supports their potential role in modulating wheat defense responses. These findings provide a comprehensive resource for understanding miRNA-mediated regulation in the wheat–B. sorokiniana pathosystem and identified promising candidate genes for future resistance breeding and genome editing efforts
9th European Conference on Space Debris
No full textOn September 8, 2024, the first of four CLUSTER-II satellites named Salsa re-entered the Earth’s atmosphere approximately 2000 km west of Easter Island. The reentry was the target of an airborne observation campaign conducted by an international team of scientists. Two hours before re-entry, the team took off aboard a Falcon 900 aircraft, equipped with 26 instruments distributed across six observation stations. This paper provides first results of the airborne observation campaign. Ten of the 26 instruments successfully detected the satellite for up to 20 seconds, with one infrared tracking camera capturing for even a longer time. The recorded intensity profiles reached their peak simultaneously at 18:47:10.7 UTC. Comparing this instant in time with the predicted fragmentation sequence, this bright flash corresponds to the main break-up event. Subsequently, there are three more flashes identified, which have led to the disintegration of the spacecraft
9th European Conference on Space Debris
No full textOn the 13th of July 2024, the ISS resupply capsule CYGNUS NG-20 entered the Earth’s atmosphere above the South Pacific for a controlled destructive re-entry, marking the end of the mission. The capsule was equipped with 5 re-entry experiments (KRUPS - Kentucky Re-Entry Universal Payload System) from the University of Kentucky. The re-entry of CYGNUS was observed from an aircraft equipped with four instrument platforms capturing imaging, spectroscopic, and polarization data which were time-synchronized using a GPS signal.
While the initial goal of the mission was to observe the KRUPS capsules after their release from the spacecraft, a delay in in-space operation shifted the trajectory downrange complicating this objective. HEFDiG deployed a new spectroscopic camera system using a transmission grating. This camera is able to detect spectra between 400 nm and 700 nm with a theoretical resolution of 0.4 nm per pixel. Finally, the altitude region of 93 km to 70 km was successfully observed giving insight into the early entry phase before the main break-up and significant fragmentation occurs. During this phase only broadband radiation was detected indicating black-body radiation from aerothermal heating of the spacecraft. Finally the break-up was observ
Education policy as a constellation of texts and practices: Understanding the effects of national education policymaking on teachers
No full textIn the context of national school reform, teachers’ voices are critical but often missing from official policy discussion. While there is much literature on schooling policy at a national level that has examined different elements of politics, policy, bureaucracy or global influences on education, there has been limited attention given to the discourses utilised in these elements and the way these impact how teachers perceive themselves within the national policy environment. This study sought to bridge this gap between national policy and teachers’ experiences by examining the overlapping spheres of politics, schooling bureaucracy and teachers and the way actions in each of these reverberate through the schooling system to impact other parts of the policy cycle. Paper 1—Funded, then Forgotten: Politics, Public Memory and National School Reform—provides the foundation for the study, by using ministerial media releases over the life of Australia’s National School Reform Agreement as a lens to analyse how federal education ministers attempted to shape public perception of schools, schooling and school reform. Paper 2—The Aporia of Education Policy: National School Reform and the Limits of Policy Enactment—examines the elements contributing to the aporia in schooling bureaucracy, revealing that factors such as government timelines, evaluation processes and the placement of accountability on schools prevents policy from being mediated to schools as intended. Paper 3—Teacher Narratives of National School Reform: Storying the Effects of Education Policy Flows on Teachers’ Work and Lives—considers the perspectives of teachers regarding national school reform through ‘storied’ post-qualitative, composite narratives which depict how national policy is perceived by teachers ‘on the ground’. Finally, Paper 4—Bridging the Extremes of Policy Research: a Narrative Exploration of the Impact of National Education Policy on Teacher Constitution of Self—presents further post-qualitive narratives of teacher perspectives regarding how national policy affects them on a personal level and how they constitute themselves as professionals within this reform environment. Overall, this study demonstrates how policy breakdowns and aporia occur at various points as national schooling policy flows towards schools and teachers. By using narrative storying to give voice to teachers’ experiences of national school reform, this study highlights how teachers’ perspectives of schooling reform are vital to their potential success and calls for a change in the relational culture between all levels of school politics, bureaucracy and school contexts
Operational and economic design of multi-terminal medium DC voltage hybrid renewable energy systems for effective power sharing
No full textThe advancement of multi-terminal medium-voltage direct current (MVDC) technology is accelerating the transition of DC distribution from point-to-point connections to renewable-integrated systems. However, the integration of remote renewable sources introduces challenges in control and economic optimization, particularly for voltage-source converter (VSC)-based designs. Therefore, this paper proposes a multi-terminal MVDC architecture for hybrid renewable energy systems with three primary objectives: to develop an effective power sharing control using a modular multilevel converter-based topology, to assess the economic feasibility of hybrid configurations under varying load and weather conditions, and to implement real-time monitoring through an Internet of Things-based cloud platform. The scope of this paper encompasses the development and validation of decentralized droop control for reliable power sharing, techno-economic analysis using the hybrid optimization of multiple energy resources (HOMER) for cost and energy optimization, real-time system monitoring through ThingSpeak, and MATLAB-based Internet of Things (IoT) integration. Additionally, it includes transient fault simulations to evaluate voltage stability and system resilience. A generalized framework that combines decentralized droop control and economic optimization is established for system sizing and operational reliability assessment. Simulation results indicate that the proposed system maintains DC voltage deviations within 3 % under steady-state conditions, 3.1 % following AC three-phase faults, and as low as 2.2 % after DC pole-to-pole short-circuit events. The unmet load percentage was extremely low (0.0165 %), while excess energy remained manageable (up to 8 %). The system achieves a levelized cost of energy (LCOE) of 0.4114 $/kWh and a renewable energy share of up to 44 %. These results demonstrate that the proposed MVDC configuration is technically robust, cost-effective, and IoT-enabled, making it well-suited for renewable energy integration in Sarawak, Malaysia
A pathway to reduce air pollution and improve life expectancy: Evidence from South Asia
No full textClean air access remains critical for effective healthcare governance and prolonging human lifespan. However, public health risks attributable to air pollution undermine public life expectancy (PLE) and strain healthcare governance in developing countries. The study examines the role of immunization, clean cooking fuel, economic growth, population, and health expenditure (HE) on PLE and air pollution across South Asian countries. The study uses robust econometric techniques such as feasible generalized least squares (FGLS), panel-corrected standard errors (PCSE), and quantile regressions (QR) for long-run estimation. The results show that clean cooking fuel correlates with PLE and air pollution, implying that minimal access, socioeconomic dynamics, and governance inefficiencies constrain the automatic health and air quality co-benefits. While immunization and economic growth improve PLE, HE strengthens health governance by reducing air pollution as an ancillary benefit. However, population size contributes to air pollution through increased resource demands and industrial activity, although the effect of economic growth is heterogeneous. The findings suggest strengthening health governance policies to improve cooking energy efficiency, optimized healthcare budgets, and enhanced cross-border cooperation to preserve air quality and foster healthy lifestyles. Therefore, this study meticulously designs policies for air pollution reduction and public health improvement to achieve dual core agendas
Deformation behavior of saturated sandy soil under offshore wind bucket-shaped foundation ultimate overburden conditions
No full textLiquefaction of saturated sandy soils poses a significant risk in earthquake-prone areas, often resulting in severe deformation and damage to infrastructure. This study through large-scale shaking table tests, investigating the deformation characteristics of saturated sandy soil foundations subjected to varying load levels, ranging from 20% to 50% of the soil’s ultimate bearing capacity (Pult). The experimental results reveal a distinct “bow-shaped” distribution in both lateral displacement and settlement, with a critical inflection point identified at 30% of Pult. When the applied load is less than or equal to 30% of Pult, lateral displacement decreases with depth. However, when the load exceeds 30% of Pult, lateral displacement increases with depth. Higher loads appear to reduce the severity of liquefaction due to enhanced soil resistance. Settlement induced by liquefaction exhibits a non-linear pattern, peaking at approximately 20% of Pult; beyond this point, settlement initially decreases and then increases again at 50% of Pult. These findings offer valuable insights into the interaction between overlying structural loads and liquefaction-induced deformation, providing a theoretical basis for the seismic design of foundations and contributing to the development of more accurate predictive models for foundation stability during earthquakes
Data-driven modeling for evaluating deformation of a deep excavation near existing tunnels
No full textThis study explores an integrated framework combining in-situ test-based numerical and data-driven modeling to assess the performance of a deep excavation-tunnel system. To achieve the goal, a case history of deep excavations adjacent to existing tunnels in silt/sand-dominated sediments is introduced to establish a base three-dimensional finite element (3D-FE) model. In-situ tests such as cone penetration test (CPT/CPTU) and seismic dilatometer test (DMT/SDMT), as an alternative to laboratory testing, are used to determine a set of advanced constitutive model parameters. The established excavation-tunnel numerical model is then validated against filed monitoring data. A dataset from numerical simulation is created for training and testing four machine learning models (i.e., artificial neural network (ANN), support vector machines (SVM), random forest (RF), and light gradient boosting machine (LightGBM)), which predict the maximum wall deflection, ground surface settlement, horizontal and vertical displacements of the tunnel. Results show that the ANN model outperforms other models in prediction capacity. Its generalization ability in practice is further enhanced by comparing field measurement data and empirical equations. The findings suggest that, with the integrated in-situ tests, FE and ANN modeling could be used to predict deformation responses of deep excavations close to existing tunnels in soft soil. The present study is useful and valuable for practical risk assessment and mitigation decisions