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Found 6374 publications
Investigation of CO2 Emission Concerning Levee Reinforcement Technologies
Publication Name: Lecture Notes in Civil Engineering
Publication Date: 2025-01-01
Volume: 580 LNCE
Issue: Unknown
Page Range: 1-10
Description:
Flooding is one of the primary causes of losses from natural disasters in numerous regions worldwide, surpassing all other types of natural hazards in terms of damage. In recent decades, flood damage has been significantly severe due to the increase in the frequency and intensity of floods. Considering that levees are built for an established design life, it is essential to consider potential changes in loads due to atmospheric climate change. Climate variability may affect hydraulic loading and soil eroding with significant precipitation or during drought or high wind conditions. These atmospheric changes over time may affect the structural integrity of the levee. The dominating failure modes for typical ground conditions along rivers are slope stability, overtopping, through seepage, and underseepage. Several technologies can be applied to prevent levee failure, strengthen the levee, avoid overtopping or internal erosion, and ground subsidence due to changing groundwater. The most common ones are concrete columns, sheet piles, geosynthetics, and deep mixing using different binders. However, these technologies come out to be costly, in terms of materials. Moreover, the primary material of these interventions is cement. Nowadays, it is accepted that the cement industry is one of the two largest producers of carbon dioxide (CO2 ). The Sustainable Development Goals (SDGs) provide comprehensive guidelines for promoting sustainable development in terms of environmental, social, and economic dimensions in all sectors of the economy, including civil engineering. The study outlines the procedure to calculate the carbon dioxide emissions of different technologies for levee reinforcement. Considering a simple scenario, the technical suitability of the investigated technologies is analyzed, and the carbon dioxide emission is analyzed separately.
Open Access: Yes
Dynamic inflation responses to war-related electricity shocks: DTW-based evidence from European energy and renewables regimes
Publication Name: Journal of International Studies
Publication Date: 2025-01-01
Volume: 18
Issue: 4
Page Range: 180-203
Description:
Russia’s invasion of Ukraine turned wholesale electricity prices into a major, but uneven, driver of inflation across Europe. The article aims to quantify dynamic inflation responses to war-related electricity shocks and to identify distinct energy-inflation regimes conditioned by renewables penetration and structural characteristics. The analysis uses a balanced monthly panel of 26 European countries (2019-2025), combining two-way fixed-effects regressions with event-time “excess” inflation profiles and correlation-and clustering based on Dynamic Time Warping. Early-phase excess inflation around February 2022 ranges from about 0.53 percentage points (cluster 6) to 1.06 percentage points (cluster 3), with clusters 1 and 5 also showing strong overshoots (≈0.94-0.91), while only clusters 1 and 3 sustain elevated excess inflation in the medium phase (≈0.71-0.76) and all regimes converge to within-0.07 to +0.16 by the late phase. DTW clustering reveals six regimes with distinct pre-war configurations of electricity prices (approximately 49-59 EUR/MWh), renewable energy shares (approximately 24-55%), and unemployment rates (approximately 4.45-8.59%). A heterogeneous-slope FE model shows that a 100 EUR/MWh electricity shock raises the monthly HICP by only 0.03 percentage points in cluster 3 and 0.09 in cluster 5. In contrast, the effects in other clusters are small and statistically insignificant, confirming a highly uneven and often muted pass-through.
Open Access: Yes
A literature outlook on the impacts of corporate social responsibility on sustainable banking operation
Publication Name: International Journal of Green Economics
Publication Date: 2025-01-01
Volume: 19
Issue: 4
Page Range: 429-447
Description:
Corporate social responsibility (CSR) has become essential in banking as stakeholders demand greater sustainability, transparency, and ethical governance. This paper provides a structured review of studies from 2014–2024, examining the relationship between CSR initiatives and banks’ financial performance. The review highlights that CSR practices such as green banking, responsible lending, ethical investment strategies, and sustainability reporting can enhance profitability, reputation, and stakeholder trust though results vary across contexts. While many studies find a positive relationship between CSR and financial performance, others report negative or neutral effects, depending on bank size, institutional stability, cultural context, and the specific CSR dimensions pursued. Guided by stakeholder, legitimacy, resource-based, and reputation theories, the review develops an integrated conceptual framework and offers policy insights for banks and regulators. It also identifies research gaps, particularly the potential of emerging technologies like blockchain and artificial intelligence to strengthen ESG risk assessment and financial inclusion. Overall, CSR remains a key but context-dependent driver of sustainable banking.
Open Access: Yes
FROM AI VIBRANCY TO LABOUR MARKET OUTCOMES: TESTING DISPLACEMENT ACROSS EDUCATION GROUPS
Publication Name: Economics and Sociology
Publication Date: 2025-01-01
Volume: 18
Issue: 4
Page Range: 131-159
Description:
Artificial intelligence is expanding rapidly, intensifying policy concerns that more vibrant AI ecosystems may displace workers and increase unemployment. This study aims to test whether national AI vibrancy is associated with higher unemployment across education groups (advanced, intermediate and basic). Using an unbalanced panel of 34–35 countries from 2017 to 2023, the analysis combines Stanford’s AI Vibrancy Score with World Bank indicators and estimates two-way fixed-and random-effects models, employing Box–Cox/log transformations and dependence-robust inference (including country/time clustering and Driscoll–Kraay standard errors). The results provide little support for the displacement hypothesis. For advanced-education unemployment, AI vibrancy is statistically insignificant in the two-way FE model. It remains insignificant under all robust corrections (ln(AI vibrancy): β=−0.099, country-clustered p=0.494, time-clustered p=0.544, Driscoll–Kraay p=0.468). For basic-education unemployment, AI vibrancy is likewise insignificant in the two-way FE model (p=0.782). It remains insignificant under country clustering (p=0.830), time clustering (p=0.813) and Driscoll–Kraay inference (p=0.819). For intermediate-education unemployment, the AI coefficient remains insignificant under country clustering (p=0.273), time clustering (p=0.310), and Driscoll–Kraay corrections (p=0.226), indicating no robust unemployment-increasing effect across education groups during the observed period.
Open Access: Yes
Preliminary Study on the Optimal Calibration of High Damping Rubber Bearings
Publication Name: Lecture Notes in Civil Engineering
Publication Date: 2025-01-01
Volume: 770 LNCE
Issue: Unknown
Page Range: 226-239
Description:
Seismic isolation emerged as an efficient technology for seismic protection. It has been proven to simultaneously reduce inter-story drift demands and horizontal accelerations in buildings when properly implemented. Since the 80s, several numerical models appeared in literature to simulate the dissipative behaviour of High Damping Rubber Bearings (HDRB) devices under different acting scenarios. Despite the efforts provided by several authors to reproduce the real behaviour of such devices through the definition of efficient numerical models, the variability of laws’ parameters in the mass-production series of devices should receive further investigations. This research presents the preliminary results pointed out by an identification procedure of no.2 existing literature models with an increasing level of computation effort. The reliability of the numerical outputs and the goodness of each numerical model have been demonstrated by comparing them with experimental tests obtained from the SISMALAB laboratory. Experimental data are composed of no. 5 samples of the same devices, subjected to both compression forces and horizontal displacement under sinusoidal cyclic deformation. The optimal values of each device have been obtained by performing an optimization process where the difference between experimental and numerical behaviour has been minimized. The well-known Genetic Algorithm has been chosen for this purpose.
Open Access: Yes
System identification with generalized Prony schemes
Publication Name: Proceedings of the American Control Conference
Publication Date: 2025-01-01
Volume: Unknown
Issue: Unknown
Page Range: 5086-5092
Description:
We propose a novel method to identify the transfer functions of single-input-single-output linear time invariant (SISO-LTI) dynamic systems. Our approach makes use of the operator based generalization of Prony's method. In particular, the operator based Prony algorithm is used to reconstruct the transfer function of the system as a linear combination of rational basis functions. A considerable benefit of the proposed method is its robustness against the estimated system order. That is, if system order is over estimated, the correct system order can be found naturally. Another important benefit is that the proposed method is shown to be asymptotically robust towards zero expectation noise with the correct choice of certain evaluation functionals. The effectiveness of the proposed method is demonstrated through numerical experiments.
Open Access: Yes
Fluctuating Free Convection Flow of Casson Dusty Fluid in an Inclined Microchannel Under Wall Shear Stress and an Inclined Magnetic Field
Publication Name: Contemporary Mathematics Singapore
Publication Date: 2025-01-01
Volume: 6
Issue: 6
Page Range: 7601-7618
Description:
This study examines the unsteady free convection flow of Casson dusty fluid within an inclined microchannel under the influence of wall shear stress and an inclined magnetic field. The fluid is assumed to contain uniformly dispersed electrically conductive dust particles, and heat is applied via Newtonian heating at one boundary. The governing partial differential equations representing the motion of both fluid and dust phases are derived and solved using the Poincaré-Lighthill Perturbation Technique (PLPT). Key physical parameters such as the Casson fluid parameter, Grashof number, magnetic field inclination, radiation, and dusty fluid interaction parameter are varied to analyze their effect on velocity and temperature profiles. Results reveal that increasing the Casson parameter reduces fluid velocity, while higher Grashof numbers and radiation levels enhance it. The magnetic field generates Lorentz forces that oppose the motion, thereby reducing both fluid and dust particle velocities. The inclined magnetic field and Newtonian heating significantly influence thermal and flow behavior. These findings have practical implications in microfluidics, industrial coatings, biomedical flows, and heat management systems, where controlling dusty fluid dynamics under external fields is crucial.
Open Access: Yes
Leadership Readiness in Higher Education: A SILDM-Based Competency Diagnosis
Publication Name: European Journal of Interdisciplinary Studies
Publication Date: 2025-01-01
Volume: 17
Issue: 2
Page Range: 44-60
Description:
This paper examines the self-perceived leadership readiness of first-year bachelor’s students enrolled in economics and business programmes, utilising the Korn Ferry Leadership Architect™ as a diagnostic tool within the broader conceptual framework of the Synced Integrated Leadership Development Model (SILDM). SILDM is a theoretically informed synthesis of established leadership and intercultural frameworks, designed to reflect the multifaceted nature of contemporary leadership. It integrates behavioural, ethical, relational, and cultural dimensions into a unified developmental perspective, addressing a key limitation in leadership education: the tendency to apply models in isolation without accounting for their interdependent dynamics. To operationalise this framework, a survey instrument based on 29 selected Korn Ferry competencies was administered to a sample of 1,307 first-year students, enabling structured self-assessment across four leadership domains: Thought, Results, People, and Self. The findings revealed higher levels of confidence in cognitive and task-oriented domains (Thought and Results), and notable developmental gaps in ethical self-regulation and interpersonal influence (Self and People). The paper proposes six pedagogically grounded interventions designed to foster more integrated, ethically grounded, and culturally responsive leadership development during the early stages of students’ academic and professional formation.
Open Access: Yes
A Comparative Evaluation of Classical and Deep Learning-Based Visual Odometry Methods for Autonomous Vehicle Navigation †
Publication Name: Engineering Proceedings
Publication Date: 2025-01-01
Volume: 113
Issue: 1
Page Range: Unknown
Description:
This study introduces a comprehensive benchmarking framework for evaluating visual odometry (VO) methods, combining classical, learning-based, and hybrid approaches. We assess 52 configurations—spanning 19 keypoint detectors, 21 descriptors, and 4 matchers—across two widely used benchmark datasets: KITTI and EuRoC. Six key trajectory metrics, including Absolute Trajectory Error (ATE) and Final Displacement Error (FDE), provide a detailed performance comparison under various environmental conditions, such as motion blur, occlusions, and dynamic lighting. Our results highlight the critical role of feature matchers, with the LightGlue–SIFT combination consistently outperforming others across both datasets. Additionally, learning-based matchers can be integrated with classical pipelines, improving robustness without requiring end-to-end training. Hybrid configurations combining classical detectors with learned components offer a balanced trade-off between accuracy, robustness, and computational efficiency, making them suitable for real-world applications in autonomous systems and robotics.
Open Access: Yes
