16168 research outputs found
Sort by
Sustainability practices and capital costs: evidence from banks and financial technology firms in global markets /
No full textThis paper examines the impact of environmental, social, and governance (ESG) disclosure on the cost of capital for banks as well as financial technology companies in Europe, America, and Asia from 2010 to 2024. The study investigates how sustainability affects financing conditions in the two institutional settings of conventional and digital financial intermediaries. We estimate the average cost of capital using the traditional WACC (weighted average cost of capital) formula, which calculates the cost and proportions of debt and equity capital. Panel regressions with firm and year fixed effects are used, along with an instrumental variable (IV) approach (2SLS), by way of peer-based ESG instruments to correct for endogeneity. The paper also carries out robustness checks such as the Anderson–Rubin weak IV tests and over identification diagnostics. The findings indicate that more ESG disclosure has a significant negative effect on WACC and debt costs and no robust impact on equity cost. Governance disclosure is revealed to be the dominant dimension and it always correlates with lower financing costs. Environmental disclosure is occasionally associated with a higher cost of equity, owing to investors’ expectation of short-term compliance costs. The results shed light on the dynamic relationship between innovation and sustainability in driving banks and financial technology firms financing environment
Influence of deposition temperature on the mechanical and tribological properties of Cr/Ni Co-doped diamond-like carbon films /
No full textThis study aimed to examine the influence of sputtering temperature on the bonding structure and properties of non-hydrogenated chromium/nickel co-doped diamond-like carbon (DLC) films synthesized via direct current magnetron sputtering. The Cr/Ni doping levels in the coatings were regulated by varying the shield opening above a chromium-nickel (20/80 at.%) target, resulting in a total metal co-doping concentration ranging from 6.1 to 8.9 at.%. The thickness of the Cr/Ni-DLC films ranged from 160 to 180 nm. Meanwhile, the deposition temperatures of 185 °C and 235 °C were achieved by adjusting the substrate-to-target distance. The XPS and Raman spectroscopy results indicated enhanced graphitization of the Cr/Ni-DLC films with a decrease in the synthesis temperature. XPS results indicated the formation of carbon-oxide and metal-oxide bonds, with no evidence of metal carbide formation in the doped DLC films. Furthermore, both the nanohardness and Young’s modulus demonstrated significant improvement, while the friction coefficient was reduced more than twice as the deposition temperature increased. These findings provide valuable insights into the influence of deposition temperature on Cr/Ni co-doped DLC films, highlighting their potential as advanced functional coatings
A novel multi-scale feature fusion with adaptive scale-space pyramid network for aerial scene recognition using remote sensing images /
No full textRemote Sensing is an area anthropogenic study undertaken worldwide. It has succeeded significantly in important applications such as climate monitoring, disaster prediction and land use planning. However, due to the diversity of scales, intra-class similarities, and complex scenes, the accurate recognition process remains challenging. Transformers' global attention mechanism helps them to overcome the limitations of CNNs' local receptive fields; however, they have drawback of increased computing complexity. To overcome such challenges, this work proposes an Adaptive Scale-Space Pyramid Network (ASSPN) for improved remote sensing image classification. The ASSPN architecture contains a learnable Gaussian pyramid module for multi-scale feature representation, a scale selection attention mechanism for dynamically weighing feature relevance, a cross-feature propagation module for fusion guided by uncertainty, and a complexity-aware adaptive pooling module for preserving semantic discriminative features. Experiments are performed three benchmark datasets such as EuroSAT, NWPU-RESISC-45, and MLRSNet. On these datasets, the ASSPN achieves state-of-the-art results with accuracies of 96.14%, 94.73%, and 95.42%, respectively. The obtained accuracy is outperforming previous CNN and transformer-based systems with significant margins. Furthermore, ASSPN is noise perturbation-resistant and shows generalization capability across a wide range of land-cover categories. Ablation studies established the complementary benefits of the core modules, while LIME-based explainability analysis confirmed the predicative trustworthiness of the model
Synthesis and antibacterial evaluation of 5-aminosalicylic acid derivatives /
No full textThe anti-inflammatory scaffold 5-aminosalicylic acid, which is widely used in therapeutic applications, was chosen for the synthesis of N-[3-(hydrazinecarbonyl)-4-hydroxyphenyl]acetamide (1) to enhance its antibacterial properties. The condensation of hydrazide 1 with aromatic aldehydes provided hydrazone derivatives 2a–f, whereas cyclocondensation reactions and other related transformations afforded five-membered heterocycles, including pyrrole 3, pyrazole 4, pyrrolidinone 7, oxadiazoles 9, 10, thiadiazole 14, and triazole 15. Additional modifications yielded acetylhydrazine derivative 11, which was O-alkylated to analogue 12. Antibacterial evaluation showed stronger activity against Gram-positive bacteria such as S. aureus and MRSA than against Gram-negative strains of E. coli and S. Enteritidis, consistent with differences in cell membrane permeability. Notably, derivatives containing pyrrolidinone 7, thiosemicarbazide 13, and 1,3,4-thiadiazole 14 exhibited potent bactericidal activity against S. aureus and MRSA, while hydrazones 2b, 2c, 2f, pyrrole 3, and pyrrolidinone 7 exhibited activity against E. coli. These results provide a practical strategy for the discovery of heterocyclic compounds and emphasise the potential of functionalised 5-aminosalicylic acid derivatives as prime candidates for the development of broad-spectrum antibacterial agents
Research on the properties of concrete with glass powder and an ultra-low amount of portland cement.
No full textThe aim of the master’s thesis is to investigate the influence of ground glass on the mechanical and physical properties of concrete and its resistance to frost effects, with the aim of reducing CO₂ emissions. The thesis consists of four parts: literature analysis, materials used in the research, experimental methods, and their results. The literature analysis part describes the chemical compositions of glass and Portland cement, as well as the properties of ground glass in concrete mixtures. The cement hydration processes are examined, and the possibilities of pozzolanic reactions using active mineral additives and the risks of alkali-silica reaction are reviewed. Cases of how to activate pozzolanic reactions and how to control or avoid alkali-silica reaction are analyzed. The influence of ground glass on the freeze–thaw cycles of concrete and the practical application of concrete containing ground glass are also reviewed. The part on materials used in the research presents the materials used in the experiments. The experimental methods section describes the methods applied for testing the specimens. The experimental results section describes the specific process of ground glass production and determines the specific surface area of ground glass particles. The cement hydration process using ground glass and silica fume was determined by the semi-adiabatic calorimetry method. The physical and mechanical properties of the new compositions, such as concrete mixture spread, density, flexural and compressive strength, are determined, and shrinkage deformation results are presented when performing an accelerated alkali-silica reaction test, as well as the resistance to salt-scaling of concrete is determined by the one-sided freezing and thawing method. The environmental impact of the new compositions was evaluated by calculating CO₂ emissions and comparing them with the standard concrete composition
S3PM: Entropy-regularized path planning for autonomous mobile robots in dense 3D point clouds of unstructured environments /
No full textAutonomous navigation in cluttered and dynamic industrial environments remains a major challenge for mobile robots. Traditional occupancy-grid and geometric planning approaches often struggle in such unstructured settings due to partial observability, sensor noise, and the frequent presence of moving agents (machinery, vehicles, humans). These limitations seriously undermine long-term reliability and safety compliance—both essential for Industry 4.0 applications. This paper introduces S3PM, a lightweight entropy-regularized framework for simultaneous mapping and path planning that operates directly on dense 3D point clouds. Its key innovation is a dynamics-aware entropy field that fuses per-voxel occupancy probabilities with motion cues derived from residual optical flow. Each voxel is assigned a risk-weighted entropy score that accounts for both geometric uncertainty and predicted object dynamics. This representation enables (i) robust differentiation between reliable free space and ambiguous/hazardous regions, (ii) proactive collision avoidance, and (iii) real-time trajectory replanning. The resulting multi-objective cost function effectively balances path length, smoothness, safety margins, and expected information gain, while maintaining high computational efficiency through voxel hashing and incremental distance transforms. Extensive experiments in both real-world and simulated settings, conducted on a Raspberry Pi 5 (with and without the Hailo-8 NPU), show that S3PM achieves 18–27% higher IoU in static/dynamic segmentation, 0.94–0.97 AUC in motion detection, and 30–45% fewer collisions compared to OctoMap + RRT* and standard probabilistic baselines. The full pipeline runs at 12–15 Hz on the bare Pi 5 and 25–30 Hz with NPU acceleration, making S3PM highly suitable for deployment on resource-constrained embedded platforms
Mechanical, electrical, and thermal performance of hemp fiber-reinforced elium biocomposites modified with activated carbon nanoparticles: experiment and simulation /
No full textThis research examines the influence of various concentrations (0%, 1%, 1.4% and 1.8% by weight) of activated carbon nanoparticles (AC NPs) on the performance of Elium biocomposites reinforced with hemp fibers. Unidirectional [0°/0°] laminates with 20% fiber volume fraction were fabricated via hand layup using two layers of 150 GSM hemp fabric and compression molded to achieve 0.9 mm cured thickness. Quasi-static tensile testing (ASTM D3039, 2 mm/min, 100 mm gauge length) revealed a pronounced non-monotonic relationship between AC NPs loading and mechanical properties, with optimal performance at 1.0 wt.% fillers and catastrophic degradation at 1.8 wt.%. AC NPs filled composites, which were then characterized by their electrical and thermal behavior. Electrically, it also achieved minimum resistivity (1.62 Ω·m) and maximum conductivity (0.62 S·m-1), in contrast to the elevated resistance (42.5 kΩ) found in samples with a higher filler content. Thermal analysis showed a slight effect on the degradation of the onset temperature (300 °C) and a higher charring after addition of AC NP. Finite element analysis (FEA) provided a corroboration for these experimental findings, with simulations verification. Microscopy revealed cohesive fractures in the 1.0 wt.% composite whereas voids and brittle failure were evident in samples with higher loading. Hence, the concentration of 1.0 wt.% AC NP offers the best trade off of mechanical, electrical, and thermal properties
Assessment of the factors influencing the development of leasing in Lithuania.
No full textA successfully operating and expanding business is the main driver of a country’s economic growth. Small and medium-sized enterprises (SMEs) play a crucial role in maintaining economic stability and creating jobs; therefore, it is especially important for them to remain competitive. Fair competition encourages businesses to seek innovative solutions to optimize operations and increase efficiency. However, such solutions are not accessible to all businesses. Due to continuously tightening lending conditions, increasing down payments, and stricter collateral requirements, external financing is becoming increasingly difficult to access, especially for SMEs. As a result, leasing becomes an excellent alternative, characterized by flexible terms and the absence of additional collateral requirements, since the leased asset itself serves as collateral. Globally, leasing is actively analyzed across various fields; however, the pace of leasing development differs significantly between countries. Therefore, it is necessary to analyze the factors determining leasing development in order to reduce the gap in leasing growth among different countries
The use of biochar and carbon credit schemes for the development of the sustainable agriculture market in Lithuania.
No full textIn recent years, the agricultural sector has faced increasing pressure not only to ensure economic viability but also to contribute to climate change mitigation objectives. European Union climate policy is increasingly focused not only on reducing greenhouse gas emissions but also on the removal of carbon dioxide from the atmosphere. In this context, biochar and carbon credit schemes are becoming significant tools for sustainable agriculture, as they have the potential to simultaneously address soil degradation, emission reduction, and farm economic stability. However, in Lithuania, the practical application of these solutions remains limited, and their economic justification has not yet been sufficiently and systematically analysed. The object of the master’s thesis is the use of biochar and carbon dioxide credit schemes for the development of the sustainable agriculture market in Lithuania. The study seeks to assess under which economic conditions the application of biochar and the generation of carbon credits can be economically justified and contribute to the development of the sustainable agriculture market. The aim of the master’s thesis is to evaluate the economic impact of biochar and carbon dioxide credit schemes on the development of the sustainable agriculture market in Lithuania, taking into account both macroeconomic and microeconomic factors. Research methods: the study applies a comprehensive research methodology, including scientific literature analysis, statistical data analysis, correlation analysis, and the evaluation of baseline and alternative economic scenarios of the analysed farm. The empirical analysis assesses the economic effect of biochar application, the dynamics of carbon credit prices, biochar application costs, and the potential for fertiliser cost savings under different macroeconomic conditions. Results: the main results of the study indicate that the economic impact of biochar and carbon dioxide credit schemes is not uniform and depends on macroeconomic factors such as fertiliser price fluctuations, agricultural commodity prices, and the dynamics of the carbon credit market. It was found that in certain periods biochar application generates a negative net economic effect; however, under favourable price and cost combinations, it can become economically justified and contribute to improved farm financial stability. The findings suggest that biochar can be regarded as a long-term, cyclical, and market-adaptive sustainable agriculture tool with the potential to support the development of the sustainable agriculture market in Lithuania
Towards patient anatomy-based simulation of Net cerebrospinal fluid flow in the intracranial compartment /
No full textBiophysics-based, patient-specific modeling remains challenging for clinical translation, particularly for cerebrospinal fluid (CSF) flow where anatomical detail and computational cost are tightly coupled. We present a computational framework for steady net CSF redistribution in an MRI-derived cranial CSF domain reconstructed from T2-weighted imaging, including the ventricular system, cranial subarachnoid space, and periarterial pathways, to the extent resolvable by clinical MRI. Cranial CSF spaces were segmented in 3D Slicer and a steady Darcy formulation with prescribed CSF production/absorption was solved in COMSOL Multiphysics®. Geometrical and flow descriptors were quantified using region-based projection operations. We assessed discretization cost–accuracy trade-offs by comparing first- and second-order finite elements. First-order elements produced a 1.4% difference in transmantle pressure and a <10% difference in element-wise mass-weighted velocity metric for 90% of elements, while reducing computation time by 75% (20 to 5 min) and peak memory usage five-fold (150 to 30 GB). This proof-of-concept framework provides a computationally tractable baseline for studying steady net CSF pathway redistribution and sensitivity to boundary assumptions, and may support future patient-specific investigations in pathological conditions such as subarachnoid hemorrhage, hydrocephalus and brain tumors