Search Results (1,409)

This study assesses the quality of financial reporting in ten Central and Eastern European countries using a methodology based on natural language processing (NLP) techniques. 570 annual reports of companies listed on the main index on the stock exchanges of 10 Central and Eastern European (CEE) countries, over the period 2019–2023, were evaluated to determine the degree of convergence of the following four measurable qualitative characteristics: relevance, exact representation, comparability and understandability. The main objective is to identify consistency in the quality of accounting information based on the application of an international financial reporting framework. The applied methodology eliminates subjective variability by implementing a standardized scoring system, aligned with the criteria developed by NiCE, using libraries such as spaCy and NLTK for term extraction, respective sentiment analysis and word frequency evaluation. The results reveal significant heterogeneity in all characteristics examined, with statistical tests confirming substantial differences between countries. The investigation of relevance revealed partial convergence, with three dimensions achieving complete uniformity, while the exact representation showed the highest variability. The assessment of comparability showed a significant difference between countries’ extreme values, and in terms of comprehensibility a formalistic approach was evident, with technical dimensions outweighing user-oriented aspects. The overall quality index varied significantly across countries, with a notable average deterioration in 2023, indicating structural vulnerabilities in financial reporting systems. These findings support initial hypotheses on the lack of homogeneity in the quality of financial reporting in the selected region, despite the implementation of international standards. Full article

With the rapid development of video streaming services, adaptive bitrate (ABR) algorithms have become a core technology for ensuring optimal viewing experiences. Traditional ABR strategies, predominantly rule-based or reinforcement learning-driven, typically employ uniform quality assessment metrics that overlook users’ subjective preference differences regarding factors such as video quality and stalling. To address this limitation, this paper proposes an adaptive video bitrate selection system that integrates preference modeling with reinforcement learning. By incorporating a preference learning module, the system models and scores user viewing trajectories, using these scores to replace conventional rewards and guide the training of the Proximal Policy Optimization (PPO) algorithm, thereby achieving policy optimization that better aligns with users’ perceived experiences. Simulation results on DASH network bandwidth traces demonstrate that the proposed optimization method improves overall Quality of Experience (QoE) by over 9% compared to other mainstream algorithms. Full article

This study investigates the thermal stability and microstructural evolution of the solid electrolyte medium used in DLyte^® dry electropolishing and dry anodizing processes. Samples were thermally aged between 30 °C and 45 °C to simulate Joule heating during industrial operation. Visual and SEM analyses revealed shape deformation and microcrack formation at temperatures above 40 °C, potentially reducing particle packing efficiency and electrolyte performance. Particle size distribution shifted from bimodal to trimodal upon aging, with an overall size reduction of up to 39.5% due to dehydration effects, impacting ionic transport properties. Weight-loss measurements indicated a diffusion-limited dehydration mechanism, stabilizing at 15–16% mass loss. Fourier transform infrared analysis confirmed water removal while maintaining the essential sulfonic acid groups responsible for ionic conductivity. In dry anodizing tests on titanium, aged electrolytes enhanced process efficiency, producing TiO₂ films with improved optical properties—color and brightness—while preserving thickness and uniformity (~70 nm). The results highlight the need to carefully control thermal exposure to maintain electrolyte integrity and ensure consistent process performance. Full article

Beech forests in the Italian peninsula are actively managed and they also support a high level of biodiversity. Hence, biodiversity conservation can be synergistic with timber production and carbon sequestration, enhancing the overall economic benefits of forest management. This study aimed to evaluate the effect of forest management regimes on bird communities in the Italian Peninsula during 2022 through audio recordings. We studied the structure, composition, and specialization of the breeding bird community in four managed beech stands (three even-aged beech stands aged 20, 60, and 100 years old, managed by a uniform shelterwood system; one uneven-aged stand, managed by a single-tree selection system) and one uneven-aged, unmanaged beech stand in the northern Apennines (Tuscany region, Italy). Between April and June 2022, data were collected through four 1-hour audio recording sessions per site, analyzing 5 min sequences. The unmanaged stand hosted a richer (a higher number of species, p < 0.001) and more specialized (a higher number of cavity-nesting species, p < 0.001; higher Woodland Bird Community Index (WBCI) values, p < 0.001; and eight characteristic species, including at least four highly specialized ones) bird community, compared to all the managed forests; moreover, the latter were homogeneous (similar to each other). Our study suggests that the unmanaged beech forests should be a priority option for conservation, while in terms of the managed beech forests, greater attention should be paid to defining the thresholds for snags, deadwood, and large trees to be retained to enhance their biodiversity value. Studies in additional sites, conducted over more years and including multi-taxon communities, are recommended for a deeper understanding and generalizable results. Full article

Reinforced concrete (RC) deep beams constructed with low-strength concrete are susceptible to sudden splitting failures in the strut region due to shear–compression stresses. To mitigate this vulnerability, various strengthening techniques, including steel plates, fiber-reinforced polymer sheets, and cementitious composites, have been explored to confine the strut area. This study investigates the structural performance of RC deep beams with low-strength concrete, strengthened externally using an Engineered Cementitious Composite (ECC) layer. To ensure effective confinement and uniform shear distribution, shear reinforcement was provided at equal intervals with configurations of zero, one, and two vertical shear reinforcements. Four-point bending tests revealed that the ECC layer significantly enhanced the shear capacity, increasing load-carrying capacity by 51.6%, 54.7%, and 46.7% for beams with zero, one, and two shear reinforcements, respectively. Failure analysis through non-linear finite element modeling corroborated experimental observations, confirming shear–compression failure characterized by damage in the concrete struts. The strut-and-tie method, modified to incorporate the tensile strength of ECC and shear reinforcement actual stress values taken from the FE analysis, was used to predict the shear capacity. The predicted values were within 10% of the experimental results, underscoring the reliability of the analytical approach. Overall, this study demonstrates the effectiveness of ECC in improving shear performance and mitigating strut failure in RC deep beams made with low-strength concrete. Full article

This paper reviews the fundamental principles and techniques of nickel electrodeposition, with a particular focus on metallizing polymeric substrates. It outlines the electrochemical mechanisms involved in depositing nickel from an acidic Watts bath, detailing the roles of key electrolyte components—i.e., nickel sulfate, nickel chloride, and boric acid—and the influence of process parameters, such as current density, temperature, and pH, on deposit quality (density and surface condition) and mechanical properties. In addressing the unique challenges posed by non-conductive polymers, this review compares emerging methods like silver conductive paint, highlighting differences in deposition time, surface resistivity, and environmental impact. Additionally, this paper examines how process parameters affect the as-deposited microstructure, adhesion, and overall mechanical properties (such as hardness, ductility, and tensile strength), while identifying critical issues such as low deposition density and substrate degradation. These insights provide a structured background for optimizing electroplating processes for applications in electronics, automotive, aerospace, and biomedical sectors, and suggest future research directions to enhance deposition uniformity, sustainability, and process control. Full article

Cannabis sativa L. is a versatile plant with applications in various sectors such as agriculture, medicine, food, and cosmetics. The therapeutic properties of cannabis are often linked to its secondary compounds. The worldwide cannabis market is undergoing swift changes due to varying legal frameworks. Medicinal cannabis (as a heterozygous and dioecious species) is distinct from most annual crops grown in controlled environments, typically propagated through stem cutting rather than seeds to ensure genetic uniformity. Consequently, as with any commercially cultivated crop, biomass yield plays a crucial role in overall productivity. The key factors involved in cultivation conditions, such as successful root establishment, stress tolerance, and the production cycle duration, are critical for safeguarding, improving, and optimizing plant yield. Grafting is a long-established horticultural practice that mechanically joins the scion and rootstock of distinct genetic origins by merging their vascular systems. This approach can mitigate undesirable traits by leveraging the strengths of particular plants, proving beneficial to various applications. Grafting is not used commercially in Cannabis. Only three very recent investigations suggest that grafting holds significant promise for enhancing both the agronomic and medicinal potential of Cannabis. This review critically examines the latest advancements in cannabis grafting and explores prospects for improving biomass (stem, root, flower, etc.) yield and secondary metabolite production. Full article

To address the growing demand for sustainable materials in advanced manufacturing, the objective of this study was to develop and characterize a novel 3D-printable biocomposite using ruminant-digested corn stover (DCS) as a reinforcement for polylactic acid (PLA). The methodology involved systematically optimizing DCS particle size (80–140 mesh) and loading concentration (5–20 wt.%), followed by fabricating composite filaments via melt extrusion and 3D printing test specimens. The resulting materials were comprehensively characterized for their morphological, physical, and mechanical properties. The optimal formulation, achieved with 120-mesh particles at 15 wt.% loading, exhibited a 15.6% increase in tensile strength to 64.17 MPa and a 21.1% enhancement in flexural modulus to 4.19 GPa compared to neat PLA. In addition to the mechanical improvements, the biocomposite offers an advantageous density reduction, enabling the fabrication of lightweight structures for resource-efficient applications. Comprehensive characterization revealed effective interfacial integration and uniform fiber dispersion, validating biological preprocessing as a viable method for unlocking the reinforcement potential of this abundant biomass. While the composite exhibits characteristic trade-offs, such as reduced impact strength, the overall performance profile makes it a promising candidate for structural applications in sustainable manufacturing. This research establishes a viable pathway for agricultural waste valorization, demonstrating that biological preprocessing can convert agricultural residues into value-added engineering materials for the circular bioeconomy. Full article

Background: Acute myeloid leukemia (AML) is a common and aggressive adults hematological malignancies. This study explored megakaryocyte–erythroid progenitors (MEPs) signature genes and constructed a prognostic model. Methods: Uniform manifold approximation and projection (UMAP) identified distinct cell types, with differential analysis between AML-MEP and normal MEP groups. Univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression selected biomarkers to build a risk model and nomogram for 1-, 3-, and 5-year survival prediction. Results: Ten differentially expressed genes (DEGs) related to overall survival (OS), six (AHSP, MYB, VCL, PIM1, CDK6, as well as SNHG3) were retained post-LASSO. The model exhibited excellent efficiency (the area under the curve values: 0.788, 0.77, and 0.847). Pseudotime analysis of UMAP-defined subpopulations revealed that MYB and CDK6 exert stage-specific regulatory effects during MEP differentiation, with MYB involved in early commitment and CDK6 in terminal maturation. Finally, although VCL, PIM1, CDK6, and SNHG3 showed significant associations with AML survival and prognosis, they failed to exhibit pathological differential expression in quantitative real-time polymerase chain reaction (qRT-PCR) experimental validations. In contrast, the downregulation of AHSP and upregulation of MYB in AML samples were consistently validated by both qRT-PCR and Western blotting, showing the consistency between the transcriptional level changes and protein expression of these two genes (p < 0.05). Conclusions: In summary, the integration of single-cell/transcriptome analysis with targeted expression validation using clinical samples reveals that the combined AHSP-MYB signature effectively identifies high-risk MEP-AML patients, who may benefit from early intensive therapy or targeted interventions. Full article

Depending on the feedstock type and the pyrolysis conditions, biochars exhibit different physical, chemical, and structural properties, which highly influence their performance in various applications. This study presents a comprehensive characterization of biochar materials derived from the waste wood of pine (Pinus sylvestris L.) and beech (Fagus sylvatica) after low-temperature pyrolysis at 270 °C, followed by chemical activation using zinc chloride. The resulting materials were thoroughly analyzed in terms of their chemical composition (FTIR), thermal behavior (TGA/DTG), structural morphology (SEM and XRD), elemental analysis, and particle size distribution. The successful modification of raw biomass into carbon-rich structures of increased aromaticity and thermal stability was confirmed. Particle size analysis revealed that the activated carbon of Fagus sylvatica (FSAC) exhibited a monomodal distribution, indicating high homogeneity, whereas Pinus sylvestris-activated carbon showed a distinct bimodal distribution. This heterogeneity was supported by elemental analysis, revealing a higher inorganic content in pine-activated carbon, likely contributing to its dimensional instability during activation. These findings suggest that the uniform morphology of beech-activated carbon may be advantageous in filtration and adsorption applications, while pine-activated carbon’s heterogeneous structure could be beneficial for multifunctional systems requiring variable pore architectures. Overall, this study underscored the potential of chemically activated biochar from lignocellulosic residues for customized applications in environmental and material science domains. Full article

Gender inequality remains a persistent challenge in academia, shaping career trajectories and access to critical resources. Research funding plays a central role in academic advancement, yet studies of gender disparities often overlook how patterns vary across disciplines and stages of the grant process. This study analyzes gender differences in both the submission and allocation phases using administrative data from four national Israeli funding agencies, covering nearly 5000 applications submitted over two years (2017–2018). It examines two key dimensions within both stages—PI gender and grant amount—and disaggregates results across 12 academic fields. The findings indicate isolated, rather than systematic, gender inequalities, with disparities appearing more frequently in STEM fields but remaining limited overall. The results underscore the importance of field-specific analysis for understanding gender inequality and suggest that targeted interventions, rather than uniform policies, are needed to promote gender equity in research funding. Full article

This study evaluates leadership uniformity—the degree to which the proposer role is evenly distributed among validator nodes over time—in Quorum-based Byzantine Fault Tolerance (QBFT), a Byzantine Fault-Tolerant (BFT) consensus algorithm used in permissioned blockchain networks. By introducing simulated follower timeouts derived from uniform, normal, lognormal, and Weibull distributions, it models a range of network conditions and latency patterns across nodes. This approach integrates Raft-inspired timeout mechanisms into the QBFT framework, enabling a more detailed analysis of leader selection under different network conditions. Three leader selection strategies are tested: Direct selection of the node with the shortest timeout, and two quorum-based approaches selecting from the top 20% and 30% of nodes with the shortest timeouts. Simulations were conducted over 200 rounds in a 10-node network. Results show that leader selection was most equitable under the Weibull distribution with shape $k=0.5$, which captures delay behavior observed in real-world networks. In contrast, the uniform distribution did not consistently yield the most balanced outcomes. The findings also highlight the effectiveness of quorum-based selection: While choosing the node with the lowest timeout ensures responsiveness in each round, it does not guarantee uniform leadership over time. In low-variability distributions, certain nodes may be repeatedly selected by chance, as similar timeout values increase the likelihood of the same nodes appearing among the fastest. Incorporating controlled randomness through quorum-based voting improves rotation consistency and promotes fairer leader distribution, especially under heavy-tailed latency conditions. However, expanding the candidate pool beyond 30% (e.g., to 40% or 50%) introduced vote fragmentation, which complicated quorum formation in small networks and led to consensus failure. Overall, the study demonstrates the potential of timeout-aware, quorum-based leader selection as a more adaptive and equitable alternative to round-robin approaches, and provides a foundation for developing more sophisticated QBFT variants tailored to latency-sensitive networks. Full article

Individuals with Autism Spectrum Disorder (ASD) often experience sensory hyperreactivities that interfere with daily life activities. White noise, characterized by its uniformity and its ability to mask environmental sounds, may serve as a tool to improve sensory and emotional regulation in children with ASD. The primary objective was to evaluate the response to white noise in improving self-regulation in minors with ASD. As a secondary objective, the study assessed whether there were differences in the response to white noise between patients with ASD and those with ASD and Intellectual Disability (ID). This study was conducted in the Child and Adolescent Psychiatry and Psychology Department of Hospital Clínic of Barcelona. A total of 54 patients, aged between 7 and 17 years, were included. The patients were divided into two groups: Group 1 consisted of patients diagnosed with ASD (n = 21), and Group 2 included patients diagnosed with ASD and ID (n = 33). White noise was offered to the patients, and their response was evaluated before and after the exposure using the Conners Teacher Rating Scale. Overall, the response to white noise in the sample was positive, with a significant difference in scores on the Conners Teacher Rating Scale (p < 0.001). When dividing the sample into the ASD group and the ASD + ID group, it was observed that the ASD + ID group tolerated white noise better and had a longer exposure time, although both groups showed improved scores on the Conners Teacher Rating Scale. White noise may be a valuable tool to enhance well-being in individuals with ASD, reduce motor restlessness, and increase attention span and emotional stability. However, its effectiveness varies across individuals. It is recommended to tailor its use to individual needs and to extend future research by incorporating physiological measures and larger sample sizes. Full article

In the industrial practice of metal forming, the consistent and reasonable characterization of the material behavior under the coupling effect of strain, strain rate, and temperature on the material flow stress is very important for the design and optimization of process parameters. The purpose of this work was to establish an appropriate constitutive model to characterize the rheological behavior of a hot-formed steel plate (22MnB5 steel) produced through the TSCR (Thin Slab Casting and Rolling) process under practical deformation temperatures (150–250 °C) and strain rates (0.001–3000 s⁻¹). Subsequently, the material flow behavior was modeled and predicted using the Johnson–Cook flow stress constitutive model. In this study, uniaxial tensile tests were conducted on 22MnB5 steel at room temperature under varying strain rates, along with elevated-temperature tensile tests at different strain rates, to obtain the engineering stress–strain curves and analyze the mechanical properties under various conditions. The results show that during room-temperature tensile testing within the strain rate range of 10⁻³ to 300 s⁻¹, the 22MnB5 steel exhibited overall yield strength and tensile strength of approximately 1500 MPa, and uniform elongation and fracture elongation of about 7% and 12%, respectively. When the strain rate reached 1000–3000 s⁻¹, the yield strength and tensile strength were approximately 2000 MPa, while the uniform elongation and fracture elongation were about 6% and 10%, respectively. Based on the experimental results, a modified Johnson–Cook constitutive model was developed and calibrated. Compared with the original model, the modified Johnson–Cook model exhibited a higher coefficient of determination (R²), indicating improved fitting accuracy. In addition, to predict the material’s damage behavior, three distinct specimen geometries were designed for quasi-static strain rate uniaxial tensile testing at ambient temperature. The Johnson–Cook failure criterion was implemented, with its constitutive parameters calibrated through integrated finite element analysis to establish the damage model. The determined damage parameters from this investigation can be effectively implemented in metal forming simulations, providing valuable predictive capabilities regarding workpiece material performance. Full article

Conventional space vector pulse width modulation (CSVPWM) with the fixed switching frequency generates significant sideband harmonics in the three-phase voltage. Discrete random switching frequency SVPWM (DRSF-SVPWM) methods have been widely applied in motor control systems for the suppression of tone harmonic energy. To further reduce the amplitude of the high-frequency harmonic with a limited switching frequency variation range, this paper proposes a time-division subbands beta distribution random SVPWM (TSBDR-SVPWM) method. The overall frequency band of the switching frequency is equally divided into N subbands, and each fundamental cycle of the line voltage is segmented into 2*(N-1) equal time intervals. Additionally, within each time segment, the switching frequency is randomly selected from the corresponding subband and follows the optimal discrete beta distribution. The switching frequency harmonic energy in the line voltage spectrum spreads across multiple frequency subbands and discrete frequency components, thereby forming a more uniform power spectrum of the line voltage. Both simulation and experimental results validate that, compared with CSVPWM, the sideband harmonic amplitude is reduced by more than 8.5 dB across the entire range of speed and torque conditions in the TSBDR-SVPWM. Furthermore, with the same variation range of the switching frequency, the proposed method achieves the lowest switching frequency harmonic amplitude and flattest line voltage spectrum compared with several state-of-the-art random modulation methods. Full article