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Signals and structures: the politics of corporate governance in Slovenia
No full textIn Slovenia’s boardrooms, governance is less a fixed blueprint than a living performance. Drawing on a decade of data from 24 public companies, we identify two distinct yet coexisting governance logics: identity-based, oriented toward symbolic compliance, and activity-based, linked to operational performance. Using factor analysis and hypothesis testing, we find that even moderate levels of state ownership are associated with stronger symbolic governance practices, while national elections prompt visible legitimacy signalling without substantive structural reform. Performance-oriented governance remains comparatively muted, suggesting that legitimacy concerns often outweigh efficiency in shaping board structures and practices. The Slovenian case illustrates how governance reforms—anchored in EU norms, sustainability frameworks, and market liberalisation—layer over, rather than replace, older institutional logics. The result is a hybrid governance form that is adaptive, performative, and politically attuned. These dynamics highlight how, in politicised markets, firms actively manage perceptions to maintain stability, often privileging visible conformity over operational change—an approach that deserves closer scrutiny from policymakers, investors, and scholars
Attitudes of Croatian Citizens toward AI-Based Body Augmentation: Generational Responses to Transhumanist Worldviews
No full textArtificial intelligence (AI) represents a key enabling force of transhumanism in contemporary visions of Homo sapiens technologicus, aimed at overcoming biological limitations of the human body. Young people, socialized in technologically saturated environments shaped by rapid technoscientific change, constitute a sociologically relevant group for examining transformations in perceptions of the body and human agency. This study empirically examines attitudes of citizens of the Republic of Croatia toward willingness to engage in AI-supported body augmentation across functional, health-related, physical-performance, and existential dimensions, with particular emphasis on generational differences. The findings show that most respondents express resistance to technological body enhancement, especially regarding cognitive control, contactless everyday functionalities, and cryonics. At the same time, a considerable proportion of respondents across all dimensions express ambivalent or undecided attitudes. Statistically significant generational differences in views on neural device control, health-preservation technologies, and physical augmentation indicate that younger generations are more inclined to perceive the body as open to technological intervention, while older generations adhere more strongly to notions of biological authenticity. The pronounced indecision among younger respondents suggests that transhumanist ideas, once confined to science fiction imaginaries, are increasingly entering everyday social consciousness without achieving full normative stabilization. By empirically identifying indecision as a distinctive generational feature, this study contributes to a sociological and interdisciplinary understanding of transhumanism as an ideological movement intertwined with AI and points to early stages of sociocultural adaptation toward transhumanist worldviews
Pilot Workload Identification During Engine Failure Landings
No full textPilot workload is a critical factor affecting flight safety, particularly in emergency situations such as engine failure during forced landings. This study aims to assess pilot workload during engine failure-induced forced landings compared to normal landings using EEG signals. EEG data were recorded from 21 pilots using a flight simulator and EEG acquisition equipment during both forced and normal landings. Subjective workload scores were obtained using a subjective workload scale. EEG features were extracted, and nonparametric tests were applied to assess the significance of these features at different workload levels. Subsequently, machine learning algorithms (SVC, KNN, RF and LightGBM) were employed to develop models for workload evaluation. The LightGBM model achieved a peak accuracy of 99.5% using the top 80% of all features (time-domain, frequency-domain and nonlinear features) as inputs. This study provides an effective quantitative approach for assessing pilot workload during emergency situations and offers valuable insights for improving flight safety and optimising pilot training programs
Preferences Regarding Parking and Sharing Use for Privately Owned Autonomous Vehicles Based on a Virtual-Actual Experience
No full textAutonomous vehicles are capable of automatically cruising and parking, presenting an opportunity for these vehicles to be shared with others during idle periods. This study conducted a face to face stated preference survey on parking and shared use of privately owned autonomous vehicles based on a virtual-actual experience in Beijing. Utilizing 232 valid samples, a nested Logit model was established to analyse the hierarchical choice behaviour regarding parking modes, parking locations and shared use of autonomous vehicles. The research results show that travellers with a favourable initial understanding of autonomous vehicles and a significantly improved perception of them after the travel experience are more likely to choose the parking mode of ‘Platform agency (parking + paid sharing)’. Travellers tend to prefer remote parking places that offer lower parking fees and higher reliability in vehicle retrieval when needed. Additionally, travellers are more inclined to share their autonomous vehicles when the vehicle-sharing service platform offers lower agency fees and higher sharing earnings and allows temporary vehicle retrieval. Increasing public sharing attitude and perception of autonomous vehicles through travel experiences and advertising can encourage more people to accept car sharing. These findings offer key insights into the factors that affect the market penetration of private vehicle-sharing services in future
Cascaded Multi-Level Inverter with Asymmetrical Voltage Sources Using Multicarrier PWM Strategies
No full textAdvanced multilevel inverters are pivotal in modern power electronics for achieving low-distortion waveforms and minimizing voltage stress on switching elements. This study introduces a cascaded H-bridge inverter design that employs asymmetrical DC sources configured in a trinary sequence, successfully delivering higher output voltage levels with fewer components than conventional topologies. A multi-carrier PWM approach is implemented with three modulation schemes Phase Disposition (PD), Phase Opposition Disposition (POD), and Alternate Phase Opposition Disposition (APOD) which are systematically evaluated through both MATLAB/Simulink simulations and hardware tests using a dSPACE DS1103 controller. Key performance measures, including total harmonic distortion, RMS voltage, crest factor, and form factor, are rigorously assessed. Experimental findings confirm that the APOD strategy offers superior harmonic suppression, while the trapezoidal MCPWM method enhances waveform quality and alleviates switch voltage stress. The results validate the proposed topology as an efficient, scalable solution for advanced power conversion applications
Kernel Extreme Learning Machine-Based Sentiment Analysis for Social Networks
No full textThe exponential growth of user-generated content on social media platforms presents both opportunities and challenges in extracting meaningful insights. Sentiment Analysis (SA), a critical component of contextual mining, enables the identification of subjective information embedded within textual data. This article proposes a novel Kernel Extreme Learning Machine-Based Sentiment Analysis of Social Networks Using Improved Dung Beetle Optimization (KELMSASN-IDBO) model, which combines advanced machine learning and nature-inspired optimization techniques to enhance sentiment classification accuracy. The model follows a structured pipeline: initially, raw textual data undergo thorough preprocessing to eliminate noise and standardize content. Subsequently, semantic features are extracted using Bidirectional Encoder Representations from Transformers (BERT) for effective word embedding. The resulting features are then classified using a Kernel Extreme Learning Machine (KELM), known for its high generalization performance and rapid learning speed. To optimize the performance of KELM, an Improved Dung Beetle Optimization (IDBO) algorithm is employed for fine-tuning hyperparameters. Experimental results demonstrate that the proposed KELMSASN-IDBO model outperforms conventional sentiment analysis techniques in terms of accuracy, efficiency, and robustness. The integration of deep contextual embeddings and hybrid optimization makes the proposed model a powerful tool for extracting sentiments from complex and large-scale social network data
Adaptive Wireless Power Transfer for Electric Vehicles: Dynamic Frequency Tuning and Intelligent Efficiency Optimization
No full textWireless Power Transfer (WPT) technology has attracted much attention because it is free from the limitations of physical cables, but its efficiency is limited by transmission distance, environmental interference and load changes. This paper presents an adaptive wireless energy transmission system with tuning and efficiency optimization of binary weighted capacitor arrays. By adjusting the resonant frequency and transmitting power in real time, combined with improved particle swarm optimization (PSO) intelligent optimization algorithm, the energy transmission efficiency and system stability can be significantly improved. The experimental results show that the power adaptive adjustment algorithm adjusts the transmit power according to SOC, and realizes fast charging, linear adjustment and trickle charging modes. Under the improved PSO strategy, the response time of the system to distance and load sudden change is less than 10 ms, the stability recovery time is less than 50 ms, and the efficiency recovery accounts for 89%, and the average efficiency of the optimized system is increased by 42.99%. When the load changes, the transmission efficiency fluctuates less than 2%, and the system has good robustness. After the introduction of metal barriers, the dynamic tuning efficiency of the system is maintained at 70.4%, and the unoptimized system efficiency is reduced to 44.6%, which indicates that the anti-interference performance of the system is good, and provides theoretical support for the design of high-efficiency wireless charging system for electric vehicles
Saša Horvat – Piotr Roszak (ur.), Neuroscience of Religion. Integratio Brain, Mind and Belifs, Springer, 2025. [Saša Horvat – Piotr Roszak (ur.), Neuroznanost religije: Integracija mozga, uma i vjerovanja, Springer, 2025.], 245 stranica.
No full textPrikaz knjige: Saša Horvat – Piotr Roszak (ur.), Neuroscience of Religion. Integratio Brain, Mind and Belifs, Springer, 2025. [Saša Horvat – Piotr Roszak (ur.), Neuroznanost religije: Integracija mozga, uma i vjerovanja, Springer, 2025.], 245 stranica
The impact of transformational leadership on frontline employees’ thriving in the hotel industry
No full textPurpose – In the fiercely competitive tourism industry, hotel management must cultivate
passionate frontline employees (FLEs) who perceive their roles as more than routine tasks,
aiming to enhance guest satisfaction. This study examines how transformational leadership
fosters FLEs’ thriving at work in Indonesian tourist hotels. Specifically, using the multiple
mediation model, this research investigates the mediating effects of a sense of calling,
acceptance of change, and friendship-based knowledge sharing (FKS).
Methodology/Design/Approach – Data were collected between January and February 2024
through a cross-sectional survey of 275 FLEs from 12 tourist hotels in Yogyakarta. SmartPLS
was used to test the hypotheses.
Findings – Transformational leadership positively influences thriving at work with sense
of calling, acceptance to change, and FKS as mediators. In addition, sense of calling and
acceptance to change sequentially enhance FKS, further strengthening thriving at work. This
serial mediation shows how transformational leadership indirectly enhances thriving through
multiple pathways.
Originality of the research – This research addresses gaps in previous studies by demonstrating
how transformational leadership drives FLEs’ thriving at work through fostering a sense of
calling, acceptance to change, and friendship knowledge sharing in the context of tourist hotels
Metaverse traveler: An expedition beyond reality
No full textPurpose – The aim of this research is to discuss the influence of metaverse platforms on
travel experiences and behavioral intention: how much there are inter-relationships between
immersion, the technical aspect, and user experience in virtual travel environments. This study
proposes and empirically tests a theoretical framework incorporating perceived enjoyment
and user curiosity as mediating variables.
Methodology/Design/Approach – The sample size used in the present study was 431
undergraduate students from an Indian university. The data collection was done through a
controlled experimental design using the drivenlisten platform.
Findings – The current study has evidence for significant positive relationships between the
technical aspect, user experience, feeling of immersion, and metaverse travel experiences.
Evidence of direct influences on travel intentions and indirect influences via perceived
enjoyment and user curiosity can be seen in this study. The structural model has shown robust
fit indices. The most important predictor of the metaverse travel experience was found to be
technical aspects, pointing toward critical technological infrastructure.
Originality of the research – This study extends the presence theory by updating knowledge
on the influence of virtual environments on travel behavior. The research makes a contribution
to the theoretical understanding of how immersive virtual environment technologies mold
travel-related decision-making processes