Search Results (59)

This study assessed the accuracy of a long-term AI-based projection of signs of facial aging and their acceptance by consumers. Standardized photographs of 25 Chinese and 25 French women were first taken at T0 and graded using ethnic-specific skin aging atlases. An AI-based algorithm then aged the photographs by 10 (T10) and 15 (T15) years. A total of 246 women from China, France, and Thailand compared these images in pairs (T0 vs. T0 + 10 or T0 + 15) and provided feedback on their overall impressions, realism, and psychological acceptance via a questionnaire. Besides lower face ptosis (p < 0.01), the simulated images revealed that regardless of ethnicity, there were no significant differences in grading. Irrespective of ethnic background, 62–78% of overall panelists found the projections realistic and liked them, while 85–96% of panelists (Chinese and French) were willing to test them. A total of 47% of Thai panelists were reluctant to try, while 4–14% found it scary. This indicated some degree of cultural influence. This study confirms women’s acceptance of future facial appearance with some degree of cultural divergence. It also highlights a valid methodology to explore skin aging for a more realistic and personalized cosmetic improvement and innovation. Full article

This study examines the relationship between crude oil returns (CRT) and Islamic stock returns (ISR) in BRIC countries during the Global Financial Crisis (GFC), employing wavelet-based comovement analysis and regression models that incorporate both contemporaneous and lagged CRT across 40 cases. The wavelet analysis reveals strong long-term comovement at low frequencies between ISR and CRT during the GFC. Contemporaneous regressions show that increases (decreases) in CRT align with corresponding movements in ISR. Lagged regressions indicate that CRT can predict ISR up to one week ahead for Brazil, Russia, and China, and up to two weeks for India, although the predictive strength weakens beyond this window. These findings challenge the perception that Islamic stocks were immune to the GFC, showing they were affected by global oil market dynamics, albeit with varying degrees of resilience across countries and time horizons. Full article

This study addresses the persistent issue of gender bias in project management by developing and validating a practical survey tool for monitoring gender-related perceptions within project implementation frameworks. Using a Knowledge, Attitudes, and Practices (KAP) approach, a survey instrument was designed to assess awareness of gender equity policies, perceptions of inclusivity, and experiences related to sexual harassment (SASH) within project teams. The tool was piloted in a Horizon Europe project (Healthy Sailing), with responses collected from 66 participants (academics, maritime professionals, researchers, and government stakeholders). Exploratory Factor Analysis (EFA) revealed a five-factor structure explaining 72.29% of total variance, with the two dominant factors—Perceived Gender Bias and Organizational Safety—demonstrating excellent internal consistency (Cronbach’s alpha > 0.90). Confirmatory Factor Analysis (CFA) and bifactor modeling indicated areas for further refinement, with RMSEA values exceeding optimal thresholds. The results underscore the potential of the KAP-based tool to support gender-sensitive quality management practices in project-based environments, while highlighting the need for ongoing psychometric validation. The study contributes a novel, empirically grounded instrument for promoting inclusivity and equity in project management. Full article

Climate change today is considered one of the most severe global problems. Additionally, it is inherently linked to sustainable development, particularly considering that it is a widespread problem affecting virtually all regions, countries, and continents. Therefore, it is essential to monitor its perception and behaviours towards it. Hence, there is the need for a diagnosis of climate-change attitudes found in various parts of the world. This premise is the foundation for the original study reported in the article. It offers the results of a survey of 300 adult rural residents from southeastern Poland. The article aims to diagnose the respondents’ attitudes towards climate change in the context of sustainable development premises. Respondents’ opinions on the potential activities their local communities could take to be more sustainable are a substantial part of the results. The most common suggestions were low-emission public transport (in the Wadowice District, it was 55% of responses) and road and street redesign to promote safe cycling and walking environments (in the Kraków and Tarnów Districts, over 50% of responses). The respondents found the promotion of sustainable development among youth and older people to be the least important (in three out of five districts, this percentage did not exceed 20%). The other thematic block was specific environmental protection and sustainable development activities that society should prioritise over a five-year horizon. The participants considered the development of new ways to eliminate waste in total production (in the Tarnów District, over 73% of responses), new technologies to curb the carbon footprint and GHG emissions (over 63% in the Wadowice District), and new technologies to scrape and monitor air pollutants (approx. 70% in the Kraków District). Full article

Air pollution is a major environmental and public health challenge, especially in urban areas where fine-grained air quality data are essential to effective interventions. Traditional monitoring networks, while accurate, often lack spatial resolution and public engagement. This study presents a novel wearable wireless sensor node (WSN) that was developed within the Horizon Europe SOCIO-BEE project to support air quality monitoring through citizen science (CS). The low-cost, body-mounted WSN measures NO₂, O₃, and PM_2.5. Three pilot campaigns were conducted in Ancona (Italy), Maroussi (Greece), and Zaragoza (Spain), and involved diverse user groups—seniors, commuters, and students, respectively. PM_2.5 sensor data were validated through two approaches: direct comparison with reference stations and spatial clustering analysis using K-means. The results show strong correlation with official PM_2.5 data (R² = 0.75), with an average absolute error of 0.54 µg/m³ and a statistical confidence interval of ±3.3 µg/m³. In Maroussi and Zaragoza, where no reference stations were available, the clustering approach yielded low intra-cluster coefficients of variation (CV = 0.50 ± 0.40 in Maroussi, CV = 0.28 ± 0.30 in Zaragoza), indicating that the measurements had high internal consistency and spatial homogeneity. Beyond technical validation, user engagement and perceptions were evaluated through pre-/post-campaign surveys. Across all pilots, over 70% of participants reported satisfaction with the system’s usability and inclusiveness. The findings demonstrate that wearable low-cost sensors, when supported by a structured engagement and data validation framework, can provide reliable, actionable air quality data, empowering citizens and informing evidence-based environmental policy. Full article

Safe real-world navigation for autonomous vehicles (AVs) requires robust perception and decision-making, especially in complex, multi-agent scenarios. Existing AV datasets are limited by their inability to capture diverse V2X communication scenarios, lack of synchronized multi-sensor data, and insufficient coverage of critical edge cases in multi-vehicle interactions. This paper introduces VRDeepSafety, a novel and scalable VR simulation platform that overcomes these limitations by integrating Vehicle-to-Everything (V2X) communication, including realistic latency, packet loss, and signal prioritization, to enhance AV accident prediction and mitigation. VRDeepSafety generates comprehensive datasets featuring synchronized multi-vehicle interactions, coordinated V2X scenarios, and diverse sensor data, including visual, LiDAR, radar, and V2X streams. Evaluated with our novel deep-learning model, VRFormer, which uniquely fuses VR sensor data with V2X using a probabilistic Bayesian inference, as well as a hierarchical Kalman and particle filter structure, VRDeepSafety achieved an 85% accident prediction accuracy (APA) at a 2 s horizon, a 17% increase in 3D object detection precision (mAP), and a 0.3 s reduction in response time, outperforming a single-vehicle baseline. Furthermore, V2X integration increased APA by 15%. Extending the prediction horizon to 3–4 s reduced APA to 70%, highlighting the trade-off between prediction time and accuracy. The VRDeepSafety high-fidelity simulation and integrated V2X provide a valuable and rigorous tool for developing safer and more responsive AVs. Full article

This qualitative study explores the perceptions and experiences of six newcomer parents from different countries (Afghanistan, Syria, Iran, Chile, Russia, and Ukraine) regarding their collaboration with Norwegian schools. Semi-structured in-depth interviews, ranging from 55 to 80 min, were conducted in participants’ native languages and English. Thematic analysis was employed to analyze the data. Four major themes emerged, as follows: (1) “Journeying Through Integration within the Norwegian Educational Landscape”; (2) “Collaboration: Dialogic or Monologic?”; (3) “Language and Communication Barriers”; and (4) “Navigating New Horizons”. The findings highlight that despite the challenges, participants expressed appreciation for the support they received from schools and teachers. The findings also indicate the need for schools to improve communication and cultural understanding to foster meaningful collaboration with newcomer parents. Schools must also provide more opportunities for parent involvement in decision-making processes. This study adds to the limited literature on newcomer parents’ perspectives on school collaboration and provides insights for policymakers, educators, and school administrators to enhance the educational experiences of newcomer students and their families in Norway. Full article

The article explores the unique friendship and creative synergy between two towering figures of late Soviet underground culture, the avant-garde jazz musician Sergei Kuriokhin and the poet Arkady Dragomoshchenko. Both outsiders in Leningrad, they shaped its literary and musical landscapes without aligning with any movements. Dragomoshchenko, a seminal poet, defied categorization, while Kuriokhin, a polymath, challenged conventions across music, performance, and politics. Their collaboration epitomized innovation, blending Dragomoshchenko’s cerebral poetry with Kuriokhin’s avant-garde music. Despite linguistic barriers, their connection transcended verbal communication, rooted in shared modes of nonlinear thinking and creative experimentation. Kuriokhin’s revolutionary Pop Mekhanika, a chaotic fusion of genres and sensory experiences, mirrored Dragomoshchenko’s relentless poetic evolution. Their friendship catalyzed pivotal encounters, such as with the American poet Lyn Hejinian, expanding their artistic horizons. Dragomoshchenko’s poetic vision, centred on perception’s fleeting nature and the boundaries of possibility, echoed Kuriokhin’s multisensory assaults on audience expectations. Through their unconventional artistry, Kuriokhin and Dragomoshchenko navigated the shifting cultural landscape of late Soviet society, embodying a spirit of defiance and exploration. Their enduring influence transcends their untimely deaths, leaving an indelible mark on Russian avant-garde culture. Full article

A global energy transition is crucial to combat climate change, involving a shift from fossil fuels to renewable sources and low-emission technologies. Solar photovoltaic technology has grown exponentially in the last decade, establishing itself as a cost-effective and sustainable option for electricity generation. However, its large-scale integration faces challenges due to its intermittency and lack of dispatchability. This study evaluates, from an energy perspective, the case of hybrid photovoltaic (PV) plants with battery storage systems. It addresses an aspect little explored in the literature: the sizing of battery storage to maintain a steady and constant 24 h power supply, which is usually avoided due to its high cost. Although the current economic feasibility is limited, the rapidly falling price of lithium batteries suggests that this solution could be viable in the near future. Using Matlab simulations, the system’s ability to deliver a constant energy production of electricity is assessed. Energy indicators are used to identify the optimal system size under different scenarios and power setpoints. The results determine the optimal storage size to supply a constant power that covers all or a large part of the daily PV generation, achieving steady and reliable electricity production. In addition, the impact of using setpoints at different time horizons is assessed. This approach has the potential to redefine the perception of solar PV, making it a dispatchable energy source, improving its integration into the electricity grid, and supporting the transition to more sustainable and resilient energy systems. Full article

Traceability is a cornerstone of sustainable honey production and consumption. Honey fraud and a lack of traceability have been recently highlighted by the European Commission. Innovative systems aimed at guaranteeing food safety ’from farm to fork’ and improved controls are highly recommended. Within the framework of the BPRACTICES project, part of the European Union’s Horizon 2020 research and innovation program, and the ERA-Net SusAn initiative—focused on Sustainable Animal Production Systems—an advanced traceability system has been developed. This system utilizes QR code and radio-frequency identification (RFID) technology, along with a user-friendly web application, to facilitate direct interactions between producers and consumers. Despite existing research, studies on the information needs of Italian consumers regarding honey and its traceability remain limited. Understanding these needs is vital for creating effective communication strategies that enhance consumer satisfaction and trust. This study aims to identify the needs of Italian consumers’ honey during the purchasing and consumption decisions. To explore consumer perceptions, behaviors, expectations, and needs regarding honey, we employed diverse social research methodologies, including a quantitative online survey, paper-and-pencil interviews, and focus groups. The results of this study indicate a robust demand for more information on honey’s origin, production processes, and beekeeping practices, aligning with the recent EU Directive 2024/1438, which mandates clear labeling. Italian consumers would be willing to pay a premium for honey that offers detailed information about production practices and transparency. The positive reception of QR code technology by consumers suggests a growing openness to digital tools that enhance transparency and access to information. Ultimately, this research emphasizes the need for the beekeeping sector to adopt sustainable practices, improve traceability systems, and actively engage with consumers to foster trust and ensure long-term viability in the honey market. By addressing these information needs, the sector can align itself with increasing consumer demand for quality, sustainability, and transparency. Full article

This essay assesses the relevance of Søren Kierkegaard’s non-pseudonymous, edifying writings for considering themes of desire, detachment, and humility within the religious context of Christian spiritual formation. Building on the argument of recent scholars who identify in Kierkegaard’s writings an account of a fundamental desire for God “implanted” in the human being, I explore the influence of this vision on Kierkegaard’s depiction of desire and detachment in his “Discourses on the Lilies and the Birds”. I then turn to how this relates to the perspective of humility that emerges from Kierkegaard’s reflections on the biblical story of “the widow’s mite”. In each case, these edifying writings aim to stir the reader into a process of interrogating faulty self-perceptions based on arbitrary measures of value. I read this mode of communication as able to initiate a “counter-experience”, provoking the reader to reorient her horizon of prior self-valuations so she might come to recognize the hidden significance of things and, ultimately, achieve a more accurate sense of oneself in relation to the authentic source of the self’s desire. Insofar as this reorientation of the self informs the practice of detachment or the development of humility, people might experience this same process in diverse ways. In this respect, the relevance of Kierkegaard’s edifying writings for reflecting on Christian spirituality is not that they provide a thoroughgoing account of detachment or humility that should replace the insights of various spiritual traditions. Rather, I argue that his discourses—when read alongside these traditions—offer a supplemental resource for reflecting on how our positionalities, dispositions, and proximate contexts will inform the divergent ways we might experience the practice of detachment or the manifestation of humility in each new life circumstance. Full article

Governments and energy providers all over the world are moving towards the use of renewable energy sources. Solar photovoltaic (PV) energy is one of the providers’ favourite options because it is comparatively cheaper, clean, available, abundant, and comparatively maintenance-free. Although the PV energy source has many benefits, its output power is dependent on continuously changing weather and environmental factors, so there is a need to forecast the PV output power. Many techniques have been employed to predict the PV output power. This work focuses on the short-term forecast horizon of PV output power. Multilayer perception (MLP), convolutional neural networks (CNN), and k-nearest neighbour (kNN) neural networks have been used singly or in a hybrid (with other algorithms) to forecast solar PV power or global solar irradiance with success. The performances of these three algorithms have been compared with other algorithms singly or in a hybrid (with other methods) but not with themselves. This study aims to compare the predictive performance of a number of neural network algorithms in solar PV energy yield forecasting under different weather conditions and showcase their robustness in making predictions in this regard. The performance of MLPNN, CNN, and kNN are compared using solar PV (hourly) data for Grahamstown, Eastern Cape, South Africa. The choice of location is part of the study parameters to provide insight into renewable energy power integration in specific areas in South Africa that may be prone to extreme weather conditions. Our data does not have lots of missing data and many data spikes. The kNN algorithm was found to have an RMSE value of 4.95%, an MAE value of 2.74% at its worst performance, an RMSE value of 1.49%, and an MAE value of 0.85% at its best performance. It outperformed the others by a good margin, and kNN could serve as a fast, easy, and accurate tool for forecasting solar PV output power. Considering the performance of the kNN algorithm across the different seasons, this study shows that kNN is a reliable and robust algorithm for forecasting solar PV output power. Full article

This paper investigates the drivers and dynamics of clustering and inter-project collaboration within the framework of the Horizon Europe and Horizon 2020 projects. Leveraging a survey-based approach, we examine key themes surrounding the perception of clustering, the willingness to share information under legal confidentiality, and motivations for engaging with partners from different projects. The survey instrument, implemented via Microsoft Forms, was distributed among the consortia of eight EU projects participating in the SOLID4B cluster. Notably, the questionnaire was meticulously crafted based on an in-depth analysis of the SOLID4B case and comprehensive discussions with project coordinators and communication and dissemination managers from all participating projects. These discussions aimed to establish a clear roadmap for the cluster, ensuring the questionnaire’s relevance and usefulness for all participants. Data analysis was conducted within the same platform, facilitating efficient data processing and visualization. Our findings reveal that a significant majority of respondents (48 out of 55) perceive clustering as a valuable asset, indicative of a positive shift in perspectives. Challenges related to confidentiality were addressed through nuanced insights, with respondents demonstrating a willingness to share routine best practices, significant breakthroughs, and deliverables within a legally protected framework. Furthermore, a robust majority (40 out of 55) expressed a keen interest in collaborative endeavors, underscoring a collective drive to extend activities beyond individual project boundaries. The study highlights the importance of clustering with other projects in maximizing the impact of the Horizon program, extending stakeholder networks, and sharing knowledge and achievements in research and innovation. These insights contribute to a deeper understanding of the motivations and challenges surrounding clustering and collaboration within the Horizon Europe and Horizon 2020 projects. Ultimately, the findings pave the way for informed strategies aimed at fostering a dynamic and interconnected research community. Full article

Project risk management (PRM) involves identifying risks, assessing their impact, and developing a contingency plan. A structured contingency management (CM) approach prevents subjective biases in analyzing risks and developing responses. Previous studies have either focused on improving the accuracy of risk estimates or analyzed, from a qualitative perspective, the relationships between perceived risk and project performance. This study aimed to improve PRM by providing a risk-perception-based contingency management framework (CMF). The CMF guides contingency depletion based on two short- and long-term cost overrun indicators and their respective thresholds. Thresholds and the initial contingency reserve amount are determined by applying the Monte Carlo method to a stochastic, discrete-event, finite-horizon, dynamic project simulation model. The study developed the CMF through a structured approach, validating the simulation model on eight specific project configurations. The results prove that the framework can be applied to any project, shaping the risk response strategy. This study contributes to PRM by explaining the relationships between risk perception and risk responses and providing a prescriptive CM tool. Full article

Anthropology has long resisted becoming a nomothetic science, thus repeatedly missing opportunities to build upon empirical theoretical constructs, choosing instead to back away into a kind of natural history of sociocultural differences. What is required are methods that focus the ethnographic gaze upon the essential structures of perception as well as sociocultural differences. The anthropology of experience and the senses is a recent movement that may be amenable to including a partnership between Husserlian phenomenology and neuroscience to build a framework for evidencing the existence of essential structures of consciousness, and the neurobiological processes that have evolved to present the world to consciousness as adaptively real. The author shows how the amalgamation of essences (sensory objects, relations, horizons, and associated intuitions) and the quest for neural correlates of consciousness can be combined to augment traditional ethnographic research, and thereby nullify the “it’s culture all the way down” bias of constructivism. Full article