Search Results (1,254)

To address the poor thermal performance and low output efficiency of conventional solid-state microchip lasers, this study proposes and implements a bonded Nd:YAG/Cr⁴⁺:YAG laser based on fiber splitter pumping. Experimental results demonstrate that at a 4.02 mJ pump pulse energy and a 100 Hz repetition rate, the system achieves four linearly polarized output beams with an average pulse energy of 0.964 mJ, a repetition rate of 100 Hz, and an optical-to-optical conversion efficiency of 23.98%. The energy distribution ratios for the upper-left, lower-left, upper-right, and lower-right beams are 22.61%, 24.46%, 25.50%, and 27.43%, with pulse widths of 2.184 ns, 2.193 ns, 2.205 ns, and 2.211 ns, respectively. As the optical axis distance increases, the far-field spot pattern transitions from a single circular profile to four fully separated spots, where the lower-right beam exhibits beam quality factors of M_x² = 1.181 and M_y² = 1.289. Simulations at a 293.15 K coolant temperature and a 4.02 mJ pump energy reveal that split pumping reduces the volume-averaged temperature rise in Nd:YAG by 28.81% compared to single-beam pumping (2.57 K vs. 3.61 K), decreases the peak temperature rise by 66.15% (6.97 K vs. 20.59 K), and suppresses peak-to-peak temperature variation by 78.6% (1.34 K vs. 6.26 K). Compared with existing multi-beam generation methods, the fiber splitter approach offers integrated advantages—including compact size, low cost, high energy utilization, superior beam quality, and elevated damage thresholds—and thus shows promising potential for automotive multi-point ignition, multi-beam single-photon counting LiDAR, and laser-induced breakdown spectroscopy (LIBS) online analysis. Full article

Generation Z (Gen Z; born 1997–2012) is reshaping global tourism through digital fluency, ethical awareness, and a desire for authentic, sustainable travel experiences. This study surveys 413 Gen Z travelers across France, Portugal, Romania, and the USA to map their booking behaviors, information sources, transport modes, accommodations, dining practices, and leisure activities. The findings reveal a strong preference for independent online bookings and social-media-influenced destination choices (Instagram, TikTok), with air and car travel being used for long-distance journeys and walking/public transit being used for local journeys. Accommodation spans commercial hotels and private rentals, while informal, local dining and nature- or culture-centered leisure prevail. Chi-square tests were performed to identify differences between countries. To reveal distinct traveler segments and their country’s modulations towards sustainability, a hierarchical cluster analysis was performed. The results uncover four segments: “Tech-Active, Nature-Oriented Minimalists” (32.3% in France); “Moderate Digital Planners” (most frequent across all countries, particularly dominant among Romanian respondents); “Disengaged and Indecisive Travelers” (overrepresented in the USA); and “Culturally Inclined, Selective Sustainability Seekers” (>30% in France/Portugal). Although sustainability is widely valued, only some segments of the studied population consistently act on these values. The results suggest that engaging Gen Z requires targeted, value-driven digital strategies that align platform design with the cohort’s diverse sustainability commitments. Full article

Void defects, manifested as distributed porosity, are common in metal additive manufacturing (AM) and can significantly degrade the mechanical performance and reliability of fabricated components. To enable real-time quality control during fabrication, this study proposes a grating laser ultrasonic method for the online evaluation of porosity in AM parts. Based on the theoretical relationship between surface acoustic wave (SAW) velocity and material porosity, a non-contact detection approach is developed, allowing the direct inference of porosity from the measured SAW velocities without requiring knowledge of the exact source–detector distance. Numerical simulations are conducted to analyze SAW propagation under varying porosity conditions and to validate the inversion model. Experimental measurements on aluminum alloy specimens with different porosity levels further confirm the sensitivity of SAW signals to internal voids. The results show consistent waveform and spectral trends between the simulation and experiment, supporting the feasibility of the proposed method for practical applications. Overall, the findings demonstrate the potential of this approach for the accurate online monitoring of void defects in metal AM components. Full article

Artificial Intelligence (AI) and computer-aided diagnosis (CAD) have revolutionised various aspects of modern life, particularly in the medical domain. These technologies enable efficient solutions for complex challenges, such as accurately segmenting brain tumour regions, which significantly aid medical professionals in monitoring and treating patients. This research focuses on segmenting glioma brain tumour lesions in MRI images by analysing them at the pixel level. The aim is to develop a deep learning-based approach that enables ensemble learning to achieve precise and consistent segmentation of brain tumours. While many studies have explored ensemble learning techniques in this area, most rely on aggregation functions like the Weighted Arithmetic Mean (WAM) without accounting for the interdependencies between classifier subsets. To address this limitation, the Choquet integral is employed for ensemble learning, along with a novel evaluation framework for fuzzy measures. This framework integrates coalition game theory, information theory, and Lambda fuzzy approximation. Three distinct fuzzy measure sets are computed using different weighting strategies informed by these theories. Based on these measures, three Choquet integrals are calculated for segmenting different components of brain lesions, and their outputs are subsequently combined. The BraTS-2020 online validation dataset is used to validate the proposed approach. Results demonstrate superior performance compared with several recent methods, achieving Dice Similarity Coefficients of 0.896, 0.851, and 0.792 and 95% Hausdorff distances of 5.96 mm, 6.65 mm, and 20.74 mm for the whole tumour, tumour core, and enhancing tumour core, respectively. Full article

The article aims to identify consumer types based on their attitudes and behaviors toward phygital tools and solutions. The analysis was based on the authors’ empirical research. The research was conducted on a sample of 2160 Polish consumers. The study employed an online survey technique. To determine the types of consumers, a 20-item scale was used, allowing the respondents to express their attitudes toward solutions and tools that improve shopping in the phygital space. The extraction of types was carried out in two steps. The first was cluster analysis, conducted using the hierarchical Ward method with the square of the Euclidean distance, and the second was non-hierarchical cluster analysis using the k-means method. As a result of the analyses, three relatively homogeneous types of consumers were distinguished: phygital integrators, digital frequenters, and physical reality anchors. The behaviours of consumers from each type were examined in the context of their impact on sustainable consumption and the sustainable development of the planet. The proposed typology contributes to developing consumer behavior theory in sustainable consumption environments. It provides practical implications for designing customer experiences that are more inclusive, resource-efficient, and aligned with responsible consumption patterns. Understanding how different consumer groups engage with phygital tools allows businesses and policymakers to tailor strategies that support equitable access to digital services and foster more sustainable, adaptive consumption journeys in an increasingly digitized marketplace. Full article

This paper investigates sustainable decision systems within green E-business models by analyzing how different O2O (online-to-offline) fulfillment structures affect emission-reduction efforts and pricing strategies in a two-tier supply chain consisting of a manufacturer and a new retailer. Three practical sales formats—package self-pickup, nearby delivery, and hybrid—are modeled using Stackelberg game frameworks that incorporate key factors such as inconvenience cost, logistics cost, processing fees, and emission-reduction coefficients. Results show that the manufacturer’s emission-reduction decisions and both parties’ pricing strategies are highly sensitive to cost conditions and consumer preferences. Specifically, higher inconvenience and abatement costs consistently reduce profitability and emission efforts; the hybrid model exhibits threshold-dependent advantages over single-mode strategies in terms of carbon efficiency and economic returns; and consumer green preference and distance sensitivity jointly shape optimal channel configurations. Robustness analysis confirms the model’s stability under varying parameter conditions. These insights provide theoretical and practical guidance for firms seeking to develop adaptive, low-carbon fulfillment strategies that align with sustainability goals and market demands. Full article

Data visualization has empowered analyzing, exploring, and communicating data effectively. It has been widely adopted across diverse disciplines. However, research indicates that data visualization in education is mainly favored in distance learning environments, leaving traditional classroom settings largely unexplored. Moreover, despite the growing emphasis on data-driven decision-making in education, a notable gap exists in using visualized assessment data to develop curriculum planning in language classrooms. Therefore, we developed a model for syllabus design and material development in an EFL classroom in Taiwan based on diagnostic test results. An online adaptive diagnostic test was used to gather visualized assessment data, which was analyzed with an AI tool to identify language learning needs and to develop the syllabus design and materials. By incorporating visualized diagnostic assessment data into the decision-making process, educators can design responsive and individualized syllabi that meet the needs of students. This approach enhances the effectiveness of language teaching and makes curriculum development more accessible and manageable for educators. Full article

The digital age has transformed education, making distance learning essential. With rapid knowledge evolution, flexible and personalized learning is crucial. This article examines how ontology and semantic web technologies enhance e-learning. Ontology structures knowledge in specific domains, while the semantic web enables data automation and integration. Their adoption revolutionizes content organization and personalization. This study explores key concepts, applications, benefits, challenges, and future implications. By analyzing innovations and obstacles, it provides recommendations for educators. Ultimately, it highlights the need for a collaborative approach to leverage these technologies for a more inclusive and adaptive educational environment. Full article

This qualitative study investigates how critical thinking is cultivated in postgraduate distance learning, focusing on two time points, 2016 and 2025, in the context of the Greek higher education system. It draws on semi-structured interviews with 30 participants (15 tutors and 15 students or graduates) from two online postgraduate programmes: Education Sciences and Education and Technologies in Distance Teaching and Learning Systems. Thematic analysis was used to explore participants’ perceptions of critical thinking development. The two-phase comparison captures how understandings and practices have evolved, particularly in light of the emergence of generative AI between 2016 and 2025. In Phase B, this research specifically examines AI’s potential role in supporting critical thinking and the pedagogical adaptations required by tutors. Nine key themes were identified. One of the most pressing concerns raised was that educators are perceived as largely ineffective in fostering critical thinking through online teaching. This study contributes empirical insight and practical recommendations to improve critical thinking cultivation in digital learning environments, especially in the age of AI. Full article

Marine animals without faces (MAWFs), are some of the most important creatures maintaining the ecological balance in marine environments. How these animals are depicted across conservation organizations may impact public perceptions and conservation efforts. We assessed the online presentation of sea stars, jellies, and corals among all public websites of institutions accredited by the Association of Zoos and Aquariums (AZA) (N = 237). Among the organizations with an aquarium (n = 125), only 55 (44 percent) profiled at least one of the three animals, resulting in 89 total profiles. Five general approaches to characterizing these animals emerged: (1) scientific social distancing, (2) beautiful and eye-catching, (3) grotesque, otherworldly, and strange, (4) brainless beauties, and (5) objects of touch, entertainment, and experience. While some practices, like touch exhibits, can support empathy outcomes among visitors, online profile practices may contribute to the objectification of these animals among visitors, which could ultimately impact conservation attitudes, intentions, and behaviors. Full article

Objectives: Online healthcare offers an effective solution to reduce regional disparities in medical access. However, building patient trust in a virtual environment, particularly amid digital divide challenges, remains critical for the sustainable development of healthcare platforms. This study investigates how doctors’ professional experience, communicated through online biographies, influences patient consultation decisions, aiming to uncover strategies that enhance trust and facilitate efficient doctor–patient matching. Methods: Drawing on trust theory and social distance theory, we develop an empirical model incorporating professional signals, follower community engagement, and sentiment intensity. Using text data and topic modeling from a leading online health platform, we analyze the impact of these factors on patient consultation behavior. Results: The findings demonstrate that professional experience significantly increases consultation purchases, partially mediated by active follower communities. Additionally, positive emotional expressions in biographies reduce perceived social distance, thereby strengthening trust and willingness to consult. These results highlight the combined effectiveness of professional signals and emotional cues in fostering patient trust. Conclusions: Strategically designed doctor profiles, integrating professional and emotional elements, can bridge the digital divide in online healthcare by enhancing trust and improving doctor-patient matching. This study advances the understanding of how online biographical narratives shape trust and decision-making, offering novel insights into the interplay of doctor-generated content, trust, and social distance. Full article

With the increasing demand for takeaway delivery, more merchants are developing their takeaway delivery system to manage order fulfillment and enhance the consumer online experience. This study presents a mathematical model for merchant-operated takeaway delivery, using an improved ant colony algorithm integrated with K-means to cluster customer locations and determine optimal routes. We propose two fairness strategies—order quantity and travel distance—to ensure equitable workload distribution among riders. The K-means algorithm is enhanced by reallocating cluster assignments based on the nodes’ distances to all cluster centers. The simulation results demonstrate that the designed algorithm and strategies generate efficient optimal delivery plans for merchants. Full article

Objective: The objective of this study was to develop and assess the clinical feasibility of auto-segmentation and auto-planning methodologies for automated radiotherapy in prostate cancer. Methods: A total of 166 patients were used to train a 3D Unet model for segmentation of the gross tumor volume (GTV), clinical tumor volume (CTV), nodal CTV (CTVnd), and organs at risk (OARs). Performance was assessed by the Dice similarity coefficient (DSC), the Recall, Precision, Volume Ratio (VR), the 95% Hausdorff distance (HD95%), and the volumetric revision degree (VRD). An auto-planning network based on a 3D Unet was trained on 77 treatment plans derived from the 166 patients. Dosimetric differences and clinical acceptability of the auto-plans were studied. The effect of OAR editing on dosimetry was also evaluated. Results: On an independent set of 50 cases, the auto-segmentation process took 1 min 20 s per case. The DSCs for GTV, CTV, and CTVnd were 0.87, 0.88, and 0.82, respectively, with VRDs ranging from 0.09 to 0.14. The segmentation of OARs demonstrated high accuracy (DSC ≥ 0.83, Recall/Precision ≈ 1.0). The auto-planning process required 1–3 optimization iterations for 50%, 40%, and 10% of cases, respectively, and exhibited significant better conformity (p ≤ 0.01) and OAR sparing (p ≤ 0.03) while maintaining comparable target coverage. Only 6.7% of auto-plans were deemed unacceptable compared to 20% of manual plans, with 75% of auto-plans considered superior. Notably, the editing of OARs had no significant impact on doses. Conclusions: The accuracy of auto-segmentation is comparable to that of manual segmentation, and the auto-planning offers equivalent or better OAR protection, meeting the requirements of online automated radiotherapy and facilitating its clinical application. Full article

Background: Charitable crowdfunding platforms have become widely used tools for raising funds to support social and humanitarian causes. As participation in these platforms is voluntary, understanding the influence of individual motivations and cultural values is essential, particularly when engaging donors across culturally diverse regions. Within the framework of Self-Determination Theory (SDT), this study explores whether consumers’ cultural orientations influence their motivations and levels of engagement in charitable crowdfunding. Methods: Data were collected through an online survey using the Computer-Assisted Web Interviewing (CAWI) method from 680 participants recruited via Amazon Mechanical Turk. Structural equation modeling was employed to analyze the effects of three cultural dimensions—collectivism, power distance, and uncertainty avoidance—on charitable giving behavior, including their interactions with intrinsic and extrinsic motivations. Results: Collectivism was found to positively predict charitable giving, while uncertainty avoidance had a negative effect. Power distance showed a mixed influence, depending on the underlying motivational factors. Comparative analysis revealed significant regional differences, particularly between respondents from the Americas and Europe, in the strength and nature of these relationships. Conclusions: The findings underscore the importance of integrating cultural factors into digital fundraising strategies and offer new insights into how individual cultural values shape prosocial behavior in online crowdfunding environments. Full article

This study examines the evolving relationship between online media coverage and protest movements by analyzing year-long demonstrations in Israel against Prime Minister Benjamin Netanyahu. Through comprehensive qualitative thematic analysis and content analyses of 219 online newspaper articles from five major Israeli newspapers; 324 social media posts across Facebook, Instagram, and Twitter; and 9 semi-structured interviews with protest leaders, this research identifies a gradual paradigm shift in protest representation in online media. The findings reveal a transition from the traditional “protest paradigm”—which frames protests as violent and remote through warlike discourse and visual distancing—toward an emerging “our protest paradigm”, characterized by rhetorical and visual proximity to protesters. This new paradigm manifests through personal testimonies in mainstream media and portrait photography on social media platforms, both creating a sense of closeness and accountability. The study further reveals a significant disconnect between protest leaders’ perceptions and legacy media, as leaders increasingly view traditional media as irrelevant despite their advisers’ recommendations to engage with it. Using polysystem theory as a theoretical framework, this research demonstrates how two media systems—legacy media and social media—operate with epistemological rigidity, challenging the previously established notion of “competitive symbiosis” between protesters and journalists. This investigation offers a novel analytical perspective through the lens of distance, illuminating how changing dynamics in online information transfer are reshaping protest coverage and production. The resulting paradigm model explains the coexistence of two simultaneous protest paradigms and provides valuable insights into the contemporary relationship between social movements, legacy media, and digital platforms in an evolving media ecosystem. Full article