Search Results (108)

This article traces the historical evolution of mural painting as a medium of cultural expression from prehistoric cave art to contemporary street interventions. Adopting a diachronic and interdisciplinary approach, it investigates how muralism has developed across civilizations in relation to techniques, symbolic systems, social function, and its embeddedness in architectural and urban contexts. The analysis is structured around key historical periods using emblematic case studies to examine the interplay between materiality, iconography, and socio-political meaning. From sacred enclosures and civic monuments to post-industrial walls and digital projections, murals reflect shifting cultural paradigms and spatial dynamics. This study emphasizes how mural painting, once integrated into sacred and imperial architecture, has become a tool for public participation, protests, and urban storytelling. Particular attention is paid to the evolving relationship between wall painting and the spaces it inhabits, highlighting the transition from permanence to ephemerality and from monumentality to immediacy. This article contributes to mural studies by offering a comprehensive framework for understanding the technical and symbolic transformations of the medium while proposing new directions for research in the context of digital urbanism and cultural memory. Full article

Background: This study compares the cost-utility, visual acuity, and humanistic outcomes of phacoemulsification surgery performed during international outreach campaigns to outcomes in the U.S. Objective: Humanitarian organizations frequently perform cataract surgeries in underserved regions, yet the outcomes of phacoemulsification in these settings remain unexplored. This study aims to compare the visual acuity outcomes, quality-of-life outcomes, and cost of phacoemulsification surgery during international outreach campaigns with those in the U.S. Methods: This retrospective review analyzed 344 cases from Women for World Health (W4WH) missions and 305 consecutive cases from the academic practice of the lead surgeon of W4WH in the US. The pre-operative (pre-op) visual acuity, post-operative (post-op) visual acuity at day 1, and best-corrected visual acuity (BCVA) at post-op month 1 were compared to baseline. The change in visual acuity was compared between the two groups. Complication rates, cost per case, and quality-of-life measures were evaluated for the mission group compared to cataract surgery outcomes in the developed world. Results: The mission cohort had worse baseline visual acuity than the U.S. cohort (1.36 logMAR vs. 0.50 logMAR, p < 0.0001) and showed greater mean improvement (1.24 logMAR vs. 0.35 logMAR, p < 0.0001). Both cohorts achieved similar BCVA at post-op month 1 (0.13 logMAR). The cost for the mission group was USD 276 per surgery. A total of 93.94% of patients in the mission group achieved a BCVA of 20/40 or better, which is comparable to the U.S. outcomes. Conclusions: The dramatic impact, immediacy, and enduring effect of cataract surgery using phacoemusification on quality of life, mental health, and economic return on investment make it the ideal procedure for humanitarian settings. Considering all of the available metrics, our data support the continued expansion of humanitarian efforts by cataract surgery organizations worldwide. Full article

Communications in delay-tolerant networking (DTN) environments like deep space face significant challenges due to immense distances and the intermittent nature of links. Overcoming these issues requires moving beyond the assumptions of immediacy and reliability that underpin traditional terrestrial Internet Protocol (IP) networks. Historically, deep-space networks have relied on custom architectures or protocols like the Bundle Protocol (BP) to address these challenges; however, such solutions impose the constraint that nodes must implement the chosen protocol for proper operation, thereby not providing interoperability with standard IP-based nodes. This paper proposes an alternative approach, leveraging innovations in IP version 6 (IPv6) and Internet Control Message Protocol version 6 (ICMPv6) to integrate delay-tolerant features directly at Layer 3. By embedding these functionalities within the existing IPv6 framework, the proposed IP-compliant solution enhances interoperability, with terrestrial networks enabling DTN nodes to seamlessly communicate with compliant IPv6 nodes. This study provides a detailed comparison of the capabilities of IPv6 and BP version 7, highlighting gaps and opportunities. Based on this analysis, a node architecture is designed to implement the necessary functionalities for DTN, paving the way for more seamless integration of deep-space and terrestrial networks while reducing complexity and improving scalability. Full article

Pathogens and their metabolites in food present significant risks to both human health and economic development. Rising living standards and increasing awareness of food safety have driven the demand for sensitive and rapid detection methods. Lanthanide-doped upconversion nanoparticles (UCNPs), with their exceptional optical properties, have emerged as a promising platform for developing biosensors to detect pathogenic bacteria and their metabolites. The integration of UCNPs with point-of-care testing (POCT) has garnered considerable attention for its portability and immediacy, highlighting a promising future for biosensing, particularly in applications requiring quick and accurate diagnostics. This review explores the recognition elements and design principles commonly used in UCNP-based biosensors and examines various applications, including lateral flow assays, microfluidic systems, photoelectrochemical devices, and smartphone-integrated platforms. Despite significant advancements, challenges remain in the applicability and commercialization of UCNP-based biosensing technology. Future research should focus on enhancing sensitivity and specificity, developing scalable and cost-effective production methods, and integrating with advanced digital technologies to enable broader adoption. Addressing these challenges, establishing regulatory frameworks, and considering sustainability will be crucial to fully realizing the potential of UCNP-based biosensors. Full article

This study examines the intraday dynamics of liquidity and trading activity on the Egyptian Exchange (EGX) to assess its market quality. Using reconstructed five-minute limit order book data, this study measures liquidity dimensions and explores anomalies through interval-of-day and day-of-week models. Key findings reveal an inverted J-shaped pattern in spreads due to information asymmetry, a U-shaped pattern in total depth, and a J-shaped market depth pattern. Additionally, significant day-of-week effects are observed, with Sundays showing the lowest liquidity and Thursdays the highest trading activity. These patterns highlight the impact of the EGX’s unique microstructure, including tick sizes and a preference for limit orders. This study underscores the influence of market structure on liquidity, trading efficiency, and cost, emphasizing the need for tailored regulatory and trading strategies. It provides valuable insights for investors optimizing trading strategies and policymakers seeking to enhance market integrity. Concluding, this research offers a foundation for understanding intraday liquidity patterns in emerging markets like the EGX and proposes future exploration of how information flows and trading mechanisms affect price discovery and market efficiency. Full article

The main objective of this paper is to illustrate the use of artificial intelligence (AI) in the tourism and air transport industries to improve tourists’ experiences, as well as provide a definition of the AI concept closest to both sectors. In order to examine and demonstrate the body of literature on AI and its application to the travel and tourism industry. This study also presents the findings of a literature review using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach in conjunction with a systematic literature review using the Web of Science (WoS) database. This approach enabled us to construct a novel AI concept in the context of tourism. This research found that AI technology offers new and creative opportunities for tourists due to this innovative tool that promotes and empowers travel and tourism organisations’ products and services. AI has helped to outline travel planning for tourists, made it easier to discover new experiences, and streamlined the booking process. The reality is that AI methods and applications are changing and improving passengers and tourists’ experiences in tourism cities and the air transport sector. Moreover, it is necessary to highlight that one of AI technology’s greatest strengths lies in the immediacy of response and advice that swiftly help tourists plan their trips, tours, detailed itineraries, and flight bookings at the same moment. This research is an antecedent attempt to define AI technology in the tourism and air transport context and to illustrate its virtues and shortcomings to improve tourists’ experiences in cities and the operational efficiency of organisations. Full article

Background: The communication skills of healthcare professionals directly impact patient interventions. Consequently, an improvement in healthcare quality indicators is observed. Objective: to adapt and validate the Interpersonal Communication Competence Scale (ICCS) in a Spanish university sample of health science students. Methods: A cross-sectional design was employed with a sample of 803 undergraduate students, utilizing the ICCS. Results: The structure and internal consistency of both the 30-item test and a short form version were analyzed. Additionally, factorial invariance, differential validity by gender, and the convergent and discriminant validity of the instrument were assessed. Benchmarks were also calculated. The complete scale, after removing five items, exhibited a total internal consistency of 0.721 and demonstrated a good fit to a hierarchical model with nine first-order factors and one second-order factor (GFI = 0.921, SRMR = 0.071). The 10-item short scale exhibited an internal consistency of 0.689 and fit a single-factor model (GFI = 0.977, SRMR = 0.059). Additionally, factorial invariance was established based on gender. Concerning convergent validity, the ICCS scales correlated with similar measures from the Social Skills Questionnaire and the Health Professional’s Communication Skills Scale. Regarding differential validity, significant differences were found only in self-disclosure, empathy, and immediacy, with higher scores in all three cases for women. Conclusions: The Spanish version of the ICCS demonstrates good psychometric properties and is a valid tool for assessing interpersonal communication competencies, both generally and specifically within health sciences. Additionally, the establishment of benchmarks in the ICCS will enable future evaluators to identify the position of their assessors relative to a university sample. Full article

Through long-form, creative, high-quality stories, slow journalism seeks to counteract the effects of speed and immediacy in news production and consumption primarily driven by technological advancements. The advantages of artificial intelligence (AI) in journalism include generating and enhancing content, reducing workloads, and consequently giving journalists more time for non-routine and creative tasks. This raises the question of where AI fits into slow journalism. Twenty-one semi-structured interviews were conducted with practitioners of slow journalism in Spain to explore their use, attitudes, and perceptions of AI in their work. The findings indicate that the interviewees make rudimentary use of AI tools, and their attitudes range from a slight lack of interest to a willingness to learn more about them, alongside concerns regarding ethical boundaries and the potential for job losses. They assert that they have a moral and human responsibility when producing stories that AI cannot enhance in terms of quality, creativity, and emotional depth. It can be concluded that AI offers little to ‘slow’ journalists due to the significant limitations in enhancing long-form reporting. At most, it may enable them to streamline repetitive and non-creative work, thereby allowing the depth required in slow journalism, at least in its current state of development. Full article

To improve the performance of earthquake early warning (EEW) systems, we propose an approach that utilizes the time-dependence of P-wave displacements to estimate the earthquake magnitude (M) based on the relationship between M and the displacement. The traditional seismological understanding posits that this relationship achieves statistical significance when the displacement reaches its final peak value, resulting in the adoption of time-constant coefficients. However, considering the potential for earlier establishment of the relationship’s significance than conventionally assumed, we analyze waveforms observed in Japan and determine the intercept in the relationship as a function of time from the P-wave onset. We demonstrate that our approach reduces the underestimation of M in the initial P-wave stages compared to the conventional technique. Consequently, we find a significant rise in the number of earlier warnings in the Japanese railway EEW system. Due to the inherent trade-off between the immediacy and accuracy of alarm outputs, the proposed method unavoidably leads to an increase in the frequency of alerts. Nonetheless, if deemed acceptable by system users, our approach can contribute to EEW performance improvement. Full article

The accurate measurement of pulverized coal concentration (PCC) is crucial for optimizing the production efficiency and safety of coal-fired power plants. Traditional microwave attenuation methods typically rely on a single frequency for analysis while neglecting valuable information in the frequency domain, making them susceptible to the varying sensitivity of the signal at different frequencies. To address this issue, we proposed an innovative frequency selection method based on principal component analysis (PCA) and orthogonal matching pursuit (OMP) algorithms and implemented a multi-frequency microwave sensing system for PCC measurement. This method transcended the constraints of single-frequency analysis by employing a developed hardware system to control multiple working frequencies and signal paths. It measured insertion loss data across the sensor cross-section at various frequencies and utilized PCA to reduce the dimensionality of high-dimensional full-path insertion loss data. Subsequently, the OMP algorithm was applied to select the optimal frequency signal combination based on the contribution rates of the eigenvectors, enhancing the measurement accuracy through multi-dimensional fusion. The experimental results demonstrated that the multi-frequency microwave sensing system effectively extracted features from the high-dimensional PCC samples and selected the optimal frequency combination. Filed experiments conducted on five coal mills showed that, within a common PCC range of 0–0.5 kg/kg, the system achieved a minimum mean absolute error (MAE) of 1.41% and a correlation coefficient of 0.85. These results indicate that the system could quantitatively predict PCC and promptly detect PCC fluctuations, highlighting its immediacy and reliability. Full article

Paul Celan’s ‘Speeches’ determine what poetry is and why we need it. He does not want ‘timeless’ poetry but still ‘lays claim to infinity’; he would ‘reach through time’. He neither refuses poetry as contrary to reason, nor elevates it as pure immediacy of meaning. He questions the ambivalent attitudes towards art—as ‘artifice’ or as ‘profound’. Celan cuts into the loose fabric of such ordinary language to shape it. Those who trumpet ‘plain sense’ against such incisive art deface it as degenerate. Celan’s poetic language presents us as ‘of the earth’ and as ‘released from it’—Büchner’s Lenz seeks clarity in the silence of alpine light but falls into madness in his isolation. He is drawn towards the life of the villagers at the foot of the mountains. He perceives the warm household fires, but it is an illusion that he can be a part of that scene. Thus, Celan enquires into art’s intensity. It is at the risk of reciprocity that a reader entertains the language of a poem. Eliot’s old ‘shadow’ between ‘the idea and the reality’ now falls between the poet’s production and the reader’s reciprocation. The reader may need someone with a free hand to hold a lantern to the script. Full article

With the constant evolution of information and communication technology (ICT), smart classrooms have profoundly influenced Education for Sustainable Development (ESD) by presenting advanced ICT that markedly improved the effectiveness and quality of teaching and learning. Teacher communication technology teaching and immediacy behaviors are crucial for leading and reforming the teaching and learning process in smart classrooms. Meanwhile, teacher–student rapport and student engagement are also key factors that influence ESD. This study aims to investigate the correlation among teacher ICT teaching, teacher immediacy behaviors, teacher–student rapport and student engagement in smart classroom teaching. We surveyed 1032 Chinese university students using the questionnaire method and analyzed the data using structural equation modeling (SEM). The findings revealed that teacher ICT teaching and immediacy behaviors exerted a noteworthy positive impact on student engagement and teacher–student rapport. Meanwhile, teacher ICT teaching markedly positively correlated with verbal immediacy but markedly negatively correlated with nonverbal immediacy. These findings have practical implications for ESD: in smart classrooms, teacher ICT teaching and their immediacy behaviors serve as vital factors in augmenting teaching quality, encouraging student engagement and fostering harmonious teacher–student rapport. Thus, teachers must harness their ICT teaching skills, flexibly assimilate instant behaviors into the teaching process and interact with students in a richer and more diversified manner to effectively augment teaching quality and promote the overall and sustainable growth of students. Furthermore, this study can inform the expansion of smart classrooms, which in the future should not only offer teachers a convenient teaching and learning environment but also evade ICT that limits teacher nonverbal immediacy behaviors. Full article

Background and Objectives: Axillary lymph node (ALN) staging is crucial for the management of invasive breast cancer (BC). Although various radiological investigations are available, ultrasound (US) is the preferred tool for evaluating ALNs. Despite its immediacy, widespread use, and good predictive value, US is limited by intra- and inter-operator variability. This study aims to evaluate US and Elastosonography Shear Wave (SW-ES) parameters for ALN staging to develop a predictive model, named the Cassandra score (CS), to improve the interpretation of findings and standardize staging. Materials and Methods: Sixty-three women diagnosed with BC and treated at two Italian hospitals were enrolled in the study. A total of 529 lymph nodes were surgically removed, underwent intraoperative US examination, and were individually sent for a final histological analysis. The study aimed to establish a direct correlation between eight US-SWES features (margins, vascularity, roundness index (RI), loss of hilum fat, cortical thickness, shear-wave elastography hardness (SWEH), peripheral infiltration (PI), and hypoechoic appearance) and the histological outcome (benign vs. malignant). Results: Several statistical models were compared. PI was strongly correlated with malignant ALNs. An ROC analysis for Model A revealed an impressive AUC of 0.978 (S.E. = 0.007, p < 0.001), while in Model B, the cut-offs of SWEH and RI were modified to minimize the risk of false negatives (AUC of 0.973, S.E. = 0.009, p < 0.001). Model C used the same cut-offs as Model B, but excluded SWEH from the formula, to make the Cassandra model usable even if the US machine does not have SW-ES capability (AUC of 0.940, S.E. = 0.015, p < 0.001). A two-tiered model was finally set up, leveraging the strong predictive capabilities of SWEH and RI. In the first tier, only SWES and RI were evaluated: a positive result was predicted if both hardness and roundness were present (SWES > 137 kPa and RI < 1.55), and conversely, a negative result was predicted if both were absent (SWES < 137 kPa and RI > 1.55). In the second tier, if there was a mix of the results (SWES > 137 kPa and RI > 1.55 or SWES < 137 kPa and RI < 1.55), the algorithm in Model B was applied. The model demonstrated an overall prediction accuracy of 90.2% in the training set, 87.5% in the validation set, and 88.9% across the entire dataset. The NPV was notably high at 99.2% in the validation set. This model was named the Cassandra score (CS) and is proposed for the clinical management of BC patients. Conclusion: CS is a simple, non-invasive, fast, and reliable method that showed a PPV of 99.1% in the malignancy prediction of ALNs, potentially being also well suited for young sonographers. Full article

The perception of nuclear power, while central to energy policy and sustainability endeavors, remains a subject of considerable debate, in which some claim that the expansion of nuclear technology poses threats to global security, while others argue that its access should be shared for development and energy purposes. In this study, a total of 11,256 tweets were gathered over a three-month period using a keyword-based approach through the Twitter Standard Search API, focusing on terms related to nuclear energy. The k-means clustering algorithm was employed to analyze tweets with the aim of determining the underlying sentiments and perspectives within the public domain, while t-SNE was used for visualizing cluster separation. The results show distinct clusters reflecting various viewpoints on nuclear power, with 71.94% of tweets being neutral, 14.64% supportive, and 13.42% negative. This study also identifies a subset of users who appear to be seeking unbiased information, signaling an opportunity for educational outreach. By leveraging the immediacy and pervasiveness of X (formerly known as Twitter), this research provides a timely snapshot of the prevailing attitudes toward nuclear power and offers insights for policymakers, educators, and industry stakeholders. Full article

The Produce Rule regulates food safety among produce growers in the United States. Policy exemptions (e.g., for farms with average produce sales under USD 30,000 over three years) pose a threat to local food safety, particularly given exempt growers’ role in fresh produce production. Understanding exempt growers’ perceptions of food safety practices and the factors influencing their voluntary adoption is crucial. A cross-sectional quantitative survey was conducted to assess growers’ current engagement, their perceptions of agricultural water safety practices, and their influence on adoption decisions. The findings indicate inadequate engagement with agricultural water safety practices, with production water-related safety practices showing higher engagement compared to post-harvest water practices. Overall, growers reported favorable perceptions toward agricultural water safety practices. The perceived compatibility, relative advantage, and observability predicted adoption decisions among exempt growers, with the perceived compatibility being the strongest predictor. Policymakers and education professionals should design strategies and tailored educational interventions and messaging for exempt growers to emphasize the compatibility, relative advantage, and observability of agricultural water safety practices. Furthermore, it is recommended to explore policies and other mechanisms to increase the perceived relative advantage (immediacy of rewards and direct benefits) for exempt growers to promote voluntary adoption of these on-farm food safety practices. Full article