Search Results (4,333)

Archaeological research fundamentally relies on detecting features to uncover hidden historical information. Airborne (aerial) LiDAR technology has significantly advanced this field by providing high-resolution 3D terrain maps that enable the identification of ancient structures and landscapes with improved accuracy and efficiency. This technical note comprehensively reviews 45 recent studies to critically examine the integration of Machine Learning (ML) and Deep Learning (DL) techniques, particularly Convolutional Neural Networks (CNNs), with airborne LiDAR derivatives for automated archaeological feature detection. The review highlights the transformative potential of these approaches, revealing their capability to automate feature detection and classification, thus enhancing efficiency and accuracy in archaeological research. CNN-based methods, employed in 32 of the reviewed studies, consistently demonstrate high accuracy across diverse archaeological features. For example, ancient city walls were delineated with 94.12% precision using U-Net, Maya settlements with 95% accuracy using VGG-19, and with an IoU of around 80% using YOLOv8, and shipwrecks with a 92% F1-score using YOLOv3 aided by transfer learning. Furthermore, traditional ML techniques like random forest proved effective in tasks such as identifying burial mounds with 96% accuracy and ancient canals. Despite these significant advancements, the application of ML/DL in archaeology faces critical challenges, including the scarcity of large, labeled archaeological datasets, the prevalence of false positives due to morphological similarities with natural or modern features, and the lack of standardized evaluation metrics across studies. This note underscores the transformative potential of LiDAR and ML/DL integration and emphasizes the crucial need for continued interdisciplinary collaboration to address these limitations and advance the preservation of cultural heritage. Full article

Spain is among the European countries with the greatest number of preserved castles and defensive structures—some estimates place the total at around 10,000, the majority of which date back to the medieval period. Yet, surprisingly, many of these fortifications remain uncatalogued and in an advanced state of ruin. This study focuses on a small fortress that has been overlooked by historiography and neglected by public authorities, yet which still stands after seven centuries: the Tower of Lopera, a castle belonging to the so-called Banda Morisca (the frontier of Al-Andalus in the 14th century). Using a combination of digital documentation techniques—namely, portable laser scanning, photogrammetry (via drone and camera), and digital image processing software—we have been able to digitize, geometrize, and document both the surviving architectural remains and their immediate physical environment. Rather than pursuing the latest technological innovations, this methodology prioritizes practical and realistic solutions based on the resources typically available to cultural heritage administrations. Our work serves two main objectives: to demonstrate the viability of applying such tools to this typology of architectural heritage and to conduct a detailed graphic and geometric analysis of the structure. Given the abundance of similar abandoned fortresses in Spain, the findings presented here could inform future heritage documentation strategies on a broader, potentially national, scale. Full article

Cystic fibrosis (CF), the most common hereditary lung disease in Caucasians, is caused by dysfunction of the cystic fibrosis transmembrane conductance regulator (CFTR). We evaluated CFTR function using a newly developed Ussing chamber system, the Multi Trans Epithelial Current Clamp (MTECC), in an in vitro model of human airway epithelia. Air–liquid interface (ALI) cultures were established from nasal brushings of healthy controls (HC) and CF patients with biallelic CFTR variants. ALI layer thickness was similar between groups (HC: 62 ± 13 µm; CF: 55 ± 9 µm). Immunofluorescence showed apical CFTR expression in HC, but reduced or absent signal in CF cultures. MTECC enabled continuous measurement of transepithelial resistance (Rt), potential difference (PD), and conductance (G_t). G_t was significantly reduced in CF cultures compared to HC (0.825 ± 0.024 vs. −0.054 ± 0.016 mS/cm²), indicating impaired cAMP-inducible ion transport by CFTR. Treatment of CF cultures with elexacaftor, tezacaftor, and ivacaftor (Trikafta^®) increased G_t, reflecting partial restoration of CFTR function. These findings demonstrate the utility of MTECC in detecting functional differences in CFTR activity and support its use as a platform for evaluating CFTR-modulating therapies. Our model may contribute to the development of personalized treatment strategies for CF patients. Full article

This study presents the first systematic evaluation of in-context learning for Tarifit machine translation, a low-resource Amazigh language spoken by 5 million people in Morocco and Europe. We assess three large language models (GPT-4, Claude-3.5, PaLM-2) across Tarifit–Arabic, Tarifit–French, and Tarifit–English translation using 1000 sentence pairs and 5-fold cross-validation. Results show that 8-shot similarity-based demonstration selection achieves optimal performance. GPT-4 achieved 20.2 BLEU for Tarifit–Arabic, 14.8 for Tarifit–French, and 10.9 for Tarifit–English. Linguistic proximity significantly impacts translation quality, with Tarifit–Arabic substantially outperforming other language pairs by 8.4 BLEU points due to shared vocabulary and morphological patterns. Error analysis reveals systematic issues with morphological complexity (42% of errors) and cultural terminology preservation (18% of errors). This work establishes baseline benchmarks for Tarifit translation and demonstrates the viability of in-context learning for morphologically complex low-resource languages, contributing to linguistic equity in AI systems. Full article

Neuroinflammation is the major contributor to the pathology of neonatal hypoxic–ischemic (HI) brain injury. Our previous studies have demonstrated that microRNA210 (miR210) inhibition with antisense locked nucleic acid (LNA) inhibitor mitigates neuroinflammation and provides neuroprotection after neonatal HI insult. However, the underlying mechanisms remain elusive. In the present study, using miR210 knockout (KO) mice and microglial cultures, we tested the hypothesis that miR210 promotes microglial activation and neuroinflammation through suppressing mitochondrial function in microglia after HI. Neonatal HI brain injury was conducted on postnatal day 9 (P9) wild-type (WT) and miR210 knockout (KO) mouse pups. We found that miR210 KO significantly reduced brain infarct size at 48 h and improved long-term locomotor functions assessed by an open field test three weeks after HI. Moreover, miR210 KO mice exhibited reduced IL1β levels, microglia activation and immune cell infiltration after HI. In addition, in vitro studies of microglia exposed to oxygen–glucose deprivation (OGD) revealed that miR210 inhibition with LNA reduced OGD-induced expression of Il1b and rescued OGD-mediated downregulation of mitochondrial iron–sulfur cluster assembly enzyme (ISCU) and mitochondrial oxidative phosphorylation activity. To validate the link between miR210 and microglia activation, isolated primary murine microglia were transfected with miR210 mimic or negative control. The results showed that miR210 mimic downregulated the expression of mitochondrial ISCU protein abundance and induced the expression of proinflammatory cytokines similar to the effect observed with ISCU silencing RNA. In summary, our results suggest that miR210 is a key regulator of microglial proinflammatory activation through reprogramming mitochondrial function in neonatal HI brain injury. Full article

Background/Objectives: The social importance of health literacy (HL) is widely understood, and its measurement is the subject of various studies. Due to the recent pandemic, several instruments for measuring HL about COVID-19 have been proposed in different countries, including the HLS-COVID-Q22 questionnaire. The diversity of cultures and languages necessitates the cross-cultural adaptation of this instrument. Thus, the present study translates, adapts, and validates the psychometric properties of the HLS-COVID-Q22 questionnaire to provide its cross-cultural adaptation from English to Spanish (Peru). Methods: As part of ensuring that the final questionnaire accommodates the cultural nuances and idiosyncrasies of the target language, the following activities were carried out: (a) a survey of 40 respondents; and (b) a focus group with 10 participants, followed by expert approval. In addition, the validity and reliability of the health instrument have been ascertained through a further pilot test administered to 490 people in the city of Tacna in southern Peru. Results: The resulting questionnaire helps measure HL in Peru, aiding better-informed decision-making for individual health choices. Conclusions: The presence of such a tool is advantageous in case of similar global health emergencies, when the questionnaire can be made readily available to support a promotion of strategies towards better self-care. Moreover, it encourages other Latin American stakeholders to adjust the instrument to their own cultural, language, and socio-economic contexts, thus invigorating the regional and global expansion of the HL study network. Full article

Recent advancements in generative artificial intelligence have significantly progressed the field of text-to-music generation, enabling users to create music from natural language descriptions. Despite the success of various models, such as MusicLM, MusicGen, and AudioLDM, the current approaches struggle to capture fine-grained genre-specific characteristics, precisely control musical attributes, and handle underrepresented cultural data. This paper introduces a novel, lightweight fine-tuning method for the AudioLDM framework using low-rank adaptation (LoRA). By updating only selected attention and projection layers, the proposed method enables efficient adaptation to musical genres with limited data and computational cost. The proposed method enhances controllability over key musical parameters such as rhythm, emotion, and timbre. At the same time, it maintains the overall quality of music generation. This paper represents the first application of LoRA in AudioLDM, offering a scalable solution for fine-grained, genre-aware music generation and customization. The experimental results demonstrate that the proposed method improves the semantic alignment and statistical similarity compared with the baseline. The contrastive language–audio pretraining score increased by 0.0498, indicating enhanced text-music consistency. The kernel audio distance score decreased by 0.8349, reflecting improved similarity to real music distributions. The mean opinion score ranged from 3.5 to 3.8, confirming the perceptual quality of the generated music. Full article

Titanium–aluminum–vanadium (Ti6Al4V) is a material chosen for spine, orthopedic, and dental implants due to its combination of desirable mechanical and biological properties. Lasers have been used to modify metal surfaces, enabling the generation of a surface on Ti6Al4V with distinct micro- and nano-scale structures. Studies indicate that topography with micro/nano features of osteoclast resorption pits causes bone marrow stromal cells (MSCs) and osteoprogenitor cells to favor differentiation into an osteoblastic phenotype. This study examined whether the biological response of human MSCs to Ti6Al4V surfaces is sensitive to laser treatment-controlled micro/nano-topography. First, 15 mm diameter Ti6Al4V discs (Spine Wave Inc., Shelton, CT, USA) were either machined (M) or additively manufactured (AM). Surface treatments included no laser treatment (NT), nanosecond laser (Ns), femtosecond laser (Fs), or nanosecond followed by femtosecond laser (Ns+Fs). Surface wettability, roughness, and surface chemistry were determined using sessile drop contact angle, laser confocal microscopy, X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). Human MSCs were cultured in growth media on tissue culture polystyrene (TCPS) or test surfaces. On day 7, the levels of osteocalcin (OCN), osteopontin (OPN), osteoprotegerin (OPG), and vascular endothelial growth factor 165 (VEGF) in the conditioned media were measured. M NT, Fs, and Ns+Fs surfaces were hydrophilic; Ns was hydrophobic. AM NT and Fs surfaces were hydrophilic; AM Ns and Ns+Fs were hydrophobic. Roughness (Sa and Sz) increased after Ns and Ns+Fs treatment for both M and AM disks. All surfaces primarily consisted of oxygen, titanium, and carbon; Fs had increased levels of aluminum for both M and AM. SEM images showed that M NT discs had a smooth surface, whereas AM surfaces appeared rough at a higher magnification. Fs surfaces had a similar morphology to their respective NT disc at low magnification, but higher magnification revealed nano-scale bumps not seen on NT surfaces. AM Fs surfaces also had regular interval ridges that were not seen on non-femto laser-ablated surfaces. Surface roughness was increased on M and AM Ns and Ns+Fs disks compared to NT and Fs disks. OCN was enhanced, and DNA was reduced on Ns and Ns+Fs, with no difference between them. OPN, OPG, and VEGF levels for laser-treated M surfaces were unchanged compared to NT, apart from an increase in OPG on Fs. MSCs grown on AM Ns and Ns+Fs surfaces had increased levels of OCN per DNA. These results indicate that MSCs cultured on AM Ns and AM Ns+Fs surfaces, which exhibited unique roughness at the microscale and nanoscale, had enhanced differentiation to an osteoblastic phenotype. The laser treatments of the surface mediated this enhancement of MSC differentiation and warrant further clinical investigation. Full article

This study examines the evolution and integration of Buddhist architecture in East Asia and emphasizes the preservation of indigenous building traditions by adapting pre-Buddhist architectural typologies, vernacular construction techniques, and localized worship practices. In addition, this study highlights the adaptive transformation of Indian Buddhist structures as they incorporate regional architectural forms, resulting in distinct monumental styles that had a profound symbolic significance. By introducing the concept of a cosmopolitan attitude, it underscores the dynamic coexistence and reciprocal influence of universalized and vernacular architectural traditions. The findings highlight the interplay between cultural universality and particularity, illustrating how architectural meaning and intention define the uniqueness of structures beyond their stylistic similarities. This study demonstrates that even when architectural forms appear similar, their function and underlying intent must be considered to fully comprehend their historical and cultural significance. Full article

This study evaluates the efficacy of commercial clean-label additives, specifically fermentates, in inhibiting mold growth in vitro and extending the shelf life of preservative-free bread. The mold growth on selected bread was modeled using the time-to-growth approach. The pH, a_w, and moisture content of fresh bread were determined. In addition, selected fermentates were characterized physicochemically. Fermentates, defined as liquid or powdered preparations containing microorganisms, their metabolites, and culture supernatants, were tested at varying concentrations (1% to 12%) to assess their antimicrobial performance and impact on bread quality parameters, including moisture content, water activity, and pH. The results showed significant differences in fermentate efficacy, with Product A as the best mold growth inhibitor in vitro and a clear dose-dependent response. For Penicillium corylophilum, inhibition increased from 51.90% at 1% to 62.60% at 4%, while P. chrysogenum had an inhibition ranging from 32.26% to 34.49%. Product F exhibited moderate activity on both molds at 4%, inhibiting between 28.48% and 46.27%. The two molds exhibited differing sensitivities to the fermentates, with P. corylophilum consistently more susceptible to inhibition. Product A displayed a low pH (2.61) and high levels of lactic acid (1053.6 mmol/L) and acetic acid (1061.3 mmol/L). Product F presented a similar pH but lower levels of lactic and acetic acid. A time-to-growth model, validated by significant coefficients (p < 0.05) and high predictive accuracy (R² > 0.95), was employed to predict the appearance of mold on bread loaves. The model revealed that higher concentrations of fermentates A and F delayed mold growth, with fermentate A demonstrating superior efficacy. At 2% concentration, fermentate A delayed mold growth for 8 days, compared to 6 days for fermentate F. At 8% concentration, fermentate A prevented mold growth for over 25 days, significantly outperforming the control (4 days). Additionally, fermentates influenced bread quality parameters, with fermentate A improving crust moisture retention and reducing water activity at higher concentrations. These findings highlight the potential of fermentates as sustainable, consumer-friendly alternatives to synthetic preservatives, offering a viable solution to the challenge of bread spoilage while maintaining product quality. Full article

The first half of the 19th century witnessed the rise of Romantic poetry, which focused in depth on individual consciousness, inner worlds, and metaphysical inquiries. This poetic orientation became particularly evident in works centred on themes such as solitude, alienation, and existential quests. Within this context, the present study aims to examine the archetypal and poetic resonances of the poetic voice in Mihail Lermontov’s poem The Demon, based on its sixth and final version dated 1841, in relation to Nikoloz Baratashvili’s poem Secret Voice. Lermontov’s poem is analyzed through the English translation by Charles Johnston, published in 1983, while Baratashvili’s poem is discussed based on the 24-line version included in the fifth edition (1895) of the anthology Poems and Letters (Leksebi da Tserilebi). This study explores the thematic and structural similarities between the two poems within the framework of comparative literature and psychoanalytic criticism, focusing on Romantic archetypes, the uncanny, the shadow figure, and ontological solitude. Furthermore, the dialogue established between Lermontov’s demonic narrator and Baratashvili’s introspective poetic voice reopens discussions on the boundaries of cultural memory, oral narrative patterns, and poetic identity. Ultimately, this comparative analysis reveals the implicit influences of The Demon on Georgian poetry and discusses the intercultural resonances of themes such as voice, self, and archetype in Romantic poetry. Full article

Background: Type 2 diabetes (T2D) is a growing public health concern, particularly in low- and middle-income countries. Although prediabetes is a major risk factor for T2D, it remains largely underdiagnosed and untreated. Structured lifestyle interventions have proven effective in preventing diabetes, but their feasibility within the Brazilian public health system remains unclear. Methods: This multicenter pilot randomized controlled trial assessed the feasibility of a culturally adapted lifestyle intervention (PROVEN-DIA) across the five regions of Brazil. A total of 220 adults at high risk for T2D were randomized to an intervention group or a control group (usual care) and followed for three months. Both groups received similar educational content on healthy eating and physical activity, but the intervention group participated in a structured and personalized lifestyle program with regular follow-up sessions. The primary outcome was adherence to dietary recommendations, assessed using the BALANCE Index—a validated dietary score (range: 0–40) based on the Brazilian Cardioprotective Diet that classifies foods into color-coded groups according to nutritional quality—along with engagement in moderate-to-vigorous physical activity (MVPA). Secondary outcomes included diet quality (DQIR), anthropometric and metabolic parameters. Results: Feasibility was demonstrated by a 93.2% retention rate (n = 205). There was no significant difference in the primary outcome (simultaneous improvement in diet and MVPA). However, the PROVEN-DIA group exhibited significantly greater improvements in diet quality, with a 2.8-point increase in the BALANCE Index (vs. 0.5 in the control, p = 0.03), and a significant improvement in the DQIR (p < 0.001). No significant differences between groups were observed in MVPA, HbA1C, glycaemia, or body weight. Conclusions: The PROVEN-DIA intervention proved feasible within the Brazilian public health context, resulting in significant improvements in dietary quality among individuals at high risk for T2D. A larger trial with longer follow-up is warranted to evaluate its effectiveness in preventing the progression to diabetes. However, to enhance physical activity outcomes, specific adaptations and targeted strategies may be required to better support participant engagement in exercise. Full article

Due to globalization, companies are exposed to a culturally diversified workforce; therefore, great emphasis is placed on identifying the most effective leadership style that would be able to manage such a workforce. Although numerous studies have attempted to identify successful leadership styles in different cultural settings, none have focused on the perceptions of top managers who work in multinational corporations (MNCs) in culturally diversified surroundings. Thus, our research attempts to identify the most preferred leadership style and characteristics from the perspective of top managers in MNCs in the United Arab Emirates (UAE). The 13 leadership characteristics analyzed in this study were generated from the 21 characteristics found by Global Leadership and Organizational Behavior Effectiveness (GLOBE) research. The participants, top managers in MNCs, needed to evaluate leadership styles by considering leadership characteristics. To ensure the objectiveness of the study, we analyzed their answers by applying the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The results indicated that the most preferred leadership characteristics were visionary, inspirational, collaborative team-oriented, and performance-oriented. Moreover, the transformational leadership style emerged as the most preferred leadership style. The study’s findings show that top managers believe that employees in MNCs in the UAE seek a leader with a vision who will inspire, motivate, and help them fulfill their true potential. Full article

Introduction: Poorly designed safety job descriptions may have a negative impact on occupational safety and health (OSH) performance. Firstly, they limit the chances of hiring highly qualified safety professionals who are vital to the success of OSH management systems in organizations. Secondly, the relationship between the presence of qualified safety professionals and the safety culture (and performance) in an organization is reciprocal. Thirdly, the low quality of job descriptions limits exploring the proper competencies needed by safety professionals before they are hired. The safety professional is thus uncertain of what level of education or training and which skills they should attain. Objectives: The main goal of the study is to integrate the analytic hierarchy process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with importance–performance analysis (IPA) to evaluate job descriptions in multiple sectors. Results: The results of the study indicate that it is vital to clearly define job levels, the overall mission, key responsibilities, time-consuming tasks, required education/certifications, and necessary personal abilities in safety job descriptions. This clarity enhances recruitment, fairness, performance management, and succession planning. The organization can then attract and retain top talent, improve performance, foster a strong safety culture, create realistic job expectations, increase employee satisfaction and productivity, and ensure that competent individuals are hired, ultimately leading to a safer and more productive workplace. Conclusion: The outcomes of this study provide a robust framework that can and should be used as a guideline to professionalize job description development and enhance talent acquisition strategies. Full article

Background/Objectives: Selective serotonin reuptake inhibitors (SSRIs), widely prescribed for anxiety disorders, may negatively impact the gut microbiota, contributing to dysbiosis. Considering the gut–brain axis’s importance in mental health, probiotics could represent an effective adjunctive strategy. This study evaluated the effects of Lactobacillus helveticus R0052 and Bifidobacterium longum R0175 on microbiota composition, metabolic activity, and immune markers in fecal samples from patients with anxiety on SSRIs, using the SHIME^® (Simulator of the Human Intestinal Microbial Ecosystem) model. Methods: The fecal microbiotas of four patients using sertraline or escitalopram were inoculated in SHIME^® reactors simulating the ascending colon. After stabilization, a 14-day probiotic intervention was performed. Microbial composition was assessed by 16S rRNA sequencing. Short-chain fatty acids (SCFAs), ammonia, and GABA were measured, along with the prebiotic index (PI). Intestinal barrier integrity was evaluated via transepithelial electrical resistance (TEER), and cytokine levels (IL-6, IL-8, IL-10, TNF-α) were analyzed using a Caco-2/THP-1 co-culture system. The statistical design employed in this study for the analysis of prebiotic index, metabolites, intestinal barrier integrity and cytokines levels was a repeated measures ANOVA, complemented by post hoc Tukey’s tests to assess differences across treatment groups. For the 16S rRNA sequencing data, alpha diversity was assessed using multiple metrics, including the Shannon, Simpson, and Fisher indices to evaluate species diversity, and the Chao1 and ACE indices to estimate species richness. Beta diversity, which measures microbiota similarity across groups, was analyzed using weighted and unweighted UniFrac distances. To assess significant differences in beta diversity between groups, a permutational multivariate analysis of variance (PERMANOVA) was performed using the Adonis test. Results: Probiotic supplementation increased Bifidobacterium and Lactobacillus, and decreased Klebsiella and Bacteroides. Beta diversity was significantly altered, while alpha diversity remained unchanged. SCFA levels increased after 7 days. Ammonia levels dropped, and PI values rose. TEER values indicated enhanced barrier integrity. IL-8 and TNF-α decreased, while IL-6 increased. GABA levels remained unchanged. Conclusions: The probiotic combination of Lactobacillus helveticus R0052 and Bifidobacterium longum R0175 modulated gut microbiota composition, metabolic activity, and inflammatory responses in samples from individuals with anxiety on SSRIs, supporting its potential as an adjunctive strategy to mitigate antidepressant-associated dysbiosis. However, limitations—including the small pooled-donor sample, the absence of a healthy control group, and a lack of significant GABA modulation—should be considered when interpreting the findings. Although the SHIME^® model is considered a gold standard for microbiota studies, further clinical trials are necessary to confirm these promising results. Full article