Search Results (1,961)

Access to nature is fundamental to human health and wellbeing, yet opportunities for direct and frequent engagement with natural environments are often restricted for individuals in the 80+ age category, particularly those in care settings or living in remote locations. There is therefore an urgent need to enhance nature connections in care settings and provide personalised, restorative experiences that reflect individuals preferred natural features. This prefeasibility pilot study developed a framework to inform the design of therapeutic care settings, grounded in the principles of biophilic neuroarchitecture and designed to support ageing well. Conducted over six months in two care environments, the study applied the biophilic pattern of Complexity and Order to simulate Natural Analogues within immersive virtual settings. Mixed methods combining wearable sensor data and self-reported wellbeing measures were used to assess psychophysiological, emotional, and cognitive responses among participants aged 80 and above. Findings revealed that VR content aligned with individual nature preferences elicited higher levels of engagement, relaxation, and positive affect. This study demonstrates the potential for implementing biophilic design applications to develop therapeutic care settings which promote wellbeing and healthy ageing, particularly where access to real nature is infrequent or limited. Full article

Multimodal imaging plays a central role in optimizing the evaluation and management of myocardial ischemia by leveraging the complementary strengths of echocardiography, cardiac magnetic resonance imaging (CMR), single photon emission computed tomography (SPECT), positron emission tomography (PET), and invasive coronary angiography (ICA). Noninvasive functional imaging is typically recommended for patients with intermediate to high pre-test probability of coronary artery disease, while coronary computed tomography angiography (CCTA) is preferred for low to intermediate risk. Stress echocardiography is valuable for detecting wall motion abnormalities and is particularly effective in multivessel or left main disease, where perfusion techniques may miss balanced ischemia. CMR offers high spatial resolution and quantitative assessment of myocardial blood flow (MBF), while SPECT and PET quantify ischemic burden, with PET providing superior accuracy for MBF and microvascular disease. ICA remains the gold standard for defining the presence, location, and severity of epicardial coronary stenosis. It is indicated when noninvasive imaging reveals high-risk features, when symptoms are refractory to medical therapy, or when noninvasive results are inconclusive. While ICA offers high spatial resolution, it alone cannot assess the hemodynamic significance of intermediate lesions, nor the coronary microvasculature. Adjunctive invasive hemodynamic and provocative coronary testing (e.g., Fractional Flow Reserve—FFR, invasive Coronary Flow Reserve—CFR, Index of Microcirculatory Resistance—IMR, acetylcholine test) provide essential insights, especially in ischemia with nonobstructive coronary arteries. Given its procedural risks, ICA should be reserved for cases where it will impact management. Intravascular imaging may be used to further characterize lesions. In summary, modality selection should be individualized based on patient characteristics, comorbidities, contraindications, and the need for anatomical versus physiological data. Integrating noninvasive and invasive modalities provides a comprehensive, patient-centered approach to ischemia evaluation. Full article

Precision agriculture increasingly recognizes the transformative potential of unmanned aerial systems (UASs) for crop monitoring and field assessment, yet research consistently highlights significant usability barriers as the main constraints to widespread adoption. Complex mission planning processes, including detailed flight plan creation and way point management, pose substantial technical challenges that mainly affect non-expert operators. Farmers and their teams generally prefer user-friendly, straightforward tools, as evidenced by the rapid adoption of GPS guidance systems, which underscores the need for simpler mission planning in UAS operations. To enhance accessibility and safety in UAS control, especially for non-expert operators in agriculture and related fields, we propose a Secure UAS Control Framework (SAUCF): a comprehensive system for natural-language-driven UAS mission management with integrated dual-factor biometric authentication. The framework converts spoken user instructions into executable flight plans by leveraging a language-model-powered mission planner that interprets transcribed voice commands and generates context-aware operational directives, including takeoff, location monitoring, return-to-home, and landing operations. Mission orchestration is performed through a large language model (LLM) agent, coupled with a human-in-the-loop supervision mechanism that enables operators to review, adjust, or confirm mission plans before deployment. Additionally, SAUCF offers a manual override feature, allowing users to assume direct control or interrupt missions at any stage, ensuring safety and adaptability in dynamic environments. Proof-of-concept demonstrations on a UAS plat-form with on-board computing validated reliable speech-to-text transcription, biometric verification via voice matching and face authentication, and effective Sim2Real transfer of natural-language-driven mission plans from simulation environments to physical UAS operations. Initial evaluations showed that SAUCF reduced mission planning time, minimized command errors, and simplified complex multi-objective workflows compared to traditional waypoint-based tools, though comprehensive field validation remains necessary to confirm these preliminary findings. The integration of natural-language-based interaction, real-time identity verification, human-in-the-loop LLM orchestration, and manual override capabilities allows SAUCF to significantly lower the technical barrier to UAS operation while ensuring mission security, operational reliability, and operator agency in real-world conditions. These findings lay the groundwork for systematic field trials and suggest that prioritizing ease of operation in mission planning can drive broader deployment of UAS technologies. Full article

Background/Objectives: Osteochondral lesions are common after acute patellar dislocation, particularly in young, active individuals. Although fixation of osteochondral fragments is a preferred treatment to restore joint congruence and prevent cartilage degeneration, the prognostic effect of lesion localization and size on postoperative outcomes remains unclear. Methods: This retrospective clinical study included 75 patients (mean age 23.8 ± 6.1 years) who underwent osteochondral fixation after patellar dislocation between 2018 and 2024. Lesions were classified by location—medial patellar facet, lateral facet, trochlear groove/lateral femoral condyle, or multiple regions—and measured on preoperative MRI for size and depth. Functional outcomes were assessed using Kujala, Lysholm, Tegner, and VAS pain scores preoperatively and 12 months postoperatively. Associations between lesion characteristics and postoperative results were analyzed using t-tests, ANOVA, and Pearson correlation. Results: Lesions were most frequently located on the medial patellar facet (42.7%), followed by the trochlear groove/lateral femoral condyle (34.7%). Larger and deeper lesions were more common in trochlear or multiple-site involvement (p = 0.002 and p = 0.031, respectively). At final follow-up, all functional scores improved significantly (Kujala: 62.4 ± 11.3 to 86.7 ± 9.1; Lysholm: 64.1 ± 12.0 to 88.2 ± 8.3; VAS: 6.2 ± 1.3 to 2.1 ± 1.1; all p < 0.001). Patients with smaller lesions (<100 mm²) and medial facet involvement achieved higher Kujala scores (p = 0.020) and lower postoperative pain (p = 0.001). The overall return-to-sport rate was 78.7%, and postoperative complications occurred in 10.7% of cases, mainly recurrent dislocation or implant irritation. Conclusions: Lesion localization and size significantly affect postoperative outcomes after osteochondral fixation for patellar dislocation. Medial facet and smaller lesions are associated with better pain relief and functional recovery, whereas large or trochlear lesions carry a less favorable prognosis. Morphological assessment of lesion characteristics should therefore guide surgical planning, fixation strategy, and postoperative rehabilitation to optimize clinical outcomes. Full article

Background: The role of pulmonary metastasectomy has been increasingly questioned in the surgical community after the PulMiCC trial challenged its benefit in colorectal cancer. However, the view on pulmonary metastasectomy among people in non-surgical disciplines remains unclear. This study explored interdisciplinary attitudes toward pulmonary metastasectomy and identified the clinical expectations shaping its future role. Methods: An anonymous online survey of active board-certified physicians in oncology, urology, gynecology and dermatology was conducted (December 2024–June 2025). Twenty items covered attitudes to local ablative therapy, referral criteria, preferred modalities and future relevance. Group comparisons used Pearson’s χ²; ordinal ratings were compared by one-way ANOVA; associations were explored with Spearman’s ρ. Results: Of 2884 contacted physicians, 165 participated (≈5.7%), and 106 completed the questionnaire. All 106 (100%) endorsed local ablative therapy as meaningful; 92/106 (86.8%) favored routine integration into multimodal care. Surgical metastasectomy was selected by 49/106 (46.2%), SBRT was selected by 27/106 (25.5%) and image-guided ablation was selected by 7/106 (6.6%); preference for surgery differed by specialty (χ²(4) = 15.31, p = 0.004), while institutional availability (in-house thoracic surgery or radiation oncology) showed no association with selecting surgery or SBRT. Key referral determinants were number of lesions (105/106; 99.1%), anatomical location (86/106; 81.1%; p < 0.02 across specialties), and lesion size (81/106; 76.4%; p < 0.05); other factors showed no consistent inter-specialty differences. The perceived usefulness of metastasectomy was high (mode 8/10) and showed a weak, non-significant correlation with referral experience (ρ = 0.172, p = 0.077). Looking ahead, 46/106 (43.4%) anticipated a declining role of local ablative therapy with novel systemic therapies; interest in biomarker analysis from metastatic tissue compared to primary tumor tissue was very high 97/106 (91.5%). Conclusions: Local ablative therapy, particularly pulmonary metastasectomy, continues to be viewed as an integral and trusted element of metastatic disease management across specialties. Despite limited prospective evidence, clinicians maintain strong confidence in its clinical value and foresee its evolution toward biologically and patient-tailored indications. However, the interpretation of these findings is limited by a low response rate and potential selection bias toward European, academically affiliated respondents. To our knowledge, this is the first study to systematically capture perceptions of pulmonary metastasectomy among non-surgical oncology-related specialists. Full article

Background/Objectives: Intracranial aneurysms affect 3–5% of the population and are associated with high morbidity and mortality, particularly after rupture. Treatment options for unruptured aneurysms include microsurgical clipping, with the pterional and supraorbital approaches commonly employed. This study compares these two approaches regarding complications and outcomes. Methods: A retrospective analysis was conducted on 241 patients treated between 2004 and 2023 at the University Hospital of Graz. Patients underwent microsurgical clipping via the pterional (n = 170) or supraorbital (n = 71) approach, chosen according to aneurysm characteristics and surgeon preference. Data on demographics, aneurysm location and size, intraoperative complications, postoperative outcomes, and follow-up were evaluated. Results: The pterional approach was predominantly used for middle cerebral artery (MCA) aneurysms (79.2%), while the supraorbital approach was more frequently applied for internal carotid artery (ICA) and anterior communicating artery (ACOM) aneurysms. Aneurysms treated via the pterional approach were significantly larger (mean width 6.88 mm vs. 5.04 mm; p < 0.01). Severe intraoperative complications, including aneurysm rupture, were significantly more common in the supraorbital group (26.8% vs. 8.8%; p < 0.001). Postoperative hypo-/anosmia occurred more often after the supraorbital approach (8.5% vs. 1.8%; p = 0.013), while temporalis muscle atrophy (11.9% vs. 1.8%; p = 0.029) and chewing difficulties (19.5% vs. 1.8%; p = 0.002) were more frequent after the pterional approach. The supraorbital group had a shorter hospital stay (7.96 vs. 8.76 days; p = 0.001). No significant differences were found in 30-day mortality (p = 0.521). At one-year, functional outcomes assessed by the modified Rankin Scale showed no significant difference (p = 0.899). Complete aneurysm occlusion and recurrence rates were also comparable between groups. Conclusions: Both approaches provide effective treatment for unruptured aneurysms with favorable long-term outcomes. The pterional approach is associated with increased muscle-related complications, whereas the supraorbital approach carries higher risks of intraoperative complications and olfactory dysfunction. Tailoring the surgical approach based on patient and aneurysm characteristics remains essential. Full article

Next Point-of-Interest (POI) recommendation is a crucial task in personalized location-based services, aiming to predict the next POI that a user might visit based on their historical trajectories. Although sequence models and Graph Neural Networks (GNNs) have achieved significant success, they often overlook the diversity and dynamics of user preferences. To address these issues, researchers have begun to employ Hypergraph Convolutional Networks (HGCNs) for disentangled representation learning. However, two critical problems have received less attention: (1) the limited expressive capacity of conventional hypergraph convolution layers, which restricts the modeling of complex nonlinear user–POI preference interactions and consequently weakens generalization performance, and (2) the inadequate utilization of contrastive learning mechanisms, which prevents fully capturing cross-view collaborative signals and limits the exploitation of complementary multi-view information. To tackle these challenges, we propose a Nonlinear Enhanced Disentangled Contrastive Hypergraph Learning (NE-DCHL) for next POI recommendation. The proposed model enhances nonlinear modeling capability and generalization by integrating ReLU activation, residual connections, and dropout regularization within the hypergraph convolution layer. A K-Nearest Neighbor (KNN)-based weighted adjacency matrix is employed to construct the geographical-view hypergraph, reducing computational complexity while maintaining essential spatial correlations. Moreover, a mini-batch InfoNCE loss and the GRACE (deep GRAph Contrastive rEpresentation learning) framework are utilized to improve efficiency and cross-view collaboration. Extensive experiments on two real-world datasets demonstrate that NE-DCHL consistently outperforms the original DCHL and other state-of-the-art approaches. Full article

Background/Objectives: Pancreatic cystic lesions (PCLs) are increasingly being detected due to the widespread use of cross-sectional imaging. Endoscopic ultrasound (EUS) is the preferred modality for evaluating their nature and malignancy risk, yet fluid analysis and cytology offer limited sensitivity. Through-the-needle biopsy (TTNB) has emerged as a more accurate diagnostic tool, though it is associated with higher adverse event (AE) rates. In 2021, our center implemented a selective TTNB protocol excluding frail or elderly patients and suspected IPMNs and standardizing the procedure to two passes, complete cyst aspiration, and selective antibiotic prophylaxis. This study aimed to compare AE rates before and after protocol implementation, evaluate safety factors including antibiotic use, and assess TTNB adequacy and diagnostic accuracy. Methods: We retrospectively analyzed consecutive patients referred for TTNB at AOUI Verona between March 2016 and March 2025, dividing them into two groups: before (Group A) and after (Group B) protocol adoption. Patients not punctured due to technical issues, lack of indication, or presumed pseudocystic nature were excluded. Results: Of 970 patients evaluated by EUS, 190 underwent TTNB (100 in Group A and 90 in Group B). Lesions were mainly located in the pancreatic body or tail, with a significantly larger size in Group B. The overall AE rate was 6.3%, significantly higher in Group A (11%) than in Group B (1%). Antibiotic prophylaxis was not associated with AE occurrence. TTNB adequacy was 88.9%, and diagnostic accuracy was 75.3%. Among 68 surgical cases, TTNB was accurate in 79.4%. Conclusions: A selective and standardized TTNB approach significantly reduces AEs while maintaining high adequacy and diagnostic accuracy. Full article

Escherichia coli (E. coli) pathotypes present in contaminated food, street food, or water are major contributors to foodborne illnesses. Polymerase chain reaction (PCR) methods are widely applied to detect and confirm E. coli pathotypes in food samples, thereby supporting outbreak prevention efforts. The objective of this study was to provide a comprehensive and reliable review of the molecular identification of E. coli isolated from street foods and to examine its public health implications. The review followed the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines and included data retrieved from seven electronic scientific databases covering the period from 1 January 2015, to 15 August 2025. Relevant full-text articles were identified using the search string (“Street food”) AND (Escherichia coli), and only those that met established inclusion and exclusion criteria were selected. A total of 23 studies from Asia, Africa, Europe, and Latin America were included. These studies analyzed a wide range of street foods and beverages. MacConkey Agar and Eosin Methylene Blue Agar were the primary culture media used for the growth and isolation of E. coli. PCR was employed in 50% of the studies to amplify specific DNA segments, enabling the identification of eight E. coli pathotypes: EHEC, ETEC, EAEC (Eagg), EIEC, EPEC, UPEC, DAEC, and APEC. Additionally, a few studies reported phylogroups such as A, B1, B2, C, D, E, and Clade 1. The prevalence of E. coli in street foods varied widely, ranging from 0.5% in Chile to 100% in Mexico. Overall, this systematic review provides an updated scientific overview highlighting persistent challenges in street food safety and E. coli contamination. Across studies, three recurring issues were identified: (1) inadequate and unhygienic vending locations, (2) poor quality of food, and (3) inappropriate food preparation practices. These findings underscore the need for strategic interventions. The evidence presented could support governments and the scientific community in advancing research on E. coli in street foods and implementing corrective measures at local or regional scales, such as educational campaigns for vendors and consumers. Full article

Community-sourced biodiversity imagery has expanded rapidly in the past decade, facilitating analyses of ecology on unprecedented spatial scales. Proliferation of these databases has also helped to reveal understudied or previously overlooked aspects of many species’ basic biology. The Evening Grosbeak (Hesperiphona vespertina) is considered to be a species of conservation concern, and many aspects of its diet have yet to be investigated, including how its diet varies seasonally and across its large North American range. The Evening Grosbeak’s striking plumage, frequent occurrences at bird feeders, and nomadic behavior all make them popular targets of bird photographers and a prime species for study using large community-sourced archives. We reviewed more than 50,000 photographs of Evening Grosbeaks archived in the Macaulay Library, a large public database, to gain a more detailed understanding of the diet of this species. While most Evening Grosbeak images found in the Macaulay Library depicted birds foraging at bird feeders, 1075 images were found to be of birds consuming natural (non-feeder) food items. We mapped the location of these natural dietary items to four distinct regions within the Evening Grosbeak’s geographical range and found a diet consisting of at least 96 species of plants from 25 families, 1 species of insect, and 2 species of lichen from 1 family. Despite the high diversity of dietary items we identified, richness estimators suggest even greater diversity of dietary foods exists, especially in the Pacific Northwest. Using these data and published literature on the Evening Grosbeak’s diet, we discuss the characteristics of preferred Evening Grosbeak dietary items, as well as the advantages and limitations of using community-science data for such analyses. To our knowledge, this is the first range-wide, descriptive study of a songbird species’ diet using photographs made publicly available in a community-sourced archive. Full article

Travel planning is a process that allows users to obtain maximum benefit from their time, cost and energy. When planning a route from one place to another, it is an important option to present alternative travel areas on the route. This study proposes a travel route planning (TRP) architecture using a Long Short-Term Memory (LSTM) and Extreme Gradient Boosting (XGBoost) model to improve both travel efficiency and environmental sustainability in route selection. This model incorporates carbon emissions directly into the route planning process by unifying user preferences, location recommendations, route optimization, and multimodal vehicle selection within a comprehensive framework. By merging environmental sustainability with user-focused travel planning, it generates personalized, practical, and low-carbon travel routes. The carbon emissions observed with TRP’s artificial intelligence (AI) recommendation route are presented comparatively with those of the user-determined route. XGBoost, Random Forest (RF), Categorical Boosting (CatBoost), Light Gradient Boosting Machine (LightGBM), (Extra Trees Regressor) ETR, and Multi-Layer Perception (MLP) models are applied to the TRP model. LSTM is compared with Recurrent Neural Networks (RNNs) and Gated Recurrent Unit (GRU) models. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Squared Error (MSE), and Normalized Root Mean Square Error (NRMSE) error measurements of these models are carried out, and the best result is obtained using XGBoost and LSTM. TRP enhances environmental responsibility awareness within travel planning by integrating sustainability-oriented parameters into the decision-making process. Unlike conventional reservation systems, this model encourages individuals and organizations to prioritize eco-friendly options by considering not only financial factors but also environmental and socio-cultural impacts. By promoting responsible travel behaviors and supporting the adoption of sustainable tourism practices, the proposed approach contributes significantly to the broader dissemination of environmentally conscious travel choices. Full article

Objective: Online maps and booking tools aim to reduce barriers to vaccination by helping users locate nearby clinics, understand service availability, and provide information about vaccination choices. The aim of this research was to explore the potential of online vaccination booking and mapping tools in facilitating antenatal vaccination uptake among Māori and Pacific hapū māmā (pregnant women) in Aotearoa. Methods: This was a qualitative descriptive study that used kaupapa Māori methodology. Focus groups with hapū māmā and semi-structured interviews with healthcare workers were conducted. Transcripts were analyzed thematically. Results: Seven hapū māmā and forty healthcare professionals participated. Three main themes were developed from interviews with hapū māmā: (i) limited awareness of online maps and bookings for vaccination services; (ii) the need for accessible, user-friendly information; and (iii) preference for flexible booking systems. Three themes were developed from the healthcare worker interviews: (i) difficulties with accessibility; (ii) promotion of tools; and (iii) usability of online platforms. Discussion: Although antenatal vaccinations are publicly funded, systemic and digital barriers persist, especially for Māori and Pacific communities. Online tools have the potential to support maternal vaccination, but require improved visibility, cultural relevance, and functionality to be effective. Full article

The present study aimed to document the diversity and seasonal dynamics of stored-product insects in an animal feed facility located in northern Greece. A total of 38 traps were installed across different operational areas of the facility and inspected over 51 consecutive sampling occasions. Captured insects were identified to the lowest possible taxonomic level, and their frequency and dominance were calculated. In total, 9047 insect species belonging to five orders, 14 families, and at least 18 insect species were recorded. The dominant species were Tribolium castaneum, T. confusum, Oryzaephilus surinamensis, Sitophilus granarius, Lasioderma serricorne, and Lepidoptera adults, which collectively accounted for more than 85% of all captures. The total number of insects exhibited marked seasonal fluctuations, with the highest captures during late summer and early autumn and minimal activity during winter. Positive and significant correlations were detected among several dominant species, notably between Lepidoptera and T. castaneum, suggesting overlapping environmental preferences within the facility. These findings provide a detailed overview of the insects associated with feed industries in Greece and underscore the importance of continuous monitoring for effective pest management. The results highlight the need for seasonally adjusted control measures and contribute to a better understanding of the dynamics of stored-product pests under industrial conditions. Full article

The wild boar (Sus scrofa) is a highly adaptable species that has spread into urban-proximate areas, consequently intensifying human–wildlife conflicts in South Korea. Understanding the range and environmental preferences of this species is crucial for efficient population management. Therefore, we investigated wild boar occupancy in Bukhansan National Park (BNP), a protected area near Seoul. We deployed camera traps at 24 locations from March to May 2022 to investigate spring season habitat use patterns. We used single-season, single-species occupancy modeling to explore the impact of environmental and anthropogenic factors on the distribution of wild boar. During 2208 trap nights, we recorded wild boars at 14 sites, with an average occupancy probability (Ψ) of 0.67 ± 0.03. The distance to human settlements was the best predictor of occupancy, with wild boars avoiding regions near human activity sites. In contrast, proximity to puddles significantly increased detection and occupancy probabilities, indicating the importance of water sources for drinking and wallowing. Wild boars also showed a preference for areas near agricultural lands but exhibited behavioral avoidance of direct human presence. Our spring season findings suggest the need for targeted management strategies that prioritize population control in areas far from settlements but adjacent to water and agricultural boundaries. This study provides critical insights into the spatial ecology of wild boars in urban-proximate landscapes and provides science-based measures for mitigating conflicts and disease risks. We recommend long-term monitoring for the assessment of seasonal variations and efficacy of management interventions. Full article

With the rapid growth of smart devices and positioning technologies, spatiotemporal data has become essential for predicting user behavior. However, many existing next-location prediction models employ oversimplified temporal modeling, neglect spatial structure and semantic relationships, and fail to capture complex location interaction patterns. This study proposes a graph neural network model that integrates spatiotemporal features to enhance next-location prediction. There are three components in the proposed method. The first is location feature representation which combines geocodes and location category embeddings to construct semantically enriched node representations. The second is temporal modeling which computes temporal similarity between historical trajectories and current behaviors to generate time-decay weights, thereby capturing behavioral periodicity and preference shifts. The third is preference integration which long-term historical preferences and short-term current preferences are modeled using a long short-term memory (LSTM) network and subsequently fused with spatial preferences to generate a comprehensive semantic representation encompassing both user preferences and location characteristics. Experiments on real-world trajectory datasets demonstrate that our proposed model achieves superior accuracy compared to state-of-the-art approaches in next-location prediction. Full article