Search Results (1,185)

Background: Older adults face increased risks of influenza infection and related complications due to declining immunity and reduced vaccine responsiveness. Despite widespread vaccination, only 30–40% mount immune response due to immunosenescence. However, no biomarkers exist to identify potential non-responders, limiting the ability to target vaccine strategies, like high-dose or adjuvanted formulations, to those unlikely to benefit from standard options. Methods: We analysed publicly available baseline bulk RNA sequencing data from peripheral blood mononuclear cells of individuals aged ≥65 years to determine baseline transcriptomic signatures predictive of influenza vaccine response. Using two independent cohorts (discovery and validation), we classified individuals as triple responders (TRs) or triple non-responders (TNRs) based on hemagglutination inhibition assay titers at Day 0 and Day 28 for three components: A/H1N1, A/H3N2, and B/Yamagata. Results: We identified 1152 differentially expressed genes between TRs and TNRs at baseline. TRs exhibited enrichment of genes involved in B cell activation and protein synthesis, while TNRs showed enrichment of genes associated with innate immune responses and platelet activation. A response score derived from gene expression achieved high predictive accuracy in the discovery cohort (area under the curve [AUC] = 0.98). However, performance declined in the validation cohort (AUC = 0.69), and did not outperform clinical predictors, such as baseline titers, sex and vaccine dose. Conclusions: While baseline transcriptomic profiles may reveal mechanistic insights into vaccine responsiveness in the elderly, they offer limited predictive utility. Future work should prioritise higher-resolution or combined cell-specific approaches, such as single-cell RNA-sequencing or flow cytometry. Full article

Contemporary nurseries of fruit trees and ornamental plants constitute a key component in the production of high-quality planting material. At present, conventional technology dominates in nurseries in Poland and throughout the European Union. It is based on universal agricultural tractors working with numerous specialized machines—typically underutilized—including sprayers, inter-row cultivation equipment, fertilizer spreaders, and tree lifters. This concept entails several limitations and high investment costs. Because of the considerable size and turning radius of such machinery, a dense network of service roads (every 15–18 m) and wide headlands must be maintained. These areas, which constitute approximately 20% of the total surface, are effectively wasted yet require continuous agronomic maintenance. An alternative concept employs a set of implements mounted on a high-clearance portal tractor (1.6–1.8 m), forming a specialized unit capable of moving above the rows of nursery crops. The study objective of the research was to evaluate the air distribution generated by an air-jet system installed on a crop-spray boom mounted on a portal sprayer, and to assess spray deposition during treatments in nursery trees. Such a configuration enables the mechanization of a broader range of nursery operations than currently possible, while reducing investment costs compared with conventional technology. One still underutilized technology consists of sprayers with an auxiliary airflow (AA) generated by air sleeves. Mean air velocity was measured in three vertical planes, and they showed lower air velocity between 1.0 m and 5.5 m. Spray deposition on apple nursery trees was assessed using a fluorescent tracer. The experimental design consists of a comparative field experiment with and without air flow support, spraying at two standard working rates (200 and 400 L·ha⁻¹) and determining the application of the liquid to plants in the nursery. The results demonstrated a positive effect of the AA system on deposition. At a travel speed of 6.0 km·h⁻¹ and an application rate of 200 L·ha⁻¹, deposition on the upper leaf surface was 68% higher with the fan engaged. For a 400 L·ha⁻¹ rate, deposition increased by 47%, with both differences statistically significant. The study showed that the nursery sprayer mounted on a high-clearance portal tractor and equipped with an AA system achieved an increase of 58% in spray deposition on the upper leaf surface when the fan was operating at 200 L·ha⁻¹ and 28% at 400 L·ha⁻¹. Substantial differences were found between deposition on the upper and lower leaf surfaces, with the former being 20–30 times greater. Given the complexity of nursery production technology, sprayers that ensure the highest possible biological efficacy and high quality of nursery material will play a pivotal role in its development. At the current stage, AA technology fulfils these requirements. Full article

Extended reality (XR) is increasingly used to address productivity, communication, and safety challenges in the construction industry, but large-scale adoption within Construction 4.0 remains limited. The existing reviews rarely provide an integrated perspective that jointly examines XR applications, underlying technology stacks, and the barriers that constrain implementation. This study fills that gap by combining a PRISMA-compliant systematic review with a bibliometric analysis of 76 journal articles published between 2019 and 2024. The review maps XR usage in construction, which XR modes, devices, and graphics engines are most prevalent, and which barriers hinder deployment in real projects. Design visualization and coordination, immersive training, and remote assistance or inspection emerge as the dominant application areas. Augmented reality (AR) and virtual reality (VR) lead the technology landscape, with Microsoft HoloLens and Meta Quest as the most frequently reported head-mounted displays and Unity as the main graphics engine. Implementation barriers are categorized into five groups—technological, organizational, economic, infrastructural, and methodological—with interoperability issues, hardware performance limitations, and the lack of standardized BIM-to-XR workflows being particularly recurrent. The review contributes to the Construction 4.0 agenda by providing a consolidated map of XR applications, technologies, and barriers, and by highlighting enablers such as open data schemas and competency-based training programs. Future research should validate AI-assisted, bidirectional BIM–XR workflows in real projects, report cost–benefit metrics, and advance interoperability standards that integrate XR into broader Construction 4.0 strategies. Full article

Quantifying riverscape topography is challenging because riverscapes comprise of both wet and dry surfaces. Advances have been made in demonstrating the capability of mounting topo-bathymetric LiDAR (Light Detection and Ranging) sensors on crewed, occupied aircraft to quantify riverscape topography. However, only recently has miniaturisation of electronic components enabled topo-bathymetric LiDAR to be mounted on consumer-grade Unoccupied Aerial Vehicles (UAVs). We evaluate the capability of a demonstration YellowScan Navigator topo-bathymetric, full waveform LiDAR sensor, mounted on a DJI Matrice 600 UAV, to survey a 1 km long reach of the braided River Feshie, Scotland. Ground-truth data, with centimetre accuracy, were collected across wet areas using an echo-sounder, and in wet and dry areas using RTK-GNSS (Real-Time Kinematic Global Navigation Satellite System). The processed point cloud had a density of 62 points/m². Ground-truth mean errors (and standard deviation) across dry gravel bars were 0.06 ± 0.04 m, along shallow channel beds were −0.03 ± 0.12 m and for deep channels were −0.08 m ± 0.23 m. Geomorphic units with a concave three-dimensional shape (pools, troughs), associated with deeper water, had larger negative errors and wider ranges of residuals than planar or convex units. The case study demonstrates the potential of using UAV topo-bathymetric LiDAR to enhance survey efficiency but a need to evaluate spatial error distribution. Full article

On 19 December 2015 and 21 February 2017, Longyearbyen was hit by major avalanches from the steep hillside of the mountain Sukkertoppen. In this article, we specifically consider the 2015 avalanche that destroyed eleven houses and buried nine people; seven were located and rescued, while two died. We describe the meteorological conditions leading up to the avalanche, the rescue operation, the media coverage, and the immediate aftermath of the catastrophe. Both events came as a result of warming, strong easterly winds, and drifting snow, with the December 2015 event being the most extreme. The 2017 avalanche damaged two houses, but no people were hurt. We analyse the catastrophes in relation to the knowledge of the risks and impacts of avalanches in Longyearbyen, as provided through field-based student courses at the University Centre of Svalbard (UNIS). To protect against further avalanche accidents, parts of Longyearbyen have been restructured, and physical barriers against avalanches have been installed on the hillside of Sukkertoppen. Now there are snow drift fences to reduce snow accumulation in the release areas, avalanche protection fences mounted in the hillside, and a large wall at the foot of the mountain to catch avalanche debris in the future. In hindsight, the accidents have contributed to an increased national awareness of the danger of severe weather events. Full article

Soil salinization is an important negative factor that reduces the fertility of irrigated arable land. The fields in southern Kazakhstan are at high risk of salinization due to the dry arid climate. In some cases, even the top layer of soil has a significant degree of salinization. The use of a UAV equipped with a multispectral camera can help in the rapid and highly detailed mapping of salinity in cultivated arable land. This article describes the process of preparing the labeled data for assessing the salinity of the top layer of soil and the comparative results achieved due to using machine learning methods in two different districts. During an expedition to the fields of the Turkestan region of Kazakhstan, fields were surveyed using a multispectral camera mounted on a UAV; simultaneously, the soil samples were collected. The electrical conductivity of the soil samples was then measured in laboratory conditions, and a set of programs was developed to configure machine learning models and to map the obtained results subsequently. A comparative analysis of the results shows that local conditions have a significant impact on the quality of the models in different areas of the region, resulting in differences in the composition and significance of the model input parameters. For the fields of the Zhetisay district, the best result was achieved using the extreme gradient boosting regressor model (linear correlation coefficient Rp = 0.86, coefficient of determination R² = 0.42, mean absolute error MAE = 0.49, mean square error MSE = 0.63). For the fields in the Shardara district, the best results were achieved using the support vector machines model (Rp = 0.82, R² = 0.22, MAE = 0.41, MSE = 0.46). This article presents the results, discusses the limitations of the developed technology for operational salinity mapping, and outlines the tasks for future research. Full article

Open-pit coal mining is characterized by multiple pollution sources, diverse types, and extensive affected areas, leading to complex air pollution with wide diffusion. Traditional fixed monitoring methods cannot address these limitations. Taking a coal mine in Xinjiang as a case study, this study developed a drone-mounted mobile atmospheric monitoring system, focusing on nitrogen dioxide (NO₂) and suspended particulate matter (PM_2.5 and PM₁₀) to explore their distribution, diffusion patterns, and influencing factors. The results show distinct seasonal pollutant characteristics: NO₂ and ozone (O₃) dominate in summer, while particulate matter prevails in winter. The temporal distribution exhibits a bimodal pattern, with high levels in the early morning and evening hours. Spatially, higher pollutant concentrations accumulate vertically below ground level, while lower levels are observed above it. Horizontally, elevated concentrations are found along northern transport corridors; however, these levels become more uniform at greater heights. A spatiotemporal prediction model integrating convolutional neural network (CNN) and long short-term memory (LSTM) network was successfully applied to real-time pollutant prediction in open-pit coal mining areas. This study provides a reliable mobile monitoring solution for open-pit coal mine air pollution and offers valuable insights for targeted pollution control in similar mining areas. Full article

Background/Objectives: Appropriate use of a dental mirror (MT) is essential for dental treatment. However, because the mirror image differs depending on the operator’s position, there are few effective tools available to train dental students and inexperienced dentists. To address this issue, a new virtual reality (VR) system was developed. Methods: Eighty-seven participants, including instructor dentists, graduate students, trainee dentists, and dental students from Niigata University, participated in the experiment. The participants manipulated the virtual dental mirror (DM) connected to three-dimensional (3D) control devices while wearing a head-mounted display (HMD) to simulate an intraoral examination and caries removal. The distance between the center of the DM and the caries, area ratio of the caries on the DM, ellipticity of the caries image, and manipulation time were measured and compared between groups. Results: The mean distance between the centers was 1.18 mm for instructor dentists and 1.56 mm for the students (p = 0.003; effect size, 0.48). Instructor dentists demonstrated significantly superior performance in all evaluation categories compared to the other groups. This suggests that the level of clinical experience affected the results. Conclusions: The newly developed VR system can quantitatively and objectively evaluate DM manipulation. Differences in the operator’s clinical experience led to variations in the techniques used for mirror image confirmation and DM manipulation. This VR system enables quantitative feedback by outputting images from the HMD to a monitor. Therefore, it has the potential to evolve into an unprecedented training tool for dental students or trainees. Full article

Urban logistics in metropolitan areas faces mounting pressure to deliver faster while controlling operational costs under strict fleet size constraints. Traditional vehicle routing models assume unlimited vehicle availability, overlooking realistic fleet utilization and spatial-temporal demand imbalances. This paper introduces the fleet-constrained metropolitan logistics problem (FCMLP), a novel framework integrating trunk linehaul scheduling, two-echelon routing, multi-trip operations, and anticipatory fleet positioning. We model the FCMLP as a Markov Decision Process capturing the stochastic and dynamic nature of metropolitan delivery flows. Our solution framework combines interpretable Bayesian Network-based demand forecasting for transparent proactive vehicle relocation decisions, parameterized cost-function approximation for dynamic order-to-linehaul assignment, and Adaptive Large Neighborhood Search for multi-trip vehicle routing. Computational experiments on synthetic instances and real-world data from a major e-commerce platform in Jakarta demonstrate 20–26% total cost reduction. Multi-trip operations alone reduce fleet size by 23%, while interpretable predictive relocation further improves performance by 7% through a 20% reduction in emergency deployments. The framework’s interpretability enhances operator trust and facilitates practical adoption, offering logistics platforms a path to improve vehicle utilization through operational efficiency and transparent predictive intelligence without expanding fleet size. Full article

Microsporidia are a group of obligate intracellular parasites with a broad host range. These parasites can cause mild to severe harm to their hosts, making them important targets for research. However, studies on common wild-caught fish from the Atlantic Eastern Central Zone (FAO Area 34) remain scarce. 576 individuals across 35 fish species from this region were collected from local markets between 2011 and 2019. The specimens were dissected, and lesions were examined using histology, wet mounts, PCR, and transmission electron microscopy. However, microsporidian infection was detected only in round sardinella (Sardinella (S.) aurita), with 19 out of 39 individuals infected. Parasitized fish weighed nearly half as much as non-infected ones, indicating a potentially significant economic impact. Molecular and ultrastructural analyses identified the parasite as Glugea (G.) thunni, a species previously reported only from the Mediterranean Sea. This study provides the first record of G. thunni in FAO Area 34, with round sardinella likely serving as its primary host. This and other closely related sequences may represent a single taxonomic entity or, more likely, a complex of a few cryptic species geographically separated across the Mediterranean Sea and the eastern and western North Atlantic regions. Full article

Ensuring thermal comfort in waiting areas is essential for visitor satisfaction and well-being. In the context of nearly zero-energy buildings (nZEBs), these spaces—typically characterized by short-term occupancy, transient user behavior, and the need for rapid temperature adjustment—pose specific challenges for HVAC control in balancing comfort and energy demand. This study investigates the influence of a ceiling-mounted fan coil unit (FCU) operating in heating mode on thermal comfort conditions in an nZEB office waiting area. Measurements were conducted at multiple points within the space to assess microclimate parameters, followed by the calculation of the predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD) indices, supported by occupant feedback collected through short interviews. The results showed that although the FCU effectively increased the average temperature, its intermittent operation and localized air jets during the heating phase caused temporary discomfort near the unit. Occupant feedback confirmed sensations of discomfort due to strong air movement during FCU operation but indicated slightly higher overall dissatisfaction and smaller variability compared to model-based PPD values, reflecting the averaging effect of occupant perception over time. These findings highlight the need for optimized FCU control strategies in waiting areas, such as operating at reduced fan speeds and preheating the heat exchanger, to enhance occupant comfort. This study contributes to improving HVAC control concepts for semi-transient spaces in nZEBs. Full article

Hulun Lake, a UNESCO Biosphere Reserve, faces mounting threats from extreme climate events and anthropogenic pressures, highlighting the need for robust biodiversity monitoring. Environmental DNA (eDNA) has emerged as a promising tool for aquatic biomonitoring, yet different bioinformatic pipelines—such as Amplicon Sequence Variant (ASV) and Operational Taxonomic Unit (OTU) clustering—may yield divergent results. This study compares ASV and OTU clustering approaches in eDNA metabarcoding alongside traditional capture-based surveys to assess fish diversity in Hulun Lake. Across all methods, we identified 43 taxa (40 species), including the critically endangered Acheilognathus hypselonotus and vulnerable Choi’s spiny loach (Cobitis choii). While eDNA methods detected 2~3 times more species than in nets (13 species), strong methodological correlations (p < 0.001) were observed between net frequencies and eDNA-derived relative abundances (based on both ASV and OTU datasets using 4th-root and log transformations). Clustering analysis of capture-based data revealed four distinct ecological zones: the areas near tourist facilities, Wuerxun River inflow region, Wulan Nuoer Lake (connected via the Wuerxun River), and the Lake Centre. Significant spatial variation (p < 0.05) between these four zones was found in eDNA datasets, whereas nets captured more heterogeneous patterns, consistent with previous studies. Community structures were shaped by both generalists (e.g., Cyprinus carpio, Hemiculter bleekeri) and habitat specialists such as Amur catfish (Silurus asotus). The Lake Centre hosted a unique assemblage, likely due to reduced human disturbance. Overall, both eDNA clustering methods outperformed capture-based survey in detecting species richness and offered semi-quantitative insights. However, discrepancies between ASV and OTU approaches were evident in resolving fine-scale community differences. We recommend an integrated monitoring strategy that combines the sensitivity of eDNA with the abundance resolution of net captured to inform spatially targeted conservation and habitat protection in this vulnerable ecosystem. Full article

Robotic arm-based antenna measurement systems offer the flexibility needed for advanced antenna measurement and diagnostics techniques but are typically limited by reach and sampling time. This work integrates two complementary contributions to overcome these constraints. First, a composite-plane range extension is introduced for a medium-size robot mounted on a mobile platform and monitored by an optical tracking system (OTS). Independent planar scans are acquired after manual repositioning of the robot and then accurately aligned and blended into a single, larger measurement plane, with positioning errors mitigated through a calibration process. Second, a localized sparse sampling strategy is proposed to accelerate planar near-field (PNF) measurements when only selected angular regions of the radiation pattern are required. The approach relies on reduced-order modeling and singular value decomposition (SVD) analysis to design non-redundant grids that preserve the degrees of freedom relevant to the truncated angular sector, thereby reducing both the number of samples and the scan area. Numerical examples for a general case and experimental validation in X-band demonstrate that the combined methodology extends the effective measurement aperture while significantly shortening acquisition time for narrow or tilted beams, enabling accurate and portable in situ characterization of complex modern antennas by means of cost-effective acquisition systems. Full article

Accurate detection of machinery-induced strip roads after forest operations is fundamental for assessing soil disturbance and supporting sustainable forest management. However, in Mediterranean pine forests where canopy openings after boom-corridor thinning are moderate, the effectiveness of different remote sensing techniques remains uncertain. Previous studies have shown that LiDAR-based methods can reliably detect logging trails in different forest stands, but their direct transfer to structurally simpler, even-aged Mediterranean stands has not been validated. This study addresses this gap by testing whether UAV-derived RGB imagery can achieve comparable accuracy to LiDAR-based methods under the canopy conditions of boom-corridor thinning. We compared four approaches for detecting strip roads in a black pine (Pinus nigra Arn.) plantation on Mount Amiata (Tuscany, Italy): one based on high-resolution UAV RGB imagery and three based on LiDAR data, namely Hillshading (Hill), Local Relief Model (LRM), and Relative Density Model (RDM). The RDM method was specifically adapted to Mediterranean conditions by redefining its return-density height interval (1–30 cm) to better capture areas of bare soil typical of recently trafficked strip roads. Accuracy was evaluated against a GNSS-derived control map using nine performance metrics and a balanced subsampling framework with bootstrapped confidence intervals and ANOVA-based statistical comparisons. Results confirmed that UAV-RGB imagery provides reliable detection of strip roads under moderate canopy openings (accuracy = 0.64, Kappa = 0.27), while the parameter-tuned RDM achieved the highest accuracy and recall (accuracy = 0.75, Kappa = 0.49). This study demonstrates that RGB-based mapping can serve as a cost-effective solution for operational monitoring, while a properly tuned RDM provides the most robust performance when computational resources are sufficient to work on large point clouds. By adapting the RDM to Mediterranean forest conditions and validating the effectiveness of low-cost UAV-RGB surveys, this study bridges a key methodological gap in post-harvest disturbance mapping, offering forest managers practical, scalable tools to monitor soil impacts and support sustainable mechanized harvesting. Full article

This article examines the “Alminhas” of the municipality of Sabugal in the Beira Alta region (Portugal) as expressions of popular religiosity and cultural heritage. The main goal of the study is to survey and analyse the iconography of tile panels found in 27 preserved oratories within the area. A qualitative methodology was employed, involving bibliographic research and fieldwork conducted across the 30 parishes of the municipality. This fieldwork involved taking photographs, georeferencing sites and collecting local testimonies. The research revealed that Christian themes, primarily focused on saving souls in purgatory, are prevalent, particularly images of Christ crucified, Our Lady of Mount Carmel, and angels interceding for the souls in flames. There are also newer devotional motifs, such as Our Lady of Fátima. The findings emphasise the importance of these structures as symbols of local identity and evidence of deep-rooted religious customs, although they are currently threatened by deterioration, vandalism and undocumented changes. This work helps to recognise the “Alminhas” as an essential part of Portuguese religious and popular artistic heritage. Full article