Search Results (228)

Achieving uniform agrochemical deposition in coffee is challenging because canopy structure, terrain, and wind conditions influence spray movement and retention. This study compared an unmanned aerial spray system (UASS), backpack sprayer, and tractor-mounted sprayers across three commercial coffee farms on Hawai‘i Island. Spray coverage, droplet density, droplet size metrics, and operational efficiency were evaluated using water-sensitive cards positioned throughout the canopy and analyzed using mixed-effects models. UASS produced significantly lower spray coverage and droplet density than the ground-based application systems, whereas backpack and tractor sprayers did not differ. Deposition patterns varied with canopy position, with application method effects depending on canopy height, depth, and aspect. Volume median diameter decreased in the upper canopy and with increasing wind speed, while relative span varied modestly among methods and was greater within the canopy interior. Canopy position and wind strongly shaped agrochemical deposition across spray platforms. Although UASS required less field labor and improved accessibility in terrain-limited systems, these operational advantages were accompanied by reduced deposition relative to ground-based sprayers. These findings demonstrate that canopy position and environmental conditions strongly influence agrochemical deposition and support UASS as a complementary application platform rather than a direct replacement for conventional sprayers under the conditions evaluated. Full article

This study presents a data-driven approach, MLS-CAPS (mobile laser scanning completeness analysis for path spacing), for defining optimal path spacing (walking path) for backpack or handheld MLS surveys in ecological applications. By using an initial high-density pilot scan of the site, captured with the same MLS system intended for subsequent full surveys, MLS-CAPS quantifies how voxel occupancy completeness, digital terrain model accuracy, and canopy height model accuracy vary with lateral distance from individual walking trajectories. This provides an objective basis for translating local vegetation structure into path spacing recommendations for subsequent MLS surveys. Case study results showed that structural complexity strongly influences the rate of decay, with denser and more complex vegetation requiring closer path spacing to maintain data completeness. While this meets expectations, what has previously been lacking is a way to quantify it in a manner that directly supports data acquisition decision making. MLS-CAPS, provided as a Python tool, allows users to define thresholds aligned with their metrics of interest, recognising that no single spacing is universally sufficient across all structural attributes. The framework therefore enables MLS operators to plan surveys that balance efficiency with accuracy, while maintaining transparency in the trade-offs between path spacing and completeness. By formalising what has previously been a trial-and-error process, this method offers a practical tool to support ecological applications of MLS across diverse environments. Full article

Background/Objectives: Adherence to partial weight-bearing prescriptions (PWBP) is challenging. The use of audio biofeedback (AB) can potentially help to better implement PWBP. This study aimed to investigate the effect of continuous AB provided by sensor insoles on partial weight-bearing load during functional tasks. Methods: Twenty older patients received a single AB training for PWBP management postoperatively. The prescribed limb load was measured (ground reaction force) during four activities (walking, walking with a 5 kg backpack, sitting–standing–sitting, and standing) with force–sensor insoles with continuous AB (n = 10) or without AB (n = 10). Individual deviation from the prescribed load and the influence of age and cognitive function were analyzed. Results: The intervention group (continuous AB) managed PWBP better for three out of four activities: The relative deviation was 104.4% ± 144.2 vs. 164.5% ± 164.5 for the 5 kg backpack walk, 57.6% ± 107.2 vs. 86.8% ± 122.4 for the sit–stand–sit task, and 8.0% ± 102.3 vs. 38.8% ± 131.7 for standing. For the 3 min walking activity, the relative deviation was 127.7% ± 121.9 vs. 116.0% ± 133.0 in favor of the control group. Mean differences were not statistically significant for any of the activities. Conclusions: After a single training session with continuous AB, PWBP can only be insufficiently met. Studies with multiple training sessions seem necessary to further test the potential of continuous AB in the management of PWBP. Full article

Global ocean models at non-eddying resolutions currently used for subseasonal to seasonal to decadal (S2S2D) prediction suffer from a severe deficit in internal variability. In ensemble data assimilation (DA), this can lead to under-dispersed ensembles that require inflation schemes. However, inflation corrections do not persist into the forecast phase, causing ensemble spread to collapse at longer lead times. This study evaluates an alternative approach: addressing the variability deficit directly within the model physics using a “Backscatter Package” (BackPack) consisting of the stochastic Stanley, stochastic GM+E, and Leith+E backscatter parameterizations. Implemented within a global MOM6/CESM framework at nominal $2/3°$ resolution using the DART ensemble DA package, the BackPack’s impacts are compared against cutting-edge adaptive inflation. The results demonstrate that the BackPack substantially increases internal variability and ensemble spread, successfully lowering the amount of required inflation. While reductions in ensemble-mean state errors are modest, the BackPack significantly improves ensemble calibration, assessed using a novel spread–error calibration ratio metric. Although this study only addresses the data assimilation phase, we expect that physics-based BackPack schemes may provide a physically sustainable pathway to maintain spread during the subsequent forecast phase. Full article

Camouflage design for jungle environments has conventionally relied on the static optimization of color, texture, and edge features, presuming that the background remains visually stable. This presumption diverges from real conditions, in which wind continuously alters leaf orientation and vegetation texture, leaving a gap between static optimization and dynamic visual reality. To address this limitation, this study developed a systematic camouflage design process that integrates the Beaufort scale into a mimetic system for simulating vegetation sway. Dominant colors were extracted using the CIE L*a*b* color space and K-means clustering, and background maps were generated via Gaussian blur. Leaf textures from five plant species were arranged through seamless tiling and overlaid onto the backgrounds to form 15 camouflage samples. Validation employed a fuzzy logic questionnaire and eye-tracking measurements. Under the present experimental conditions, which used screen presentation under visible light, pattern A-13 performed best. Derived from the Terminalia mantaly leaf texture in the dark green variant, it achieved the most favorable balance between distinctiveness from the regional reference pattern and disruption of target–background segmentation, whereas C-15, the light green variant, consistently ranked last. The proposed process is reproducible and applicable to civilian equipment such as tents and backpacks. Full article

Mosquito control personnel work within health departments, public works, private companies, and other agencies. These essential outdoor workers have highly specialized training and are faced with a variety of potential health and safety hazards (e.g., arthropod bites and stings, exposure to insecticides and other chemicals, working with heavy equipment, noise, heat, solar ultraviolet radiation, slips, trips, and/or falls). Mosquito control personnel undergo employer-provided and other types of training on a variety of topics from regulatory updates to new surveillance and control techniques that are required for safety purposes and to maintain their applicator license. Here, an exploratory baseline survey was conducted among members of the North Carolina Mosquito and Vector Control Association (NCMVCA) and the Virginia Mosquito Control Association (VMCA). There was a 28% response rate so results should be interpreted with caution in this pilot study. Most respondents reported utilizing ultra-low volume insecticide application equipment for controlling adult mosquitoes. Backpack sprayers were utilized by less than half of respondents. Those who reported using respirators showed higher concern about insecticide-related health effects than those who did not use respirators. Outdoor workers encounter various potential hazards and utilize several forms of personal protective equipment to reduce risks. This baseline work can be considered a starting point for implementing and strengthening occupational safety and health awareness and preventive measures for mosquito control workers. Knowledge of health and safety hazards can reduce workplace risk. Full article

In Burke County, North Carolina, a Hepatitis A outbreak among unsheltered residents exposed gaps in access to clinic-based care and prompted early, ad hoc “backpack medicine” outreach efforts to deliver care directly in nontraditional settings. While this approach addressed immediate needs, it highlighted the inadequacy of isolated interventions, prompting local partners to pursue more structured, coordinated, and community-driven approaches to homeless health system design. This project report describes how Burke County Public Health, in partnership with the University of North Carolina at Chapel Hill, applied systems thinking, community coalition building, and human-centered design to transition from reactive outreach to a structured, sustainable mobile health delivery model for people experiencing homelessness. Guided by Community Coalition Action Theory (CCAT), partners used human-centered design methods to engage over 40 community stakeholders and 10 individuals with lived experience of homelessness or housing instability. Through empathy mapping, iterative prototyping, and thematic analysis, the team identified priority service gaps, defined operational requirements, and developed prototype service models, while building cross-agency readiness for implementation. Full article

Background/Objectives: Maintaining an upright posture is a complex, adaptive neurophysiological process that relies on a set of stereotypical muscle synergies. Despite extensive research on postural control, the interaction between muscle dynamics and ground reaction forces during progressive loading remains poorly understood. Methods: Twenty-five healthy men, aged 21–25, performed a 30 s quiet standing task on a tensometric platform. The protocol involved seven loading levels—from no load to higher loads using progressive weights in a backpack. The three components, Rx, Ry, and Rz, of the ground reaction force (GRF) and surface electromyographic activity from six muscles of the lower limb were recorded, namely medial (GAM) and lateral heads (GAL) of m. gastrocnemius, rectus femoris (RF), and vastus lateralis (VL) from m. quadriceps femoris, m. biceps femoris (BF), and m. semitendinosus (ST). The recently developed intercriteria analysis (ICrA) was utilized to enhance understanding of the central nervous system’s adaptive mechanisms under changing load conditions. Results: The ICrA results show that the RF–VL muscle pair is stable and does not depend on load, while the BF–ST pair is semi-stable across different weights. Also, ICrA indicates a significant increase in synchronization between specific muscle groups at higher load levels, suggesting the recruitment of additional muscle coupling. Regarding the influence of increasing weight (W) on GRF, the analysis reveals a positive consonance relation between W and Rz in 100% of subjects. Conclusions: The study shows that during progressive external loading, the central nervous system maintains vertical stability by reorganizing muscle coupling. Some of these are specific to individuals. Coactivation of the antagonistic muscle pairs at higher loads suggests a transition from a basic to a more complex adaptive strategy. Full article

Background/Objectives: Spinal pain is common among schoolchildren and is associated with poor postural habits and sedentary behavior. Schools represent an optimal setting for prevention; however, they are also key environments for prevention strategies in children who already experience spinal pain. This study focused on children aged 9–11 years and aimed to evaluate the effectiveness of a physiotherapist-led, classroom-based workshop as a prevention intervention to improve spinal pain outcomes. Methods: A quasi-experimental single-group pre–post intervention study was conducted in public primary schools. The intervention consisted of two 45 min theoretical–practical sessions. A 21-item questionnaire assessed spinal pain, postural habits, backpack-related behaviors, physical activity, screen use and spinal literacy at baseline and three months post-intervention. McNemar and Wilcoxon tests were applied (p < 0.05). Results: A total of 287 schoolchildren participated. Cervical and thoracic pain decreased significantly (p = 0.036; p = 0.040), while lumbar pain showed no change. Postural habits improved: sitting with back support increased (+12.7%; p < 0.001), sitting on the chair edge decreased (−10.5%; p < 0.001), and side-lying sleeping increased (p = 0.006). Knowledge of proper backpack load distribution also improved (+17.9%; p < 0.001). No significant changes were observed in physical activity, screen use, rising-from-bed technique, or backpack type. Conclusions: The workshop improved upper-spine pain, spinal literacy and modifiable habits, while automated motor behaviors and family-dependent routines showed limited change. Full article

Urban parks are often regarded as carbon sinks, yet their net carbon performance depends on the balance between vegetation carbon uptake and maintenance-related emissions, as well as the accurate representation of within-park spatial heterogeneity. This study used backpack LiDAR, field vegetation surveys, and maintenance inventories to quantify annual carbon sequestration, maintenance emissions, and net carbon budget in 44 plots covering nine biotope types across 16 parks in central Xianyang, China. A four-level biotope classification incorporating canopy openness, ground cover, tree composition, and vertical stratification was applied to link LiDAR-derived three-dimensional structure with ecological-unit-level carbon accounting. Carbon sequestration and net carbon budget differed significantly among biotopes, whereas maintenance emissions did not. Closed broadleaved single-layer forest showed the highest carbon sequestration density (0.772 kg C m⁻²), while hard-surfaced partly closed broadleaved single-layer forest showed the lowest value (0.132 kg C m⁻²). Closed woody biotopes functioned as strong carbon sinks, partly closed biotopes as weak sinks, and the partly open short-grass biotope was the only carbon source. Three-dimensional green volume density was the strongest positive predictor of net carbon budget (β = 0.417, p = 0.032), followed by stem density (β = 0.276, p = 0.048), whereas irrigation-related emissions showed a significant negative coefficient (β = −0.276, p = 0.021). Carbon sequestration explained more variation in net carbon budget than maintenance emissions (adjusted R² = 0.409 vs. 0.134). These findings suggest that backpack LiDAR can support fine-scale identification of priority carbon-sink units in urban parks and that low-carbon park management should prioritize three-dimensional woody vegetation structure while reducing high-input irrigation where feasible. Full article

Ablation and harvesting are among the most labor-intensive and physically demanding operations in oil palm cultivation, often resulting in significant drudgery and safety concerns when performed manually through climbing or pole-assisted methods. To overcome these challenges, a motorized backpack-type machine was developed and evaluated for its field performance, ergonomics, and economic feasibility. The machine met required quality standards and exhibited satisfactory performance under field conditions, achieving average ablation and harvesting capacities of 286 inflorescences per day and 4.115 t day⁻¹, with actual field capacities of 0.727 ha h⁻¹ (ablation), 0.516 ha h⁻¹ (sickle), and 0.537 ha h⁻¹ (chisel), and field efficiencies of 81.23%, 76.3%, and 79.91%, respectively. Ergonomic evaluation indicated that operation of the machine falls within a moderate workload category, thereby reducing operator fatigue compared to manual methods. Economic analysis further revealed that the cost of operation was substantially reduced to 3.02 USD t⁻¹ and 60.40 USD ha⁻¹ year⁻¹, resulting in increased harvester earnings of 174.72% and 64.83% compared to climbing and pole harvesting methods, respectively. These findings demonstrate that the motorized backpack machine is a practical, efficient, and economically viable alternative to traditional techniques and minimizes drudgery while improving productivity and profitability in oil palm plantations. Full article

Backpack mobile mapping systems (MMS) equipped with LiDAR and RGB cameras, as well as an optional GNSS/INS direct georeferencing unit, are increasingly utilized in forest inventory applications. In general, LiDAR point clouds provide detailed structural information, whereas imagery offers visual specifics of surface features. However, cameras typically operate at lower acquisition rates compared to LiDAR. In proximal mapping, another challenge is the inconsistent reception of GNSS signals beneath forest canopies. Additionally, georeferencing accuracy may differ between LiDAR and imagery due to biases in the system calibration parameters and variations in post-processing approaches. To address these challenges, this study introduces a Backpack MMS that uses cameras configured at elevated frame rates to enhance image overlap. Concurrently, this study presents an algorithmic approach to addressing georeferencing issues by integrating imagery and LiDAR data, thereby enhancing system calibration and improving platform trajectory. The method is based on the hypothesis that forest environments are rich with geometrically well-defined features, such as tree trunks and ground patches. By identifying conjugate primitives in point clouds from both imagery and LiDAR, the procedure optimizes feature models while simultaneously minimizing calibration biases and/or trajectory errors. The proposed approach is validated using multiple field datasets collected in diverse forest environments. Quantitative results show that the procedure reduces image–LiDAR feature misalignment across all datasets from up to 1.1 m in the planimetric direction and 2 m in the vertical direction to within 5 cm in both. The feature fitting accuracy also improves from 2.9 cm to 0.85 cm for LiDAR point clouds and from 10 cm to 0.9 cm for image-based point clouds. However, the results indicate that despite increased data availability, imagery alone remains less reliable than LiDAR for extracting structural information. Nevertheless, the proposed image–LiDAR alignment strategy represents a crucial step toward developing a comprehensive tree inventory. Full article

Background: Special Forces Operators often carry out missions in conditions where the use of motor vehicles is impossible. Additional external load across areas with variable inclination may reduce walking efficiency and consequently limit the combat capability of soldiers. The aim of the study was to determine how ground inclination affects the spatiotemporal structure of gait in Special Forces Operators (SFO) with different military loads. Methods: The study included 50 operators from Polish special forces units. Measurements of walking were performed using the h/p/cosmos Gaitway 1D + 3D treadmill. Tests were conducted at four uphill inclination levels: 0%, 5%, 10%, and 15%. Each participant completed trials both without external load and with a 27 kg load (helmet, tactical vest, and backpack). Statistical analyses were performed using the Friedman test, the Durbin–Conover post hoc test, and linear mixed models (LMM) to assess interaction effects. The Robinson Symmetry Index (SI) was calculated to assess asymmetry between the dominant and non-dominant limbs. Results: Increasing inclination caused statistically significant changes in the spatiotemporal structure of gait. The greatest modifications were observed at 10–15% inclinations, particularly under the maximum load of 27 kg. A significant shortening of step length and gait cycle time was noted, while cadence showed a slight upward trend, especially at a 15% inclination with the highest load. Step width remained stable. Conclusions: Ground inclination, especially when combined with the additional mass of military equipment, significantly affects the locomotion of Special Forces Operators. The stable SI values and consistent step width indicate a high level of gait stability and effective adaptive mechanisms. However, the extent of spatiotemporal modifications observed at inclinations of 10–15% with a 27 kg load may increase the risk of overuse injuries among operators. Full article

Accurately monitoring physical activity, including stationary cycling on an exercise bike, is important in managing chronic diseases and rehabilitation after lower limb surgery. This study aimed to validate a new smartphone-based sensor application (the BeSAFE+) for activity recognition and step counting across five phone placements, using the SENS Motion^® system as a reference standard, and observed activity time as ground truth. In a laboratory-based study, 20 participants performed walking, brisk walking, running, high- and low-intensity cycling, sitting, standing, and lying activities while carrying five smartphones placed in the front and back trouser pockets, a backpack, a running armband, and a fanny pack, and wearing the activity tracker. The front pocket placement had the most accurate classification during cycling activities (89–93%) versus SENS Motion^® (96–98%). For other activities, the highest overall classification accuracy was achieved with the phone in the back pocket. Overall, the SENS Motion^® activity tracker demonstrated higher classification accuracy than most smartphone placements across all activities, except for running. Nevertheless, several smartphone placements and Application Programming Interface (API) approaches achieved activity recognition and step count estimates that were not significantly different from the SENS Motion^® activity tracker, indicating that smartphone-based activity recognition can be valid under specific conditions. Full article

Sidewalk high-definition (HD) maps require centimetre-level representation of pedestrian barriers to support mobility assistance and barrier-free infrastructure management. This study evaluates six mobile light detection and ranging (LiDAR) platforms for sidewalk HD mapping: terrestrial laser scanning (TLS), a push-cart mobile mapping system (MMS), two backpack systems (GNSS/INS (Global Navigation Satellite System/Inertial Navigation System)-aided and SLAM (simultaneous localization and mapping)-based), and two handheld systems (GNSS/INS-aided and SLAM-based). Surveys were conducted at two sites with contrasting occlusion and GNSS conditions (park and dense downtown corridors). Point clouds were transformed to a common control network, with independent checkpoints for absolute accuracy. The reference dataset achieved a planimetric root mean square error (RMSE) of 0.017–0.049 m and vertical RMSE of 0.009–0.014 m across sites. Platforms were compared for positional accuracy, point density, and extractability of key accessibility attributes (effective width, step height, and longitudinal slope). Cart-mounted MMS provided stable geometry under occlusion, while SLAM-based handheld mapping improved robustness in GNSS-degraded areas; backpack SLAM performance depended on loop-closure opportunities and scene dynamics. We provide guidance on selecting pedestrian-scale LiDAR platforms for sidewalk HD mapping under different survey conditions. Full article