Movement Patterns Research Articles

The early peak knee abduction moment waveform is a novel risk factor predicting anterior cruciate ligament injury in young athletes: A prospective study.

In this study, prospective data were used to evaluate whether the early peak knee abduction moment waveform is associated with the risk of anterior cruciate ligament (ACL) injury. Biomechanical data from 84 athletes who participated in the study as adolescents were analysed after cross-referencing national health registry data to confirm ACL reconstruction in the subsequent years. The knee abduction moment waveform shape was obtained with cluster analysis for the first 100 ms of a cutting manoeuvre (1776 trials in total) and classified as either containing an early peak knee abduction moment or not, and the odds ratio for later ACL injury was then calculated. Additionally, discrete kinematic and kinetic variables were extracted, and tested against the risk of ACL injury using mixed model logistic regression. Of 84 athletes, 8 (all female) sustained a total of 13 ACL injuries in the years after motion analysis data collection. Six clusters of knee abduction moment waveform shapes were identified. Two clusters containing 446 trials were classified as an early peak knee abduction waveform. This waveform was associated with a 7.2-fold increase in the risk of ACL injury (95% confidence interval: 2.4-24.6; p < 0.001). Of the kinematic and kinetic variables tested, only the knee abduction angle at initial contact was associated with an increased risk of ACL injury (p < 0.001). This is the first study to confirm the association between the early peak knee abduction moment waveform and the risk of ACL injury. Using waveforms, instead of discrete peak values of the knee abduction moment, may better represent risky movement patterns. Replicating these findings in a larger cohort will support the use of this method to screen athletes for risk and guide targeted preventive interventions and their efficacy. Level II.

Investigating the role of path architecture complexity in users’ movement patterns in hospital circulation systems: case studies in Golestan, Iran

Purpose This study aims to explore how users’ movement is influenced by different hospital ward layouts, by using space syntax theory. This study also compared four circulation patterns to find the best one for the study goal. Design/methodology/approach The authors used both qualitative and quantitative methods to study how users’ wayfinding in hospitals depends on various indicators and factors. The study used Depth Map software to do case studies and then analyzed the indicators from theoretical foundations and used the Pearson Test to check the correlation between indicators. This study also looked at Iran’s Ministry of Health standards for ward layouts. Finally, the results obtained from the research data were compared to achieve a suitable model based on the research objectives. Findings The linear-patterned plan was the best for easy wayfinding and accessibility among four patterns. The optimal hospital circulation patterns can improve wayfinding and reduce wayfinding problems and user movement. Originality/value By pioneering space syntax in hospital research, this study unveils the novel interaction between path architecture and user movement. It gives new insights into current trends, helping architects, administrators and policymakers improve health-care design, efficiency and patient experience.

GIATAR: a Spatio-temporal Dataset of Global Invasive and Alien Species and their Traits

Monitoring and managing the global spread of invasive and alien species requires accurate spatiotemporal records of species presence and information about the biological characteristics of species of interest including life cycle information, biotic and abiotic constraints and pathways of spread. The Global Invasive and Alien Traits And Records (GIATAR) dataset provides consolidated dated records of invasive and alien presence at the country-scale combined with a suite of biological information about pests of interest in a standardized, machine-readable format. We provide dated presence records for 46,666 alien taxa in 249 countries constituting 827,300 country-taxon pairs in locations where the taxon’s invasive status is either alien, invasive, or unknown, joined with additional biological information for thousands of taxa. GIATAR is designed to be quickly updateable with future data and easy to integrate into ongoing research on global patterns of alien species movement using scripts provided to query and analyze data. GIATAR provides crucial data needed for researchers and policymakers to compare global invasion trends across a wide range of taxa.

The Hippocampus Represents Information about Movements in Their Temporal Position in a Learned Motor Sequence.

Our repertoire of motor skills is filled with sequential movements that need to be performed in a specific order. Here, we used functional magnetic resonance imaging to investigate whether the human hippocampus, a region known to support temporal order in non-motor memory, represents information about the order of sequential motor actions in human participants (both sexes). We also examined such representations in other regions of the motor network (i.e., the premotor cortex, supplementary motor area, anterior superior parietal lobule, and striatum) already known for their critical role in motor sequence learning. Results showed that the hippocampus represents information about movements in their learned temporal position in the sequence, but not about movements or temporal positions in random movement patterns. Other regions of the motor network coded for movements in their learned temporal position, as well as movements and positions in random movement patterns. Importantly, movement coding contributed to sequence learning patterns in primary, supplementary, and premotor cortices but not in striatal and parietal regions. Our findings deepen our understanding of how striatal and cortical regions contribute to motor sequence learning and point to the capacity of the hippocampus to represent movements in their temporal context, an ability possibly explaining its contribution to motor learning.

The relationship between executed cut angle and speed with lower extremity joint angles during unanticipated side-step cutting in soccer players

BackgroundCertain movements patterns have been indicated in knee injuries during cutting while running tasks. Differences in the executed cut angle (ECA) could partially account for group differences in joint kinematics previously observed, including sex differences. Research QuestionAre there relationships between joint angles with entry speed and ECA during side-step cutting in soccer players? MethodsThis cross-sectional study recruited 21 (10 females) soccer players. Participants completed 45o unanticipated side-step cuts in both directions. Kinematic data were captured with a 12 camera motion capture system with 46 reflective markers placed on the participants. Peak joint angles were determined during the stance phase of the cutting task. Entry speed and ECA were determined from pelvis markers. Hierarchical linear models examined relationships between angles, entry speed, and ECA, after accounting for age, sex, and leg preference. Regression coefficients with 95% confidence intervals were reported and statistical significance (p<0.05) were examined using the Wald statistic. ResultsThe mean ECA (24.6o) was lower than the intended 45o angle. Peak joint angles were significantly related to both ECA and entry speed. Specifically, an increase in ECA by 10o (i.e., sharper cuts) would increase hip internal rotation and ankle plantarflexion by 1.8 to 2.1o, and decrease hip adduction, knee abduction and ankle eversion by 1.3 to 2.4o. Faster entry speeds by 0.5m/s would increase hip flexion, hip internal rotation and knee extension angles by 1.8 to 3.8o, and decrease knee abduction by 2.6o. SignificanceStudies evaluating cutting while running should consider ECA and entry speed in their design. Potential differences could confound between-group comparisons of joint angles, including when comparing sexes, and impact interpretations of injury risk.

Postbreeding ecology of wood ducks in the Illinois River Valley

AbstractThe wood duck (Aix sponsa) consistently ranks within the top 5 harvested duck species for both Illinois and the Mississippi Flyway. While substantial research has been done on wood ducks, especially their breeding ecology, few studies have investigated the postbreeding ecology of the species. We captured and marked wood ducks with either a very high frequency (VHF) radio transmitter or a solar‐charged global system of mobile communication (GSM) transmitter during the postbreeding period from August through September 2018–2020. Capture locations were within the La Grange Pool of the Illinois River extending from near Pekin, Illinois to the La Grange Lock and Dam near Meredosia, Illinois, USA. We used conventional radio‐telemetry techniques to track wood ducks to determine cover type use, home range size, daily movement patterns, survival, and migration chronology. Home range size (95% minimum convex polygon) for wood ducks averaged 6,820 ± 572 ha (SE) and we did not find evidence for a difference by age, sex, or transmitter type. Daily movement distance in August (2,031 ± 51 m) was similar to daily movement distance in September (1,922 ± 44 m), but daily movement distances for August and September were less than daily movement distance for October (3,509 ± 53 m) and November (3,347 ± 106 m). Wood ducks primarily used wetlands with woody (45.0%) and emergent vegetation (40.4%), and the most commonly used wetland types by wood ducks were impounded wetlands (53.8%), lakes (17.6%), and ponds (10.7%). Model‐derived survival during the postbreeding period was 0.79 (95% CI = 0.74–0.84). Daily survival was positively related to increased river level and had a mean increase of 4.06 ± 0.67% for every 0.3‐m increase in the Illinois River level at low river levels (1.5–3.0 m) and a mean increase of 1.38 ± 0.32% for every 0.3‐m increase in the Illinois River level at high river levels (4.0–5.5 m). Average departure date of wood ducks leaving the Illinois River Valley was 27 October (range =13 August–15 December), and adult male wood ducks left the study area 11–16 days earlier than the other age and sex cohorts (H2 = 11.6, P = 0.01). Providing additional waterfowl sanctuaries that contain wooded wetlands, especially in years of low river levels, may increase survival for wood ducks during the postbreeding period.

Integration of multiscale fusion of residual neural network with 2-D gramian angular fields for lower limb movement recognition based on multi-channel sEMG signals

The human lower limb movements recognition (LLMR) plays a pivotal role in active lower limb exoskeleton robots. Employing surface electromyography (sEMG) signals for LLMR allows for the convenient, rapid and stable capture of signal variations, facilitating efficient identification of lower limb motion patterns. However, current sEMG-based LLMR methods face challenges such as incomplete feature extraction, limited contextual information and restricted feature extraction scales during feature extraction. This paper proposed a LLMR method based on Gramian Angular Fields (GAF) and multiscale fusion of Residual Neural Network (MS-ResNet). The denoised sEMG time series was transformed into Gramian Angular Difference Field (GADF) matrix based on GAF. The MS-ResNet model, incorporating ResNet and multiscale feature fusion concepts, was proposed to comprehensively capture global and local information through different-scale feature extraction and fusion, so as to improve recognition performance. sEMG signals from 11 muscles of the preferred leg of 15 healthy subjects were recorded during six common lower limb movements. Experimental analysis investigated the impact of the convolutional kernel size (k × k) in Stream 2 of MS-ResNet and the number of muscles involved on recognition performance. The study revealed that selecting k as 13, coupled with 11 muscles, yielded optimal model performance with the average cross-individual recognition accuracy reaching 97.62 %, demonstrating the model’s efficiency in LLMR. This method could provide a viable solution for developing more efficient and reliable LLMR systems, applicable to lower limb exoskeleton robots and intelligent prosthetics.

Identifying loci in mobility networks with applications in New Zealand work commutes: a statistical test for identifying extreme stationary distribution values in Markov transition matrices

Human mobility describes physical patterns of movement of people within a spatial system. Many of these patterns, including daily commuting, are cyclic and quantifiable. These patterns capture physical phenomena tied to processes studied in urban planning, epidemiology, and other social, behavioral, and economic sciences. This paper advances human mobility research by proposing a statistical method for identifying locations that individual move to and through at a rate proportionally higher than other locations, using commuting data for the country of New Zealand as a case study. We term these locations mobility loci and they capture a global property of communities in which people commute. The method makes use of a directed-graph representation where vertices correspond to locations, and traffic between locations correspond to edge weights. Following a normalization, the graph can be regarded as a Markov chain whose stationary distribution can be calculated. The proposed permutation procedure is then applied to determine which stationary distribution values are larger than what would be expected, given the structure of the directed graph and traffic between locations. The results of this method are evaluated, including a comparison to what is already known about commuting patterns in the area as well as a comparison with similar features.

Seasonal habitat use and diel vertical migration in female spurdog in Nordic waters

BackgroundStudying habitat use and vertical movement patterns of individual fish over continuous time and space is innately challenging and has therefore largely remained elusive for a wide range of species. Amongst sharks, this applies particularly to smaller-bodied and less wide-ranging species such as the spurdog (Squalus acanthias Linnaeus, 1758), which, despite its importance for fisheries, has received limited attention in biologging and biotelemetry studies, particularly in the North-East Atlantic.MethodsTo investigate seasonal variations in fine-scale niche use and vertical movement patterns in female spurdog, we used archival data from 19 pregnant individuals that were satellite-tagged for up to 365 days in Norwegian fjords. We estimated the realised niche space with kernel densities and performed continuous wavelet analyses to identify dominant periods in vertical movement. Triaxial acceleration data were used to identify burst events and infer activity patterns.ResultsPregnant females frequently utilised shallow depths down to 300 m at temperatures between 8 and 14 °C. Oscillatory vertical moments revealed persistent diel vertical migration (DVM) patterns, with descents at dawn and ascents at dusk. This strict normal DVM behaviour dominated in winter and spring and was associated with higher levels of activity bursts, while in summer and autumn sharks predominantly selected warm waters above the thermocline with only sporadic dive and bursts events.ConclusionsThe prevalence of normal DVM behaviour in winter months linked with elevated likely foraging-related activity bursts suggests this movement behaviour to be foraging-driven. With lower number of fast starts exhibited in warm waters during the summer and autumn months, habitat use in this season might be rather driven by behavioural thermoregulation, yet other factors may also play a role. Individual and cohort-related variations indicate a complex interplay of movement behaviour and habitat use with the abiotic and biotic environment. Together with ongoing work investigating fine-scale horizontal movement as well as sex- and age-specific differences, this study provides vital information to direct the spatio-temporal distribution of a newly reopened fishery and contributes to an elevated understanding of the movement ecology of spurdog in the North-East Atlantic and beyond.Graphical

Travel patterns and spatial structure: understanding winter tourism by trajectory data mining

ABSTRACT Mining tourists’ spatiotemporal patterns are fundamental for comprehending and applying spatial structure theories in tourism research. This study mines 27,981 tourist-generated trajectories in Beijing winter tourism to reveal the spatiotemporal patterns and spatial structures using a framework combining similarity measures and improved density-based spatial clustering of applications with noise algorithm. The findings indicate that Beijing winter tourism has established a spatial structure consisting of “three poles-two axes-two secondary poles.” A total of 50 popular routes and 12 patterns of winter tourism can be categorized into three main types and six subcategories: winter tourism leading (skiing oriented, skating oriented), winter tourism with sightseeing (urban snow scene sightseeing, mountain snow scene sightseeing), and winter tourism with leisure (skiing + hot spring therapy, skating + city walking). The findings demonstrate that identifying spatial structures through tourism pattern mining is scientific and feasible. This study examines the movement patterns of tourists to reveal tourism spatial structure and incorporates spatial geography theory to assure the accuracy and scientific validity of the identification process, which enables a comprehensive knowledge of the spatial structure of Beijing's winter tourism industry and broadens the application scenario of spatial geography theory in the era of big data.

Synergistic self-driven and heterogeneous effect of a biomass-derived urchin-like Mn3O4/C3N4 Janus micromotor catalyst for efficient degradation of carbamazepine.

It is well known that obtaining efficient carbamazepine degradation materials or rapid carbamazepine-removal methods is still a challenge in the field of environmental remediation. Hence, the present study aimed to concurrently address these issues by combining a self-driven, heterostructured and low-cost biomass-templated urchin-like Janus micromotor catalyst for highly efficient carbamazepine degradation. The catalyst could autonomously move in a circle-like motion pattern via O2 bubbles generated from the Mn3O4-catalyzed decomposition of H2O2 with a velocity of 223.5 ± 7.0 μm s-1 in 1% H2O2. Benefiting from the well-structured heterojunction at the interface of C3N4 and Mn3O4, carbamazepine (CBZ) was degraded by 61% in 100 min under sunlight irradiation. In addition, density functional theory calculation results proved that the formation of the heterojunction structure promoted the generation of photo-generated carriers. Thus, the presented method provides a promising pathway for the rational construction and preparation of movable catalysts for the efficient removal of organic pollutants from wastewater.

Movement and diving behavior of satellite-tagged male sperm whales in the Gulf of Alaska

Male sperm whales (Physeter macrocephalus) are known to interact with and depredate from commercial longline fishing vessels targeting sablefish (Anoplopoma fimbria) in the Gulf of Alaska (GOA). This study aims to better understand their movement patterns and diving behavior in this region, and in relation to depredation behavior. Between 2007 and 2016 a total of 33 satellite tags were deployed on sperm whales interacting with fishing vessels in the eastern GOA. A subset of these tags also collected dive characteristics. We used state space models to interpolate hourly positions from tags and estimate behavioral state from 29 usable tag records, 14 of which had associated dive information. Whales exhibited slower horizontal movement (1.4 km/hr) within GOA waters compared to south of the GOA (5.5 km/hr), indicating tagged whales sped up when they left the region. Behavioral states indicated primarily foraging behavior (82% of locations) in the GOA and primarily transiting behavior (74% of locations) when whales left the GOA. Dive data showed average ( ± Standard Deviation) maximum dive depths of 396 m ( ± 166), and dive durations of 32 min (± 9). Generalized additive models indicated that dives were significantly deeper and longer during the daytime than dawn, dusk, or nighttime, and dives were significantly deeper and shorter during quarter moons, when tidal currents are weakest. Maximum dive depth decreased in areas of higher sablefish CPUE, suggesting a potential link between the sablefish fishery and depredation behavior. As seafloor depth increased, up to 800 m, dives became deeper, indicating that whales were likely targeting both bathypelagic and mesopelagic prey. This highlights the importance of the GOA continental slope as a foraging ground for male sperm whales. This enhanced understanding of sperm whale foraging ecology informs management and conservation efforts in high latitude foraging grounds.

The effect of cumulative eye movements’ guidance of experts on transition from novice to expert

AbstractBased on the assumptions of cognitive load theory, this study aims to utilize the eye movement data collected from multiple experts to scaffold novice graphic designers. The study has two main stages. In the first stage, eye tracking was used to record the eye movements of 7 experts, who covered eight topics explaining how to use Photoshop. The areas of interest and fixation durations were analyzed for each topic to extract the common patterns. Instructional videos were produced with the guidance of both eye movement patterns and multimedia design principles. In the second stage of this study, those videos were delivered to 30 university students. The experiment group watched the guided videos, whereas the control group watched straight videos, i.e., content without guidance. The guidance elements were reduced (faded) as students got familiar with the interface. All participants were assigned to perform tasks as soon as they completed the videos. The findings showed that the knowledge scores did not significantly differ between groups. Still, the average performance scores of the experiment group were considerably higher than that of the control group. Considering the transition process, the experiment group outperformed the others. The topics in which experts’ eye movements highly matched each other resulted in high-performance gaps among groups.

The efficiency of detecting seabird behaviour from movement patterns: the effect of sampling frequency on inferring movement metrics in Procellariiformes

BackgroundRecent technological advances have resulted in low-cost GPS loggers that are small enough to be used on a range of seabirds, producing accurate location estimates (± 5 m) at sampling intervals as low as 1 s. However, tradeoffs between battery life and sampling frequency result in studies using GPS loggers on flying seabirds yielding locational data at a wide range of sampling intervals. Metrics derived from these data are known to be scale-sensitive, but quantification of these errors is rarely available. Very frequent sampling, coupled with limited movement, can result in measurement error, overestimating movement, but a much more pervasive problem results from sampling at long intervals, which grossly underestimates path lengths.MethodsWe use fine-scale (1 Hz) GPS data from a range of albatrosses and petrels to study the effect of sampling interval on metrics derived from the data. The GPS paths were sub-sampled at increasing intervals to show the effect on path length (i.e. ground speed), turning angles, total distance travelled, as well as inferred behavioural states.ResultsWe show that distances (and per implication ground speeds) are overestimated (4% on average, but up to 20%) at the shortest sampling intervals (1–5 s) and underestimated at longer intervals. The latter bias is greater for more sinuous flights (underestimated by on average 40% when sampling > 1-min intervals) as opposed to straight flight (11%). Although sample sizes were modest, the effect of the bias seemingly varied with species, where species with more sinuous flight modes had larger bias. Sampling intervals also played a large role when inferring behavioural states from path length and turning angles.ConclusionsLocation estimates from low-cost GPS loggers are appropriate to study the large-scale movements of seabirds when using coarse sampling intervals, but actual flight distances are underestimated. When inferring behavioural states from path lengths and turning angles, moderate sampling intervals (10–30 min) may provide more stable models, but the accuracy of the inferred behavioural states will depend on the time period associated with specific behaviours. Sampling rates have to be considered when comparing behaviours derived using varying sampling intervals and the use of bias-informed analyses are encouraged.

Ontogeny of horizontal movement patterns of rehabilitated grey seal juveniles (Halichoerus grypus) in the Baltic Sea

The ethical considerations and scepticism over the ecological benefits have fuelled debate about the rehabilitation of wildlife. Although there is evidence that many rehabilitated species are able to survive after rehabilitation, there is a paucity of research on the behaviour of rehabilitated pinnipeds, including grey seals (Halichoerus grypus). In this study, 14 rehabilitated grey seal juveniles were equipped with biotelemetry devices in order to conduct remote post-release monitoring and to investigate ontogeny of their movements in the Baltic Sea. The study revealed that their movements were similar to wild, non-rehabilitated grey seal pups when leaving their natal site: at first, they exhibited highly exploratory behaviour with largely transient movements, then switched into a resident movement pattern, while maximising foraging and minimising travelling time. Neither sex nor year of release, which varied in terms of rehabilitation time and body mass, had a significant effect on the ontogeny of these movements. Movements were significantly influenced by the time after release, suggesting that rehabilitated juveniles have gained experience and developed their movements over time in order to survive in the wild.

Identification and characterization of particle clusters in fluidized beds via image processing technique: Method development and assessment

Clusters have a significant impact on gas–solid hydrodynamics, thus have garnered sustained research efforts for several decades. Recently, the image processing technology has been popularly used in characterizing clusters due to its non-invasive nature and high spatiotemporal resolution. This study introduced an innovative method for cluster identification by utilizing non-local means filtering and the maximum between-cluster variance. An exhaustive evaluation of image processing-based identification techniques was conducted using the flow data from CFD-DEM simulations. The approach can accurately reproduce the cluster dynamics throughout the entire bed without the need of manual adjustments, whereas traditional global threshold methods often fall short in reliably predicting clusters with low concentration or larger size. At lower gas velocities, there is a clear correlation between cluster characteristic parameters, while this type of relationship diminishes at higher gas velocities. Furthermore, clusters at different horizontal positions exhibit distinct morphologies and movement patterns.

Modelling the maximum ceiling temperature with bifurcated plume in tunnel fires

Evaluation of the temperature profile induced by tunnel fire is of great significance for fire detection and structural damage assessment. In this work, a special plume model, namely, the “plume bifurcation” is introduced, and its impact on the temperature distribution is analysed theoretically. Full-scale tunnel fire experiments and numerical simulations are conducted to investigate the plume evolution under various heat release rates and ventilation conditions. Results show that the plume will sperate into two sub-streams under strong ventilation condition, resulting in the multi-dimensional plume movement pattern when rising. The sub-plume impingement point location, quantified by the longitudinal vertical deflection angle θv and horizontal bifurcation angle θh, is correlated with the fire heat release rate and ventilation condition. The plume bifurcation angle is 0 when the dimensionless ventilation velocity V′≤0.33, marking a single-stream plume; and rapidly increase and then slowly decrease with V′ when V′>0.33, representing the sudden occurrence and decay trend of plume bifurcation with the ventilation velocity. Finally, a novel bifurcated plume-based model to estimate the maximum ceiling temperature is proposed. This study reveals the role of multi-dimensional smoke movement in reshaping the temperature field, providing new perspectives for a deeper understanding of the smoke transport behaviour in longitudinally ventilated tunnel fires.

Understanding the Role of Eye Movement Pattern and Consistency in Isolated English Word Reading Through Hidden Markov Modeling.

In isolated English word reading, readers have the optimal performance when their initial eye fixation is directed to the area between the beginning and word center, that is, the optimal viewing position (OVP). Thus, how well readers voluntarily direct eye gaze to this OVP during isolated word reading may be associated with reading performance. Using Eye Movement analysis with Hidden Markov Models, we discovered two representative eye movement patterns during lexical decisions through clustering, which focused at the OVP and the word center, respectively. Higher eye movement similarity to the OVP-focusing pattern predicted faster lexical decision time in addition to cognitive abilities and lexical knowledge. However, the OVP-focusing pattern was associated with longer isolated single letter naming time, suggesting conflicting visual abilities required for identifying isolated letters and multi-letter words. In contrast, in both word and pseudoword naming, although clustering did not reveal an OVP-focused pattern, higher consistency of the first fixation as measured in entropy predicted faster naming time in addition to cognitive abilities and lexical knowledge. Thus, developing a consistent eye movement pattern focusing on the OVP is essential for word orthographic processing and reading fluency. This finding has important implications for interventions for reading difficulties.

Interpreting the spatial distribution of soil properties with a physically-based distributed hydrological model

Digital soil maps are commonly data-driven as the development of physically-based models for soil mapping is difficult due to the complexity of soils. However, physically-based hydrologic models have been successful in simulating water dynamics. Since water movement is a major driver of pedogenesis, the physical rules that govern water movement might help explain and predict the spatial variation of soil properties. Here, we demonstrate the novel use of a physically-based, distributed hydrologic model to inform the spatial distribution of soil properties. The Distributed Hydrology Soil Vegetation Model (DHSVM) was utilized to simulate soil moisture content (SM) and water table depth (WTD) in two hillslope catchments under pasture and forest management wherein hydrologic model outputs were then compared with soil properties measured in situ. SM sensors and wells were installed in both catchments to validate simulations of soil water movement via Nash-Sutcliffe Efficiency (E). In-situ observations were made at 87 sites within both catchments to study the connection between simulated water movement (SM and WTD) and observed soil properties, namely the depth and thickness of the argillic (Bt), fragic (Btx), and C horizons, and the depth of redoximorphic features. The simulated time series of SM and WTD were also clustered per season using Dynamic Time Warping (DTW), which identified similarity among time series at varying timescales. Model validation suggested that simulations of surficial SM (0–20 cm) were reasonable (E = 0.45), however, simulated subsurface SM (45–60 cm) and WTD were not sufficiently accurate. The thickness of Btx horizons were spatially grouped into different populations by SM clusters from every season except spring. For the other properties, only SM dynamics of specific seasons grouped into significantly different populations, suggesting that the explanatory power of simulated water movement varies seasonally and was greater during winter. Here, we show clusters of simulated SM separated soil properties into statistically different populations, showing that hydrologic models could inform areas that followed different water dynamics related to pedogenic trajectories and related biogeochemical processes not necessarily simulated by the model. As such, physically-based modeling of water dynamics can, therefore, inform and advance digital soil mapping by linking water movement patterns stemming from hydrologic model outputs to spatial patterns of soil properties and pedogenesis.

The biomechanical assessment of two stemless shoulder arthroplasty prostheses in uniformly poor-quality bone mineral density cadaveric specimens

BackgroundStemless shoulder arthroplasty offers several advantages, such as preserving bone stock and reducing periprosthetic fracture risk. However, implant motion can deter osteointegration and increase bone resorption, where micromotion less than 0.150 mm is crucial for bony ingrowth and vital to the success of the implant. The interaction between the implant and the metaphyseal bone and its effects on stability remains unclear. Therefore, this cadaveric study aims to assess the immediate stability of two stemless prostheses in low bone density specimens. MethodsTwenty cadaveric shoulders were used to compare the stability of two stemless shoulder implants by Zimmer-Biomet (model A) and Exactech (model B), subjected to loads of 220 N, 520 N, and 820 N to assess strain and micromotion. FindingsMicromotion at 220 N load was 0.061 ± 0.080 mm and 0.053 ± 0.050 mm, and at 520 N load, 0.279 ± 0.37 mm and 0.311 ± 0.35 mm for models A and B, respectively. The estimated mean force required to achieve a 150 μm micromotion was 356 ± 116 N and 315 ± 61 N for models A and B, respectively. Motion analysis revealed distinct movement patterns for each implant, with model B demonstrating better force distribution on the bone despite no significance. InterpretationForces over 520 N (high postoperative rehabilitation force) could hinder bone integration with prostheses due to excessive micromotion. Conversely, forces around 220 N (preconditioning loading force) are considered safe for prosthesis stability even with low bone density. These insights may caution against using stemless implants when bone density is low, and help guide clinical decisions on the duration of rehabilitation and sling use after stemless arthroplasty.