Symmetry in Triple Hop Distance Hides Asymmetries in Knee Function After ACL Reconstruction in Athletes at Return to Sports.

BACKGROUND: After anterior cruciate ligament reconstruction (ACLR), a battery of strength and hop tests is frequently used to determine the readiness of an athlete to successfully return to sports. However, the anterior cruciate ligament reinjury rate remains alarmingly high. PURPOSE: To evaluate the lower limb function of athletes after ACLR at the time when they had been cleared to return to sports (RTS). We aimed to evaluate if passing discharge criteria ensures restoration of normal lower limb biomechanics in terms of kinematics, kinetics, work, and percentage work contribution during a triple hop for distance. STUDY DESIGN: Controlled laboratory study. METHODS: Integrated 3-dimensional motion analysis was performed in 24 male athletes after ACLR when cleared to RTS and 23 healthy male controls during the triple-hop test. The criteria for RTS were (1) clearance by the surgeon and the physical therapist, (2) completion of a sports-specific on-field rehabilitation program, and (3) limb symmetry index >90% after quadriceps strength and hop battery tests. Lower limb and trunk kinematics, as well as knee joint moments and work, were calculated. Between-limb differences (within athletes after ACLR) and between-group differences (between ACLR and control groups) were evaluated using mixed linear models. RESULTS: Although achieving 97% limb symmetry in distance hopped and displaying almost 80% symmetry for knee work absorption in the second rebound and third landing, the ACLR cohorts demonstrated only 51% and 66% limb symmetry for knee work generation in the first and second rebound phases, respectively. During both work generation phases of the triple hop, the relative contribution of the involved knee was significantly smaller, with a prominent compensation from the hip joint (P < .001, for all phases) as compared with the uninvolved limb and the controls. In addition, patients deployed a whole body compensatory strategy to account for the between-limb differences in knee function, mainly at the hip, pelvis, and trunk. CONCLUSION: Symmetry in the triple hop for distance masked important deficits in the knee joint work. These differences were more prominent during work generation (concentric-propulsive) than work absorption (eccentric-landing). CLINICAL RELEVANCE: Symmetry in hop distance during the triple hop test masked significant asymmetries in knee function after ACLR and might not be the appropriate outcome to use as a discharge criterion. Differences between limbs in athletes after ACLR were more prominent during the power generation than the absorption phase.

Potential of deep learning segmentation for the extraction of archaeological features from historical map series.

Historical maps present a unique depiction of past landscapes, providing evidence for a wide range of information such as settlement distribution, past land use, natural resources, transport networks, toponymy and other natural and cultural data within an explicitly spatial context. Maps produced before the expansion of large-scale mechanized agriculture reflect a landscape that is lost today. Of particular interest to us is the great quantity of archaeologically relevant information that these maps recorded, both deliberately and incidentally. Despite the importance of the information they contain, researchers have only recently begun to automatically digitize and extract data from such maps as coherent information, rather than manually examine a raster image. However, these new approaches have focused on specific types of information that cannot be used directly for archaeological or heritage purposes. This paper provides a proof of concept of the application of deep learning techniques to extract archaeological information from historical maps in an automated manner. Early twentieth century colonial map series have been chosen, as they provide enough time depth to avoid many recent large-scale landscape modifications and cover very large areas (comprising several countries). The use of common symbology and conventions enhance the applicability of the method. The results show deep learning to be an efficient tool for the recovery of georeferenced, archaeologically relevant information that is represented as conventional signs, line-drawings and text in historical maps. The method can provide excellent results when an adequate training dataset has been gathered and is therefore at its best when applied to the large map series that can supply such information. The deep learning approaches described here open up the possibility to map sites and features across entire map series much more quickly and coherently than other available methods, opening up the potential to reconstruct archaeological landscapes at continental scales.

Correction: Long Term Population, City Size and Climate Trends in the Fertile Crescent: A First Approximation.

[This corrects the article DOI: 10.1371/journal.pone.0152563.].

Long Term Population, City Size and Climate Trends in the Fertile Crescent: A First Approximation.

Over the last 8000 years the Fertile Crescent of the Near East has seen the emergence of urban agglomerations, small scale polities and large territorial empires, all of which had profound effects on settlement patterns. Computational approaches, including the use of remote sensing data, allow us to analyse these changes at unprecedented geographical and temporal scales. Here we employ these techniques to examine and compare long term trends in urbanisation, population and climate records. Maximum city size is used as a proxy for the intensity of urbanisation, whilst population trends are modelled from settlement densities in nine archaeological surveys conducted over the last 30 years across the region. These two measures are then compared with atmospheric moisture levels derived from multiple proxy analyses from two locations close to the study area, Soreq Cave in Israel and Lake Van in south-eastern Turkey, as well as wider literature. The earliest urban sites emerged during a period of relatively high atmospheric moisture levels and conform to a series of size thresholds. However, after the Early Bronze Age maximum urban size and population levels increase rapidly whilst atmospheric moisture declines. We argue that although the initial phase of urbanization may have been linked to climate conditions, we can see a definitive decoupling of climate and settlement patterns after 2000 BC. We relate this phenomenon to changes in socio-economic organisation and integration in large territorial empires. The complex relationships sustaining urban growth during this later period resulted in an increase in system fragility and ultimately impacted on the sustainability of cities in the long term.