Predicting the temporal activity patterns of new venues.

Estimating revenue and business demand of a newly opened venue is paramount as these early stages often involve critical decisions such as first rounds of staffing and resource allocation. Traditionally, this estimation has been performed through coarse-grained measures such as observing numbers in local venues or venues at similar places (e.g., coffee shops around another station in the same city). The advent of crowdsourced data from devices and services carried by individuals on a daily basis has opened up the possibility of performing better predictions of temporal visitation patterns for locations and venues. In this paper, using mobility data from Foursquare, a location-centric platform, we treat venue categories as proxies for urban activities and analyze how they become popular over time. The main contribution of this work is a prediction framework able to use characteristic temporal signatures of places together with k-nearest neighbor metrics capturing similarities among urban regions, to forecast weekly popularity dynamics of a new venue establishment in a city neighborhood. We further show how we are able to forecast the popularity of the new venue after one month following its opening by using locality and temporal similarity as features. For the evaluation of our approach we focus on London. We show that temporally similar areas of the city can be successfully used as inputs of predictions of the visit patterns of new venues, with an improvement of 41% compared to a random selection of wards as a training set for the prediction task. We apply these concepts of temporally similar areas and locality to the real-time predictions related to new venues and show that these features can effectively be used to predict the future trends of a venue. Our findings have the potential to impact the design of location-based technologies and decisions made by new business owners

Prevalence of abnormal findings in 230 knees of asymptomatic adults using 3.0 T MRI.

OBJECTIVE: To identify abnormalities in asymptomatic sedentary individuals using 3.0 Tesla high-resolution MRI. MATERIALS AND METHODS: The cohort comprised of 230 knees of 115 uninjured sedentary adults (51 males, 64 females; median age: 44 years). All participants had bilateral knee 3.0 T MRIs. Two senior musculoskeletal radiologists graded all intraarticular knee structures using validated scoring systems. Participants completed Knee Injury and Osteoarthritis Outcome Score questionnaires at the time of the MRI scan. RESULTS: MRI showed abnormalities in the majority (97%) of knees. Thirty percent knees had meniscal tears: horizontal (23%), complex (3%), vertical (2%), radial (2%) and bucket handle (1%). Cartilage and bone marrow abnormalities were prevalent at the patellofemoral joint (57% knees and 48% knees, respectively). Moderate and severe cartilage lesions were common, in 19% and 31% knees, respectively, while moderate and severe bone marrow oedema in 19% and 31% knees, respectively. Moderate-intensity lesion in tendons was found in 21% knees and high-grade tendonitis in 6% knees-the patellar (11% and 2%, respectively) and quadriceps (7% and 2%, respectively) tendons being most affected. Three percent partial ligamentous ruptures were found, especially of the anterior cruciate ligament (2%). CONCLUSION: Nearly all knees of asymptomatic adults showed abnormalities in at least one knee structure on MRI. Meniscal tears, cartilage and bone marrow lesions of the patellofemoral joint were the most common pathological findings. Bucket handle and complex meniscal tears were reported for the first time in asymptomatic knees

Is the immediate effect of marathon running on novice runners' knee joints sustained within 6 months after the run? A follow-up 3.0 T MRI study.

OBJECTIVE: To evaluate changes in the knee joints of asymptomatic first-time marathon runners, using 3.0 T MRI, 6 months after finishing marathon training and run. MATERIALS AND METHODS: Six months after their participation in a baseline study regarding their knee joints, 44 asymptomatic novice marathoners (17 males, 27 females, mean age 46 years old) agreed to participate in a repeat MRI investigation: 37 completed both a standardized 4-month-long training programme and the marathon (marathon runners); and 7 dropped out during training (pre-race dropouts). The participants already underwent bilateral 3.0 T MRIs: 6 months before and 2 weeks after their first marathon, the London Marathon 2017. This study was a follow-up assessment of their knee joints. Each knee structure was assessed using validated scoring/grading systems at all time points. RESULTS: Two weeks after the marathon, 3 pre-marathon bone marrow lesions and 2 cartilage lesions showed decrease in radiological score on MRI, and the improvement was sustained at the 6-month follow-up. New improvements were observed on MRI at follow-up: 5 pre-existing bone marrow lesions and 3 cartilage lesions that remained unchanged immediately after the marathon reduced in their extent 6 months later. No further lesions appeared at follow-up, and the 2-week post-marathon lesions showed signs of reversibility: 10 of 18 bone marrow oedema-like signals and 3 of 21 cartilage lesions decreased on MRI. CONCLUSION: The knees of novice runners achieved sustained improvement, for at least 6 months post-marathon, in the condition of their bone marrow and articular cartilage

Predicting the temporal activity patterns of new venues

Estimating revenue and business demand of a newly opened venue is paramount as these early stages often involve critical decisions such as first rounds of staffing and resource allocation. Traditionally, this estimation has been performed through coarse-grained measures such as observing numbers in local venues or venues at similar places (e.g., coffee shops around another station in the same city). The advent of crowdsourced data from devices and services carried by individuals on a daily basis has opened up the possibility of performing better predictions of temporal visitation patterns for locations and venues. In this paper, using mobility data from Foursquare, a location-centric platform, we treat venue categories as proxies for urban activities and analyze how they become popular over time. The main contribution of this work is a prediction framework able to use characteristic temporal signatures of places together with k-nearest neighbor metrics capturing similarities among urban regions, to forecast weekly popularity dynamics of a new venue establishment in a city neighborhood. We further show how we are able to forecast the popularity of the new venue after one month following its opening by using locality and temporal similarity as features. For the evaluation of our approach we focus on London. We show that temporally similar areas of the city can be successfully used as inputs of predictions of the visit patterns of new venues, with an improvement of 41% compared to a random selection of wards as a training set for the prediction task. We apply these concepts of temporally similar areas and locality to the real-time predictions related to new venues and show that these features can effectively be used to predict the future trends of a venue. Our findings have the potential to impact the design of location-based technologies and decisions made by new business owners

Improved Exercise-Related Skeletal Muscle Oxygen Consumption Following Uptake of Endurance Training Measured Using Near-Infrared Spectroscopy

Skeletal muscle metabolic function is known to respond positively to exercise interventions. Developing non-invasive techniques that quantify metabolic adaptations and identifying interventions that impart successful response are ongoing challenges for research. Healthy non-athletic adults (18–35 years old) were enrolled in a study investigating physiological adaptations to a minimum of 16 weeks endurance training prior to undertaking their first marathon. Before beginning training, participants underwent measurements of skeletal muscle oxygen consumption using near-infrared spectroscopy (NIRS) at rest (resting muscleV˙O2) and immediately following a maximal exercise test (post-exercise muscleV˙O2). Exercise-related increase in muscleV˙O2 (ΔmV˙O2) was derived from these measurements and cardio-pulmonary peakV˙O2 measured by analysis of expired gases. All measurements were repeated within 3 weeks of participants completing following the marathon and marathon completion time recorded. MuscleV˙O2 was positively correlated with cardio-pulmonary peakV˙O2 (r = 0.63, p < 0.001). MuscleV˙O2 increased at follow-up (48% increase; p = 0.004) despite no change in cardio-pulmonary peakV˙O2 (0% change; p = 0.97). Faster marathon completion time correlated with higher cardio-pulmonary peakV˙O2 (rpartial = −0.58, p = 0.002) but not muscleV˙O2 (rpartial = 0.16, p = 0.44) after adjustment for age and sex [and adipose tissue thickness (ATT) for muscleV˙O2 measurements]. Skeletal muscle metabolic adaptions occur following training and completion of a first-time marathon; these can be identified non-invasively using NIRS. Although the cardio-pulmonary system is limiting for running performance, skeletal muscle changes can be detected despite minimal improvement in cardio-pulmonary function

Can marathon running improve knee damage of middle-aged adults? A prospective cohort study.

Objectives: To evaluate the short-term impact of long-distance running on knee joints using MRI. Methods: 82 healthy adults participating in their first marathon underwent 3T (Tesla) MRI of both knees 6 months before and half a month after the marathon: 71 completed both the 4 month-long standardised training programme and the marathon; and 11 dropped-out during training and did not run the marathon. Two senior musculoskeletal radiologists graded the internal knee structures using validated scoring systems. Participants completed Knee Injury and Osteoarthritis Outcome Score questionnaires at each visit for self-reporting knee function. Results: Premarathon and pretraining MRI showed signs of damage, without symptoms, to several knee structures in the majority of the 82 middle-aged volunteers. However, after the marathon, MRI showed a reduction in the radiological score of damage in: subchondral bone marrow oedema in the condyles of the tibia (p=0.011) and femur (p=0.082). MRI did also show an increase in radiological scores to the following structures: cartilage of the lateral patella (p=0.0005); semimembranosus tendon (p=0.016); iliotibial band (p<0.0001) and the prepatellar bursa (p=0.016). Conclusion: Improvement to damaged subchondral bone of the tibial and femoral condyles was found following the marathon in novice runners, as well as worsening of the patella cartilage although asymptomatic. This is the most robust evidence to link marathon running with knee joint health and provides important information for those seeking to understand the link between long distance running and osteoarthritis of the main weight-bearing areas of the knee