Curve Reconstruction via the Global Statistics of Natural Curves

Reconstructing the missing parts of a curve has been the subject of much computational research, with applications in image inpainting, object synthesis, etc. Different approaches for solving that problem are typically based on processes that seek visually pleasing or perceptually plausible completions. In this work we focus on reconstructing the underlying physically likely shape by utilizing the global statistics of natural curves. More specifically, we develop a reconstruction model that seeks the mean physical curve for a given inducer configuration. This simple model is both straightforward to compute and it is receptive to diverse additional information, but it requires enough samples for all curve configurations, a practical requirement that limits its effective utilization. To address this practical issue we explore and exploit statistical geometrical properties of natural curves, and in particular, we show that in many cases the mean curve is scale invariant and oftentimes it is extensible. This, in turn, allows to boost the number of examples and thus the robustness of the statistics and its applicability. The reconstruction results are not only more physically plausible but they also lead to important insights on the reconstruction problem, including an elegant explanation why certain inducer configurations are more likely to yield consistent perceptual completions than others.Comment: CVPR versio

Survival probabilities in time-dependent random walks

We analyze the dynamics of random walks in which the jumping probabilities are periodic {\it time-dependent} functions. In particular, we determine the survival probability of biased walkers who are drifted towards an absorbing boundary. The typical life-time of the walkers is found to decrease with an increment of the oscillation amplitude of the jumping probabilities. We discuss the applicability of the results in the context of complex adaptive systems.Comment: 4 pages, 3 figure

Temporal oscillations and phase transitions in the evolutionary minority game

The study of societies of adaptive agents seeking minority status is an active area of research. Recently, it has been demonstrated that such systems display an intriguing phase-transition: agents tend to {\it self-segregate} or to {\it cluster} according to the value of the prize-to-fine ratio, $R$. We show that such systems do {\it not} establish a true stationary distribution. The winning-probabilities of the agents display temporal oscillations. The amplitude and frequency of the oscillations depend on the value of $R$. The temporal oscillations which characterize the system explain the transition in the global behavior from self-segregation to clustering in the $R<1$ case.Comment: 5 pages, 5 figure

Self-Segregation vs. Clustering in the Evolutionary Minority Game

Complex adaptive systems have been the subject of much recent attention. It is by now well-established that members (`agents') tend to self-segregate into opposing groups characterized by extreme behavior. However, while different social and biological systems manifest different payoffs, the study of such adaptive systems has mostly been restricted to simple situations in which the prize-to-fine ratio, $R$, equals unity. In this Letter we explore the dynamics of evolving populations with various different values of the ratio $R$, and demonstrate that extreme behavior is in fact {\it not} a generic feature of adaptive systems. In particular, we show that ``confusion'' and ``indecisiveness'' take over in times of depression, in which case cautious agents perform better than extreme ones.Comment: 4 pages, 4 figure

Delayed Effect of Acupuncture Treatment in OA of the Knee: A Blinded, Randomized, Controlled Trial

To assess the efficacy in providing improved function and pain relief by administering 8 weeks of acupuncture as adjunctive therapy to standard care in elderly patients with OA of the knee. This randomized, controlled, blinded trial was conducted on 55 patients with OA of the knee. Forty-one patients completed the study (26 females, 15 males, mean age ± SD 71.7 ± 8.6 years). Patients were randomly divided into an intervention group that received biweekly acupuncture treatment (n = 28) and a control group that received sham acupuncture (n = 27), both in addition to standard therapy, for example, NSAIDS, cyclooxygenase-2 inhibitors, acetaminophen, intra-articular hyaluronic acid and steroid injections. Primary outcomes measures were changes in the Knee Society Score (KSS) knee score and in KSS function and pain ratings at therapy onset, at 8 weeks (closure of study) and at 12 weeks (1 month after last treatment). Secondary outcomes were patient satisfaction and validity of sham acupuncture. There was significant improvement in all three scores in both groups after 8 and 12 weeks compared with baseline (P < .05). Significant differences between the intervention and control groups in the KSS knee score (P = .036) was apparent only after 12 weeks. Patient satisfaction was higher in the intervention group. Adjunctive acupuncture treatment seems to provide added improvement to standard care in elderly patients with OA of the knee. Future research should determine the optimal duration of acupuncture treatment in the context of OA

Strategy updating rules and strategy distributions in dynamical multiagent systems

In the evolutionary version of the minority game, agents update their strategies (gene-value $p$) in order to improve their performance. Motivated by recent intriguing results obtained for prize-to-fine ratios which are smaller than unity, we explore the system's dynamics with a strategy updating rule of the form $p \to p \pm \delta p$ ($0 \leq p \leq 1$). We find that the strategy distribution depends strongly on the values of the prize-to-fine ratio $R$, the length scale $\delta p$, and the type of boundary condition used. We show that these parameters determine the amplitude and frequency of the the temporal oscillations observed in the gene space. These regular oscillations are shown to be the main factor which determines the strategy distribution of the population. In addition, we find that agents characterized by $p={1 \over 2}$ (a coin-tossing strategy) have the best chances of survival at asymptotically long times, regardless of the value of $\delta p$ and the boundary conditions used.Comment: 4 pages, 7 figure

Global Retinoblastoma Presentation and Analysis by National Income Level.

Importance: Early diagnosis of retinoblastoma, the most common intraocular cancer, can save both a child's life and vision. However, anecdotal evidence suggests that many children across the world are diagnosed late. To our knowledge, the clinical presentation of retinoblastoma has never been assessed on a global scale. Objectives: To report the retinoblastoma stage at diagnosis in patients across the world during a single year, to investigate associations between clinical variables and national income level, and to investigate risk factors for advanced disease at diagnosis. Design, Setting, and Participants: A total of 278 retinoblastoma treatment centers were recruited from June 2017 through December 2018 to participate in a cross-sectional analysis of treatment-naive patients with retinoblastoma who were diagnosed in 2017. Main Outcomes and Measures: Age at presentation, proportion of familial history of retinoblastoma, and tumor stage and metastasis. Results: The cohort included 4351 new patients from 153 countries; the median age at diagnosis was 30.5 (interquartile range, 18.3-45.9) months, and 1976 patients (45.4%) were female. Most patients (n = 3685 [84.7%]) were from low- and middle-income countries (LMICs). Globally, the most common indication for referral was leukocoria (n = 2638 [62.8%]), followed by strabismus (n = 429 [10.2%]) and proptosis (n = 309 [7.4%]). Patients from high-income countries (HICs) were diagnosed at a median age of 14.1 months, with 656 of 666 (98.5%) patients having intraocular retinoblastoma and 2 (0.3%) having metastasis. Patients from low-income countries were diagnosed at a median age of 30.5 months, with 256 of 521 (49.1%) having extraocular retinoblastoma and 94 of 498 (18.9%) having metastasis. Lower national income level was associated with older presentation age, higher proportion of locally advanced disease and distant metastasis, and smaller proportion of familial history of retinoblastoma. Advanced disease at diagnosis was more common in LMICs even after adjusting for age (odds ratio for low-income countries vs upper-middle-income countries and HICs, 17.92 [95% CI, 12.94-24.80], and for lower-middle-income countries vs upper-middle-income countries and HICs, 5.74 [95% CI, 4.30-7.68]). Conclusions and Relevance: This study is estimated to have included more than half of all new retinoblastoma cases worldwide in 2017. Children from LMICs, where the main global retinoblastoma burden lies, presented at an older age with more advanced disease and demonstrated a smaller proportion of familial history of retinoblastoma, likely because many do not reach a childbearing age. Given that retinoblastoma is curable, these data are concerning and mandate intervention at national and international levels. Further studies are needed to investigate factors, other than age at presentation, that may be associated with advanced disease in LMICs

Depth Based Fruit Detection from Viewer-Based Pose

Abstract Seeking to accurately detect and localize fruit of any color in 3D space for selective agrobotical operations, we exploit data given by Time-of-Flight or RGB-D cameras and propose a novel shape-based fruit detector using a fruit pose reference frame relative to the viewer. Surface normals, which are shaped-based local features, are accumulated into bins of different shapes along the reference frame&apos;s axes. The used normals are represented using two angles from a viewer-based reference frame, to achieve a representation that is suitable for fruit types that are almost symmetric around an axis (e.g., bell-peppers), without having an effect on fruit types with no axis-symmetry. Results are shown on a particularly challenging pepper dataset