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. © 2020 American Medical Association. All rights reserved

A behavior-based malware spreading model for vehicle-to-vehicle communications in VANET networks

Network attacking using malware has become very popular on the Internet and in many other networks, namely Vehicular Ad-hoc Network (VANET) networks. It is required to have the model describing the malware spreading based on factors, which directly affect this process to limit its influences. In this paper, we propose a mathematical model called SEIR-S (Susceptible– Exposed–Infectious–Recovered–Susceptible) based on the characteristics of the VANET network and the well-known disease-spreading model SIR (Susceptible–Infectious–Recovered). We take into account possible behaviors of malware and provide the corresponding states to vehicles: Susceptible (S), Exposed (E), Infectious (I), Recovered (R). We evaluate the basic reproduction number R0 of the model and perform a stability analysis of the proposed model. The results show that, when R0 < 1, the malware spreading will gradually decrease, and, when R0 > 1, that spreading cannot be extinguished. We also point out the condition that we can control the endemic in the VANET network. In addition, the correctness of the proposed model is verified using both numerical analysis and agent-based simulation on NetLogo. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

De enzymatische produktie van 100 tja mandelonitril uit HeN en benzaldehyde met optimale reactor configuratie

Document(en) uit de collectie Chemische ProcestechnologieDelftChemTechApplied Science

High efficiency green/yellow and red InGaN/AlGaN nanowire light-emitting diodes grown by molecular beam epitaxy

We report on the achievement of high efficiency green, yellow, and red InGaN/AlGaN dot-in-a-wire nanowire light-emitting diodes grown on Si(111) by molecular beam epitaxy. The peak emission wavelengths were altered by varying the growth conditions, including the substrate temperature, and In/Ga flux ratio. The devices demonstrate relatively high (>40%) internal quantum efficiency at room temperature, relative to that measured at 5 K. Moreover, negligible blue-shift in peak emission spectrum associated with no efficiency droop was measured when injection current was driven up to 556 A/cm2

Bi-objective optimization for the vehicle routing problem with time windows: Using route similarity to enhance performance

Abstract. The Vehicle Routing Problem with Time Windows is a complex combinatorial optimization problem which can be seen as a fusion of two well known sub-problems: the Travelling Salesman Problem and the Bin Packing Problem. Its main objective is to find the lowest-cost set of routes to deliver demand, using identical vehicles with limited capacity, to customers with fixed service time windows. In this paper, we consider the minimization of the number of routes and the total cost simultaneously. Although previous evolutionary studies have considered this problem, none of them has focused on the similarity of solutions in the population. We propose a method to measure route similarity and incorporate it into an evolutionary algorithm to solve the bi-objective VRPTW. We have applied this algorithm to a publicly available set of benchmark instances, resulting in solutions that are competitive or better than others previously published. Key words: Vehicle routing problem, multi-objective optimization, evolutionary algorithm, similarity of solutions