Collision Avoidance Smartphone

There are many instances in day-to-day life where people cannot or would rather not pay full attention to their surroundings. Walking while preoccupied with a smartphone or walking while blind are excellent examples where technology could be used to make the task of avoiding 2collisions reactive, instead of proactive. A device which monitors a user’s surroundings and notifies the user when a potential collision is detected (and, additionally, notifying them as to where the obstacle is with respect to them) could be used to make walking distracted less of a hazard for the user and those around the user and potentially improve navigation for the visually impaired. The device will connect with the smartphone via bluetooth and the information sent by the device will be displayed over a smartphone app, and haptic feedback for the visually impaired. The device should be rechargeable, self-contained, small enough to connect to a smartphone, and it should be able to communicate with any smartphone that has bluetooth capability making the device universal

Multi-objective evolution for Generalizable Policy Gradient Algorithms

Performance, generalizability, and stability are three Reinforcement Learning (RL) challenges relevant to many practical applications in which they present themselves in combination. Still, state-of-the-art RL algorithms fall short when addressing multiple RL objectives simultaneously and current human-driven design practices might not be well-suited for multi-objective RL. In this paper we present MetaPG, an evolutionary method that discovers new RL algorithms represented as graphs, following a multi-objective search criteria in which different RL objectives are encoded in separate fitness scores. Our findings show that, when using a graph-based implementation of Soft Actor-Critic (SAC) to initialize the population, our method is able to find new algorithms that improve upon SAC's performance and generalizability by 3% and 17%, respectively, and reduce instability up to 65%. In addition, we analyze the graph structure of the best algorithms in the population and offer an interpretation of specific elements that help trading performance for generalizability and vice versa. We validate our findings in three different continuous control tasks: RWRL Cartpole, RWRL Walker, and Gym Pendulum.Comment: 23 pages, 12 figures, 10 table

Exploring the nature and synchronicity of early cluster formation in the Large Magellanic Cloud - IV. Evidence for multiple populations in Hodge 11 and NGC 2210

We present a multiple population search in two old Large Magellanic Cloud (LMC) Globular clusters, Hodge 11 and NGC 2210. This work uses data from the Advanced Camera for Surveys and Wide Field Camera 3 on the Hubble Space Telescope from programme GO- 14164 in Cycle 23. Both of these clusters exhibit a broadened main sequence with the second population representing (20±~5) per cent forNGC2210 and (30±~5) per cent forHodge 11. In both clusters, the smaller population is redder than the primary population, suggesting CNO variations. Hodge 11 also displays a bluer second population in the horizontal branch, which is evidence for helium enhancement. However, even though NGC 2210 shows similarities to Hodge 11 in the main sequence, there does not appear to be a second population on NGC 2210's horizontal branch. This is the first photometric evidence that ancient LMC Globular clusters exhibit multiple stellar populations.Fil: Gilligan, Christina K.. Dartmouth College; Estados UnidosFil: Chaboyer, Brian. Dartmouth College; Estados UnidosFil: Cummings, Jeffrey D.. University Johns Hopkins; Estados UnidosFil: Mackey, Dougal. Australian National University. Research School of Astronomy & Astrophysics; AustraliaFil: Cohen, Roger E.. Space Telescope Science Institute; Estados UnidosFil: Geisler, Douglas. Universidad de La Serena; ChileFil: Grocholski, Aaron J.. University of Washington; Estados UnidosFil: Parisi, Maria Celeste. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; ArgentinaFil: Sarajedini, Ata. University of Florida; Estados UnidosFil: Ventura, Paolo. Osservatorio Astronomico Di Roma; ItaliaFil: Villanova, Sandro. Universidad de Concepción; ChileFil: Yang, Soung-Chul. Korea Astronomy And Space Science Institute; Corea del SurFil: Wagner-Kaiser, Rachel. University of Florida; Estados Unido

Exploring the nature and synchronicity of early cluster formation in the Large Magellanic Cloud - V. Multiple populations in ancient globular clusters

We examine four ancient LargeMagellanic Cloud (LMC) globular clusters (GCs) for evidence of multiple stellar populations using the Advanced Camera for Surveys andWide Field Camera 3 on the Hubble Space Telescope Programme GO-14164. NGC 1466, NGC 1841, and NGC 2257 all show evidence for a redder, secondary population along themain sequence. Reticulum does not showevidence for the presence of a redder population, but thisGChas the least number of stars and Monte Carlo simulations indicate that the sample of main-sequence stars is too small to robustly infer whether a redder population exists in this cluster. The second, redder, population of the other three clusters constitutes ∼ 30 - 40 per cent of the total population along the main sequence. This brings the total number of ancient LMC GCs with known split or broadened main sequences to five. However, unlike for Hodge 11 and NGC 2210 (see Gilligan et al. (2019)), none of the clusters shows evidence for multiple populations in the horizontal branch. We also do not find evidence of a second population along the red giant branch.Fil: Gilligan, Christina K.. Dartmouth College; Estados UnidosFil: Chaboyer, Brian. Dartmouth College; Estados UnidosFil: Cummings, Jeffrey D.. University Johns Hopkins; Estados UnidosFil: Mackey, Dougal. Australian National University; AustraliaFil: Cohen, Roger E.. Space Telescope Science Institute; Estados UnidosFil: Geisler, Douglas. Universidad de Concepción; ChileFil: Grocholski, Aaron J.. University of Florida; Estados UnidosFil: Parisi, Maria Celeste. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; ArgentinaFil: Sarajedini, Ata. University of Florida; Estados UnidosFil: Ventura, Paolo. Osservatorio Astronomico Di Roma; ItaliaFil: Villanova, Sandro. Universidad de Concepción; ChileFil: Yang, Soung-Chul. Korea Astronomy And Space Science Institute; Corea del SurFil: Wagner-Kaiser, Rachel. University of Florida; Estados Unido

Exploring the nature and synchronicity of early cluster formation in the Large Magellanic Cloud - IV. Evidence for multiple populations in Hodge 11 and NGC 2210

We present a multiple population search in two old Large Magellanic Cloud (LMC) Globular clusters, Hodge 11 and NGC 2210. This work uses data from the Advanced Camera for Surveys and Wide Field Camera 3 on the Hubble Space Telescope from programme GO14164 in Cycle 23. Both of these clusters exhibit a broadened main sequence with the second population representing (20 ±∼5) per cent for NGC 2210 and (30±∼5) per cent for Hodge 11. In both clusters, the smaller population is redder than the primary population, suggesting CNO variations. Hodge 11 also displays a bluer second population in the horizontal branch, which is evidence for helium enhancement. However, even though NGC 2210 shows similarities to Hodge 11 in the main sequence, there does not appear to be a second population on NGC 2210’s horizontal branch. This is the first photometric evidence that ancient LMC Globular clusters exhibit multiple stellar populations.This research has used NASA’s Astrophysics Data System. Based on observations made with the NASA/ESA Hubble Space Telescope, obtained from the data archive at the Space Telescope Science Institute. STScI is operated by the Association of Universities for Research in Astronomy, Inc. under NASA contract NAS 5- 26555. This work was supported in part by STScI through a grant HST-GO-14164. DG gratefully acknowledges support from the Chilean Centro de Excelencia en Astrof´ısica y Tecnolog´ıas Afines (CATA) BASAL grant AFB-170002. DG also acknowledges financial support from the Direccion de Investigaci ´ on y Desarrollo ´ de la Universidad de La Serena through the Programa de Incentivo a la Investigacion de Acad ´ emicos (PIA-DIDULS). DM gratefully ´ acknowledges support from an Australian Research Council (ARC) Future Fellowship (FT160100206). SV gratefully acknowledges the support provided by Fondecyt reg. n. 1170518

Connective Tissue Growth Factor in Regulation of RhoA Mediated Cytoskeletal Tension Associated Osteogenesis of Mouse Adipose-Derived Stromal Cells

Background: Cytoskeletal tension is an intracellular mechanism through which cells convert a mechanical signal into a biochemical response, including production of cytokines and activation of various signaling pathways. Methods/Principal Findings: Adipose-derived stromal cells (ASCs) were allowed to spread into large cells by seeding them at a low-density (1,250 cells/cm 2), which was observed to induce osteogenesis. Conversely, ASCs seeded at a high-density (25,000 cells/cm 2) featured small cells that promoted adipogenesis. RhoA and actin filaments were altered by changes in cell size. Blocking actin polymerization by Cytochalasin D influenced cytoskeletal tension and differentiation of ASCs. To understand the potential regulatory mechanisms leading to actin cytoskeletal tension, cDNA microarray was performed on large and small ASCs. Connective tissue growth factor (CTGF) was identified as a major regulator of osteogenesis associated with RhoA mediated cytoskeletal tension. Subsequently, knock-down of CTGF by siRNA in ASCs inhibited this osteogenesis. Conclusions/Significance: We conclude that CTGF is important in the regulation of cytoskeletal tension mediated AS

Efficient Learning and Feature Selection in High Dimensional Regression

We present a novel algorithm for efficient learning and feature selection in high-dimensional regression problems. We arrive at this model through a modification of the standard regression model, enabling us to derive a probabilistic version of the well-known statistical regression technique of backfitting. Using the expectation-maximization algorithm, along with variational approximation methods to overcome intractability, we extend our algorithm to include automatic relevance detection of the input features. This variational Bayesian least squares (VBLS) approach retains its simplicity as a linear model, but offers a novel statistically robust black-box approach to generalized linear regression with high-dimensional inputs. It can be easily extended to nonlinear regression and classification problems. In particular, we derive the framework of sparse Bayesian learning, the relevance vector machine, with VBLS at its core, offering significant computational and robustness advantages for this class of methods. The iterative nature of VBLS makes it most suitable for real-time incremental learning, which is crucial especially in the application domain of robotics, brain-machine interfaces, and neural prosthetics, where real-time learning of models for control is needed. We evaluate our algorithm on synthetic and neurophysiological data sets, as well as on standard regression and classification benchmark data sets, comparing it with other competitive statistical approaches and demonstrating its suitability as a drop-in replacement for other generalized linear regression techniques

Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. Methods: We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting. Findings: Globally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 3·9% (95% uncertainty interval [UI] 3·1-4·6) from 1990 to 2017; however, the all-age YLD rate increased by 7·2% (6·0-8·4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7·9% (6·6-9·2) for males and 6·5% (5·4-7·7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs 1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-harm and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]). Interpretation: Global all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury

Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. METHODS: The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries-Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised