Fine-Grained Product Class Recognition for Assisted Shopping

Assistive solutions for a better shopping experience can improve the quality of life of people, in particular also of visually impaired shoppers. We present a system that visually recognizes the fine-grained product classes of items on a shopping list, in shelves images taken with a smartphone in a grocery store. Our system consists of three components: (a) We automatically recognize useful text on product packaging, e.g., product name and brand, and build a mapping of words to product classes based on the large-scale GroceryProducts dataset. When the user populates the shopping list, we automatically infer the product class of each entered word. (b) We perform fine-grained product class recognition when the user is facing a shelf. We discover discriminative patches on product packaging to differentiate between visually similar product classes and to increase the robustness against continuous changes in product design. (c) We continuously improve the recognition accuracy through active learning. Our experiments show the robustness of the proposed method against cross-domain challenges, and the scalability to an increasing number of products with minimal re-training.Comment: Accepted at ICCV Workshop on Assistive Computer Vision and Robotics (ICCV-ACVR) 201

Adoption as a Social Marker: Innovation Diffusion with Outgroup Aversion

Social identities are among the key factors driving behavior in complex societies. Signals of social identity are known to influence individual behaviors in the adoption of innovations. Yet the population-level consequences of identity signaling on the diffusion of innovations are largely unknown. Here we use both analytical and agent-based modeling to consider the spread of a beneficial innovation in a structured population in which there exist two groups who are averse to being mistaken for each other. We investigate the dynamics of adoption and consider the role of structural factors such as demographic skew and communication scale on population-level outcomes. We find that outgroup aversion can lead to adoption being delayed or suppressed in one group, and that population-wide underadoption is common. Comparing the two models, we find that differential adoption can arise due to structural constraints on information flow even in the absence of intrinsic between-group differences in adoption rates. Further, we find that patterns of polarization in adoption at both local and global scales depend on the details of demographic organization and the scale of communication. This research has particular relevance to widely beneficial but identity-relevant products and behaviors, such as green technologies, where overall levels of adoption determine the positive benefits that accrue to society at large.Comment: 26 pages, 10 figure

Spatial heterogeneity promotes coexistence of rock-paper-scissor metacommunities

The rock-paper-scissor game -- which is characterized by three strategies R,P,S, satisfying the non-transitive relations S excludes P, P excludes R, and R excludes S -- serves as a simple prototype for studying more complex non-transitive systems. For well-mixed systems where interactions result in fitness reductions of the losers exceeding fitness gains of the winners, classical theory predicts that two strategies go extinct. The effects of spatial heterogeneity and dispersal rates on this outcome are analyzed using a general framework for evolutionary games in patchy landscapes. The analysis reveals that coexistence is determined by the rates at which dominant strategies invade a landscape occupied by the subordinate strategy (e.g. rock invades a landscape occupied by scissors) and the rates at which subordinate strategies get excluded in a landscape occupied by the dominant strategy (e.g. scissor gets excluded in a landscape occupied by rock). These invasion and exclusion rates correspond to eigenvalues of the linearized dynamics near single strategy equilibria. Coexistence occurs when the product of the invasion rates exceeds the product of the exclusion rates. Provided there is sufficient spatial variation in payoffs, the analysis identifies a critical dispersal rate $d^*$ required for regional persistence. For dispersal rates below $d^*$, the product of the invasion rates exceed the product of the exclusion rates and the rock-paper-scissor metacommunities persist regionally despite being extinction prone locally. For dispersal rates above $d^*$, the product of the exclusion rates exceed the product of the invasion rates and the strategies are extinction prone. These results highlight the delicate interplay between spatial heterogeneity and dispersal in mediating long-term outcomes for evolutionary games.Comment: 31pages, 5 figure

Trends in long-term prescribing of dependence forming medicines

Using patient-level primary care data to estimate the extent to which antidepressant medicines are prescribed to people continuously for long periods of time. Aim This descriptive research used patient-level primary care data to estimate the extent to which antidepressant medicines are prescribed to people continuously for long periods of time. The study also drew on survey data and data on the number of prescriptions dispensed. Findings - The number of antidepressant prescriptions dispensed each year in England doubled between 2008 and 2018 - Survey data show that the proportion of adults reporting use of antidepressants in the past year increased in the 1990s, and again between 2007 and 2014 - The average length of time that antidepressants are continuously prescribed to people for has increased over time. - Some types of antidepressants (for example, tricyclics and other antidepressants) tend to be prescribed for longer periods than other types (such as SSRIs). - In 2014, one in twelve prescribing periods for tricyclics and other antidepressants lasted for three years or more Methods The analyses in this report are descriptive and show the overall prevalence of long-term prescribing in each year. We used a sample of around 50,000 patients prescribed at least one antidepressant medicine between 2000 and 2017. This was drawn from the Clinical Practice Research Datalink (CPRD). The CPRD contains data about prescriptions issued by GPs (including the length and size of prescription) and characteristics of the patients prescribed to (such as their age, sex, and area where they live). Medicines were grouped for analysis into: tricyclics, selective serotonin reuptake inhibitors (SSRIs), and other ADMs. The length of individual prescriptions and continuous prescribing periods were derived using information on consultation dates, the quantity of tablets prescribed, and the numeric daily dose

Daytime precipitation estimation using bispectral cloud classification system

Two previously developed Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) algorithms that incorporate cloud classification system (PERSIANN-CCS) and multispectral analysis (PERSIANN-MSA) are integrated and employed to analyze the role of cloud albedo from Geostationary Operational Environmental Satellite-12 (GOES-12) visible (0.65 μm) channel in supplementing infrared (10.7 mm) data. The integrated technique derives finescale (0.04° × 0.04° latitudelongitude every 30 min) rain rate for each grid box through four major steps: 1) segmenting clouds into a number of cloud patches using infrared or albedo images; 2) classification of cloud patches into a number of cloud types using radiative, geometrical, and textural features for each individual cloud patch; 3) classification of each cloud type into a number of subclasses and assigning rain rates to each subclass using a multidimensional histogram matching method; and 4) associating satellite gridbox information to the appropriate corresponding cloud type and subclass to estimate rain rate in grid scale. The technique was applied over a study region that includes the U.S. landmass east of 115°W. One reference infrared-only and three different bis-pectral (visible and infrared) rain estimation scenarios were compared to investigate the technique's ability to address two major drawbacks of infrared-only methods: 1) underestimating warm rainfall and 2) the inability to screen out no-rain thin cirrus clouds. Radar estimates were used to evaluate the scenarios at a range of temporal (3 and 6 hourly) and spatial (0.04°, 0.08°, 0.12°, and 0.24° latitude-longitude) scales. Overall, the results using daytime data during June-August 2006 indicate that significant gain over infrared-only technique is obtained once albedo is used for cloud segmentation followed by bispectral cloud classification and rainfall estimation. At 3-h, 0.04° resolution, the observed improvement using bispectral information was about 66% for equitable threat score and 26% for the correlation coefficient. At coarser 0.24° resolution, the gains were 34% and 32% for the two performance measures, respectively. © 2010 American Meteorological Society

Non-genomic regulation of intermediate conductance potassium channels by aldosterone in human colonic crypt cells

BACKGROUND: Aldosterone has a rapid, non-genomic, inhibitory effect on macroscopic basolateral K+ conductance in the human colon, reducing its capacity for Cl− secretion. The molecular identity of the K+ channels constituting this aldosterone inhibitable K+ conductance is unclear. AIM: To characterise the K+ channel inhibited by aldosterone present in the basolateral membrane of human colonic crypt cells. METHODS: Crypts were isolated from biopsies of healthy sigmoid colon obtained during colonoscopy. The effect of aldosterone on basolateral K+ channels, and the possible involvement of Na+:H+ exchange, were studied by patch clamp techniques. Total RNA from isolated crypts was subjected to reverse transcriptase-polymerase chain reaction (RT-PCR) using primers specific to intermediate conductance K+ channels (KCNN4) previously identified in other human tissues. RESULTS: In cell attached patches, 1 nmol/l aldosterone significantly decreased the activity of intermediate conductance (27 pS) K+ channels by 31%, 53%, and 54% after 1, 5 and 10, minutes, respectively. Increasing aldosterone concentration to 10 nmol/l produced a further 56% decrease in channel activity after five minutes. Aldosterone 1–10 nmol/l had no effect on channel activity in the presence of 20 µmol/l ethylisopropylamiloride, an inhibitor of Na+:H+ exchange. RT-PCR identified KCNN4 mRNA, which is likely to encode the 27 pS K+ channel inhibited by aldosterone. CONCLUSION: Intermediate conductance K+ channels (KCNN4) present in the basolateral membranes of human colonic crypt cells are a target for the non-genomic inhibitory effect of aldosterone, which involves stimulation of Na+:H+ exchange, thereby reducing the capacity of the colon for Cl− secretion