Diodia kuntzei (Spermacoceae-Rubiaceae), some adaptations of an annual species to constantly changing habitat: aerial, subaquatic, and underground fruit formation

Diodia kuntzei is an annual palustrine species, with prostrate stems rooting at the nodes, very narrow corolla tubes and fruits with thickened spongy pericarp. Frequently, the species is a food source for wild herbivores and livestock. It is widely distributed in South America, in Venezuela, northern Brazil, Peru, Paraguay, Bolivia, and northern Argentina (Corrientes, Misiones, and Entre Ríos). It grows in seasonally waterlogged habitats or shallow water bodies. In the taxonomic review of the genus, a mention was made of the presence of “fruits between the roots” for Diodia kuntzei, suggesting probable amphicarpy, a very rare condition in Rubiaceae. Amphicarpy can be defined as the production of aerial and subterranean fruits on the same plant. In Diodia, it was reported in the perennial species Diodia virginiana. Field collections and observations of Diodia kuntzei were performed in Argentina, Paraguay, and Bolivia. Based on greenhouse plants and field observations, we report for the first time amphicarpy in D. kuntzei, a phenomenon particularly unusual in an annual plant species. Underground fruits are white, achlorophilic, and irregular in shape. As in other amphicarpic species, the underground flowers are cleistogamous and probably obligate autogamous. Additionally, based on aquarium cultivated plants, subaquatic flower (also cleistogamous) and fruit formation was observed. This preliminary data reveal that D. kuntzei ensures its local persistence by means of underground fruits and vegetative reproduction, and attains long distance dispersal by means of aerial or subaquatic fruits (hydrochory). Future experimental studies to confirm these reproductive strategies, both in the field and in the greenhouse, are needed. Acknowledgements: PICT 3517

Model Selection Using Database Characteristics: Developing a Classification Tree for Longitudinal Incidence Data

When managers and researchers encounter a data set, they typically ask two key questions: (1) Which model (from a candidate set) should I use? And (2) if I use a particular model, when is it going to likely work well for my business goal? This research addresses those two questions and provides a rule, i.e., a decision tree, for data analysts to portend the “winning model” before having to fit any of them for longitudinal incidence data. We characterize data sets based on managerially relevant (and easy-to-compute) summary statistics, and we use classification techniques from machine learning to provide a decision tree that recommends when to use which model. By doing the “legwork” of obtaining this decision tree for model selection, we provide a time-saving tool to analysts. We illustrate this method for a common marketing problem (i.e., forecasting repeat purchasing incidence for a cohort of new customers) and demonstrate the method\u27s ability to discriminate among an integrated family of a hidden Markov model (HMM) and its constrained variants. We observe a strong ability for data set characteristics to guide the choice of the most appropriate model, and we observe that some model features (e.g., the “back-and-forth” migration between latent states) are more important to accommodate than are others (e.g., the inclusion of an “off” state with no activity). We also demonstrate the method\u27s broad potential by providing a general “recipe” for researchers to replicate this kind of model classification task in other managerial contexts (outside of repeat purchasing incidence data and the HMM framework)

Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments

Firms using online advertising regularly run experiments with multiple versions of their ads since they are uncertain about which ones are most effective. During a campaign, firms try to adapt to intermediate results of their tests, optimizing what they earn while learning about their ads. Yet how should they decide what percentage of impressions to allocate to each ad? This paper answers that question, resolving the well-known “learn-and-earn” trade-off using multi-armed bandit (MAB) methods. The online advertiser’s MAB problem, however, contains particular challenges, such as a hierarchical structure (ads within a website), attributes of actions (creative elements of an ad), and batched decisions (millions of impressions at a time), that are not fully accommodated by existing MAB methods. Our approach captures how the impact of observable ad attributes on ad effectiveness differs by website in unobserved ways, and our policy generates allocations of impressions that can be used in practice. We implemented this policy in a live field experiment delivering over 750 million ad impressions in an online display campaign with a large retail bank. Over the course of two months, our policy achieved an 8% improvement in the customer acquisition rate, relative to a control policy, without any additional costs to the bank. Beyond the actual experiment, we performed counterfactual simulations to evaluate a range of alternative model specifications and allocation rules in MAB policies. Finally, we show that customer acquisition would decrease by about 10% if the firm were to optimize click-through rates instead of conversion directly, a finding that has implications for understanding the marketing funnel

Fusing Data with Correlations

Many applications rely on Web data and extraction systems to accomplish knowledge-driven tasks. Web information is not curated, so many sources provide inaccurate, or conflicting information. Moreover, extraction systems introduce additional noise to the data. We wish to automatically distinguish correct data and erroneous data for creating a cleaner set of integrated data. Previous work has shown that a na\"ive voting strategy that trusts data provided by the majority or at least a certain number of sources may not work well in the presence of copying between the sources. However, correlation between sources can be much broader than copying: sources may provide data from complementary domains (\emph{negative correlation}), extractors may focus on different types of information (\emph{negative correlation}), and extractors may apply common rules in extraction (\emph{positive correlation, without copying}). In this paper we present novel techniques modeling correlations between sources and applying it in truth finding.Comment: Sigmod'201

Absorbent products for urinary/faecal incontinence: a comparative evaluation of key product designs

Background: The UK health service, nursing homes and public spend around £94 million per year on incontinence pads (absorbent products) to contain urine and/or faeces, but the research base for making informed choices between different product designs is very weak.Objectives: The aim of this trial was to compare the performance and cost-effectiveness of the key absorbent product designs to provide a more solid basis for guiding selection and purchase.A further aim was to carry out the first stage in the development of a quality of life instrument for measuring the impact of absorbent product use on users' lives.Design: The work involved three clinical trials focusing on the three biggest market sectors. Each trial had a similar crossover design in which each participant tested all products within their group in random order.Settings, participants and methods: In Trial 1, 85 women with light urinary incontinence living in the community tested three products from each of the four design categories available (total of 12 test products): disposable inserts (pads); menstrual pads; washable pants with integral pad; and washable inserts. In Trial 2a, 85 moderate/heavily incontinent adults (urinary or urinary/faecal) living in the community (49 men and 36 women) tested three (or two) products from each of the five design categories available (total of 14 test products): disposable inserts (with mesh pants); disposable diapers (nappies); disposable pull-ups (similar to toddlers' trainer pants); disposable T-shaped diapers (nappies with waist-band); and washable diapers. All products were provided in a daytime and a (mostly more absorbent) night-time variant. In these first two trials, the test products were selected on the basis of data from pilot studies. In Trial 2b, 100 moderate/heavily incontinent adults (urinary or urinary/faecal) living in 10 nursing homes (27 men and 73 women) evaluated one product from each of the four disposable design categories from Trial 2a. Products were selected on the basis of product performance in Trial 2a and, again, daytime and night-time variants were provided. The first phase of work to develop a quality of life tool for measuring the impact of using different pad designs was carried out by interviewing participants from Trials 1 and 2a.Outcome measures: Product performance was characterised using validated questionnaires, which asked the participants (in Trials 1 and 2a) or carers (all participants in Trial 2b, except for the few who could report for themselves) to evaluate various aspects of pad performance (leakage, ease of putting on, discreetness, etc.) using a five-point scale (very good–very poor) at the end of the week (or 2 weeks for Trial 2b) of product testing. In addition, participants/carers were asked to save individual used pads in bags for weighing and to indicate the severity of any leakage from them on a three-point scale (none, a little, a lot). These data were used to determine differences in leakage performance. Numbers of laundry items and pads used were recorded to estimate costs, and skin health changes were recorded by the participant or by the researchers (Trial 2b). At the end of testing, participants were interviewed and ranked their preferences (with and without costs), stated the acceptability of each design (highly acceptable–totally unacceptable) and recorded their overall opinion on a visual analogue scale (VAS) of 0–100 points (worst design–best design). This VAS score was used with product costs to estimate cost-effectiveness. In addition, a timed pad changing exercise was conducted with 10 women from Trial 2b to determine any differences between product designs.Results: Results presented are for statistically and clinically significant findings.<br/

The effects of cropping intensity and cropland expansion of Brazilian soybean production on green water flows

As land use change alters how green water is appropriated, cropland expansion is instrumental in re-allocating green water towards agriculture. Alongside cropland expansion, agricultural intensification practices modify crop water use and land and water productivity. Particularly, one form of agricultural intensification known as multi-cropping (the cultivation of a piece of land sequentially more than once a year) can result in greater agricultural output per unit of land, as well as more productive use of the available water throughout the annual rainfall cycle. We assess the influence of these two processes, cropland expansion and agricultural intensification, in agricultural green water use in Brazilian agriculture. We applied the biophysical crop model Environmental Policy Integrated Climate (EPIC) to estimate green water use for single and double cropping of soybean (Glycine max) and maize (Zea mays) in Brazil. The first part of our study analyses changes in soybean green water use and virtual water content nationwide between 1990 and 2013, and in a second part we look into the effect of double-cropping on water use for soybean and maize in the Brazilian states of Paraná and Mato Grosso between 2003 and 2013. The results show that cropland expansion plays a more prominent effect in green water use for production of soybean than intensification, and harvested area increase was responsible for the appropriation of an additional 95 km3 of green water in 2013 when compared to 1990, an increase of 155%. We estimate that an additional green water use of around 26 km3 related to second season maize was appropriated through increase of cropping frequency, and without expansion of cropland, in 2013 in the selected states. We discuss the importance of considering multi cropping practices when assessing green water sustainability, and the importance of differentiating green water appropriation through expansion and through cropping frequency changes

Water footprints of cities indicators for sustainable consumption and production

Water footprints have been proposed as sustainabilityindicators, relating the consumption of goods likefood to the amount of water necessary for their productionand the impacts of that water use in the source regions. Wefurther developed the existing water footprint methodology,by globally resolving virtual water flows from production toconsumption regions for major food crops at 5 arcmin spatialresolution. We distinguished domestic and internationalflows, and assessed local impacts of export production. Applyingthis method to three exemplary cities, Berlin, Delhiand Lagos, we find major differences in amounts, composition,and origin of green and blue virtual water imports,due to differences in diets, trade integration and crop waterproductivities in the source regions. While almost all ofDelhi’s and Lagos’ virtual water imports are of domestic origin,Berlin on average imports from more than 4000 km distance,in particular soy (livestock feed), coffee and cocoa.While 42% of Delhi’s virtual water imports are blue waterbased, the fractions for Berlin and Lagos are 2 and 0.5 %, respectively,roughly equal to the water volumes abstracted inthese two cities for domestic water use. Some of the externalsource regions of Berlin’s virtual water imports appear tobe critically water scarce and/or food insecure. However, forderiving recommendations on sustainable consumption andtrade, further analysis of context-specific costs and benefitsassociated with export production will be required