Distortions to Agricultural Incentives in Ecuador

Distorted incentives, agricultural and trade policy reforms, national agricultural development, Agricultural and Food Policy, International Relations/Trade, F13, F14, Q17, Q18,

Cache-Based Multi-Query Optimization for Data-Intensive Scalable Computing Frameworks

In modern large-scale distributed systems, analytics jobs submitted by various users often share similar work, for example scanning and processing the same subset of data. Instead of optimizing jobs independently, which may result in redundant and wasteful processing, multi-query optimization techniques can be employed to save a considerable amount of cluster resources. In this work, we introduce a novel method combining in-memory cache primitives and multi-query optimization, to improve the efficiency of data-intensive, scalable computing frameworks. By careful selection and exploitation of common (sub)expressions, while satisfying memory constraints, our method transforms a batch of queries into a new, more efficient one which avoids unnecessary recomputations. To find feasible and efficient execution plans, our method uses a cost-based optimization formulation akin to the multiple-choice knapsack problem. Extensive experiments on a prototype implementation of our system show significant benefits of worksharing for both TPC-DS workloads and detailed micro-benchmarks

Distributing Tourists Among POIs with an Adaptive Trip Recommendation System

Traveling is part of many people leisure activities and an increasing fraction of the economy comes from the tourism. Given a destination, the information about the different attractions, or points of interest (POIs), can be found on many sources. Among these attractions, finding the ones that could be of interest for a specific user represents a challenging task. Travel recommendation systems deal with this type of problems. Most of the solution in the literature does not take into account the impact of the suggestions on the level of crowding of POIs. This paper considers the trip planning problem focusing on user balancing among the different POIs. To this aim, we consider the effects of the previous recommendations, as well as estimates based on historical data, while devising a new recommendation. The problem is formulated as a multi-objective optimization problem, and a recommendation engine has been designed and implemented for exploring the solution space in near real-time, through a distributed version of the Simulated Annealing approach. We test our solution using a real dataset of users visiting the POIs of a touristic city, and we show that we are able to provide high quality recommendations, yet maintaining the attractions not overcrowded

In-memory caching for multi-query optimization of data-intensive scalable computing workloads

In modern large-scale distributed systems, analytics jobs submitted by various users often share similar work. Instead of optimizing jobs independently, multi-query optimization techniques can be employed to save a considerable amount of cluster resources. In this work, we introduce a novel method combining in-memory cache primitives and multi-query optimization, to improve the efficiency of data-intensive, scalable computing frameworks. By careful selection and exploitation of common (sub) expressions, while satisfying memory constraints, our method transforms a batch of queries into a new, more efficient one which avoids unnecessary recomputations. To find feasible and efficient execution plans, our method uses a cost-based optimization formulation akin to the multiple-choice knapsack problem. Experiments on a prototype implementation of our system show significant benefits of worksharing for TPC-DS workloads

CoPart: a context-based partitioning technique for big data

The MapReduce programming paradigm is frequently used in order to process and analyse a huge amount of data. This paradigm relies on the ability to apply the same operation in parallel on independent chunks of data. The consequence is that the overall performances greatly depend on the way data are partitioned among the various computation nodes. The default partitioning technique, provided by systems like Hadoop or Spark, basically performs a random subdivision of the input records, without considering the nature and correlation between them. Even if such approach can be appropriate in the simplest case where all the input records have to be always analyzed, it becomes a limit for sophisticated analyses, in which correlations between records can be exploited to preliminarily prune unnecessary computations. In this paper we design a context-based multi-dimensional partitioning technique, called COPART, which takes care of data correlation in order to determine how records are subdivided between splits (i.e., units of work assigned to a computation node). More specifically, it considers not only the correlation of data w.r.t. contextual attributes, but also the distribution of each contextual dimension in the dataset. We experimentally compare our approach with existing ones, considering both quality criteria and the query execution times

Taxon-related pollen source areas for lake basins in the southern Alps: an empirical approach

The pollen/vegetation relationship in broadleaved forests dominated by Castanea sativa was analysed using an empirical approach. The pollen content of surface sediments of three lake basins of different sizes (6.3, 22.2, and 101.2ha) in Ticino (southern Switzerland) was used for a comparison with the surrounding vegetation. We surveyed the vegetation around the two small lakes, Lago di Origlio and Lago di Muzzano, and estimated the relative crown coverage of tree species. The regional vegetation outside the lake catchment (ca. >1km) was determined with the data from the first Swiss National Forest Inventory. For the third large lake, basin of Ponte Tresa, we used only this latter approach for comparison with pollen data. We compare uncorrected and corrected pollen percentages with vegetational data that were processed with distance-weighting functions. To assess the degree of correspondence between pollen and vegetation data we define a ratio pollen/vegetation, which allows a comparison at the taxon level. The best fit between total pollen load and vegetation is reached for a distance from the lake shore of ca. 300 m for Lago di Origlio (150×350m in size) and of ca. 600m for Lago di Muzzano (300×750m in size). Beside these general patterns, our analysis reveals taxon-specific pollen dispersal patterns that are in agreement with results from previous studies in northern Europe. Ratios of species with local (proximal) and long-distance (distal) pollen dispersal provide evidence that pollen dispersal mechanisms can influence the size of the taxon-related pollen source area, from small (100-400m) to large (>5km) for the same lake. The proportion of distal species increases with increasing lake size, highlighting the predominance of atmospheric pollen transport. We conclude that the large species-related differences in pollen source areas have to be taken into account when the provenance at a site is estimated and discusse

Testing rimegepant for migraine—time to revise the trial design?

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Recycling of waste oils as rejuvenators for aged bitumen in RAP

The recycling of materials considered "waste" is an important goal for developing low environmental impact processes, even in pavement constructions. Therefore, the use of reclaimed asphalt pavement (RAP) is an important strategy in the preparation of new roads [1-2]. Anyway, the bituminous binder in RAP has been subjected to oxidative aging, that determines a physical hardening and limits its workability and performances like the cracking susceptibility. For this reason, quite expensive additives, acting as rejuvenators, must be used together with RAP to restore the binder original viscosity and properties, thus allowing an increase in the percentage of RAP in the new formulations. In this study the recyclability of a waste mineral oil (MO) from the automotive industry and a waste domestic cooking vegetable oil (VO) as rejuvenators for aged bitumen in RAP was tested (Figure 1). The oxidized bituminous binder in RAP was simulated using a 50/70 base bitumen that was artificially aged in laboratory. Several mixtures were prepared by adding different percentage of recycled oils to restore the desired properties. Waste oils were compared measuring compatibility, diffusivity, and rejuvenating efficiency. The domestic cooking vegetable oil resulted the best rejuvenating agent and about 4.0 wt.% of this additive is enough to restore binder viscosity and stiffness