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Arthropod-borne viruses (arboviruses) are among the most common agents of human febrile illness worldwide and the most important emerging pathogens, causing multiple notable epidemics of human disease over recent decades. Despite the public health relevance, little is know about the geographic distribution, relative impact, and risk factors for arbovirus infection in many regions of the world. Our objectives were to describe the arboviruses associated with acute undifferentiated febrile illness in participating clinics in four countries in South America and to provide detailed epidemiological analysis of arbovirus infection in Iquitos, Peru, where more extensive monitoring was conducted. A clinic-based syndromic surveillance system was implemented in 13 locations in Ecuador, Peru, Bolivia, and Paraguay. Serum samples and demographic information were collected from febrile participants reporting to local health clinics or hospitals. Acute-phase sera were tested for viral infection by immunofluorescence assay or RT-PCR, while acute- and convalescent-phase sera were tested for pathogen-specific IgM by ELISA. Between May 2000 and December 2007, 20,880 participants were included in the study, with evidence for recent arbovirus infection detected for 6,793 (32.5%). Dengue viruses (Flavivirus) were the most common arbovirus infections, totaling 26.0% of febrile episodes, with DENV-3 as the most common serotype. Alphavirus (Venezuelan equine encephalitis virus [VEEV] and Mayaro virus [MAYV]) and Orthobunyavirus (Oropouche virus [OROV], Group C viruses, and Guaroa virus) infections were both observed in approximately 3% of febrile episodes. In Iquitos, risk factors for VEEV and MAYV infection included being male and reporting to a rural (vs urban) clinic. In contrast, OROV infection was similar between sexes and type of clinic. Our data provide a better understanding of the geographic range of arboviruses in South America and highlight the diversity of pathogens in circulation. These arboviruses are currently significant causes of human illness in endemic regions but also have potential for further expansion. Our data provide a basis for analyzing changes in their ecology and epidemiology.

The purpose of this paper is to determine trends in the wages and living standards of male agricultural labourers in Central Chile during the agrarian expansion, c. 1870-1930. We found that nominal wages increased eightfold; this is relevant because wage labour became the main rural labour regime in this period. Nominal wages rose steadily from the early 1870s until 1910, and with significant fluctuations thereafter, before plummeting with the Great Depression. Real wages also increased, but only slightly. Furthermore, during certain short periods, agricultural labourers' real wages were similar to or higher than those of low-skilled urban workers. However, the persistent gap between agricultural and non-agricultural wages was one of the causal factors of the outmigration of rural workers.

Given a collection of n objects equipped with a distance function d(·, ·), the Nearest Neighbor Graph (NNG) consists in finding the nearest neighbor of each object in the collection. Without an index the total cost of NNG is quadratic. Using an index the cost would be sub-quadratic if the search for individual items is sublinear. Unfortunately, due to the so called curse of dimensionality the indexed and the brute force methods are almost equally inefficient. In this paper we present an efficient algorithm to build the Near Neighbor Graph (nNG), that is an approximation of NNG, using only the index construction, without actually searching for objects.

Similarity search is a difficult problem and various indexing schemas have been defined to process similarity queries efficiently in many applications, including multimedia databases and other repositories handling complex objects. Metric indices support efficient similarity searches, but most of them are designed for main memory. Thus, they can handle only small datasets, suffering serious performance degradations when the objects reside on disk. Most reallife database applications require indices able to work on secondary memory. Among a plethora of indices, the List of Clustered Permutations (LCP) has shown to be competitive in main memory.We introduce a secondary-memory variant of the LCP, which maintains the low number of distance evaluations when comparing the permutations themselves, and also needs a low number of I/O operations at construction and searching.

The classic use of Stream Processing platforms enables working with data in real time, which allows you to generate data analysis quickly attending to a decisionmaking process. However, you can use these platforms for other applications such as indexing and subsequent use of similarity search objects in a database. The images can be displayed on a metric space, which has features that allow rules to discard a not similar image quickly without making costly computations. This paper presents the use of a Stream Processing platform to index images generated by different users. For this, it is necessary to represent these images by vectors containing different MPGE-7 features. This paper shows a Stream Processing platform using its processing elements (PEs) in parallel to speed up the operations involved in the index construction.

Metric space searching is an emerging technique to address the problem of similarity searching in many applications. In order to efficiently answer similarity queries, the database must be indexed. In some interesting real applications dynamism is an indispensable property of the index. There are very few actually dynamic indexes that support not only searches, but also insertions and deletions of elements. The dynamic spatial approximation tree (DSAT) is a data structure specially designed for searching in metric spaces, which compares favorably against other data structures in high dimensional spaces or queries with low selectivity. Insertions are efficient and easily supported in DSAT, but deletions degrade the structure over time. Several methods are proposed to handle deletions over the DSAT. One of them has shown to be superior to the others, in the sense that it permits controlling the expected deletion cost as a proportion of the insertion cost and searches does not overly degrade after several deletions. In this paper we propose and study a new alternative deletion method, based on the better existing strategy. The outcome is a fully dynamic data structure that can be managed through insertions and deletions over arbitrarily long periods of time without any significant reorganization.

The Distal Spatial Approximation Tree (DiSAT) is one of the most competitive indexes for exact proximity searching. The absence of parameters, the most salient feature, makes the index a suitable choice for a practitioner. The most serious drawback is the static nature of the index, not allowing further insertions once it is built. On the other hand, there is an old approach from Bentley and Saxe (BS) allowing the dynamization of decomposable data structures. The only requirement is to provide a decomposition operation. This is precisely our contribution, we define a decomposition operation allowing the application of the BS technique. The resulting data structure is competitive against the static counterparts.

El rol del sector agrícola durante la ISI y el debate respecto del salario agrícola y las condiciones de vida de los campesinos tienen una larga historiografía, sin embargo hasta la actualidad existe poca información empírica relativa a los ingresos del campesinado en el largo plazo. En este trabajo nos proponemos reflexionar acerca del nivel que alcanzaron los salarios durante el período y para ello presentaremos una nueva serie de salarios reales para 1934-1973. Buscamos analizar su comportamiento en función de la productividad laboral del sector, en relación con los jornales industriales y considerando el marco institucional en este período.

With the technology advance and the growth of Internet, the information that can be found in this net, as well as the number of users that access to look for specific data is bigger. Therefore, it is desirable to have a search system that allows to retrieve information at a reasonable time and in an efficient way. In this paper we show two computing paradigms appropriate to apply in the treatment of large amounts of data consisting of objects such as images, text, sound and video, using hybrid computing over MPI+OpenMP and GPGPU. The proposal is developed through experience gained in the construction of various indexes and the subsequent search, through them, of multimedia objects.

El rol del sector agrícola durante la ISI y el debate respecto del salario agrícola y las condiciones de vida de los campesinos tienen una larga historiografía, sin embargo hasta la actualidad existe poca información empírica relativa a los ingresos del campesinado en el largo plazo. En este trabajo nos proponemos reflexionar acerca del nivel que alcanzaron los salarios durante el período y para ello presentaremos una nueva serie de salarios reales para 1934-1973. Buscamos analizar su comportamiento en función de la productividad laboral del sector, en relación con los jornales industriales y considerando el marco institucional en este período.//The role of the agricultural sector during the ISI period and the debate about the agricultural wage and the living conditions of the farm workers have a long historiography. But until today there is little information about workers' income in the long run. In this paper we want to reflect about the wage level reached during this period and for that we will present a new wage series for 1934-1973. We seek to analyze their behavior considering the sector labour productivity, its relation with industrial wages and the institutional frame in this period. Reprinted by permission of Estudios de Economía Departamento de Economía, Universidad de Chile