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The scalability of similarity joins is threatened by the unexpected data characteristic of data skewness. This is a pervasive problem in scientific data. Due to skewness, the uneven distribution of attributes occurs, and it can cause a severe load imbalance problem. When database join operations are applied to these datasets, skewness occurs exponentially. All the algorithms developed to date for the implementation of database joins are highly skew sensitive. This paper presents a new approach for handling data-skewness in a character- based string similarity join using the MapReduce framework. In the literature, no such work exists to handle data skewness in character-based string similarity join, although work for set based string similarity joins exists. Proposed work has been divided into three stages, and every stage is further divided into mapper and reducer phases, which are dedicated to a specific task. The first stage is dedicated to finding the length of strings from a dataset. For valid candidate pair generation, MR-Pass Join framework has been suggested in the second stage. MRFA concepts are incorporated for string similarity join, which is named as “MRFA-SSJ” (MapReduce Frequency Adaptive – String Similarity Join) in the third stage which is further divided into four MapReduce phases. Hence, MRFA-SSJ has been proposed to handle skewness in the string similarity join. The experiments have been implemented on three different datasets namely: DBLP, Query log and a real dataset of IP addresses & Cookies by deploying Hadoop framework. The proposed algorithm has been compared with three known algorithms and it has been noticed that all these algorithms fail when data is highly skewed, whereas our proposed method handles highly skewed data without any problem. A set-up of the 15-node cluster has been used in this experiment, and we are following the Zipf distribution law for the analysis of skewness factor. Also, a comparison among existing and proposed techniques has been shown. Existing techniques survived till Zipf factor 0.5 whereas the proposed algorithm survives up to Zipf factor 1. Hence the proposed algorithm is skew insensitive and ensures scalability with a reasonable query processing time for string similarity database join. It also ensures the even distribution of attributes.

The prolonged drought in Chile’s Coquimbo region has created a permanent state of emergency, forcing the state to spend millions each year distributing drinking water to rural communities. The purpose of this article is to detail a study focused on optimizing the supply of drinking water through trucks in the 15 communes of the region and how the problem was faced in a context of a slowonset disaster.

A geo-referenced census and optimization analysis of the 5.541 households that receive drinking water was conducted to determine the feasibility of removing trucks from the system. To generate a greater reduction in distribution costs, it was suggested to incorporate water distribution infrastructure projects, changing the concept of ‘expenses’ to ‘investment’.

The study was born out of the concern for the increased demand for drinking water from rural areas. The proposed and implemented framework allowed an additional 20% reduction in the initial transportation costs; this confirmed the assumption that the proposed optimization model alone would not offer a robust solution and was complemented and integrated with this type of alternative, forming an “integrated model”.

The paper has implications for the resilience of territories affected by climate change.

The methodology can be replicated in other areas where similar interactions occur.

Families impacted by drought can improve their quality of life and reduce distress in the face of the constant emergency.

This research aims to contribute knowledge from the perspective of a slow-onset disaster where water resources are scarce. It presents a framework where two disciplines converge, resulting in an “integrated model” that, through its implementation, reduces the costs of resource delivery while simultaneously improving the sanitary conditions of the beneficiary families.

Polyurethane (PUR) foam parts are traditionally manufactured using metallic molds, an unsuitable approach for prototyping purposes. Thus, rapid tooling of disposable molds using fused filament fabrication (FFF) with polylactic acid (PLA) and glycol-modified polyethylene terephthalate (PETG) is proposed as an economical, simpler and faster solution compared to traditional metallic molds or three-dimensional (3D) printing with other difficult-to-print thermoplastics, which are prone to shrinkage and delamination (acrylonitrile butadiene styrene, polypropilene-PP) or high-cost due to both material and printing equipment expenses (PEEK, polyamides or polycarbonate-PC). The purpose of this study has been to evaluate the ease of release of PUR foam on these materials in combination with release agents to facilitate the mulding/demoulding process.

PETG, PLA and hardenable polylactic acid (PLA 3D870) have been evaluated as mold materials in combination with aqueous and solvent-based release agents within a full design of experiments by three consecutive molding/demolding cycles.

PLA 3D870 has shown the best demoldability. A mold expressly designed to manufacture a foam cushion has been printed and the prototyping has been successfully achieved. The demolding of the part has been easier using a solvent-based release agent, meanwhile the quality has been better when using a water-based one.

The combination of PLA 3D870 and FFF, along with solvent-free water-based release agents, presents a compelling low-cost and eco-friendly alternative to traditional metallic molds and other 3D printing thermoplastics. This innovative approach serves as a viable option for rapid tooling in PUR foam molding.

The purpose of this paper is to improve future teacher training by assessment of university graduates’ satisfaction with their preparation in Basic Education teaching.

This descriptive study employed a self-administered survey questionnaire to a representative sample of 235 graduates between 2014 and 2016 from three universities in Chile. The questionnaire generated information about the graduates’ background (age, gender, parents’ education and prestige of secondary school attended); an evaluation of three dimensions of their degree program (instructional quality, infrastructure and employability), and experiences in the labor market (including salary). Analysis of variance was used to assess relationships between satisfaction, and other variables.

In general, graduates were satisfied with all aspects of their training. Satisfaction levels were higher from those assumed to have lower expectations. Contrary to this hypothesis, university prestige is not directly related to satisfaction. Instead, expectations and employability moderate the effect of prestige.

The sample is not representative of the 59 universities in Chile nor of the many other degree programs offered in those universities.

Program directors concerned about improving the public reputation or prestige of their program will benefit from efforts to improve the quality of the program and its infrastructure, and relevance for entrance into the world of work.

This study provides information not previously available about graduate satisfaction in teaching degree programs in Chile.

The purpose of this paper is to determine which of the two variables would be a more reliable proxy for quality of university training: graduates’ satisfaction with their degree program, or institutional prestige.

Graduates of professional psychology and teaching programs from three Chilean universities responded to a questionnaire asking their perception of different aspects of their degree program and experiences in their first employment. The three universities differ significantly in the proportion of applicants admitted, and in their prestige.

Salary levels are highly related to profession, but unrelated to graduates’ ratings of quality of curriculum or teaching methods. Overall satisfaction with the university experience is not linked to job satisfaction. Job satisfaction, on the other hand, is highly influenced by salary and secondarily by instructional practices and perceived work relevance of the degree program.

This study is based on data from 3 of Chile’s 60 universities, and graduates of two programs. Most employment in the two professions is regulated by labor agreements. Generalizability of results is limited. Graduates may not have been employed enough to demonstrate their capacities.

The findings offer more evidence that prestige ratings are an unreliable indicator of the quality of formation offered by universities. If the government seeks to reduce income inequality, public subsidies of higher education should be based on program quality rather than on institutional prestige.

The findings are directly relevant to the current debate in Chile about what might and what might not help to reduce severe economic inequality.

Although scarce in the literature of entrepreneurship, the Aztec and Mayas (as well as the Incas), two of the most important civilizations in ancient Latin America, are considered by us as entrepreneurs. This is our departing point for understanding where entrepreneurship was born and built in Latin America. Unfortunately, its indigenous communities still are far behind in terms of labor, quality of life, poverty, and economic opportunities. From the ethnic entrepreneurship theory and after a deep literature review, a model is proposed for our region, a starting point to analyze and understand its processes in our region, thus making an impact on the development of public policies that can ultimately alleviate and improve the condition of this communities, and by going back to its roots, give a clearer picture of the reasons behind the present and future condition of entrepreneurship in Latin America.