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The objective of the research was to evaluate the efficiency in the use of anionic polyacrylamide, organosilane and a sulfonate for the certainty of low volume traffic roads in the Peruvian highlands above 2000 m.s.n.m. Tests were carried out with the selected materials; Subgrade, Quarry 1 and Quarry 2, with the stabilizers, which obtained CBR values ​​above 40% minimum for paved roads. The best expression option in terms of its mechanical physical behavior was used using an anionic polyacrylamide dosage of 1kg/m3.

A difficult task in computer science is designing algorithms. This task is particularly complex when efficient algorithms must be constructed for computationally difficult optimization problems. Two fundamental problems in both combinatorial optimization and machine learning are the maximum independent set problem and the automatic data clustering. The best specific algorithms for both problems are heuristic and have been constructed by combining primary heuristics. However, the possible combinations explored so far are a minimum number of the entire combinatorial space. The automatic exploration of such space would, therefore, allow finding more efficient algorithmic combinations. This article reports new algorithms for both problems constructed by the automatic generation of algorithms, an emerging field that allows to automatically produce an adequate algorithm for a specific set of instances of the problem. The best algorithms generated after the computational experimentation are reported and compared with existing heuristics, demonstrating that the new algorithms are competitive.

Bar codes can help track and trace health products in the supply chain. But to do so efficiently, they should be based on global standards rather than a proprietary system, and the captured data should be integrated into national health information systems to achieve end-to-end data visibility., The United Nations Population Fund (UNFPA) and the United States Agency for International Development (USAID) DELIVER PROJECT work together to strengthen public health commodity supply chains by standardizing bar coding under a single set of global standards. From 2015, UNFPA and USAID collaborated to pilot test how tracking and tracing of bar coded health products could be operationalized in the public health supply chains of Ethiopia and Pakistan and inform the ecosystem needed to begin full implementation. Pakistan had been using proprietary bar codes for inventory management of contraceptive supplies but transitioned to global standards-based bar codes during the pilot. The transition allowed Pakistan to leverage the original bar codes that were preprinted by global manufacturers as opposed to printing new bar codes at the central warehouse. However, barriers at lower service delivery levels prevented full realization of end-to-end data visibility. Key barriers at the district level were the lack of a digital inventory management system and absence of bar codes at the primary-level packaging level, such as single blister packs. The team in Ethiopia developed an open-sourced smartphone application that allowed the team to scan bar codes using the mobile phone's camera and to push the captured data to the country's data mart. Real-time tracking and tracing occurred from the central warehouse to the Addis Ababa distribution hub and to 2 health centers. These pilots demonstrated that standardized product identification and bar codes can significantly improve accuracy over manual stock counts while significantly streamlining the stock-taking process, resulting in efficiencies. The pilots also showed that bar coding technology by itself is not sufficient to ensure data visibility. Rather, by using global standards for identification and data capture of pharmaceuticals and medical devices, and integrating the data captured into national and global tracking systems, countries are able to lay the foundation for interoperability and ensure a harmonized language between global health stakeholders.