Abstract
Soil erosion is a serious environmental problem. An estimation of the expected soil loss by water-caused erosion can be calculated considering the Revised Universal Soil Loss Equation (RUSLE). Geographical Information Systems (GIS) provide different tools to create categorical maps of soil erosion risk which help to study the risk assessment of soil loss. The objective of this study was to develop a GIS open source application (in QGIS), using the RUSLE methodology for estimating erosion rate at the watershed scale (desktop application) and provide the same application via web access (web application). The applications developed allow one to generate all the maps necessary to evaluate the soil erosion risk. Several libraries and algorithms from SEXTANTE were used to develop these applications. These applications were tested in Montalegre municipality (Portugal). The maps involved in RUSLE method-soil erosivity factor, soil erodibility factor, topographic factor, cover management factor, and support practices-were created. The estimated mean value of the soil loss obtained was 220 ton km(-2) year(-1) ranged from 0.27 to 1283 ton km(-2) year(-1). The results indicated that most of the study area (80 %) is characterized by very low soil erosion level (<321 ton km(-2) year(-1)) and in 4 % of the studied area the soil erosion was higher than 962 ton km(-2) year(-1). It was also concluded that areas with high slope values and bare soil are related with high level of erosion and the higher the P and C values, the higher the soil erosion percentage. The RUSLE web and the desktop application are freely available.

Abstract
In order to converge in the presence of concurrent updates, modern eventually consistent replication systems rely on causality information and operation semantics. It is relatively easy to use semantics of high-level operations on replicated data structures, such as sets, lists, etc. However, it is difficult to exploit semantics of operations on registers, which store opaque data. In existing register designs, concurrent writes are resolved either by the application, or by arbitrating them according to their timestamps. The former is complex and may require user intervention, whereas the latter causes arbitrary updates to be lost. In this work, we identify a register construction that generalizes existing ones by combining runtime causality ordering, to identify concurrent writes, with static data semantics, to resolve them. We propose a simple conflict resolution template based on an application-predefined order on the domain of values. It eliminates or reduces the number of conflicts that need to be resolved by the user or by an explicit application logic. We illustrate some variants of our approach with use cases, and how it generalizes existing designs.

Abstract

Abstract
The ability to detect and quantify small amounts of DNA in biological complex samples is a hot research area. Up until recently most of the work performed in this area used label-dependent protocols that increases its complexity and overall costs. The aim the work was to develop a label-free technology suitable for DNA detection and quantification using real complex DNA samples. The applicability of this system was tested using synthetic ssDNA targets that guaranteed the systems specificity, in the sense that only complementary sequences hybridized with the probe. When using real samples extracted from Vitis vinifera L. the system was able to successfully detect and quantify the DNA present without any of the time consuming and costly amplification steps. The detection and quantification limits of the proposed system were 60 +/- 20 nM and 201 +/- 20 nM, respectively for Target 1 concentrations between 31 and 350 nM. This method can easily be applied to other species and purposes, allowing the direct detection of DNA in a label-free environment with high accuracy and specificity.

Abstract
Monitoring an individual's performance in a task, especially in the workplace context, is becoming an increasingly interesting and controversial topic in a time in which workers are expected to produce more, better and faster. The tension caused by this competitiveness, together with the pressure of monitoring, may not work in favour of the organization's objectives. In this paper, we present an innovative approach on the problem of performance management. We build on the fact that computers are nowadays used as major work tools in many workplaces to devise a non-invasive method for distributed performance monitoring based on the observation of the worker's interaction with the computer. We then look at musical selection both as a pleasant and as an effective method for improving performance in the workplace. The proposed approach will allow team coordinators to assess and manage their co-workers' performance continuously and in real-time, using a distributed service-based architecture. Copyright (c) 2015 John Wiley & Sons, Ltd.

Abstract
Effective and efficient implementation of intelligent and/or recently emerged networked manufacturing systems require an enterprise level integration. The networked manufacturing offers several advantages in the current competitive atmosphere by way to reduce, by shortening manufacturing cycle time and maintaining the production flexibility thereby achieving several feasible process plans. The first step in this direction is to integrate manufacturing functions such as process planning and scheduling for multi jobs in a network based manufacturing system. It is difficult to determine a proper plan that meets conflicting objectives simultaneously. This paper describes a mobile-agent based negotiation approach to integrate manufacturing functions in a distributed manner; and its fundamental framework and functions are presented. Moreover, ontology has been constructed by using the Protege software which possesses the flexibility to convert knowledge into Extensible Markup Language (XML) schema of Web Ontology Language (OWL) documents. The generated XML schemas have been used to transfer information throughout the manufacturing network for the intelligent interoperable integration of product data models and manufacturing resources. To validate the feasibility of the proposed approach, an illustrative example along with varied production environments that includes production demand fluctuations is presented and compared the proposed approach performance and its effectiveness with evolutionary algorithm based Hybrid Dynamic-DNA (HD-DNA) algorithm. The results show that the proposed scheme is very effective and reasonably acceptable for integration of manufacturing functions.