This paper presents a model for measuring intellectual capital (IC) within small and medium-sized enterprises (SMEs) in correlation with the key factors for the successful implementation of knowledge management (KM). Most of the existing IC measurement models are intended to cover general aspects. The kernel of these models could be customized/extended to handle more specific aspects, like KM. The focus of this study is the integration between an IC measurement model and the key factors for successful implementing of KM. The paper identifies, analyses and compares IC elements that are relevant for SMEs and how they can be linked with the IC measurement methods for determining if a company is ready for KM. For this purpose, a general IC measurement model is taken as reference for the study.

Around the world, there are thousands of metal structures completely or partially buried in the soil. The main concern in their design is corrosion. Corrosion is a mechanism that degrades materials and causes structural failures in infrastructures, which can lead to severe effects on the environment and have direct impact on the population health. In addition, corrosion is extremely complex in the underground environment due to the variability of the local conditions. The problem is that there are many methods to its evaluation but none have been clearly established. In order to ensure the useful life of such structures, engineers usually consider an excess thickness that increases the economic cost of manufacturing and does not satisfy the principles of efficiency in the use of resources. In this paper, an extended revision of the existing methods to evaluate corrosion is carried out to optimize the design of buried steel structures according to their service life. Thus, they are classified into two categories depending on the information they provide: qualitative and quantitative methods. As a result, it is concluded that the most exhaustive methodologies for estimating soil corrosion are quantitative methods fed by non-electrochemical data based on experimental studies that measure the mass loss of structures.

Knowledge of the free draft of ports is essential for the adequate management of ports. To maintain these drafts, it is necessary to carry out dredging periodically, and to conduct bathymetries using traditional techniques, such as echo sounding. However, an echo sounder is very expensive and its accuracy is subject to weather conditions. Thus, the use of recent advancements in remote sensing techniques provide a better solution for mapping and estimating the evolution of the seabed in these areas. This paper presents a cost-effective and practical method for estimating satellite-derived bathymetry for highly polluted and turbid waters at two different ports in the cities of Luarca and Candás in the Principality of Asturias (Spain). The method involves the use of the support vector machine (SVM) technique and open Sentinel-2 satellite imagery, which the European Space Agency has supplied. Models were compared to the bathymetries that were obtained from the in situ data collected by a single beam echo sounder that the Port Service of the Principality of Asturias provided. The most accurate values of the training and testing dataset in Candás, were R² = 0.911 and RMSE = 0.3694 m, and R² = 0.8553 and RMSE = 0.4370 m, respectively. The accuracies of the training and testing dataset values in Luarca were R² = 0.976 and RMSE = 0.4409 m, and R² = 0.9731 and RMSE = 0.4640 m, respectively. The regression analysis results of the training and testing dataset were consistent. The approaches that have been developed in this work may be included in the monitoring of future dredging activities in ports, especially where the water is polluted, muddy and highly turbid.

The following paper proposes a study about the existing solutions for dealing with uncertainty while solving the planning and scheduling problem at steel industry manufacturing processes. The different techniques designed to cope with uncertainty in manufacturing scheduling are discussed, along with the main uncertainty factors affecting the scheduling. The paper proposes a classification for the main uncertainties affecting the steelmaking process and analyzes the existing literature about solutions for the scheduling with uncertainty in the steel sector in terms of approaches followed and uncertainty types considered. Finally, the main remarks and future challenges within this field are presented.

In order to enlarge the shelf life and avoid the waste of fresh-cut (FC) products, novel packaging techniques with antimicrobial properties have been proposed. In this work, we analyzed the potential environmental benefits of using films reinforced with bactericidal ZnO nanoparticles (NP) for FC produce packaging, when compared to the traditional polypropylene (PP) films. A biodegradable, polylactic acid (PLA) package and a non-biodegradable, polypropylene package, both coated with ZnO NP, were considered as novel technologies. The eco-profile of the considered alternatives was assessed via two life cycle assessments (LCAs). Firstly, an attributional LCA was performed in order to compare the materials in terms of their production and end of life (EOL) processes, allowing us to extend the conclusions to different food products. Secondly, a consequential LCA was performed taking into account the whole life cycle of the fresh vegetable, with special attention to the environmental implications of the produce losses among the chain. The uncertainties of the models were assessed via Monte Carlo approach. In both cases, the scenarios concerning the PLA and PP active packages with ZnO NP showed a better profile than the traditional techniques, specifically when considering the full supply chain of the FC vegetables in the consequential LCA. As agricultural production is the main contributor to the environmental impact of the cycle, the avoidance of wastes by extending the shelf life through the novel packages leads to the impact reduction of FC products.