ALBERT

Description: This study identifies the determinants of corporate social responsibility (CSR) application in the hotel industry of the Colombian Caribbean. A structured CSR questionnaire was applied to a sample of 224 hotels and multivariate statistical analysis was carried out with the support of the DYANE software. The findings suggest that the degree of CSR application is influenced by the size, age, category, type of contract, financial performance, and level of investment in innovation of the establishments; as well as by the sex, age, level of education, and degree of the directors’ autonomy in CSR-related decision-making and their motivations and perceived obstacles. This study on CSR is one of the first that has been applied in the hotel industry of the Colombian Caribbean and the results have important theoretical and practical implications to academia and the hospitality industry. Businessmen have valuable information to improve the levels of CSR in their companies and therefore contribute to a more responsible and sustainable tourism development in the Colombian Caribbean. Future research should include other variables like the type of corporate governance and the risk appetite of the decision-making body of the hotel and the social responsibility of all the stakeholders implicated in the destination.

Description: Despite the large amounts of resources destined to developing filtering algorithms of LiDAR point clouds in order to obtain a Digital Terrain Model (DTM), the task remains a challenge. As a society advancing towards the democratization of information and collaborative processes, the researchers should not only focus on improving the efficacy of filters, but should also consider the users’ needs with a view toward improving the usability and accessibility of the filters in order to develop tools that will provide solutions to the challenges facing this field of study. In this work, we describe the Hybrid Overlap Filter (HyOF), a new filtering algorithm implemented in the free R software environment. The flow diagram of HyOF differs in the following ways from that of other filters developed to date: (1) the algorithm is formed by a combination of sequentially operating functions (i.e., the output of the first function provides the input of the second), which are capable of functioning independently and thus enabling integration of these functions with other filtering algorithms; (2) the variable penetrability is defined and used, along with slope and elevation, to identify ground points; (3) prior to selection of the seed points, the original point cloud is processed with the aim of removing points corresponding to buildings; and (4) a new method based on a moving window, with longitudinal overlap between windows and transverse overlap between passes, is used to select the seed points. Our hybrid filtering method is tested using 15 reference samples acquired by the International Society of Photogrammetry and Remote Sensing (ISPRS) and is evaluated in comparison with 33 existing filtering algorithms. The results show that our hybrid filtering method produces an average total error of 3.34% and an average Kappa coefficient of 92.62%. The proposed algorithm is one of the most accurate filters that has been tested with the ISPRS reference samples.

Description: Green infrastructure has acquired greater importance in recent years in relation to climate change adaptation. Green infrastructure planning has been identified as a new and innovative means of land planning that can contribute to preventing the impacts of climate change. However, this has been explored more thoroughly in urban areas than at the regional scale. The present study proposes a methodology including multi-criteria evaluation techniques for assessing the ESS involved in the fight against climate change and for the spatial planning of multifunctional green infrastructure areas based on the results of this assessment. Application of the methodology for green infrastructure planning aimed at confronting climate change at landscape level in the region of Galicia (NW Spain) successfully delimited multifunctional green infrastructure zones. Results show that delimited zones have a higher provision potential for more ESS than protected natural areas and areas that are not part of the green infrastructure.

Description: TiO2 electrochemical biosensors represent an option for biomolecules recognition associated with diseases, food or environmental contaminants, drug interactions and related topics. The relevance of TiO2 biosensors is due to the high selectivity and sensitivity that can be achieved. The development of electrochemical biosensors based on nanostructured TiO2 surfaces requires knowing the signal extracted from them and its relationship with the properties of the transducer, such as the crystalline phase, the roughness and the morphology of the TiO2 nanostructures. Using relevant literature published in the last decade, an overview of TiO2 based biosensors is here provided. First, the principal fabrication methods of nanostructured TiO2 surfaces are presented and their properties are briefly described. Secondly, the different detection techniques and representative examples of their applications are provided. Finally, the functionalization strategies with biomolecules are discussed. This work could contribute as a reference for the design of electrochemical biosensors based on nanostructured TiO2 surfaces, considering the detection technique and the experimental electrochemical conditions needed for a specific analyte.