h i g h l i g h t sWe present a multi-objective optimization algorithm for shading design. We combine Harmony search and Pareto-based procedures. Thermal and daylighting performances of external shading were considered. We applied the optimization process to a residential social housing in Madrid. t r a c tIn this paper we address the problem of designing new energy-efficient static daylight devices that will surround the external windows of a residential building in Madrid. Shading devices can in fact largely influence solar gains in a building and improve thermal and lighting comforts by selectively intercepting the solar radiation and by reducing the undesirable glare. A proper shading device can therefore significantly increase the thermal performance of a building by reducing its energy demand in different climate conditions. In order to identify the set of optimal shading devices that allow a low energy consumption of the dwelling while maintaining high levels of thermal and lighting comfort for the inhabitants we derive a multi-objective optimization methodology based on Harmony Search and Pareto front approaches. The results show that the multi-objective approach here proposed is an effective procedure in designing energy efficient shading devices when a large set of conflicting objectives characterizes the performance of the proposed solutions.
Are extant proteins the exquisite result of natural selection or are they random sequences slightly edited by evolution? This question has puzzled biochemists for long time and several groups have addressed this issue comparing natural protein sequences to completely random ones coming to contradicting conclusions. Previous works in literature focused on the analysis of primary structure in an attempt to identify possible signature of evolutionary editing. Conversely, in this work we compare a set of 762 natural proteins with an average length of 70 amino acids and an equal number of completely random ones of comparable length on the basis of their structural features. We use an ad hoc Evolutionary Neural Network Algorithm (ENNA) in order to assess whether and to what extent natural proteins are edited from random polypeptides employing 11 different structure-related variables (i.e. net charge, volume, surface area, coil, alpha helix, beta sheet, percentage of coil, percentage of alpha helix, percentage of beta sheet, percentage of secondary structure and surface hydrophobicity). The ENNA algorithm is capable to correctly distinguish natural proteins from random ones with an accuracy of 94.36%. Furthermore, we study the structural features of 32 random polypeptides misclassified as natural ones to unveil any structural similarity to natural proteins. Results show that random proteins misclassified by the ENNA algorithm exhibit a significant fold similarity to portions or subdomains of extant proteins at atomic resolution. Altogether, our results suggest that natural proteins are significantly edited from random polypeptides and evolutionary editing can be readily detected analyzing structural features. Furthermore, we also show that the ENNA, employing simple structural descriptors, can predict whether a protein chain is natural or random.
A B S T R A C TConsidering several real case studies, moisture distribution due to rising damp in Venetian brick masonries is discussed and empirical models are developed. Moisture content and soluble salt data of 25 historical buildings in Venice are analysed. Data are scrutinized using statistical methods, obtaining contour plots and estimating the validity of linear and non-linear models. The models confirm that masonries are usually soaked with water till 120-150 cm over sea level, while the evaporation zone ranges in height from 200 cm to 350 cm. In the perpendicular section, moisture distribution depends on several contingent factors such as, among them, the proximity and the exposition of the external façades to the water action.
The development of high-tech industrial parks has transformed the urban landscape in China. However, little is known of the perception of these changes by those affected by their planning and implementation. In order to shed light on this issue, we conducted a study of the Zhejiang Hangzhou Future Sci-Tech City, informed by field research on the environmental and socioeconomic status of the area and semi-structured interviews with stakeholders (residents, workers and government representatives). The data was collected and analysed using a grounded theory approach and modelled via a structural topic model (STM) to identify the most significant issues that people raised in relation to the development of the high-tech industrial park. The main finding of the study is the clear and shared perception of growing prosperity, associated with the improvements to both economic and social infrastructure and the attendant employment and business opportunities. Stakeholders also highlighted improvements to the area’s landscape quality. Nonetheless, stakeholders also identified a set of concerns centred on the threat to cultural identity, the reduction of agricultural land and the diminishing of diversity and flexibility of pathways to urban development. It is these concerns that, in their view, should serve to frame future phases of the Future Sci-Tech City construction.
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