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We studied the performance of the AZTI Marine Biotic Index AMBI manipulating input data collected from lagoonal ecosystems. Our data set consisted of macrofaunal abundance and biomass counts gathered at a variety of sites at which the disturbance status was known. Input data were also manipulated using a set of transformations of increasing severity. Biotic indices were calculated using raw and transformed abundance, biomass and production. Among the three categories of AMBI-based indices, medium transformation of data gave the highest correlation with pressures. However, increasing the severity of transformation generally resulted in a decrease of the correlation with environmental factors. The relative importance of ecological groups changed when using abundance or biomass, sometimes leading to an improved ecological status classification. Being biomass and production more ecologically relevant than abundance, using them to derive AMBI-based new indices seems intriguing, at least in lagoonal waters, where the community is naturally disturbed and dominated by opportunists.

Abstract Globally, three-quarter of a billion people live without electricity. Besides, hundreds of million use a solar lantern for less than 4 h a day. Most of the access-deprived are in the Global South, predominantly in Sub-Saharan Africa and South Asia. The United Nations framed the seventh Sustainable Development Goal to improve access. Solar photovoltaic powered mini-grids are increasingly extending better service to deprived regions. However, poor load-factor and expensive storage adversely affect viability. Also, these mini-grids do not support infrequent large loads to avoid further loss of load-factor. Electric cooking is efficient and non-polluting; water treatment facilities can save millions from contaminant and pathogen by providing clean water. Besides, both electric cooking and water treatment are less expensive than alternatives. But mini-grids frequently do not support these. Indeed, the presence of sustained productive loads favourably influences the mini-grid economy. This study investigates the role of critical household loads to deliver similar bearing on the mini-grid economy. Results underscore realisation of desirable impact with household collaboration under a demand-response program. Collaborative consumption can lower initial investment by 62% and reduce the unit energy cost to $0.23. Also, cooperation improves the mini-grid load factor and promotes viability. Additionally, fast deployment needs during and after Covid-19 remains inherently supported while mitigating the pandemic induced financial stress of both consumer and mini-grid operator. This study of 88 nation-states underscores that demand response in a mini-grid can not only improve affordability for all consumers, but it can also bring 186 million people within affordable access.

Abstract Italy reformed its water and sanitation services in 1994. The strategy aimed at transforming public entities, financed by the central budget, into self-sufficient professional companies regulated at arms' length. Nearly 20 years after, the reform has failed to deliver (despite some partial success). Italians have been divided in two parties: those blaming public sector inefficiencies and calling for competitive tendering; and those refusing to privatize water and willing to go back to the fiscal budget. In this article, we suggest that both parties are wrong. Underperformance is not related to the ownership structure of water companies, but rather to poor regulatory design and lack of understanding of the regulatory requirements that are implicit in the management model chosen, namely the concession contract.

The article contains laboratory data comparing the rate of gasification of five types of woody plants—beech, oak, willow, poplar and rose. The gasification rate was determined thermogravimetrically. Carbon dioxide and steam were used as gasification gases. Willow wood was the most gasifiable, whereas rose wood the least.

Abstract Time series data is a sequence of values recorded systematically over a period which are mostly used for prediction, clustering, and analysis. The two essential features of a time series data are trend and seasonality. Preprocessing of the time series data is necessary for performing prediction tasks. In most of the cases, the trend and the seasonality are removed before applying the regression algorithms. The accuracy of such algorithms depends upon the functions used for the removal of trend and seasonality. Clustering of an unlabeled time series data with the presence of trend and seasonality is challenging. In this paper, we propose a probabilistic representational learning method for grouping the time series data. We introduce five terminologies in our method of clustering namely the trendlets, uplets, downlets, equalets and trendlet string. These elements are the representational building blocks of our proposed method. Experiments on the proposed algorithm are performed with the renewable energy data on the electricity supply system of continental Europe which includes the demand and inflow of renewable energy for the term 2012 to 2014 and UCR-2018 time series archive containing 128 datasets. We compared our proposed representational method with various clustering algorithms using the silhouette score. Mini-batch k-means and agglomerative hierarchical clustering algorithms show better performance in terms of quality, logical accordance with data and time taken for clustering.

Abstract Given the need to reduce the CO2 emissions coming from the manufacturing sector, it is important, for planning purposes, to know which countries and which manufacturing sub-sectors have the greatest potential for reducing energy use. Using data from the International Atomic Energy Agency and the United Nations Industrial Development Organization, the authors estimate trends in global decoupling of energy use and manufacturing value added, compare energy-use intensity in six country groups and estimate the potential for reducing energy use and CO2 emissions under two scenarios and compare selected sub-sector energy intensity and estimate the potential for reducing energy use CO2 emissions. The comparison of energy intensities across country groups and among countries suggests that there still remains significant potential to reduce energy use and associated CO2 emissions. The analysis of four sub-sectors in developing and transition economies also shows similar but varied potential for reducing energy use and associated CO2 emissions.

The study is on the variation of pressure in different faces of rectangular plan-shaped tall buildings with interference conditions due to the presence of another building with the same shape and dimension connected through a multipurpose bridge. The analysis is done on computational fluid dynamics (namely ANSYS CFX) for 0° to 90° wind incidence angle (WIA). The buildings are spaced 60 m from each other. Different cases have been taken and analyzed based on the different positions of the bridge (i.e., 0.33H, 0.5H, and 0.67H) and compared with the isolated case (i.e., buildings without the bridge). A comparison study has been done in the form of interference factor (IF), so we can clearly understand the effect of the bridge at different heights of the building and isolated conditions on rectangular plan-shaped buildings. The study shows that when the bridge is at 0.5H and 0.33H, the force coefficient along X and Y produces similar results to an isolated condition for WIA of 60° and 30°, respectively.

Resume La Chromatographie gazeuse inverse (CGI) a dilution infinie a ete utilisee pour determiner la composante dispersive γSD de l'energie de surface de quelques oxydes et hydroxydes metalliques. Le point de charge nulle (PCN) de ces solides a ete determine par potentiometrie alors que leurs points isoelectriques (PIE) ont ete calcules par des mesures de leur potentiel zeta en milieu aqueux. Cette etude a permis egalement de determiner les proprietes acido-basiques (au sens de Bronstedt) des surfaces etudiees dont l'energie interfaciale γ a ete appreciee d'apres les travaux de Sohnel. Les nouvelles correlations lineaires trouvees entre γSD des solides et leurs PCN (ou leurs PIE, ou encore le pH de leurs suspensions aqueuses) ont permis de connaitre la composante polaire de leur energie de surface en fonction de PCN ou de PIE de ces solides.

Abstract Sugarcane is a major crop cultivated globally and the residue left over after the crop harvest and extraction of juice is a good biomass source that can be used for the production of several useful chemicals. The sugarcane bagasse is an excellent substrate for the production of various biochemicals and enzymes through fermentation. Now major interest is focused on the utilization of these residue for biofuel production. The sugarcane crop residue is rich in cellulose and hemicellulose, hence it can be used for the production of bioethanol and other liquid transportation fuels. The present review gives a detailed account of the availability of sugarcane residue and various commercially important products that can be produced from this residue. It also provides recent developments in R&D on the bioconversion of sugarcane crop residue for value added products.