Driving forces for agroforestry uptake in Mediterranean Europe: application of the analytic network process

The factors that determine the implementation of four alternative agroforestry practices or no agroforestry on a theoretical 200 ha farm in Mediterranean Europe were examined using an analytic network process (ANP) model. The four agroforestry practices considered were implementation of a form of (i) high natural and cultural value agroforestry, (ii) agroforestry with high value trees, and agroforestry for (iii) arable and (iv) livestock systems. The ANP model was developed in a participatory manner through a systematic series of quantitative questionnaires and workshops with agroforestry researchers. In general, all the Mediterranean agroforestry systems were associated with high benefits and opportunities, but also with high costs and high risks. The greatest benefits were attributed to high natural and cultural value agroforestry systems, which greatly contributed to the highest priority of this system. Overall ranking of priorities for the agroforestry management alternatives show robustness in the sensitivity analysis. The “no agroforestry” land use became the preferred option when costs were given a weighting of 0.50 or greater

Analiza bronce voltametrijom mikrokristala i tankoslojnom kromatografijom

Corrosion potentials of five samples of bronzes having different compositions and the stripping peak potentials of their main components were determined by abrasive stripping voltammetry. Using thin-layer chromatography in combination with electrochemical dissolution of bronzes in the two electrode sampler, the ions of tin, copper, lead and nickel were detected as the products of electro-oxidation of bronzes. It is shown that the dissolution of tin is preferential at low potential differences between the electrodes in the sampler, while the electro-oxidation of copper is significant only at a potential difference higher than 8 V.Određeni su korozijski potencijali pet uzoraka bronci različitoga sastava i potencijali oksidacije njihovih glavnih sastojaka. Kromatografskom je analizom dokazano da su produkti elektrokemijske oksidacije bronce ioni kositra, bakra, olova i nikla. Pokazano je da se kod malog napona u dvoelektrodnoj elektrokemijskoj ćeliji pretežito oksidira kositar, dok se bakar znatnije oksidira tek kod napona većih od 8 V

Lightning Performance Improvement Of 123 kV Line Ston – Komolac By Use Of Line Surge Arresters

This paper presents HEP - Transmission System Operator Ltd. Line surge arrester (LSA) application pilot project on the Ston – Komolac 123 kV line. This 44 km long single circuit shielded transmission line operates in the region with a high lightning activity (keraunic level about 70 thunder days). In addition, it was very difficult to obtain good footing resistance. For these reasons, considered line used to have very bad lightning performance. It was decided to install Line surge arresters for line lightning performance improvement. In order to optimize arrester installation configuration sigma slp software simulations were performed. LSA are installed according to the results of the software simulations. LSA are installed in summer 2007 (110 gapless, IEC-class II Line arresters). Sixty one LSA are equipped with Excount - II monitoring sensors (monitoring arrester leakage current and peak of the impulse current). Based on the 8-month experience, LSA installation has improved line lightning performance. New line performance is close to the targeted once (improvement by 50 to 60 %). Surge arrester monitors collect very interesting information. Collected info will be compared with the software simulations

Universal hidden order in amorphous cellular geometries

Partitioning space into cells with certain extreme geometrical properties is a central problem in many fields of science and technology. Here we investigate the Quantizer problem, defined as the optimisation of the moment of inertia of Voronoi cells, i.e., similarly-sized ‘sphere-like’ polyhedra that tile space are preferred. We employ Lloyd’s centroidal Voronoi diagram algorithm to solve this problem and find that it converges to disordered states associated with deep local minima. These states are universal in the sense that their structure factors are characterised by a complete independence of a wide class of initial conditions they evolved from. They moreover exhibit an anomalous suppression of long-wavelength density fluctuations and quickly become effectively hyperuniform. Our findings warrant the search for novel amorphous hyperuniform phases and cellular materials with unique physical properties

Impact Evaluation of Wet-Weather Events on Influent Flow and Loadings of a Water Resource Recovery Facility

Since the introduction of environmental legislation and directives in Europe, the impact of combined sewer overflows (CSO) on receiving water bodies has become a priority concern in water and wastewater treatment industry. Time-consuming and expensive local sampling and monitoring campaigns have been carried out to estimate the characteristic flow and pollutant concentrations of CSO water. This study focused on estimating the frequency and duration of wet-weather events and their impacts on influent flow and wastewater characteristics of the largest Italian water resource recovery facility (WRRF) in Castiglione Torinese. Eight years (viz. 2009–2016) of routinely collected influent data in addition to the arithmetic mean daily precipitation rates (PI) of the plant catchment area, were elaborated. Relationships between PI and volumetric influent flow rate (Qin), chemical oxygen demand (COD), ammonium concentration (N-NH4) and total suspended solids (TSS) are investigated. Time series data mining (TSDM) method is implemented for segmentation of time series by use of sliding window algorithm to partition the available records associated with wet and dry weather events based on the daily variation of PI time series. Appling the methodology in conjunction with results obtained from data reduction techniques, a wet-weather definition is proposed for the plant. The results confirm that applied methodology on routinely collected plant data can be considered as a good substitute for time-consuming and expensive sampling campaigns and plant monitoring programs usually conducted for accurate emergency response and long-term preparedness for extreme climate conditions

A Genetic Algorithm for Cost-Aware Business Processes Execution in the Cloud

International audienceWith the generalization of the Cloud, software providers can distribute their software as a service without investing in large infrastructure. However, without an effective resource allocation method, their operation cost can grow quickly, hindering the profitability of the service. This is the case for BPM as a Service providers that want to handle hundreds of customers with a given quality of service. Since there are variations in the needed load and in the number of users of the service , the allocation and scheduling methods must be able to adjust the cloud resource quantity and size, and the distribution of customers on these resources. In this paper, we present a cost optimization model and an heuristic based on genetic algorithms to adjust resource allocation to the needs of a set of customers with varying BPM task throughput. Ex-perimentations using realistic customer loads and cloud resources capacities show the gain of these methods compared to previous approaches. Results show that, in our case, using our algorithm on split groups of customers can provide better results

Efficient Migration-Aware Algorithms for Elastic BPMaaS

International audienceAs for all kind of software, customers expect to find business process execution provided as a service (BPMaaS). They expect it to be provided at the best cost with guaranteed SLA. From the BPMaaS provider point of view it can be done thanks to the provision of an elastic cloud infrastructure. Providers still have to provide the service at the lowest possible cost while meeting customers expectation. We propose a customer-centric service model that link the BP execution requirement to cloud resources, and that optimize the deployment of customer’s (or tenants) processes in the cloud to adjust constantly the provision to the needs. However, migrations between cloud configurations can be costly in terms of quality of service and a provider should reduce the number of migrations. We propose a model for BPMaaS cost optimization that take into account a maximum number of migrations for each tenants. We designed a heuristic algorithm and experimented using various customer load configurations based on customer data, and on an actual estimation of the capacity of cloud resources

A historical perspective of biomedical explainable AI research

The black-box nature of most artificial intelligence (AI) models encourages the development of explainability methods to engender trust into the AI decision-making process. Such methods can be broadly categorized into two main types: post hoc explanations and inherently interpretable algorithms. We aimed at analyzing the possible associations between COVID-19 and the push of explainable AI (XAI) to the forefront of biomedical research. We automatically extracted from the PubMed database biomedical XAI studies related to concepts of causality or explainability and manually labeled 1,603 papers with respect to XAI categories. To compare the trends pre- and post-COVID-19, we fit a change point detection model and evaluated significant changes in publication rates. We show that the advent of COVID-19 in the beginning of 2020 could be the driving factor behind an increased focus concerning XAI, playing a crucial role in accelerating an already evolving trend. Finally, we present a discussion with future societal use and impact of XAI technologies and potential future directions for those who pursue fostering clinical trust with interpretable machine learning models.</p

Biomimetic, Mild Chemical Synthesis of CdTe-GSH Quantum Dots with Improved Biocompatibility

Multiple applications of nanotechnology, especially those involving highly fluorescent nanoparticles (NPs) or quantum dots (QDs) have stimulated the research to develop simple, rapid and environmentally friendly protocols for synthesizing NPs exhibiting novel properties and increased biocompatibility

Characteristics and drivers of forest cover change in the post-socialist era in Croatia: evidence from a mixed-methods approach

© 2016, Springer-Verlag Berlin Heidelberg.Extensive forests in Croatia represent an important biological and economic resource in Europe. They are characterised by heterogeneity in forest management practices dating back to the socialist planned economy of the pre-1991 era. In this study we investigated the difference in rates of deforestation and reforestation in private- and state-owned forests during the post-socialist period and the causal drivers of change. The selected region of Northern Croatia is characterised by a high percentage of privately owned forests with minimal national monitoring and control. We used a mixed-methods approach which combines remote sensing, statistical modelling and a household-based questionnaire survey to assess the rates of forest cover change and factors influencing those changes. The results show that predominantly privately owned forests in Northern Croatia have recorded a net forest loss of 1.8 % during the 1991–2011 period, while Croatia overall is characterised by a 10 % forest cover increase in predominantly state-owned forests. Main factors influencing forest cover changes in private forests are slope, altitude, education structure, population age and population density. The results also show that the deforestation in private forests is weakening overall, mostly due to the continuation of the de-agrarisation and de-ruralisation processes which began during socialism