Statistical Analysis and Modeling of Jobs in a Grid Environment

The existence of good probabilistic models for the job arrival process and the delay components introduced at different stages of job processing in a Grid environment is important for the improved understanding of the Grid computing concept. In this study, we present a thorough analysis of the job arrival process in the EGEE infrastructure and of the time durations a job spends at different states in the EGEE environment. We define four delay components of the total job delay and model each component separately. We observe that the job inter-arrival times at the Grid level can be adequately modelled by a rounded exponential distribution, while the total job delay (from the time it is generated until the time it completes execution) is dominated by the computing element’s register and queuing times and the worker node’s execution times. Further, we evaluate the efficiency of the EGEE environment by comparing the job total delay performance with that of a hypothetical ideal super-cluster and conclude that we would obtain similar performance if we submitted the same workload to a super-cluster of size equal to 34% of the total average number of CPUs participating in the EGEE infrastructure. We also analyze the job inter-arrival times, the CE’s queuing times, the WN’s execution times, and the data sizes exchanged at the kallisto.hellasgrid.gr cluster, which is node in the EGEE infrastructure. In contrast to the Grid level, we find that at the cluster level the job arrival process exhibits self-similarity/long-range dependence. Finally, we propose simple and intuitive models for the job arrival process and the execution times at the cluster level.     

Dose-Dependent Cytotoxicity of Polypropylene Microplastics (PP-MPs) in Two Freshwater Fishes

The massive accumulation of plastics over the decades in the aquatic environment has led to the dispersion of plastic components in aquatic ecosystems, invading the food webs. Plastics fragmented into microplastics can be bioaccumulated by fishes via different exposure routes, causing several adverse effects. In the present study, the dose-dependent cytotoxicity of 8–10 μm polypropylene microplastics (PP-MPs), at concentrations of 1 mg/g (low dose) and 10 mg/g dry food (high dose), was evaluated in the liver and gill tissues of two fish species, the zebrafish (Danio rerio) and the freshwater perch (Perca fluviatilis). According to our results, the inclusion of PP-MPs in the feed of D. rerio and P. fluviatilis hampered the cellular function of the gills and hepatic cells by lipid peroxidation, DNA damage, protein ubiquitination, apoptosis, autophagy, and changes in metabolite concentration, providing evidence that the toxicity of PP-MPs is dose dependent. With regard to the individual assays tested in the present study, the biggest impact was observed in DNA damage, which exhibited a maximum increase of 18.34-fold in the liver of D. rerio. The sensitivity of the two fish species studied differed, while no clear tissue specificity in both fish species was observed. The metabolome of both tissues was altered in both treatments, while tryptophan and nicotinic acid exhibited the greatest decrease among all metabolites in all treatments in comparison to the control. The battery of biomarkers used in the present study as well as metabolomic changes could be suggested as early-warning signals for the assessment of the aquatic environment quality against MPs. In addition, our results contribute to the elucidation of the mechanism induced by nanomaterials on tissues of aquatic organisms, since comprehending the magnitude of their impact on aquatic ecosystems is of great importance.     

Novel Insights into Factor D Inhibition

Complement-mediated diseases or complementopathies, such as Paroxysmal nocturnal hemoglobinuria (PNH), cold agglutinin disease (CAD), and transplant-associated thrombotic microangiopathy (TA-TMA), demand advanced complement diagnostics and therapeutics be adopted in a vast field of medical specialties, such as hematology, transplantation, rheumatology, and nephrology. The miracle of complement inhibitors as “orphan drugs” has dramatically improved morbidity and mortality in patients with otherwise life-threatening complementopathies. Efficacy has been significantly improved by upstream inhibition in patients with PNH. Different molecules may exert diverse characteristics in vitro and in vivo. Further studies remain to show safety and efficacy of upstream inhibition in other complementopathies. In addition, cost and availability issues are major drawbacks of current treatments. Therefore, further developments are warranted to address the unmet clinical needs in the field of complementopathies. This state-of-the-art narrative review aims to delineate novel insights into factor D inhibition as a promising target for complementopathies.     

Variation of density of diesel and biodiesel mixtures in three different temperature ranges

The use of biodiesel fuel is becoming increasingly imperative nowadays and it is necessary to know the change of density. In this work the variation of density of diesel-biodiesel blends across the scale of 0–100% by adding each time 2% biodiesel and then measuring the density of three different temperatures (5, 15, 25°C) covering and the usual scale of temperatures the use of mixtures of diesel-biodiesel. Through the extraction of equations can be known in advance the relationship of density of diesel-biodiesel blend, and temperature that is used.     

A structured methodology for assessing and improving e-services in digital cities

Many cities all over the world are making large investments for the construction of big network infrastructures, in order to offer to local public organizations, businesses and citizens high speed connectivity, and on top of them useful e-services, aiming to achieve various social and economic objectives. The value generated from these costly ‘digital city’ investments is actually the value provided to the citizens and businesses by the e-services that will be developed and run on these network infrastructures. This paper proposes and validates a structured methodology for assessing and improving e-services developed in digital cities. The proposed methodology assesses the various types of value generated by an e-service, and also the relations among them, allowing a more structured evaluation, a deeper understanding of the value generation process and also identification and prioritization of the improvements that should be made in the e-service with the usually scarce resources in municipalities. This methodology is applied for the evaluation of an e-learning service developed in the Greek city of Karlovassi for young citizens, and also for the prioritization of the necessary improvements in it. The above application provided positive and encouraging evidence concerning the validity, usefulness and applicability of the proposed method.     

Parallel cooperative micro-particle swarm optimization: A master–slave model

A parallel master–slave model of the recently proposed cooperative micro-particle swarm optimization approach is introduced. The algorithm is based on the decomposition of the original search space in subspaces of smaller dimension. Each subspace is probed by a subswarm of small size that identifies suboptimal partial solution components. A context vector that serves as repository for the best attained partial solutions of all subswarms is used for the evaluation of the particles. The required modifications to fit the original algorithm within a parallel computation framework are discussed along with their impact on performance. Also, both linear and random allocation of direction components to subswarms are considered to render the algorithm capable of capturing possible correlations among decision variables. The proposed approach is evaluated on two types of computer systems, namely an academic cluster and a desktop multicore system, using a popular test suite. Statistical analysis of the obtained results reveals that, besides the expected run-time superiority of the parallel model, significant improvements in solution quality can also be achieved. Different factors that may affect performance are pointed out, offering intuition on the expected behavior of the parallel model.     

Improving the Design of Greek Hollow Clay Bricks

The hollow clay brick is the typical building unit that is employed not only over the whole Greece but also in many other Mediterranean countries. Nevertheless, its design is completely empirical. In this study, the design of the hollow clay brick is analyzed by employing a finite element package. To carry out this analysis, the thermal conductivity of the solid clay is measured by the transient hot-wire technique. As a consequence of the analysis, an improvement of 24 % in the design of the hollow clay brick is proposed.     

Finding all roots of 2?×?2 nonlinear algebraic systems using back-propagation neural networks

The objective of this research is the numerical estimation of the roots of a complete 2?×?2 nonlinear algebraic system of polynomial equations using a feed forward back-propagation neural network. The main advantage of this approach is the simple solution of the system, by building a structure—including product units—that simulates exactly the nonlinear system under consideration and find its roots via the classical back-propagation approach. Examples of systems with four or multiple roots were used, in order to test the speed of convergence and the accuracy of the training algorithm. Experimental results produced by the network were compared with their theoretical values.