Techno economic and environmental assessment of Flettner rotors for marine propulsion

Wind energy is a mature renewable energy source that offers significant potential for near-term (2020) and long-term (2050) greenhouse gas (GHG) emissions reductions. Similar to all sectors of the transportation industry, the marine industry is also focused towards reduction of environmental emissions. A direct consequence of this being is a renewed interest in utilising wind as supplementary energy source for propulsion on cargo/merchant ships. This research utilises a techno economic and environmental analysis approach to assess the possibility and benefits of harnessing wind energy, with an aim to establish the potential role of wind energy in reducing GHG emissions during conventional operation of marine vessels. The employed approach enables consistent assessment of different competing traditional propulsion systems when operated in conjunction with a novel environmental friendly technology, in this instance being the Flettner rotor technology. The assessment specifically focuses on quantifying the potential and relative reduction in fuel consumption and pollutant emissions that may be accrued while operating on typical Sea Lines of Communication. The results obtained indicate that the implementation of Flettner towers on commercial vessels could result in potential savings of up to 20% in terms of fuel consumption, and similar reductions in environmental emissions

Characterization of a big data storage workload in the cloud

The proliferation of big data processing platforms has led to radically different system designs, such as MapReduce and the newer Spark. Understanding the workloads of such systems facilitates tuning and could foster new designs. However, whereas MapReduce workloads have been characterized extensively, relatively little public knowledge exists about the characteristics of Spark workloads in representative environments. To address this problem, in this work we collect and analyze a 6-month Spark workload from a major provider of big data processing services, Databricks. Our analysis focuses on a number of key features, such as the long-term trends of reads and modifications, the statistical properties of reads, and the popularity of clusters and of file formats. Overall, we present numerous findings that could form the basis of new systems studies and designs. Our quantitative evidence and its analysis suggest the existence of daily and weekly load imbalances, of heavy-tailed and bursty behaviour, of the relative rarity of modifications, and of proliferation of big data specific formats

Techno economic and environmental assessment of wind assisted marine propulsion systems

In recent years, the increase in marine fuel prices coupled with stricter regulations on pollutant emissions set by the International Maritime Organization have promoted the research in new propulsion technologies and the utilisation of cleaner fuels. This paper describes a novel methodology to enable quantifying and evaluating the environmental and economic benefits that new technologies and fuels could allow in the marine sector. The proposed techno economic and environmental analysis approach enables consistent assessment of different traditional propulsion systems (diesel engine and gas turbine) when operated in conjunction with a novel environmental friendly technology, such as a vertical axis wind turbine. The techno-economic and environmental assessment is focused on the potential reduction in fuel consumption and pollutant emissions that may be accrued while operating on typical Sea Lines Of Communication (Mediterranean, North Sea, Atlantic). The study demonstrates the benefits of the installation of two vertical axis wind turbines on the deck of a ship in conjunction with conventional power plants. The analysis indicates that the performance of the wind turbines and the corresponding benefits strongly depend on the routes and environment in which they operate (therefore favourable wind conditions) allowing fuel savings from 14% (in the gas turbine case) to 16% (in the diesel engine case). The study also indicates that possible benefits may diminish for weak wind conditions. The results reported in this paper establish the economic benefits of installing vertical axis wind turbines in conjunction with conventional technology (Diesel and Gas Turbine Power plants) when installed on a ship travelling through the Atlantic Ocean. The primary purpose of this study is to introduce a methodology to demonstrate the application, performance and economic benefits of the technology at a preliminary design phase and further form a foundation for more elaborate analysis on the subject in the future

Quantifying signals with power-law correlations: A comparative study of detrended fluctuation analysis and detrended moving average techniques

Detrended fluctuation analysis (DFA) and detrended moving average (DMA) are two scaling analysis methods designed to quantify correlations in noisy non-stationary signals. We systematically study the performance of different variants of the DMA method when applied to artificially generated long-range power-law correlated signals with an {\it a-priori} known scaling exponent $\alpha_{0}$ and compare them with the DFA method. We find that the scaling results obtained from different variants of the DMA method strongly depend on the type of the moving average filter. Further, we investigate the optimal scaling regime where the DFA and DMA methods accurately quantify the scaling exponent $\alpha_{0}$, and how this regime depends on the correlations in the signal. Finally, we develop a three-dimensional representation to determine how the stability of the scaling curves obtained from the DFA and DMA methods depends on the scale of analysis, the order of detrending, and the order of the moving average we use, as well as on the type of correlations in the signal.Comment: 15 pages, 16 figure

Occurrence of testicular microlithiasis in androgen insensitive hypogonadal mice

<b>Background</b>: Testicular microliths are calcifications found within the seminiferous tubules. In humans, testicular microlithiasis (TM) has an unknown etiology but may be significantly associated with testicular germ cell tumors. Factors inducing microlith development may also, therefore, act as susceptibility factors for malignant testicular conditions. Studies to identify the mechanisms of microlith development have been hampered by the lack of suitable animal models for TM.<BR/> <b>Methods</b>: This was an observational study of the testicular phenotype of different mouse models. The mouse models were: cryptorchid mice, mice lacking androgen receptors (ARs) on the Sertoli cells (SCARKO), mice with a ubiquitous loss of androgen ARs (ARKO), hypogonadal (hpg) mice which lack circulating gonadotrophins, and hpg mice crossed with SCARKO (hpg.SCARKO) and ARKO (hpg.ARKO) mice.<BR/> <b>Results</b>: Microscopic TM was seen in 94% of hpg.ARKO mice (n=16) and the mean number of microliths per testis was 81 +/- 54. Occasional small microliths were seen in 36% (n=11) of hpg testes (mean 2 +/- 0.5 per testis) and 30% (n=10) of hpg.SCARKO testes (mean 8 +/- 6 per testis). No microliths were seen in cryptorchid, ARKO or SCARKO mice. There was no significant effect of FSH or androgen on TM in hpg.ARKO mice.<BR/> <b>Conclusions</b>: We have identified a mouse model of TM and show that lack of endocrine stimulation is a cause of TM. Importantly, this model will provide a means with which to identify the mechanisms of TM development and the underlying changes in protein and gene expression

Protein disulfide-isomerase interacts with a substrate protein at all stages along its folding pathway

In contrast to molecular chaperones that couple protein folding to ATP hydrolysis, protein disulfide-isomerase (PDI) catalyzes protein folding coupled to formation of disulfide bonds (oxidative folding). However, we do not know how PDI distinguishes folded, partly-folded and unfolded protein substrates. As a model intermediate in an oxidative folding pathway, we prepared a two-disulfide mutant of basic pancreatic trypsin inhibitor (BPTI) and showed by NMR that it is partly-folded and highly dynamic. NMR studies show that it binds to PDI at the same site that binds peptide ligands, with rapid binding and dissociation kinetics; surface plasmon resonance shows its interaction with PDI has a Kd of ca. 10−5 M. For comparison, we characterized the interactions of PDI with native BPTI and fully-unfolded BPTI. Interestingly, PDI does bind native BPTI, but binding is quantitatively weaker than with partly-folded and unfolded BPTI. Hence PDI recognizes and binds substrates via permanently or transiently unfolded regions. This is the first study of PDI's interaction with a partly-folded protein, and the first to analyze this folding catalyst's changing interactions with substrates along an oxidative folding pathway. We have identified key features that make PDI an effective catalyst of oxidative protein folding – differential affinity, rapid ligand exchange and conformational flexibility

A branch and efficiency algorithm for the optimal design of supply chain networks

Supply chain operations directly affect service levels. Decision on amendment of facilities is generally decided based on overall cost, leaving out the efficiency of each unit. Decomposing the supply chain superstructure, efficiency analysis of the facilities (warehouses or distribution centers) that serve customers can be easily implemented. With the proposed algorithm, the selection of a facility is based on service level maximization and not just cost minimization as this analysis filters all the feasible solutions utilizing Data Envelopment Analysis (DEA) technique. Through multiple iterations, solutions are filtered via DEA and only the efficient ones are selected leading to cost minimization. In this work, the problem of optimal supply chain networks design is addressed based on a DEA based algorithm. A Branch and Efficiency (B&E) algorithm is deployed for the solution of this problem. Based on this DEA approach, each solution (potentially installed warehouse, plant etc) is treated as a Decision Making Unit, thus is characterized by inputs and outputs. The algorithm through additional constraints named “efficiency cuts”, selects only efficient solutions providing better objective function values. The applicability of the proposed algorithm is demonstrated through illustrative examples