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  • 1
    Publication Date: 2019
    Description: At present, university professors lack the tools to know which is the most sustainable activity and/or strategy that should be incorporated into large-group theoretical classes in order to improve our students’ learning process whilst taking each scenario into account. These scenarios have different order thinking levels, numbers of students, available time, classroom size and professor skills, among other factors to consider. In architecture schools we have this problem in theoretical lectures. This project has developed and applied a new multi-criteria decision making tool incorporating a mathematical algorithm in order to choose the best set of active learning activities for each case for these lectures in architectural technology courses. This process has relied on seminars involving experts and the use of The Integrated Value Model for Sustainable Assessment. This tool has been very useful to solve the aforementioned problems because architecture professors have been able to choose the most sustainable activity for each scenario considering the alternative sustainability indexes. This first application has been highly useful to assist professors to incorporate active learning methodologies in their classes and to promote lecturers’ management of their course contents and time. Future improved versions of this tool will increase its interactivity and broaden its scope.
    Electronic ISSN: 2071-1050
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by MDPI
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  • 2
    Publication Date: 2019
    Description: A new strategy was applied to develop nano-quasicrystalline phase in well-known AlNiCo ternary system. This approach was based on electroless Ni-P plating of the starting powders and subsequent ball milling in a protective atmosphere without additional annealing or sintering processes. Microstructural evolution and phase transformation of both raw and coated particles were analyzed by scanning electron microscope (SEM) and X-ray diffraction (XRD), respectively. After 360 min of mechanical alloying, the peaks demonstrating the formation of nano-quasicrystalline phase appeared in XRD pattern of the coated powders, while those in mechanically alloyed raw powders remained mostly unchanged. The formation of nano-quasicrystalline phase in the vicinity of the primary elements was also confirmed by the corresponding selected area diffraction patterns, and images generated by transmission electron microscope (TEM).
    Electronic ISSN: 1996-1944
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Published by MDPI
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  • 3
    Publication Date: 2018
    Description: The sequencing of ancient DNA samples provides a novel way to find, characterize, and distinguish exogenous genomes of endogenous targets. After sequencing, computational composition analysis enables filtering of undesired sources in the focal organism, with the purpose of improving the quality of assemblies and subsequent data analysis. More importantly, such analysis allows extinct and extant species to be identified without requiring a specific or new sequencing run. However, the identification of exogenous organisms is a complex task, given the nature and degradation of the samples, and the evident necessity of using efficient computational tools, which rely on algorithms that are both fast and highly sensitive. In this work, we relied on a fast and highly sensitive tool, FALCON-meta, which measures similarity against whole-genome reference databases, to analyse the metagenomic composition of an ancient polar bear (Ursus maritimus) jawbone fossil. The fossil was collected in Svalbard, Norway, and has an estimated age of 110,000 to 130,000 years. The FASTQ samples contained 349 GB of nonamplified shotgun sequencing data. We identified and localized, relative to the FASTQ samples, the genomes with significant similarities to reference microbial genomes, including those of viruses, bacteria, and archaea, and to fungal, mitochondrial, and plastidial sequences. Among other striking features, we found significant similarities between modern-human, some bacterial and viral sequences (contamination) and the organelle sequences of wild carrot and tomato relative to the whole samples. For each exogenous candidate, we ran a damage pattern analysis, which in addition to revealing shallow levels of damage in the plant candidates, identified the source as contamination.
    Electronic ISSN: 2073-4425
    Topics: Biology
    Published by MDPI
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  • 4
    Publication Date: 2019
    Description: This study evaluates the potential of carbon dioxide-enhanced oil recovery (CO2-EOR) to reduce greenhouse gas emissions without compromising oil production goals. A novel, dynamic carbon lifecycle analysis (d-LCA) was developed and used to understand the evolution of the environmental impact (CO2 emissions) and mitigation (geologic CO2 storage) associated with an expanded carbon capture, utilization and storage (CCUS) system, from start to closure of operations. EOR operational performance was assessed through CO2 utilization rates, which relate usage of CO2 to oil production. Because field operational strategies have a significant impact on reservoir engineering parameters that affect both CO2 storage and oil production (e.g., sweep efficiency, flood conformance, fluid saturation distribution), we conducted a scenario analysis that assessed the operational and environmental performance of four common and novel CO2-EOR field development strategies. Each scenario was evaluated with and without stacked saline carbon storage, an EOR/storage combination strategy where excess CO2 from the recycling facility is injected into an underlying saline aquifer for long-term carbon storage. The dynamic interplay between operational and environmental performance formed the basis of our CCUS technology analysis. The results showed that all CO2-EOR evaluated scenarios start operating with a negative carbon footprint and, years into the project, transitioned into operating with a positive carbon footprint. The transition points were significantly different in each scenario. Water-alternating-gas (WAG) was identified as the CO2 injection strategy with the highest potential to co-optimize EOR and carbon storage goals. The results provide an understanding of the evolution of the system’s net carbon balance in all four field development strategies studied. The environmental performance can be significantly improved with stacked storage, where a negative carbon footprint can be maintained throughout the life of the operation in most of the injection scenarios modelled. This information will be useful to CO2-EOR operators seeking value in storing more CO2 through a carbon credit program (e.g., the 45Q carbon credit program in the USA). Most importantly, this study serves as confirmation that CO2-EOR can be operationally designed to both enhance oil production and reduce greenhouse gas emissions into the atmosphere.
    Electronic ISSN: 1996-1073
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by MDPI
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  • 5
    Publication Date: 2019
    Description: Background: Alpinia officinarum Hance is both an herbal medicine and a condiment, and generally has different cultivars such as Zhutou galangal and Fengwo galangal. The appearance of these A. officinarum cultivars is similar, but their chemical composition and quality are different. It is therefore important to discriminate between different A. officinarum plants to ensure the consistency of the efficacy of the medicine. Therefore, we used an electronic nose (E-nose) to explore the differences in odor information between the two cultivars for fast and robust discrimination. Methods: Odor and volatile components of all A. officinarum samples were detected by the E-nose and gas chromatography-mass spectrometry (GC-MS), respectively. The E-nose sensors and GC-MS data were analyzed respectively by principal component analysis (PCA), the correlation between E-nose sensors and GC-MS data were analyzed by partial least squares (PLS). Results: It was found that Zhutou galangal and Fengwo galangal can be discriminated by combining the E-nose with PCA, and the E-nose sensors S2, S6, S7, S9 were important sensors for distinguishing different cultivars of A. officinarum. A total of 56 volatile components of A. officinarum were identified by the GC-MS analysis, and the composition and content of the volatile components from the two different A. officinarum cultivars were different, in particular the relative contents of 1,8-cineole and α-farnesene. The classification result by PCA analysis based on GC-MS data was consistent with the E-nose results. The PLS analysis demonstrated that the volatile terpene, alcohol and ester components primarily interacted with the sensors S2 and S7, indicating that particular E-nose sensors were highly correlated with some aroma constituents. Conclusions: Combined with advanced chemometrics, the E-nose detection technology can discriminate two cultivars of A. officinarum, with GC-MS providing support to determine the material basis of the E-nose sensors’ response.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI
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  • 6
    Publication Date: 2016-10-15
    Description: The ever increasing growth of the production of high-throughput sequencing data poses a serious challenge to the storage, processing and transmission of these data. As frequently stated, it is a data deluge. Compression is essential to address this challenge—it reduces storage space and processing costs, along with speeding up data transmission. In this paper, we provide a comprehensive survey of existing compression approaches, that are specialized for biological data, including protein and DNA sequences. Also, we devote an important part of the paper to the approaches proposed for the compression of different file formats, such as FASTA, as well as FASTQ and SAM/BAM, which contain quality scores and metadata, in addition to the biological sequences. Then, we present a comparison of the performance of several methods, in terms of compression ratio, memory usage and compression/decompression time. Finally, we present some suggestions for future research on biological data compression.
    Electronic ISSN: 2078-2489
    Topics: Computer Science
    Published by MDPI
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  • 7
    Publication Date: 2019
    Description: Variation in solar irradiance causes power generation fluctuations in solar power plants. Power grid operators need accurate irradiance forecasts to manage this variability. Many factors affect irradiance, including the time of year, weather and time of day. Cloud cover is one of the most important variables that affects solar power generation, but is also characterized by a high degree of variability and uncertainty. Deep learning methods have the ability to learn long-term dependencies within sequential data. We investigate the application of Gated Recurrent Units (GRU) to forecast solar irradiance and present the results of applying multivariate GRU to forecast hourly solar irradiance in Phoenix, Arizona. We compare and evaluate the performance of GRU against Long Short-Term Memory (LSTM) using strictly historical solar irradiance data as well as the addition of exogenous weather variables and cloud cover data. Based on our results, we found that the addition of exogenous weather variables and cloud cover data in both GRU and LSTM significantly improved forecasting accuracy, performing better than univariate and statistical models.
    Electronic ISSN: 1996-1073
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by MDPI
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  • 8
    Publication Date: 2018-04-25
    Description: Mathematics, Vol. 6, Pages 63: A New Descent Algorithm Using the Three-Step Discretization Method for Solving Unconstrained Optimization Problems Mathematics doi: 10.3390/math6040063 Authors: Mina Torabi Mohammad-Mehdi Hosseini In this paper, three-step Taylor expansion, which is equivalent to third-order Taylor expansion, is used as a mathematical base of the new descent method. At each iteration of this method, three steps are performed. Each step has a similar structure to the steepest descent method, except that the generalized search direction, step length, and next iterative point are applied. Compared with the steepest descent method, it is shown that the proposed algorithm has higher convergence speed and lower computational cost and storage.
    Electronic ISSN: 2227-7390
    Topics: Mathematics
    Published by MDPI
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  • 9
    Publication Date: 2019
    Description: This study proposes a framework for the allocation of risk in public private partnerships (PPP) projects. Its contribution lies in the recognition and incorporation of risks introduced by project stakeholders, and as articulated by the principal-agent theory (PAT). The framework assesses risks and routes these risks to those parties best equipped to mitigate their impact on the project. This allocation of risk is facilitated by a thirteen-step process. The practical benefit of this study lies in outlining a clear, systematic method for allocating risk efficiently to both the government and private enterprise parties of the project. In so doing, risk mitigation can be expected to improve project performance, optimize stakeholder goals, and enhance sustainability objectives, including improved operational life-cycle efficiency and elevated social and community benefits.
    Electronic ISSN: 2071-1050
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by MDPI
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  • 10
    Publication Date: 2018
    Description: In small-scale combustors, the ratio of area to the combustor volume increases and hence heat loss from the combustor’s wall is significantly enhanced and flame quenching occurs. To solve this problem, non-premixed vortex flow is employed to stabilize flames in a meso-scale combustion chamber to generate small-scale power or thrust for propulsion systems. In this experimental investigation, the effects of thermal recuperation on the characteristics of asymmetric non-premixed vortex combustion are studied. The exhaust gases temperature, emissions and the combustor wall temperature are measured to evaluate thermal and emitter efficiencies. The results illustrate that in both combustors (with/without thermal recuperator), by increasing the combustion air mass flowrate, the wall temperature increases while the wall temperature of combustor with thermal recuperator is higher. The emitter efficiency calculated based on the combustor wall temperature is significantly increased by using thermal recuperator. Thermal efficiency of the combustion system increases up to 10% when thermal recuperator is employed especially in moderate Reynolds numbers (combustion air flow rate is 120 mg/s).
    Electronic ISSN: 1996-1073
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by MDPI
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