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  • Computational Methods  (36)
  • Other low-carbon energy technologies  (29)
  • Oxford University Press  (65)
  • 2015-2019  (65)
  • 1970-1974
  • 1945-1949
  • 1
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    Calculations of effectiveness factors and the criteria of mass transfer effect for high-temperature methanation (HTM) catalyst (2015)
    Oxford University Press
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    Publication Date: 2015-08-16
    Description: Natural gas is an extremely important bridge fuel to a low-carbon energy economy for improving local air quality. Coal to synthetic natural gas (SNG) is an effective way to convert the high-carbon energy (coal) into the low-carbon energy with rich hydrogen (natural gas). For the modern coal to SNG industry, the high-temperature methanation (HTM) catalyst plays an important role, and the advanced evaluation process should necessitate the elimination of mass transfer effect. Some simple but effective model catalysts, such as slab and sphere, can be very helpful in defining the reaction conditions, and thus facilitating the evaluation process for real HTM catalysts. In this work, slab and sphere model catalysts were adopted to derive mass transfer and reaction-coupled equations, the numerical methods were used to solve the coupled equations for the concentration profiles in catalysts, and the effectiveness factors were accordingly calculated. By taking advantage of the Thiele module and the Weisz–Prater module , the criteria for the elimination of mass transfer effect in the HTM catalyst evaluation process were successfully defined. This work also complements the Weisz–Prater criterion by incorporating ‘negative reaction orders’.
    Keywords: Other low-carbon energy technologies
    Print ISSN: 1748-1317
    Electronic ISSN: 1748-1325
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 2
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    A novel low-carbon space conditioning system incorporating phase-change materials and earth-air heat exchangers (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-16
    Description: The energy expended for conditioning buildings around the world is worryingly large and increasing every year. Currently, almost half of houses around the world use some type of energy-expensive conventional air-conditioning system. These systems are high emitters of gases such as carbon dioxide and so high contributors to climate change. Consequently, alternatives must be considered. Earth–air heat exchangers (EAHEs) and phase-change materials (PCMs) may be options; they have, however, limitations. This paper proposes a novel hybrid space-conditioning system combining EAHEs with PCMs, which uses surfaces as sources of heating or cooling to provide better temperature distribution across a space and comfort enhancement with low energy use. The idea is to use an EAHE to provide cool air to discharge the PCM, consequently helping to overcome most of the limitations of both strategies. Two of a series of experiments undertaken to test the proposed system are reported in this article. The EAHE + PCM system compared with a reference room could decrease temperature swings by up to 47%. The system was proved to work although further work is required to make it commercially viable.
    Keywords: Other low-carbon energy technologies
    Print ISSN: 1748-1317
    Electronic ISSN: 1748-1325
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 3
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    Numerical investigation of turbulent flow heat transfer and pressure drop of AL2O3/water nanofluid in helically coiled tubes (2015)
    Oxford University Press
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    Publication Date: 2015-08-16
    Description: Passive convective heat transfer enhancement can be achieved by improving the thermo-physical properties of the working fluid, changing flow geometry or both. This work presents a numerical study to investigate the combined effect of using helical coils and nanofluids on the heat transfer characteristics and pressure losses in turbulent flow regime. The developed computational fluid dynamics models were validated against published experimental data and empirical correlations. Results have shown that combining the effects of alumina (Al 2 O 3 ) nanoparticles and tube coiling could enhance the heat transfer coefficient by up to 60% compared with that of pure water in straight tube at the same Reynolds number. Also, results showed that the pressure drop in helical coils using Al 2 O 3 nanofluid for volume fraction of 3% was six times that of water in straight tubes (80% of the pressure drop increase is due to nanoparticles addition), while the effect of Reynolds number on the pressure drop penalty factor was found to be insignificant.
    Keywords: Other low-carbon energy technologies
    Print ISSN: 1748-1317
    Electronic ISSN: 1748-1325
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 4
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    Readdressing working fluid selection with a view to designing a variable geometry ejector (2015)
    Oxford University Press
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    Publication Date: 2015-08-16
    Description: A number of factors influence the performance of an ejector, e.g. working fluid, geometry and operating conditions. In the present work, six low-environmental-impact working fluids were evaluated for their use in an ejector cooling system running on low-temperature thermal energy. The numerical analysis was based on a model applying the 1D constant-pressure mixing theory. Ejector performance was assessed for the temperatures of the generator, evaporator and condenser in the range of 80–120°C, 5–15°C and 25–40°C, respectively. The results indicated that owing to its high coefficient of performance and moderate operating pressures throughout the entire ejector cycle, isobutane is a good choice for a refrigerant. The area ratio required for running the ejector in critical mode, under changing operating conditions, varied in a significant range regardless of the selected refrigerant. This clearly indicates the importance of a variable geometry ejector design to strengthen the position of ejector cooling systems among other refrigeration technologies.
    Keywords: Other low-carbon energy technologies
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 5
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    Constructal optimization of a disc-shaped body with cooling channels for specified power pumping (2015)
    Oxford University Press
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    Publication Date: 2015-08-16
    Description: The thermal performance of a disc-shaped heat generation body with cooling channels is investigated by using constructal theory based on previous model of heat convection on a disc and previous analytical method of heat conduction on a disc. By taking minimum dimensionless maximum thermal resistance as optimization objective, the optimal aspect ratio of the elemental sector in the radial-pattern disc is obtained for the specified power pumping of the elemental sector; the optimal width ratio of the first-order and elemental cooling channels and the optimal dimensionless radius of the elemental sector are obtained for the specified power pumping of the disc. There exists a critical radius of the disc to determine whether the radial-pattern design and branched-pattern design should be adopted. These conclusions are different from those obtained by Wechsatol et al. 's model, and the essential reason for these differences is that the power pumping is specified in this article, but not the specified flow rate number in Wechsatol et al. 's model. Finally, the assumption about the heat capacity of the coolant and the thermal conductivity of the disc is validated. An analytical method is introduced in this article, which can provide another thought for the constructal optimization of disc with heat convection. The optimal constructs of the discs are obtained for the specified power pumping, which provides some different guidelines for the design of disc with heat convection.
    Keywords: Other low-carbon energy technologies
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 6
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    Computational study of a 2D capillary pump evaporator (2015)
    Oxford University Press
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    Publication Date: 2015-08-16
    Description: Capillary pump loop (CPL) is a two-phase heat transfer device considered as a useful solution for thermal control applications in spacecrafts, satellites and electronic components. The purpose of this paper is to study various aspects of the working state of the CPL evaporator. A two-dimensional computational model was developed in order to analyze the flow and the phase transformation inside a cylindrical evaporator. At the present analysis, different cases were studied by changing liquid saturation temperature, inclination angle of the evaporator and the length of the porous heated wick. Water, ammonia, acetone and freon-134 were used as working liquids for numerical experiments. Results present the evaporator capability to vaporize each working liquid and find out its possibility of dry-out causing failure. This information is useful in choosing the best working liquid for an evaporator, enabling bigger amounts of heat to be transferred.
    Keywords: Other low-carbon energy technologies
    Print ISSN: 1748-1317
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 7
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    Design guideline for application of earth-to-air heat exchanger coupled with solar chimney as a natural heating system (2015)
    Oxford University Press
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    Publication Date: 2015-08-16
    Description: In the present paper, design of solar chimney (SC) and earth-to-air heat exchanger (EAHE) to meet the thermal need of flat buildings are studied regarding adaptive thermal comfort criteria. Investigation on the effects of geometric features shows that the design of SC with the air gap and outlet sizes of 0.2 m and also EAHE with the diameter and length of 0.5 and 25.0 m reveals better performance. Thermal comfort analysis shows that the SC is capable to power the underground heating system during few hours of the sunny days even at the ambient temperature as low as 0°C and the heating demand of 1000 W without needing the auxiliary devices. In addition, the required numbers of SCs and the underground air channels are strongly influenced by environmental outdoor conditions and heating demand of building and are approximately calculated by: $$\hbox{ room }\phantom{\rule{0.08em}{0ex}}\hbox{ volume/50 }\phantom{\rule{0.08em}{0ex}}\hbox{ and }\phantom{\rule{0.08em}{0ex}}\hbox{ 2 }\times (\hbox{ room }\phantom{\rule{0.08em}{0ex}}\hbox{ volume/50 })+\hbox{ 1, }$$ respectively.
    Keywords: Other low-carbon energy technologies
    Print ISSN: 1748-1317
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 8
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    High speed BLASTN: an accelerated MegaBLAST search tool (2015)
    Oxford University Press
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    Publication Date: 2015-09-19
    Description: Sequence alignment is a long standing problem in bioinformatics. The Basic Local Alignment Search Tool (BLAST) is one of the most popular and fundamental alignment tools. The explosive growth of biological sequences calls for speedup of sequence alignment tools such as BLAST. To this end, we develop high speed BLASTN (HS-BLASTN), a parallel and fast nucleotide database search tool that accelerates MegaBLAST—the default module of NCBI-BLASTN. HS-BLASTN builds a new lookup table using the FMD-index of the database and employs an accurate and effective seeding method to find short stretches of identities (called seeds) between the query and the database. HS-BLASTN produces the same alignment results as MegaBLAST and its computational speed is much faster than MegaBLAST. Specifically, our experiments conducted on a 12-core server show that HS-BLASTN can be 22 times faster than MegaBLAST and exhibits better parallel performance than MegaBLAST. HS-BLASTN is written in C++ and the related source code is available at https://github.com/chenying2016/queries under the GPLv3 license.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 9
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    3dRNAscore: a distance and torsion angle dependent evaluation function of 3D RNA structures (2015)
    Oxford University Press
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    Publication Date: 2015-05-29
    Description: Model evaluation is a necessary step for better prediction and design of 3D RNA structures. For proteins, this has been widely studied and the knowledge-based statistical potential has been proved to be one of effective ways to solve this problem. Currently, a few knowledge-based statistical potentials have also been proposed to evaluate predicted models of RNA tertiary structures. The benchmark tests showed that they can identify the native structures effectively but further improvements are needed to identify near-native structures and those with non-canonical base pairs. Here, we present a novel knowledge-based potential, 3dRNAscore, which combines distance-dependent and dihedral-dependent energies. The benchmarks on different testing datasets all show that 3dRNAscore are more efficient than existing evaluation methods in recognizing native state from a pool of near-native states of RNAs as well as in ranking near-native states of RNA models.
    Keywords: Computational Methods
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    Topics: Biology
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  • 10
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    SPATIAL: A System-level PAThway Impact AnaLysis approach (2016)
    Oxford University Press
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    Publication Date: 2016-06-21
    Description: The goal of pathway analysis is to identify the pathways that are significantly impacted when a biological system is perturbed, e.g. by a disease or drug. Current methods treat pathways as independent entities. However, many signals are constantly sent from one pathway to another, essentially linking all pathways into a global, system-wide complex. In this work, we propose a set of three pathway analysis methods based on the impact analysis, that performs a system-level analysis by considering all signals between pathways, as well as their overlaps. Briefly, the global system is modeled in two ways: (i) considering the inter-pathway interaction exchange for each individual pathways, and (ii) combining all individual pathways to form a global, system-wide graph. The third analysis method is a hybrid of these two models. The new methods were compared with DAVID, GSEA, GSA, PathNet, Crosstalk and SPIA on 23 GEO data sets involving 19 tissues investigated in 12 conditions. The results show that both the ranking and the P -values of the target pathways are substantially improved when the analysis considers the system-wide dependencies and interactions between pathways.
    Keywords: Computational Methods
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    Topics: Biology
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  • 11
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    Goldmine integrates information placing genomic ranges into meaningful biological contexts (2016)
    Oxford University Press
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    Publication Date: 2016-07-09
    Description: Bioinformatic analysis often produces large sets of genomic ranges that can be difficult to interpret in the absence of genomic context. Goldmine annotates genomic ranges from any source with gene model and feature contexts to facilitate global descriptions and candidate loci discovery. We demonstrate the value of genomic context by using Goldmine to elucidate context dynamics in transcription factor binding and to reveal differentially methylated regions (DMRs) with context-specific functional correlations. The open source R package and documentation for Goldmine are available at http://jeffbhasin.github.io/goldmine .
    Keywords: Computational Methods
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    Topics: Biology
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  • 12
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    Defining the multivalent functions of CTCF from chromatin state and three-dimensional chromatin interactions (2016)
    Oxford University Press
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    Publication Date: 2016-07-28
    Description: CCCTC-binding factor (CTCF) is a multi-functional protein that is assigned various, even contradictory roles in the genome. High-throughput sequencing-based technologies such as ChIP-seq and Hi-C provided us the opportunity to assess the multivalent functions of CTCF in the human genome. The location of CTCF-binding sites with respect to genomic features provides insights into the possible roles of this protein. Here we present the first genome-wide survey and characterization of three important functions of CTCF: enhancer insulator, chromatin barrier and enhancer linker. We developed a novel computational framework to discover the multivalent functions of CTCF based on chromatin state and three-dimensional chromatin architecture. We applied our method to five human cell lines and identified ~46 000 non-redundant CTCF sites related to the three functions. Disparate effects of these functions on gene expression were found and distinct genomic features of these CTCF sites were characterized in GM12878 cells. Finally, we investigated the cell-type specificities of CTCF sites related to these functions across five cell types. Our study provides new insights into the multivalent functions of CTCF in the human genome.
    Keywords: Computational Methods
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    Topics: Biology
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  • 13
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    SubmiRine: assessing variants in microRNA targets using clinical genomic data sets (2015)
    Oxford University Press
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    Publication Date: 2015-05-03
    Description: MicroRNAs (miRNAs) regulate gene expression by binding to partially complementary sequences on target mRNA transcripts, thereby causing their degradation, deadenylation, or inhibiting their translation. Genomic variants can alter miRNA regulation by modifying miRNA target sites, and multiple human disease phenotypes have been linked to such miRNA target site variants (miR-TSVs). However, systematic genome-wide identification of functional miR-TSVs is difficult due to high false positive rates; functional miRNA recognition sequences can be as short as six nucleotides, with the human genome encoding thousands of miRNAs. Furthermore, while large-scale clinical genomic data sets are becoming increasingly commonplace, existing miR-TSV prediction methods are not designed to analyze these data. Here, we present an open-source tool called SubmiRine that is designed to perform efficient miR-TSV prediction systematically on variants identified in novel clinical genomic data sets. Most importantly, SubmiRine allows for the prioritization of predicted miR-TSVs according to their relative probability of being functional. We present the results of SubmiRine using integrated clinical genomic data from a large-scale cohort study on chronic obstructive pulmonary disease (COPD), making a number of high-scoring, novel miR-TSV predictions. We also demonstrate SubmiRine's ability to predict and prioritize known miR-TSVs that have undergone experimental validation in previous studies.
    Keywords: Computational Methods
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    Topics: Biology
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  • 14
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    Numerical analysis of solar-assisted seasonal 'open' thermochemical heat storage (2015)
    Oxford University Press
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    Publication Date: 2015-05-13
    Description: In the last decade, interest in heat storage systems has been increasing. These systems will have increasing importance for utilization of solar energy in domestic heating systems. As solar energy is a diurnal cyclic resource, storing excess solar energy for long- or short-term periods will both increase the utilization of solar energy systems and decrease fossil fuel consumption. The relatively new heat storage method using thermochemical storage has shown some significant advantages such as low heat loss (-〉 zero), high heat storage density and low space requirement. These important properties make thermochemical storage a promising alternative for long-term energy storage. In the present study, a numerical investigation on ‘open’ seasonal thermochemical storage has been undertaken. The simulation results show that the volume/mass of the absorbent, mass flow rate and relative humidity of air have significant importance on the reaction kinetics and system performance during the system discharging process. Conversely, total collector area, solar radiation and mass flow rate of air are important parameters during the charging process. The results conclude that, overall, reactor design is the most important factor for storage performance. In addition, reaction advancement ( X ) has a significant importance on process efficiency.
    Keywords: Other low-carbon energy technologies
    Print ISSN: 1748-1317
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 15
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    Optimization of building-integrated photovoltaic thermal air system combined with thermal storage (2015)
    Oxford University Press
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    Publication Date: 2015-05-13
    Description: Photovoltaic (PV) combined with phase change material (PV/PCM) system is a hybrid solar system that uses a PCM to reduce the PV temperature and to store energy for other applications. This study aims to increase the integrated PV efficiency of buildings by incorporating PCM while utilizing the stored heat in PCM for controlling indoor conditions. Experiments have been carried out on a prototype PV/PCM air system using monocrystalline PV modules. Transient simulations of the system performance have also been performed using a commercial computational fluid dynamics package based on the finite volume method. The results from simulation were validated by comparing it with experimental results. The results indicate that PCM is effective in limiting temperature rise in PV device and the heat from PCM can enhance night ventilation and decrease the building energy consumption to achieve indoor thermal comfort for certain periods of time.
    Keywords: Other low-carbon energy technologies
    Print ISSN: 1748-1317
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 16
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    Thermal energy storage: the role of the heat pipe in performance enhancement (2015)
    Oxford University Press
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    Publication Date: 2015-05-13
    Description: Heat pipes and thermosyphons—devices of high effective thermal conductivity—have been studied for many years for enhancing the performance of solid, liquid and phase change material (PCM) heat stores. However, as the applications of heat storage widen, from micro-electronics thermal control to concentrated solar heat storage and vehicle thermal management, and even for chemical reactor isothermalization, the challenges facing heat storage increasingly are moving from those associated with the ‘standard’ diurnal storage, in itself a problem for low thermal conductivity materials, to response times measured in a few hours or even minutes. While high thermal conductivity metals such as foams can be impregnated with a PCM, for example, to increase local conductivity, the rapid heat input and removal necessitates a more radical approach—heat pipes, possibly with feedback control, with innovative PCM interfaces. This paper reviews the use of heat pipes in conventional and rapid response PCM and liquid or cold storage applications and introduces some novel concepts that might overcome current limitations.
    Keywords: Other low-carbon energy technologies
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 17
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    Identifying bottlenecks in charging infrastructure of plug-in hybrid electric vehicles through agent-based traffic simulation (2015)
    Oxford University Press
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    Publication Date: 2015-05-13
    Description: The effect of different charging infrastructure configurations on the electric-driven distance of plug-in hybrid electric vehicles (e-mileage) has been investigated, using an agent-based traffic simulation. Our findings suggest that the same e-mileage can be achieved with fewer charging poles if the poles support charging from several parking slots around them, and the charging cable is switched from one vehicle to the next. We also find that the charging power supported by most Finnish charging stations, 3.7 kW, and the cable switching delay of 1 h seem to be sufficient for effective workplace charging.
    Keywords: Other low-carbon energy technologies
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 18
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    Identification of RNA polymerase III-transcribed Alu loci by computational screening of RNA-Seq data (2015)
    Oxford University Press
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    Publication Date: 2015-01-24
    Description: Of the ~1.3 million Alu elements in the human genome, only a tiny number are estimated to be active in transcription by RNA polymerase (Pol) III. Tracing the individual loci from which Alu transcripts originate is complicated by their highly repetitive nature. By exploiting RNA-Seq data sets and unique Alu DNA sequences, we devised a bioinformatic pipeline allowing us to identify Pol III-dependent transcripts of individual Alu elements. When applied to ENCODE transcriptomes of seven human cell lines, this search strategy identified ~1300 Alu loci corresponding to detectable transcripts, with ~120 of them expressed in at least three cell lines. In vitro transcription of selected Alu s did not reflect their in vivo expression properties, and required the native 5'-flanking region in addition to internal promoter. We also identified a cluster of expressed Alu Ya5-derived transcription units, juxtaposed to snaR genes on chromosome 19, formed by a promoter-containing left monomer fused to an Alu -unrelated downstream moiety. Autonomous Pol III transcription was also revealed for Alu s nested within Pol II-transcribed genes. The ability to investigate Alu transcriptomes at single-locus resolution will facilitate both the identification of novel biologically relevant Alu RNAs and the assessment of Alu expression alteration under pathological conditions.
    Keywords: Computational Methods
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  • 19
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    Robust classification of protein variation using structural modelling and large-scale data integration (2016)
    Oxford University Press
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    Publication Date: 2016-04-08
    Description: Existing methods for interpreting protein variation focus on annotating mutation pathogenicity rather than detailed interpretation of variant deleteriousness and frequently use only sequence-based or structure-based information. We present VIPUR, a computational framework that seamlessly integrates sequence analysis and structural modelling (using the Rosetta protein modelling suite) to identify and interpret deleterious protein variants. To train VIPUR, we collected 9477 protein variants with known effects on protein function from multiple organisms and curated structural models for each variant from crystal structures and homology models. VIPUR can be applied to mutations in any organism's proteome with improved generalized accuracy (AUROC .83) and interpretability (AUPR .87) compared to other methods. We demonstrate that VIPUR's predictions of deleteriousness match the biological phenotypes in ClinVar and provide a clear ranking of prediction confidence. We use VIPUR to interpret known mutations associated with inflammation and diabetes, demonstrating the structural diversity of disrupted functional sites and improved interpretation of mutations associated with human diseases. Lastly, we demonstrate VIPUR's ability to highlight candidate variants associated with human diseases by applying VIPUR to de novo variants associated with autism spectrum disorders.
    Keywords: Computational Methods
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  • 20
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    Review of heat pipe heat exchangers for enhanced dehumidification and cooling in air conditioning systems (2016)
    Oxford University Press
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    Publication Date: 2016-08-26
    Description: Heat pipe heat exchangers could be employed as run-around coils in air conditioning systems for enhanced dehumidification and cooling. This article reviews some of the works conducted on the cooling and dehumidification aspects in various air conditioning systems. They have been proved to be effective in enhancing dehumidification and reducing air conditioning costs especially in hot and humid tropical countries.
    Keywords: Other low-carbon energy technologies
    Print ISSN: 1748-1317
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 21
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    Towards clean and sustainable distributed energy system: the potential of integrated PEMFC-CHP (2016)
    Oxford University Press
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    Publication Date: 2016-08-26
    Description: The mitigation options to meet the ambitious carbon reduction targets set by the UK government are discussed in this paper, including the use of carbon capture and storage (CCS) technology, clean renewable energy integration and a proposed system of integrated fuel cell combined heat and power (FC-CHP) technology. Analysis shows that the use of CCS technology within the current infrastructure can abate half the electricity-associated CO 2 emissions; however, this comes at a high cost penalty. The emissions associated with domestic heat cannot be prevented without changes in the energy infrastructure. Hydrogen-powered fuel cells can provide clean energy at a range of scales and high efficiencies, especially when employed with a CHP system. However, production of CO 2 -free hydrogen is essential for fuel cell technology to contribute substantially to a low carbon economy globally. In this work, three methods were investigated for small-scale distributed hydrogen production, namely steam methane reforming, water electrolysis (WE) and cold plasma jet (CPJ). The criteria used for comparisons include the associated CO 2 emissions and the cost of energy production. CPJ decomposition of methane shows a high potential when combined with integrated FC-CHP technology for economically viable and CO 2 -free generation of energy, especially in comparison to WE. Including the value of the solid carbon product makes the plasma system most attractive economically.
    Keywords: Other low-carbon energy technologies
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  • 22
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    Endoreversible modeling and optimization of multistage isothermal chemical engines under linear mass transfer law via Hamilton-Jacobi-Bellman theory (2016)
    Oxford University Press
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    Publication Date: 2016-08-26
    Description: A multistage continuous isothermal endoreversible chemical engine system with a finite driving fluid is investigated in this paper, and the mass transfer law obeys the linear mass transfer law [ $$g\propto \mathrm{\Delta }\mu $$ ]. Under the condition that both the initial time and the initial key component concentration in the driving fluid are fixed, the maximum power output of the multistage chemical engine system and the corresponding optimal concentration configuration of the key component in the driving fluid are derived by applying Hamilton–Jacobi–Bellman (HJB) theory, and numerical examples for three different boundary conditions are given. The results show that the difference between the chemical potential of the key component and the Carnot chemical potential for the maximum power output is a constant, and the key component concentration in the driving fluid decreases with the increase of time nonlinearly; when both the process period and the final concentration of the key component are fixed, there is an optimal control strategy for the maximum power output of the multistage chemical engine system, and the maximum power outputs of the system and the corresponding optimal control strategies are different for different final concentrations. The obtained results can provide some theoretical guidelines for the optimal designs and operations of practical energy conversion systems.
    Keywords: Other low-carbon energy technologies
    Print ISSN: 1748-1317
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    Thermodynamic analysis and optimization of the Atkinson engine by using NSGA-II (2016)
    Oxford University Press
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    Publication Date: 2016-08-26
    Description: Recently, several studies have been conducted regarding the Atkinson cycle and Atkinson engine which have resulted in various thermal efficiency and output power analysis. In the present study, output power and engine thermal efficiency are maximized via employing the NSGA-II approach and thermodynamic analysis. The multi-objective evolutionary approach on the basis of the NSGA-II method is implemented throughout this work for optimizing the above-mentioned variables. To evaluate the aforementioned goal, two objective functions which comprises the power output ( W ) and cycle efficiency ( ) have been included in the optimization process simultaneously.
    Keywords: Other low-carbon energy technologies
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    High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder (2015)
    Oxford University Press
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    Publication Date: 2015-10-15
    Description: Intrinsically disordered proteins and regions (IDPs and IDRs) lack stable 3D structure under physiological conditions in-vitro , are common in eukaryotes, and facilitate interactions with RNA, DNA and proteins. Current methods for prediction of IDPs and IDRs do not provide insights into their functions, except for a handful of methods that address predictions of protein-binding regions. We report first-of-its-kind computational method DisoRDPbind for high-throughput prediction of RNA, DNA and protein binding residues located in IDRs from protein sequences. DisoRDPbind is implemented using a runtime-efficient multi-layered design that utilizes information extracted from physiochemical properties of amino acids, sequence complexity, putative secondary structure and disorder and sequence alignment. Empirical tests demonstrate that it provides accurate predictions that are competitive with other predictors of disorder-mediated protein binding regions and complementary to the methods that predict RNA- and DNA-binding residues annotated based on crystal structures. Application in Homo sapiens, Mus musculus, Caenorhabditis elegans and Drosophila melanogaster proteomes reveals that RNA- and DNA-binding proteins predicted by DisoRDPbind complement and overlap with the corresponding known binding proteins collected from several sources. Also, the number of the putative protein-binding regions predicted with DisoRDPbind correlates with the promiscuity of proteins in the corresponding protein–protein interaction networks. Webserver: http://biomine.ece.ualberta.ca/DisoRDPbind/
    Keywords: Computational Methods
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    NetDecoder: a network biology platform that decodes context-specific biological networks and gene activities (2016)
    Oxford University Press
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    Publication Date: 2016-06-03
    Description: The sequential chain of interactions altering the binary state of a biomolecule represents the ‘information flow’ within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein–protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes—network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code ( http://www.NetDecoder.org ) for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets.
    Keywords: Computational Methods
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    limma powers differential expression analyses for RNA-sequencing and microarray studies (2015)
    Oxford University Press
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    Publication Date: 2015-04-21
    Description: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
    Keywords: Computational Methods
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    GRASP: Guided Reference-based Assembly of Short Peptides (2015)
    Oxford University Press
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    Publication Date: 2015-02-18
    Description: Protein sequences predicted from metagenomic datasets are annotated by identifying their homologs via sequence comparisons with reference or curated proteins. However, a majority of metagenomic protein sequences are partial-length, arising as a result of identifying genes on sequencing reads or on assembled nucleotide contigs, which themselves are often very fragmented. The fragmented nature of metagenomic protein predictions adversely impacts homology detection and, therefore, the quality of the overall annotation of the dataset. Here we present a novel algorithm called GRASP that accurately identifies the homologs of a given reference protein sequence from a database consisting of partial-length metagenomic proteins. Our homology detection strategy is guided by the reference sequence, and involves the simultaneous search and assembly of overlapping database sequences. GRASP was compared to three commonly used protein sequence search programs (BLASTP, PSI-BLAST and FASTM). Our evaluations using several simulated and real datasets show that GRASP has a significantly higher sensitivity than these programs while maintaining a very high specificity. GRASP can be a very useful program for detecting and quantifying taxonomic and protein family abundances in metagenomic datasets. GRASP is implemented in GNU C++, and is freely available at http://sourceforge.net/projects/grasp-release .
    Keywords: Computational Methods
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    HiTSelect: a comprehensive tool for high-complexity-pooled screen analysis (2015)
    Oxford University Press
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    Publication Date: 2015-02-18
    Description: Genetic screens of an unprecedented scale have recently been made possible by the availability of high-complexity libraries of synthetic oligonucleotides designed to mediate either gene knockdown or gene knockout, coupled with next-generation sequencing. However, several sources of random noise and statistical biases complicate the interpretation of the resulting high-throughput data. We developed HiTSelect, a comprehensive analysis pipeline for rigorously selecting screen hits and identifying functionally relevant genes and pathways by addressing off-target effects, controlling for variance in both gene silencing efficiency and sequencing depth of coverage and integrating relevant metadata. We document the superior performance of HiTSelect using data from both genome-wide RNAi and CRISPR/Cas9 screens. HiTSelect is implemented as an open-source package, with a user-friendly interface for data visualization and pathway exploration. Binary executables are available at http://sourceforge.net/projects/hitselect/ , and the source code is available at https://github.com/diazlab/HiTSelect .
    Keywords: Computational Methods
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    Epidaurus: aggregation and integration analysis of prostate cancer epigenome (2015)
    Oxford University Press
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    Publication Date: 2015-01-24
    Description: Integrative analyses of epigenetic data promise a deeper understanding of the epigenome. Epidaurus is a bioinformatics tool used to effectively reveal inter-dataset relevance and differences through data aggregation, integration and visualization. In this study, we demonstrated the utility of Epidaurus in validating hypotheses and generating novel biological insights. In particular, we described the use of Epidaurus to (i) integrate epigenetic data from prostate cancer cell lines to validate the activation function of EZH2 in castration-resistant prostate cancer and to (ii) study the mechanism of androgen receptor ( AR ) binding deregulation induced by the knockdown of FOXA1 . We found that EZH2 's noncanonical activation function was reaffirmed by its association with active histone markers and the lack of association with repressive markers. More importantly, we revealed that the binding of AR was selectively reprogramed to promoter regions, leading to the up-regulation of hundreds of cancer-associated genes including EGFR . The prebuilt epigenetic dataset from commonly used cell lines (LNCaP, VCaP, LNCaP-Abl, MCF7, GM12878, K562, HeLa-S3, A549, HePG2) makes Epidaurus a useful online resource for epigenetic research. As standalone software, Epidaurus is specifically designed to process user customized datasets with both efficiency and convenience.
    Keywords: Computational Methods
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    Mitigation countermeasures to face urban warming (2015)
    Oxford University Press
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    Publication Date: 2015-02-12
    Keywords: Other low-carbon energy technologies
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    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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    RPI-Pred: predicting ncRNA-protein interaction using sequence and structural information (2015)
    Oxford University Press
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    Publication Date: 2015-02-18
    Description: RNA-protein complexes are essential in mediating important fundamental cellular processes, such as transport and localization. In particular, ncRNA-protein interactions play an important role in post-transcriptional gene regulation like mRNA localization, mRNA stabilization, poly-adenylation, splicing and translation. The experimental methods to solve RNA-protein interaction prediction problem remain expensive and time-consuming. Here, we present the RPI-Pred (RNA-protein interaction predictor), a new support-vector machine-based method, to predict protein-RNA interaction pairs, based on both the sequences and structures. The results show that RPI-Pred can correctly predict RNA-protein interaction pairs with ~94% prediction accuracy when using sequence and experimentally determined protein and RNA structures, and with ~83% when using sequences and predicted protein and RNA structures. Further, our proposed method RPI-Pred was superior to other existing ones by predicting more experimentally validated ncRNA-protein interaction pairs from different organisms. Motivated by the improved performance of RPI-Pred, we further applied our method for reliable construction of ncRNA-protein interaction networks. The RPI-Pred is publicly available at: http://ctsb.is.wfubmc.edu/projects/rpi-pred .
    Keywords: Computational Methods
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    ModuleBlast: identifying activated sub-networks within and across species (2015)
    Oxford University Press
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    Publication Date: 2015-02-18
    Description: Identifying conserved and divergent response patterns in gene networks is becoming increasingly important. A common approach is integrating expression information with gene association networks in order to find groups of connected genes that are activated or repressed. In many cases, researchers are also interested in comparisons across species (or conditions). Finding an active sub-network is a hard problem and applying it across species requires further considerations (e.g. orthology information, expression data and networks from different sources). To address these challenges we devised ModuleBlast, which uses both expression and network topology to search for highly relevant sub-networks. We have applied ModuleBlast to expression and interaction data from mouse, macaque and human to study immune response and aging. The immune response analysis identified several relevant modules, consistent with recent findings on apoptosis and NFB activation following infection. Temporal analysis of these data revealed cascades of modules that are dynamically activated within and across species. We have experimentally validated some of the novel hypotheses resulting from the analysis of the ModuleBlast results leading to new insights into the mechanisms used by a key mammalian aging protein.
    Keywords: Computational Methods
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    Enhancer modeling uncovers transcriptional signatures of individual cardiac cell states in Drosophila (2015)
    Oxford University Press
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    Publication Date: 2015-02-18
    Description: Here we used discriminative training methods to uncover the chromatin, transcription factor (TF) binding and sequence features of enhancers underlying gene expression in individual cardiac cells. We used machine learning with TF motifs and ChIP data for a core set of cardiogenic TFs and histone modifications to classify Drosophila cell-type-specific cardiac enhancer activity. We show that the classifier models can be used to predict cardiac cell subtype cis -regulatory activities. Associating the predicted enhancers with an expression atlas of cardiac genes further uncovered clusters of genes with transcription and function limited to individual cardiac cell subtypes. Further, the cell-specific enhancer models revealed chromatin, TF binding and sequence features that distinguish enhancer activities in distinct subsets of heart cells. Collectively, our results show that computational modeling combined with empirical testing provides a powerful platform to uncover the enhancers, TF motifs and gene expression profiles which characterize individual cardiac cell fates.
    Keywords: Computational Methods
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    Optimizing RNA structures by sequence extensions using RNAcop (2015)
    Oxford University Press
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    Publication Date: 2015-09-30
    Description: A key aspect of RNA secondary structure prediction is the identification of novel functional elements. This is a challenging task because these elements typically are embedded in longer transcripts where the borders between the element and flanking regions have to be defined. The flanking sequences impact the folding of the functional elements both at the level of computational analyses and when the element is extracted as a transcript for experimental analysis. Here, we analyze how different flanking region lengths impact folding into a constrained structure by computing probabilities of folding for different sizes of flanking regions. Our method, RNAcop (RNA context optimization by probability), is tested on known and de novo predicted structures. In vitro experiments support the computational analysis and suggest that for a number of structures, choosing proper lengths of flanking regions is critical. RNAcop is available as web server and stand-alone software via http://rth.dk/resources/rnacop .
    Keywords: Computational Methods
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    Control of micro-CHP and thermal energy storage for minimising electrical grid utilisation (2016)
    Oxford University Press
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    Publication Date: 2016-02-05
    Description: The efficient use of combined heat and power (CHP) systems in buildings presents a control challenge due to their simultaneous production of thermal and electrical energy. The use of thermal energy storage coupled with a CHP engine provides an interesting solution to the problem—the electrical demands of the building can be matched by the CHP engine, while the resulting thermal energy can be regulated by the thermal energy store. Based on the thermal energy demands of the building the thermal store can provide extra thermal energy or absorb surplus thermal energy production. This paper presents a multi-input multi-output inverse-dynamics-based control strategy that will minimise the electrical grid utilisation of a building, while simultaneously maintaining a defined operative temperature. Electrical demands from lighting and appliances within the building are considered. In order to assess the performance of the control strategy, a European Standard validated simplified dynamic building physics model is presented that provides verified heating demands. Internal heat gains from solar radiation and internal loads are included within the model. Results indicate the control strategy is effective in minimising the electrical grid use and maximising the utilisation of the available energy when compared with conventional heating systems.
    Keywords: Other low-carbon energy technologies
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    Thermodynamic optimization of a triple-shaft open intercooled, recuperated gas turbine cycle. Part 2: power and efficiency optimization (2016)
    Oxford University Press
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    Publication Date: 2016-02-05
    Description: The power and the efficiency of a triple-shaft open intercooled, recuperated gas turbine cycle are analyzed and optimized based on the model established using thermodynamic optimization theory in Part 1 of this paper by adjusting the low-pressure compressor inlet relative pressure drop, the mass flow rate and the distribution of pressure losses along the flow path. First, the power output is optimized by adjusting the intercooling pressure ratio, the air mass flow rate or the distribution of pressure losses along the flow path. Second, the thermodynamic first-law efficiency is optimized subject to a fixed fuel flow rate and a fixed overall size by seeking the optimal intercooling pressure ratio, the compressor inlet pressure drop and optimal flow area allocation ratio between the low-pressure compressor inlet and the power turbine outlet. The numerical examples show that increase in effectiveness of intercooler increases power output and its corresponding efficiency and increase in effectiveness of recuperator decreases power output appreciably but increases its corresponding efficiency; there exist an optimal low-pressure compressor inlet relative pressure drop and an optimal intercooling pressure ratio, which lead to a maximum power. For a fixed fuel mass rate and a fixed overall area of low-pressure compressor inlet and power turbine outlet, maximum thermodynamic first-law efficiency is obtained by optimizing low-pressure compressor inlet relative pressure drop and intercooling pressure ratio. The double-maximum thermodynamic first-law efficiency is obtained by searching optimal flow area allocation between low-pressure compressor inlet and power turbine outlet.
    Keywords: Other low-carbon energy technologies
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    Transient simulation of a solar absorption cooling system (2016)
    Oxford University Press
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    Publication Date: 2016-02-05
    Description: With non-renewable energy sources depleting quickly, solar energy could prove a viable option owing to its abundance and eco-friendliness. Modeling and simulation of a solar energy-driven single-stage absorption chiller was carried out using the transient simulation software ‘TRNSYS’. An evacuated tube collector coupled with an insulated tank served as heat source for the absorption chiller. Experiments were conducted to evaluate the efficiency parameters of the collector as well as the loss coefficient for the storage tank. These parameters along with standard chiller performance data were used to model the system. The influence of climatic conditions, storage capacity and various control schemes with and without auxiliary heating on the output of the system is analyzed and presented in the paper.
    Keywords: Other low-carbon energy technologies
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    Thermochemical cooling system based on adsorption pumping pipe (2016)
    Oxford University Press
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    Publication Date: 2016-02-05
    Description: Based upon the theoretical principle of the thermochemical energy storage pumping pipe system, a new cooling system has been presented. In order to analyse the performance and design of the system based on adsorption pumping pipe process, a simplified mathematical model is developed. Both simulation and experimental results are given and discussed. The comparison of various methods (ammonium dissolves, evaporation of CO 2 , etc.) showed that it is the simplest and most reliable to use adsorbents such as zeolite in this cooling system. A total of 250 g zeolite 13X could reduce the temperature of 330 ml by 15°C in 2–3 min (for beverage self-cooling applications). For future work, a large scale demonstration system is required to prove the viability and long term performance of thermochemical cooling/energy storage system.
    Keywords: Other low-carbon energy technologies
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    Thermodynamic optimization of a triple-shaft open intercooled-recuperated gas turbine cycle. Part 1: description and modeling (2016)
    Oxford University Press
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    Publication Date: 2016-02-05
    Description: Considering the flow processes of the working fluid with the pressure drops, a thermodynamic model for a triple-shaft open intercooled-recuperated gas turbine cycle is established using thermodynamic optimization theory in Part 1 of this paper. The relative pressure drops associated with the flow through various cross-sectional areas are derived as functions of the low-pressure compressor inlet relative pressure drop. The analytical formulae of the cycle's power and efficiency are derived. The performance of the model cycle is optimized by adjusting the compressor inlet pressure, the mass flow rate and the distribution of pressure losses along the flow path in Part 2 of this paper.
    Keywords: Other low-carbon energy technologies
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    Theoretical estimates of exposure timescales of protein binding sites on DNA regulated by nucleosome kinetics (2016)
    Oxford University Press
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    Publication Date: 2016-03-01
    Description: It is being increasingly realized that nucleosome organization on DNA crucially regulates DNA–protein interactions and the resulting gene expression. While the spatial character of the nucleosome positioning on DNA has been experimentally and theoretically studied extensively, the temporal character is poorly understood. Accounting for ATPase activity and DNA-sequence effects on nucleosome kinetics, we develop a theoretical method to estimate the time of continuous exposure of binding sites of non-histone proteins (e.g. transcription factors and TATA binding proteins) along any genome. Applying the method to Saccharomyces cerevisiae , we show that the exposure timescales are determined by cooperative dynamics of multiple nucleosomes, and their behavior is often different from expectations based on static nucleosome occupancy. Examining exposure times in the promoters of GAL1 and PHO5, we show that our theoretical predictions are consistent with known experiments. We apply our method genome-wide and discover huge gene-to-gene variability of mean exposure times of TATA boxes and patches adjacent to TSS (+1 nucleosome region); the resulting timescale distributions have non-exponential tails.
    Keywords: Computational Methods
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    BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling (2015)
    Oxford University Press
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    Publication Date: 2015-10-31
    Description: Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx .
    Keywords: Computational Methods
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    Analysis of a SrCl2-NH3 solid sorption refrigeration system (2015)
    Oxford University Press
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    Publication Date: 2015-11-07
    Description: The performance of a solid sorption refrigeration system that uses SrCl 2 and NH 3 as the working pair is analysed based on the heat and mass transfer aspects of the solid sorbent reactors (absorber/generator). The transient, heat and mass transfer model duly considers the effects of reactor wall mass and contact conductance between the reactor wall and the bed. A decent comparison is obtained between the theoretical results and published experimental results on a reactor. The complete system consisting of two absorber/generators, condenser, expansion valve and evaporator is then analysed using the heat and mass transfer model of the reactors. Results are obtained in terms of the coefficient of performance (COP) and specific cooling power (SCP). Results show the possibility of optimizing the bed and operating parameters so as to obtain high COP and/or SCP. The bed thickness, sink temperature and the global reaction advancement are found to affect the performance of the system significantly.
    Keywords: Other low-carbon energy technologies
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    Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction (2015)
    Oxford University Press
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    Publication Date: 2015-12-02
    Description: Despite the biological importance of non-coding RNA, their structural characterization remains challenging. Making use of the rapidly growing sequence databases, we analyze nucleotide coevolution across homologous sequences via Direct-Coupling Analysis to detect nucleotide-nucleotide contacts. For a representative set of riboswitches, we show that the results of Direct-Coupling Analysis in combination with a generalized Nussinov algorithm systematically improve the results of RNA secondary structure prediction beyond traditional covariance approaches based on mutual information. Even more importantly, we show that the results of Direct-Coupling Analysis are enriched in tertiary structure contacts. By integrating these predictions into molecular modeling tools, systematically improved tertiary structure predictions can be obtained, as compared to using secondary structure information alone.
    Keywords: Computational Methods
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    BayesPI-BAR: a new biophysical model for characterization of regulatory sequence variations (2015)
    Oxford University Press
    Details
    Publication Date: 2015-12-02
    Description: Sequence variations in regulatory DNA regions are known to cause functionally important consequences for gene expression. DNA sequence variations may have an essential role in determining phenotypes and may be linked to disease; however, their identification through analysis of massive genome-wide sequencing data is a great challenge. In this work, a new computational pipeline, a Bayesian method for protein–DNA interaction with binding affinity ranking (BayesPI-BAR), is proposed for quantifying the effect of sequence variations on protein binding. BayesPI-BAR uses biophysical modeling of protein–DNA interactions to predict single nucleotide polymorphisms (SNPs) that cause significant changes in the binding affinity of a regulatory region for transcription factors (TFs). The method includes two new parameters (TF chemical potentials or protein concentrations and direct TF binding targets) that are neglected by previous methods. The new method is verified on 67 known human regulatory SNPs, of which 47 (70%) have predicted true TFs ranked in the top 10. Importantly, the performance of BayesPI-BAR, which uses principal component analysis to integrate multiple predictions from various TF chemical potentials, is found to be better than that of existing programs, such as sTRAP and is-rSNP, when evaluated on the same SNPs. BayesPI-BAR is a publicly available tool and is able to carry out parallelized computation, which helps to investigate a large number of TFs or SNPs and to detect disease-associated regulatory sequence variations in the sea of genome-wide noncoding regions.
    Keywords: Computational Methods
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    Power and power density analyzes of an endoreversible modified variable-temperature reservoir Brayton cycle with isothermal heat addition (2016)
    Oxford University Press
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    Publication Date: 2016-02-05
    Description: The mistakes in recent literatures are analyzed, and a new model for an endoreversible closed modified Brayton cycle with isothermal heat addition coupled to variable-temperature reservoirs is established using finite-time thermodynamics in this paper. The range of isothermal heat addition modification is determined, and the analytical formulae of the dimensionless power output, thermal efficiency and dimensionless power density of the cycle are derived. The effects of the cycle parameters on the global performances of power output and power density and the performances at maximum power design and maximum power density are analyzed by numerical calculations. The results show that there exist optimal compressor pressure ratios, respectively, which lead to maximum dimensionless power output and maximum dimensionless power density, that the optimal compressor pressure ratio and the thermal efficiency at maximum power design are always smaller than the corresponding ones at maximum power density design, and that dimensionless power output and maximum specific volume at maximum power design are always bigger than the corresponding ones at maximum power density design. The results imply that the power density design possesses the advantages such as smaller equipment volume and higher thermal efficiency at the cost of disadvantages such as bigger compressor pressure ratio and power output loss. Maximizing the power density gives a compromise between power and the size of the engine. The calculations also show that an endoreversible closed modified Brayton cycle with isothermal heat addition cannot work at the maximum thermal efficiency design point.
    Keywords: Other low-carbon energy technologies
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    Computational and molecular tools for scalable rAAV-mediated genome editing (2015)
    Oxford University Press
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    Publication Date: 2015-03-14
    Description: The rapid discovery of potential driver mutations through large-scale mutational analyses of human cancers generates a need to characterize their cellular phenotypes. Among the techniques for genome editing, recombinant adeno-associated virus (rAAV)-mediated gene targeting is suited for knock-in of single nucleotide substitutions and to a lesser degree for gene knock-outs. However, the generation of gene targeting constructs and the targeting process is time-consuming and labor-intense. To facilitate rAAV-mediated gene targeting, we developed the first software and complementary automation-friendly vector tools to generate optimized targeting constructs for editing human protein encoding genes. By computational approaches, rAAV constructs for editing ~71% of bases in protein-coding exons were designed. Similarly, ~81% of genes were predicted to be targetable by rAAV-mediated knock-out. A Gateway-based cloning system for facile generation of rAAV constructs suitable for robotic automation was developed and used in successful generation of targeting constructs. Together, these tools enable automated rAAV targeting construct design, generation as well as enrichment and expansion of targeted cells with desired integrations.
    Keywords: Computational Methods
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    SwiftLib: rapid degenerate-codon-library optimization through dynamic programming (2015)
    Oxford University Press
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    Publication Date: 2015-03-14
    Description: Degenerate codon (DC) libraries efficiently address the experimental library-size limitations of directed evolution by focusing diversity toward the positions and toward the amino acids (AAs) that are most likely to generate hits; however, manually constructing DC libraries is challenging, error prone and time consuming. This paper provides a dynamic programming solution to the task of finding the best DCs while keeping the size of the library beneath some given limit, improving on the existing integer-linear programming formulation. It then extends the algorithm to consider multiple DCs at each position, a heretofore unsolved problem, while adhering to a constraint on the number of primers needed to synthesize the library. In the two library-design problems examined here, the use of multiple DCs produces libraries that very nearly cover the set of desired AAs while still staying within the experimental size limits. Surprisingly, the algorithm is able to find near-perfect libraries where the ratio of amino-acid sequences to nucleic-acid sequences approaches 1; it effectively side-steps the degeneracy of the genetic code. Our algorithm is freely available through our web server and solves most design problems in about a second.
    Keywords: Computational Methods
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    DEEP: a general computational framework for predicting enhancers (2015)
    Oxford University Press
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    Publication Date: 2015-01-10
    Description: Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer's properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo -derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/ .
    Keywords: Computational Methods
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    Systematic identification and correction of annotation errors in the genetic interaction map of Saccharomyces cerevisiae (2016)
    Oxford University Press
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    Publication Date: 2016-03-19
    Description: The yeast mutant collections are a fundamental tool in deciphering genomic organization and function. Over the last decade, they have been used for the systematic exploration of ~6 000 000 double gene mutants, identifying and cataloging genetic interactions among them. Here we studied the extent to which these data are prone to neighboring gene effects (NGEs), a phenomenon by which the deletion of a gene affects the expression of adjacent genes along the genome. Analyzing ~90,000 negative genetic interactions observed to date, we found that more than 10% of them are incorrectly annotated due to NGEs. We developed a novel algorithm, GINGER, to identify and correct erroneous interaction annotations. We validated the algorithm using a comparative analysis of interactions from Schizosaccharomyces pombe . We further showed that our predictions are significantly more concordant with diverse biological data compared to their mis-annotated counterparts. Our work uncovered about 9500 new genetic interactions in yeast.
    Keywords: Computational Methods
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    PON-mt-tRNA: a multifactorial probability-based method for classification of mitochondrial tRNA variations (2016)
    Oxford University Press
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    Publication Date: 2016-03-19
    Description: Transfer RNAs (tRNAs) are essential for encoding the transcribed genetic information from DNA into proteins. Variations in the human tRNAs are involved in diverse clinical phenotypes. Interestingly, all pathogenic variations in tRNAs are located in mitochondrial tRNAs (mt-tRNAs). Therefore, it is crucial to identify pathogenic variations in mt-tRNAs for disease diagnosis and proper treatment. We collected mt-tRNA variations using a classification based on evidence from several sources and used the data to develop a multifactorial probability-based prediction method, PON-mt-tRNA, for classification of mt-tRNA single nucleotide substitutions. We integrated a machine learning-based predictor and an evidence-based likelihood ratio for pathogenicity using evidence of segregation, biochemistry and histochemistry to predict the posterior probability of pathogenicity of variants. The accuracy and Matthews correlation coefficient (MCC) of PON-mt-tRNA are 1.00 and 0.99, respectively. In the absence of evidence from segregation, biochemistry and histochemistry, PON-mt-tRNA classifies variations based on the machine learning method with an accuracy and MCC of 0.69 and 0.39, respectively. We classified all possible single nucleotide substitutions in all human mt-tRNAs using PON-mt-tRNA. The variations in the loops are more often tolerated compared to the variations in stems. The anticodon loop contains comparatively more predicted pathogenic variations than the other loops. PON-mt-tRNA is available at http://structure.bmc.lu.se/PON-mt-tRNA/ .
    Keywords: Computational Methods
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    ALVIS: interactive non-aggregative visualization and explorative analysis of multiple sequence alignments (2016)
    Oxford University Press
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    Publication Date: 2016-05-06
    Description: Sequence Logos and its variants are the most commonly used method for visualization of multiple sequence alignments (MSAs) and sequence motifs. They provide consensus-based summaries of the sequences in the alignment. Consequently, individual sequences cannot be identified in the visualization and covariant sites are not easily discernible. We recently proposed Sequence Bundles , a motif visualization technique that maintains a one-to-one relationship between sequences and their graphical representation and visualizes covariant sites. We here present Alvis, an open-source platform for the joint explorative analysis of MSAs and phylogenetic trees, employing Sequence Bundles as its main visualization method. Alvis combines the power of the visualization method with an interactive toolkit allowing detection of covariant sites, annotation of trees with synapomorphies and homoplasies, and motif detection. It also offers numerical analysis functionality, such as dimension reduction and classification. Alvis is user-friendly, highly customizable and can export results in publication-quality figures. It is available as a full-featured standalone version ( http://www.bitbucket.org/rfs/alvis ) and its Sequence Bundles visualization module is further available as a web application ( http://science-practice.com/projects/sequence-bundles ).
    Keywords: Computational Methods
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    Effects of thermocouples physical size on the performance of the TEG-TEH system (2016)
    Oxford University Press
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    Publication Date: 2016-08-26
    Description: The effects of thermocouples physical size on the performance of a thermoelectric heat pump (TEH) driven by a thermoelectric generator (TEG) device are investigated in this article. The physical size refers to the length and the cross-sectional area of the thermocouples. The performance analysis is multiobjective, including stable electrical current, heating load, coefficient of performance, maximum heating load and maximum heating temperature difference. A characteristic parameter, i.e. area–length ratio, is defined to describe the thermocouples physical size. The influences of the parameter are analyzed by detailed numerical examples. A practical example is proposed to show how to select appropriate thermoelectric modules (TEMs) to construct a high-performance TEG–TEH system satisfying different requirements. The results show that an improvement in its performance is possible by optimizing internal physical size of thermocouples. The conclusion obtained could be used for the selection of TEMs and the design of the TEG–TEH system.
    Keywords: Other low-carbon energy technologies
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    Effect of the working liquid to the capillary pumped loop performance (2016)
    Oxford University Press
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    Publication Date: 2016-08-26
    Description: The purpose of this paper is to present a theoretical analysis of the capillary pumped loop (CPL) performance using different working liquids. CPL is a passive heat transfer device, using no mechanical pump to circulate the working liquid, usually composed of a liquid tank, an evaporator, a condenser, a liquid and a vapor line. Heat load is applied on the external surface of the evaporator, partially transferred to the wick inside. Because of this heat load capillary forces are developed inside the porous structure, due to meniscus formation between liquid and vapor surface of the liquid, causing a pressure oscillation capable to pump the flow out of the evaporator. In this paper CPL performance is evaluated using different working liquids, such as water, ammonia, acetone and freon-134. These have different thermophysical properties such as latent heat, viscosity and density, causing different behavior when used as working liquid. Water was found more stable for higher temperature differences, due to higher latent heat of vaporization, while ammonia could take advantage of its viscosity for small temperature differences.
    Keywords: Other low-carbon energy technologies
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    Design and optimization of a thermoacoustic heat engine using reinforcement learning (2016)
    Oxford University Press
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    Publication Date: 2016-08-26
    Description: The thermoacoustic heat engine (TAHE) is a type of prime mover that converts thermal power to acoustic power. It is composed of two heat exchangers (the devices heat source and sink), some kind of porous medium where the conversion of power takes place and a tube that houses the acoustic wave produced. Its simple design and the fact that it is one of a few prime movers that do not require moving parts make such a device an attractive alternative for many practical applications. The acoustic power produced by the TAHE can be used to generate electricity, drive a heat pump or a refrigeration system. Although the geometry of the TAHE is simple, the behavior of the engine is complex with 30+ design parameters that affect the performance of the device; therefore, designing such a device remains a significant challenge. In this work, a radical design methodology using reinforcement learning (RL) is employed for the design and optimization of a TAHE for the first time. Reinforcement learning is a machine learning technique that allows optimization by specifying ‘good’ and ‘bad’ behavior using a simple reward scheme r . Although its framework is simple, it has proved to be a very powerful tool in solving a wide range of complex decision-making/optimization problems. The RL technique employed by the agent in this work is known as Q-learning. Preliminary results have shown the potential of the RL technique to solve this type of complex design problem, as the RL agent was able to figure out the correct configuration of components that would create positive acoustic power output. The learning agent was able to create a design that yielded an acoustic power output of 643.31 W with a thermal efficiency of 3.29%. It is eventually hoped that with increased understanding of the design problem, in terms of the RL framework, it will be possible to ultimately create an autonomous RL agent for the design and optimization of complex TAHEs with minimal predefined conditions/restrictions.
    Keywords: Other low-carbon energy technologies
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    A novel method for the identification of conserved structural patterns in RNA: From small scale to high-throughput applications (2016)
    Oxford University Press
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    Publication Date: 2016-10-14
    Description: Functional RNA regions are often related to recurrent secondary structure patterns (or motifs), which can exert their role in several different ways, particularly in dictating the interaction with RNA-binding proteins, and acting in the regulation of a large number of cellular processes. Among the available motif-finding tools, the majority focuses on sequence patterns, sometimes including secondary structure as additional constraints to improve their performance. Nonetheless, secondary structures motifs may be concurrent to their sequence counterparts or even encode a stronger functional signal. Current methods for searching structural motifs generally require long pipelines and/or high computational efforts or previously aligned sequences. Here, we present BEAM (BEAr Motif finder), a novel method for structural motif discovery from a set of unaligned RNAs, taking advantage of a recently developed encoding for RNA secondary structure named BEAR (Brand nEw Alphabet for RNAs) and of evolutionary substitution rates of secondary structure elements. Tested in a varied set of scenarios, from small- to large-scale, BEAM is successful in retrieving structural motifs even in highly noisy data sets, such as those that can arise in CLIP-Seq or other high-throughput experiments.
    Keywords: Computational Methods
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    Function-driven discovery of disease genes in zebrafish using an integrated genomics big data resource (2016)
    Oxford University Press
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    Publication Date: 2016-12-01
    Description: Whole exome sequencing (WES) accelerates disease gene discovery using rare genetic variants, but further statistical and functional evidence is required to avoid false-discovery. To complement variant-driven disease gene discovery, here we present function-driven disease gene discovery in zebrafish ( Danio rerio ), a promising human disease model owing to its high anatomical and genomic similarity to humans. To facilitate zebrafish-based function-driven disease gene discovery, we developed a genome-scale co-functional network of zebrafish genes, DanioNet ( www.inetbio.org/danionet ), which was constructed by Bayesian integration of genomics big data. Rigorous statistical assessment confirmed the high prediction capacity of DanioNet for a wide variety of human diseases. To demonstrate the feasibility of the function-driven disease gene discovery using DanioNet, we predicted genes for ciliopathies and performed experimental validation for eight candidate genes. We also validated the existence of heterozygous rare variants in the candidate genes of individuals with ciliopathies yet not in controls derived from the UK10K consortium, suggesting that these variants are potentially involved in enhancing the risk of ciliopathies. These results showed that an integrated genomics big data for a model animal of diseases can expand our opportunity for harnessing WES data in disease gene discovery.
    Keywords: Computational Methods
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    Localized structural frustration for evaluating the impact of sequence variants (2016)
    Oxford University Press
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    Publication Date: 2016-12-04
    Description: Population-scale sequencing is increasingly uncovering large numbers of rare single-nucleotide variants (SNVs) in coding regions of the genome. The rarity of these variants makes it challenging to evaluate their deleteriousness with conventional phenotype–genotype associations. Protein structures provide a way of addressing this challenge. Previous efforts have focused on globally quantifying the impact of SNVs on protein stability. However, local perturbations may severely impact protein functionality without strongly disrupting global stability (e.g. in relation to catalysis or allostery). Here, we describe a workflow in which localized frustration, quantifying unfavorable local interactions, is employed as a metric to investigate such effects. Using this workflow on the Protein Databank, we find that frustration produces many immediately intuitive results: for instance, disease-related SNVs create stronger changes in localized frustration than non-disease related variants, and rare SNVs tend to disrupt local interactions to a larger extent than common variants. Less obviously, we observe that somatic SNVs associated with oncogenes and tumor suppressor genes (TSGs) induce very different changes in frustration. In particular, those associated with TSGs change the frustration more in the core than the surface (by introducing loss-of-function events), whereas those associated with oncogenes manifest the opposite pattern, creating gain-of-function events.
    Keywords: Computational Methods
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    Personalized characterization of diseases using sample-specific networks (2016)
    Oxford University Press
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    Publication Date: 2016-12-17
    Description: A complex disease generally results not from malfunction of individual molecules but from dysfunction of the relevant system or network, which dynamically changes with time and conditions. Thus, estimating a condition-specific network from a single sample is crucial to elucidating the molecular mechanisms of complex diseases at the system level. However, there is currently no effective way to construct such an individual-specific network by expression profiling of a single sample because of the requirement of multiple samples for computing correlations. We developed here with a statistical method, i.e. a sample-specific network (SSN) method, which allows us to construct individual-specific networks based on molecular expressions of a single sample. Using this method, we can characterize various human diseases at a network level. In particular, such SSNs can lead to the identification of individual-specific disease modules as well as driver genes, even without gene sequencing information. Extensive analysis by using the Cancer Genome Atlas data not only demonstrated the effectiveness of the method, but also found new individual-specific driver genes and network patterns for various types of cancer. Biological experiments on drug resistance further validated one important advantage of our method over the traditional methods, i.e. we can even identify such drug resistance genes that actually have no clear differential expression between samples with and without the resistance, due to the additional network information.
    Keywords: Computational Methods
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    Order restricted inference for oscillatory systems for detecting rhythmic signals (2016)
    Oxford University Press
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    Publication Date: 2016-12-17
    Description: Motivation: Many biological processes, such as cell cycle, circadian clock, menstrual cycles, are governed by oscillatory systems consisting of numerous components that exhibit rhythmic patterns over time. It is not always easy to identify such rhythmic components. For example, it is a challenging problem to identify circadian genes in a given tissue using time-course gene expression data. There is a great potential for misclassifying non-rhythmic as rhythmic genes and vice versa. This has been a problem of considerable interest in recent years. In this article we develop a constrained inference based methodology called Order Restricted Inference for Oscillatory Systems (ORIOS) to detect rhythmic signals. Instead of using mathematical functions (e.g. sinusoidal) to describe shape of rhythmic signals, ORIOS uses mathematical inequalities. Consequently, it is robust and not limited by the biologist's choice of the mathematical model. We studied the performance of ORIOS using simulated as well as real data obtained from mouse liver, pituitary gland and data from NIH3T3, U2OS cell lines. Our results suggest that, for a broad collection of patterns of gene expression, ORIOS has substantially higher power to detect true rhythmic genes in comparison to some popular methods, while also declaring substantially fewer non-rhythmic genes as rhythmic. Availability and Implementation: A user friendly code implemented in R language can be downloaded from http://www.niehs.nih.gov/research/atniehs/labs/bb/staff/peddada/index.cfm . Contact: peddada@niehs.nih.gov
    Keywords: Computational Methods
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    Experimental analysis of an unconventional desiccant-based air-conditioning system: the influence of cooling air flow and chiller on the energy and environmental performance (2015)
    Oxford University Press
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    Publication Date: 2015-11-07
    Description: Nowadays, the increasing demand of summer cooling is typically covered by electric chillers, often determining electric peak loads and black-outs. Thus, a wide interest is spreading in small scale natural gas-fired cogenerators driving desiccant-based air-conditioning systems, which represent interesting alternatives to conventional systems based on vapor compression cooling only. In this article, experimental tests performed on an air handling unit (AHU) equipped with a desiccant wheel (DW), coupled to a small scale cogenerator and an electric chiller are described. A new layout of the desiccant-based AHU is investigated, considering a third flow (the cooling air), besides the process air flow and the regeneration one. A cross-flow heat exchanger between process air and cooling air is used; the cooling air, cooled by an adiabatic humidifier, is aimed to precool the process air exiting the DW. The relevant influence of the heat exchanger and of the humidifier, as well as that of the chiller performance, on global primary energy requirements, water consumption and CO 2 equivalent emissions of the system is experimentally evaluated.
    Keywords: Other low-carbon energy technologies
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    Genomes to natural products PRediction Informatics for Secondary Metabolomes (PRISM) (2015)
    Oxford University Press
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    Publication Date: 2015-11-17
    Description: Microbial natural products are an invaluable source of evolved bioactive small molecules and pharmaceutical agents. Next-generation and metagenomic sequencing indicates untapped genomic potential, yet high rediscovery rates of known metabolites increasingly frustrate conventional natural product screening programs. New methods to connect biosynthetic gene clusters to novel chemical scaffolds are therefore critical to enable the targeted discovery of genetically encoded natural products. Here, we present PRISM, a computational resource for the identification of biosynthetic gene clusters, prediction of genetically encoded nonribosomal peptides and type I and II polyketides, and bio- and cheminformatic dereplication of known natural products. PRISM implements novel algorithms which render it uniquely capable of predicting type II polyketides, deoxygenated sugars, and starter units, making it a comprehensive genome-guided chemical structure prediction engine. A library of 57 tailoring reactions is leveraged for combinatorial scaffold library generation when multiple potential substrates are consistent with biosynthetic logic. We compare the accuracy of PRISM to existing genomic analysis platforms. PRISM is an open-source, user-friendly web application available at http://magarveylab.ca/prism/ .
    Keywords: Computational Methods
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    cMonkey2: Automated, systematic, integrated detection of co-regulated gene modules for any organism (2015)
    Oxford University Press
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    Publication Date: 2015-07-25
    Description: The cMonkey integrated biclustering algorithm identifies conditionally co-regulated modules of genes (biclusters). cMonkey integrates various orthogonal pieces of information which support evidence of gene co-regulation, and optimizes biclusters to be supported simultaneously by one or more of these prior constraints. The algorithm served as the cornerstone for constructing the first global, predictive Environmental Gene Regulatory Influence Network (EGRIN) model for a free-living cell, and has now been applied to many more organisms. However, due to its computational inefficiencies, long run-time and complexity of various input data types, cMonkey was not readily usable by the wider community. To address these primary concerns, we have significantly updated the cMonkey algorithm and refactored its implementation, improving its usability and extendibility. These improvements provide a fully functioning and user-friendly platform for building co-regulated gene modules and the tools necessary for their exploration and interpretation. We show, via three separate analyses of data for E. coli, M. tuberculosis and H. sapiens , that the updated algorithm and inclusion of novel scoring functions for new data types (e.g. ChIP-seq and transcription factor over-expression [TFOE]) improve discovery of biologically informative co-regulated modules. The complete cMonkey 2 software package, including source code, is available at https://github.com/baliga-lab/cmonkey2 .
    Keywords: Computational Methods
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    A sustainable transport solution for a Slovenia town (2015)
    Oxford University Press
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    Publication Date: 2015-11-07
    Description: Authorities in Slovenia and other EU member states are confronted with problems of city transportation. Fossil-fuel-based transport poses two chief problems—local and global pollution, and dwindling supplies and ever-increasing costs. An elegant solution is to gradually replace the present automobile fleet with electric vehicles (EVs). This article explores the economics and practical viability of the provision of solar electricity for the charging of EVs by installation of economical available Photovoltaic modules. A steep decline in the module, inverter and installation costs is reported herein. Present estimates indicate that for the prevailing solar climate of Celje—a medium-sized Slovenian town—the cost would be only 2 euros and 11 cents per kWh of generated solar electricity.
    Keywords: Other low-carbon energy technologies
    Print ISSN: 1748-1317
    Electronic ISSN: 1748-1325
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Published by Oxford University Press
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    Reverse flow in natural convection heat pipe solar water heater (2015)
    Oxford University Press
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    Publication Date: 2015-11-07
    Description: System performance of a natural convection (thermosyphon) solar water heater depends on design and setup of collector and storage tank as well as environmental factors such as solar intensity, ambient temperature and wind conditions. The relative height separating the tank and collector mainly influences the magnitude of the thermosyphon flow rates, including both forward and reverse flow at night. In this experimental investigation, an array of evacuated tube heat pipe solar collectors was connected to an insulated hot water storage tank. The effect of the separation height between tank and collectors was investigated and reported. Thermosyphon water flow rates were measured using a dye-injection procedure in both forward and reverse flow directions. The results showed that reverse flow always occurred in the evenings and was about 5–11 times less than forward flow. The overnight mean water temperature drop was independent of the height separating the collectors and storage tank and ranged between 2 and 10°C. The temperature drop was greater when the night was cooler.
    Keywords: Other low-carbon energy technologies
    Print ISSN: 1748-1317
    Electronic ISSN: 1748-1325
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Published by Oxford University Press
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    Topology independent comparison of RNA 3D structures using the CLICK algorithm (2017)
    Oxford University Press
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    Publication Date: 2017-01-10
    Description: RNA molecules are attractive therapeutic targets because non-coding RNA molecules have increasingly been found to play key regulatory roles in the cell. Comparing and classifying RNA 3D structures yields unique insights into RNA evolution and function. With the rapid increase in the number of atomic-resolution RNA structures, it is crucial to have effective tools to classify RNA structures and to investigate them for structural similarities at different resolutions. We previously developed the algorithm CLICK to superimpose a pair of protein 3D structures by clique matching and 3D least squares fitting. In this study, we extend and optimize the CLICK algorithm to superimpose pairs of RNA 3D structures and RNA–protein complexes, independent of the associated topologies. Benchmarking Rclick on four different datasets showed that it is either comparable to or better than other structural alignment methods in terms of the extent of structural overlaps. Rclick also recognizes conformational changes between RNA structures and produces complementary alignments to maximize the extent of detectable similarity. Applying Rclick to study Ribonuclease III protein correctly aligned the RNA binding sites of RNAse III with its substrate. Rclick can be further extended to identify ligand-binding pockets in RNA. A web server is developed at http://mspc.bii.a-star.edu.sg/minhn/rclick.html .
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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