Recent Submissions

  • Metagenomic Methods: From Seawater to the Database

    Reza, Md. Shaheed; Kobiyama, Atsushi; Rashid, Jonaira; Yamada, Yuichiro; Ikeda, Yuri; Ikeda, Daisuke; Mizusawa, Nanami; Yanagisawa, Saki; Ikeo, Kazuho; Sato, Shigeru; Ogata, Takehiko; Kudo, Toshiaki; Kaga, Shinnosuke; Watanabe, Shiho; Naiki, Kimiaki; Kaga, Yoshimasa; Segawa, Satoshi; Mineta, Katsuhiko; Bajic, Vladimir B.; Gojobori, Takashi; Watabe, Shugo (Springer Singapore, 2019-07-24) [Book Chapter]
    In this article, methods or techniques of metagenomics including targeted 16S/18S rRNA analyses and shotgun sequencing will be discussed. It is sometimes difficult, especially for beginners, to follow the manufacturer’s recommendation as mentioned in the protocol and to go through different steps from the preparation of starting material (e.g., DNA), library preparation, and so on. We will try to explain all the steps in detail and share our experience here. It all starts with collection of samples and collection of ecological/environmental metadata followed by sample fractionation (optional), extraction of DNA, sequencing, and finally data analyses to interpret results. Sample collection has always been the most important part of a study as it requires proper planning, a good workforce to execute, permission(s) of sampling from appropriate authority, and precaution(s) about endangered species during sampling. Here, we first describe methodology for a shallow river and in the later section methodology for a deep marine bay. In either case, slight modifications can be made to succeed in sampling. Determination of physicochemical parameters as metadata simultaneously is also an important task. These samples are then processed to extract DNA which needs to be representative of all cells present in the sample. Finally, sequencing is done by a next-generation sequencer, and data analyses are completed. Through these methods, scientists are now able to overcome the unculturability problem of more than 99% of environmental microorganisms and uncovered functional gene diversity of environmental microorganisms.
  • Marine Metagenomic Sequence Counts of Reads Assigned to Taxa Consistently Proportionate to Read Counts Obtained for per g of Seawater Sample

    Kudo, Toshiaki; Reza, Md. Shaheed; Kobiyama, Atsushi; Rashid, Jonaira; Yamada, Yuichiro; Ikeda, Yuri; Ikeda, Daisuke; Mizusawa, Nanami; Yanagisawa, Saki; Ikeo, Kazuho; Sato, Shigeru; Ogata, Takehiko; Kaga, Shinnosuke; Watanabe, Shiho; Naiki, Kimiaki; Kaga, Yoshimasa; Segawa, Satoshi; Mineta, Katsuhiko; Bajic, Vladimir B.; Gojobori, Takashi; Watabe, Shugo (Springer Singapore, 2019-07-24) [Book Chapter]
    Development of high-throughput DNA sequencing technologies has enabled scientists to generate vast amounts of genetic information that may provide a comprehensive understanding of key roles played by environmental microorganisms. Generally the microorganisms inhabit a particular niche and correlate well with environmental changes. It is accepted that the read counts obtained through metagenomic analyses correlate semi-quantitatively with the relative abundance of bacterial species. In our marine metagenomic study conducted on the Ofunato Bay, Iwate Prefecture, Japan, we observed such correlation which exists for bacterioplankton Candidatus Pelagibacter ubique, identified as the dominant bacterial species of the bay. Shotgun metagenomic analyses identified three strains of Ca. Pelagibacter in the bay, viz., dmdA-HTCC1062, dmdA-HTCC9022, and O19-dmdA, that showed a dynamic change throughout the year particularly in the 10-m depth zone. Interestingly, the total abundances of those strains that fall in the Ca. Pelagibacter genus were found to correlate well with the read counts per g seawater samples used for analyses. It is assumed that whole-genome sequence (WGS) reads for members of the metagenome would show similar trend provided that proper precautions are taken to ensure collection of representative sample from the environment.
  • A Simplified Method to Engineer CRISPR/Cas9-Mediated Geminivirus Resistance in Plants

    Ali, Zahir; Zaidi, Syed Shan-e-Ali; Tashkandi, Manal; Mahfouz, Magdy M. (Springer New York, 2019-06-21) [Book Chapter]
    Throughout the world, geminiviruses cause devastating losses in economically important crops, including tomato, cotton, cassava, potato, chili, and cucumber; however, control mechanisms such as genetic resistance remain expensive and ineffective. CRISPR/Cas9 is an adaptive immunity mechanism used by prokaryotes to defend against invading nucleic acids of phages and plasmids. The CRISPR/Cas9 system has been harnessed for targeted genome editing in a variety of eukaryotic species, and in plants, CRISPR/Cas9 has been used to modify or introduce many traits, including virus resistance. Recently, we demonstrated that the CRISPR/Cas9 system could be used to engineer plant immunity against geminiviruses by directly targeting the viral genome for degradation. In this chapter, we describe a detailed method for engineering CRISPR/Cas9-mediated resistance against geminiviruses. This method may provide broad, durable viral resistance, as it can target conserved regions of the viral genome and can also be customized to emerging viral variants. Moreover, this method can be used in many crop species, as it requires little or no knowledge of the host plant’s genome.
  • Energy Stable Simulation of Two-Phase Equilibria with Capillarity

    Sun, Shuyu (Springer International Publishing, 2019-06-19) [Book Chapter]
    We consider the affect of capillary pressure on the Van der Waals fuid and on the Peng-Robinson fluid by minimizing total Helmholtz energy in given total volume, temperature, and total moles. We propose simple but conditionally energy stable numerical schemes, and we provide interesting numerical examples. We compare our numerical results with the prediction of Kelvin’s equation, indicating that Kelvin’s equation works well only when the temperature is not too low.
  • Accelerated Phase Equilibrium Predictions for Subsurface Reservoirs Using Deep Learning Methods

    Zhang, Tao; Li, Yiteng; Sun, Shuyu (Springer International Publishing, 2019-06-19) [Book Chapter]
    Multiphase fluid flow with complex compositions is an increasingly attractive research topic with more and more attentions paid on related engineering problems, including global warming and green house effect, oil recovery enhancement and subsurface water pollution treatment. Prior to study the flow behaviors and phase transitions in multi-component multiphase flow, the first effort should be focused on the accurate prediction of the total phase numbers existing in the fluid mixture, and then the phase equilibrium status can be determined. In this paper, a novel and fast prediction technique is proposed based on deep learning method. The training data is generated using a selected VT dynamic flash calculation scheme and the network constructions are deeply optimized on the activation functions. Compared to previous machine learning techniques proposed in literatures to accelerate vapor liquid phase equilibrium calculation, the total number of phases existing in the mixture is determined first and other phase equilibrium properteis will be estimated then, so that we do not need to ensure that the mixture is in two phase conditions any more. Our method could handle fluid mixtures with complex compositions, with 8 different components in our example and the original data is in a large amount. The analysis on prediction performance of different deep learning models with various neural networks using different activation functions can help future researches selecting the features to construct the neural network for similar engineering problems. Some conclusions and remarks are presented at the end to help readers catch our main contributions and insight the future related researches.
  • Experimental Study of Totally Optimal Decision Rules

    Azad, Mohammad; Moshkov, Mikhail (Springer International Publishing, 2019-05-27) [Book Chapter]
    In this paper, we experimentally study the existence of totally optimal decision rules which are optimal relative to the length and coverage simultaneously for nine decision tables from the UCI Machine Learning Repository. Totally optimal rules can be useful when we consider decision rules as a way for knowledge representation. We study not only exact but also approximate decision rules based on the three uncertainty measures: entropy, Gini index, and misclassification error. To investigate the existence of totally optimal rules, we use an extension of dynamic programming that allows us to make multi-stage optimization of decision rules relative to the length and coverage. Experimental results show that totally optimal decision rules exist in many cases. However, the behavior of graphs describing how the number of rows of decision tables with totally optimal decision rules depends on the accuracy of rules is irregular.
  • Soil Properties: Physics Inspired, Data Driven

    Santamarina, Carlos; Park, Junghee; Terzariol, Marco; Cardona, Alejandro; Castro, Gloria M.; Cha, Wonjun; Garcia, Adrian; Hakiki, Farizal; Lyu, Chuangxin; Salva, Marisol; Shen, Yuanjie; Sun, Zhonghao; Chong, Song-Hun (Springer International Publishing, 2019-05-24) [Book Chapter]
    Research and engineering projects during the last century have advanced the understanding of soil behavior and contributed extensive datasets. Nevertheless, the granular nature of soils challenges the accurate prediction of soil properties. In this context, a physics-inspired and data-driven approach helps us anticipate the soil response. The granular nature of soils defines their inherent properties (e.g., non-linear, non-elastic, porous, pervious) and their effective stress-dependent stiffness, frictional strength and dilation upon shear. The revised soil classification builds on the physical understanding of soils (e.g., packing characteristics and the effect of pore fluid chemistry on fines) and the extensive data accumulated in the field. Asymptotically correct compression models adequately fit experimental data and avoid numerical difficulties. Constant volume friction reflects particle shape and it is strongly dependent on stress path. Repetitive loading leads to characteristic asymptotic conditions (terminal density, and either ratcheting or shakedown). Data and physical analyses suggest a power relationship between void ratio and hydraulic conductivity. The pore-scale origin of suction is interfacial tension and contact angle. P-wave velocity is a good indicator of loss of saturation and S-wave velocity measures the skeletal shear stiffness. Permittivity, electrical conductivity and thermal conductivity are sensitive to water content. Finally, ubiquitous sensors, information technology and cellular communication support the development of effective laboratory characterization techniques and allow us to access large databases. These are transformative changes in geotechnical engineering.
  • Quantitative Phosphoproteomic Using Titanium Dioxide Micro-Columns and Label-Free Quantitation

    Barrios-Llerena, Martin; Le Bihan, Thierry (Mass Spectrometry of Proteins, Springer Nature, 2019-04-12) [Book Chapter]
    Phosphorylation events are important during cellular function. Analysis of phosphorylation in complex samples has been extensively studied using large-scale phosphopeptide enrichment methods. Quantitative analysis of the enriched phosphopeptides is subsequently performed using label-based methodologies (e.g., SILAC, iTRAQ, and others). Here we describe the protocol for the quantitative analysis of phosphopeptides, enriched with titanium dioxide micro-column, using an intensity-based label-free quantitation.
  • Strigolactone Biosynthesis and Signal Transduction

    Jia, Kunpeng; Li, Changsheng; Bouwmeester, Harro J.; Al-Babili, Salim (Strigolactones - Biology and Applications, Springer Nature, 2019-04-02) [Book Chapter]
    Strigolactones (SLs) are a group of carotenoid derivatives that act as a hormone regulating plant development and response to environmental stimuli. SLs are also released into soil as a signal indicating the presence of a host for symbiotic arbuscular mycorrhizal fungi and root parasitic weeds. In this chapter, we provide an overview on the enormous progress that has been recently made in elucidating SL biosynthesis and signal transduction. We describe the tailoring pathway from the carotenoid precursor to the central intermediate carlactone, highlighting the stereospecificity of the involved enzymes, the all-trans/9-cis-β-carotene isomerase (D27), the 9-cis-specific CAROTENOID CLEAVAGE DIOXYGENASE 7 (CCD7), as well as CCD8 and its unusual catalytic activity. We then outline the oxidation of carlactone by cytochrome P450 enzymes, such as the Arabidopsis MORE AXILLARY GROWTH 1 (MAX1), into different SLs and the role of other enzymes in generating this diversity, and discuss why plants produce many different SLs. This is followed by depicting hormonal and nutritional factors that regulate SL biosynthesis and release, and by a description of transport mechanisms. In the second part of our chapter, we focus on SL perception and signal transduction, describing the SL receptor DECREASED APICAL DOMINANCE 2 (DAD2)/DWARF14 (D14) and its unique features, the central function of protein degradation mediated by the F-box protein MAX2 and its homologs. We also discuss the latest advances in understanding how SLs regulate the transcription of target genes and the role of SMXL/D53 transcription inhibitors.
  • Concentrated Photovoltaic (CPV): From Deserts to Rooftops

    Burhan, Muhammad; Shahzad, Muhammad Wakil; Ng, Kim Choon (Lecture Notes in Computer Science, Springer Nature, 2019-03-29) [Book Chapter]
    The current photovoltaic market is completely dominated by the conventional single junction PV panels, despite the fact that the highest energy efficiency of multi-junction solar cells is in the form of concentrated photovoltaic (CPV) system. CPV technology has faced many challenges of reliability and performance since its conception. However, despite much improvement in design and reliability, CPV technology is still unable to gain the attention of customers and energy planners with its high-performance potential. Due to its response to only solar beam radiations, CPV systems are believed to be only suitable to operate in clear sky weather conditions. That’s why the current gigantic CPV systems are only designed to be installed in open desert regions. It is still lacking the same application scope which the conventional PV is experiencing. With the aim to boost its market potential, in this chapter, a compact CPV design is discussed with low cost but highly accurate performance, to be targeted to install at the rooftop of commercial and residential building in the urban region. In addition, the performance of CPV system is also evaluated and compared with the different conventional PV system in the tropical weather condition with low beam radiation availability.
  • Genetic Engineering for the Improvement of Oil Content and Associated Traits in Jatropha curcas L.

    Mastan, Shaik G.; Rathore, Mangal Singh; Kumari, Swati; Muppala, Reddy P.; Kumar, Nitish (Jatropha, Challenges for a New Energy Crop, Springer Nature, 2019-03-29) [Book Chapter]
    Interminably increasing petroleum rates and exhaustion of fossil reserves have ignited a global search for substitutes to renewable fuel sources. Many oil-generating plants, crops and trees have been considered for biofuel; among these Jatropha curcas is regarded as one of the most promising oilseed plants as its seeds contain oil content up to 35%. Because fossil oil consumption is increasing day-by-day, there is an urgent need to enhance the oil content. Transgenic technology is one of the advanced techniques that have been applied to enhance oil content and modify the composition of fatty acids in seed oils. Increasing seed oil content can be done by modifying the enzyme’s level expression in the triacylglycerol biosynthetic pathway. In this chapter, an effort is made to highlight the potential of transgenic technology towards the enhancement of the oil content and in altering the candidate gene expression for biosynthesis of triacylglycerol.
  • Methods for the recombinant expression of active tyrosine kinase domains: Guidelines and pitfalls

    Díaz Galicia, M. Escarlet; Aldehaiman, Abdullah; Hong, Seungbeom; Arold, Stefan T.; Grunberg, Raik (Methods in Enzymology, Elsevier BV, 2019-03-26) [Book Chapter]
    Protein tyrosine kinases (PTKs) are key signaling molecules and important drug targets. Although the efficient recombinant production of active PTKs is important for both pharmaceutical industry and academic research, most PTKs are still obtained from conventional, expensive and time-consuming insect-cell based expression. Host toxicity, kinase inactivity, insolubility and heterogeneity are among the reasons thought to preclude PTK expression in Escherichia coli. Herein we review these presumed roadblocks and their possible solutions for bacterial expression of PTKs, and give an overview on kinase activity assays. Finally, we report our experiences and observations with the kinases Src, Lyn and FAK as examples to illustrate implementation, effects and pitfalls of E. coli expression and in vitro assaying of PTKs.
  • Particle Migration and Clogging in Radial Flow: A Microfluidics Study

    Zhao, Budi; Liu, Q.; Santamarina, Carlos (Water Resources Development and Management, Springer Nature, 2019-03-25) [Book Chapter]
    Migratory particles in porous media experience mechanical and chemo-physical interactions with fluids, pore walls and other particles. The resulting forces (buoyant weight, drag, inertia, and electrical particle-particle and particle-wall) determine particle migration, adhesion and pore clogging. We investigate underlying pore-scale phenomena in convergent radial flow using microfluidic chips. Images reveal distinct clogging mechanics as a function of the particle mass density. The heavy glass particles collide with pore walls and the transient increase in the local volume fraction of particles enhances the probability of bridge formation and clogging at pore throats. On the other hand, quasi-buoyant latex particles follow streamlines closely, but can stick to nearby pore walls at pore constrictions as electrical attraction towards the wall overcomes the repulsive forces. A clogged pore increases the tortuosity of streamlines and promotes further clogging at nearby pores. Statistical data gathered through image analyses identify causal interactions between sequential clogging events.
  • Local and Global Approaches to Study of Decision and Inhibitory Trees and Rule Systems

    Alsolami, Fawaz; Azad, Mohammad; Chikalov, Igor; Moshkov, Mikhail (Management-Reihe Corporate Social Responsibility, Springer Nature, 2019-03-13) [Book Chapter]
    This chapter is devoted to the study of time complexity of decision and inhibitory trees and rule systems over arbitrary sets of attributes represented by information systems.
  • Multi-pruning and Restricted Multi-pruning of Decision Trees

    Alsolami, Fawaz; Azad, Mohammad; Chikalov, Igor; Moshkov, Mikhail (Management-Reihe Corporate Social Responsibility, Springer Nature, 2019-03-13) [Book Chapter]
    In this chapter, we consider two questions related to decision trees: (i) how to construct decision trees with reasonable number of nodes and reasonable number of misclassifications when they are used for knowledge representation, and (ii) how to improve the prediction accuracy of decision trees when they are used as classifiers. We created so-called multi-pruning approach based on dynamic programming algorithms for bi-criteria optimization of CART-like decision trees relative to the number of nodes and the number of misclassifications. This approach allows us to construct the set of all Pareto optimal points and to derive, for each such point, decision trees with parameters corresponding to that point. Experiments with decision tables from the UCI ML Repository show that, very often, we can find a suitable Pareto optimal point and derive a decision tree with small number of nodes at the expense of small increment in the number of misclassifications. Multi-pruning approach includes a procedure which constructs decision trees that, as classifiers, often outperform decision trees constructed by CART. We considered a modification of multi-pruning approach (restricted multi-pruning) that requires less memory and time but usually keeps the quality of constructed trees as classifiers or as a way for knowledge representation. Based on the uncertainty measure abs which is applicable both to decision tables with single- and many-valued decisions, we extended the considered approaches to the case of decision tables with many-valued decisions.
  • Bi-criteria Optimization Problem for Rules and Systems of Rules: Cost Versus Cost

    Alsolami, Fawaz; Azad, Mohammad; Chikalov, Igor; Moshkov, Mikhail (Management-Reihe Corporate Social Responsibility, Springer Nature, 2019-03-13) [Book Chapter]
    In this chapter, we consider algorithms which construct the sets of Pareto optimal points for bi-criteria optimization problems for decision rules and rule systems relative to two cost functions. We show how the constructed set of Pareto optimal points can be transformed into the graphs of functions which describe the relationships between the considered cost functions. We compare 13 greedy heuristics for construction of decision rules from the point of view of single-criterion optimization (relative to length or coverage) and bi-criteria optimization (relative to length and coverage). At the end of the chapter, we generalize the obtained results to the case of inhibitory rules and systems of inhibitory rules.
  • Preliminary Results for Decision and Inhibitory Trees, Tests, Rules, and Rule Systems

    Alsolami, Fawaz; Azad, Mohammad; Chikalov, Igor; Moshkov, Mikhail (Management-Reihe Corporate Social Responsibility, Springer Nature, 2019-03-13) [Book Chapter]
    Earlier, some relatively simple results were considered for binary decision tables with many-valued decisions: relationships among decision trees, rules and tests, bounds on their complexity, greedy algorithms for construction of decision trees, rules and tests, and dynamic programming algorithms for minimization of tree depth and rule length. In this chapter, we mention these results without proofs and extend them to inhibitory trees, tests, rules and rule systems over binary decision tables with many-valued decisions.
  • Explaining Examples

    Alsolami, Fawaz; Azad, Mohammad; Chikalov, Igor; Moshkov, Mikhail (Management-Reihe Corporate Social Responsibility, Springer Nature, 2019-03-13) [Book Chapter]
    In this chapter, we discuss briefly main notions: problems with many-valued decisions, decision tables corresponding to these problems, decision and inhibitory trees, rules, and systems of rules. We consider only depth of trees, and length of rules and systems of rules. After that, we concentrate on consideration of simple examples of problems with many-valued decisions from different areas of applications: fault diagnosis, computational geometry, combinatorial optimization, and analysis of data. At the end, we discuss two examples which explain why we study not only decision but also inhibitory rules and trees.
  • Three Approaches to Handle Inconsistency in Decision Tables

    Alsolami, Fawaz; Azad, Mohammad; Chikalov, Igor; Moshkov, Mikhail (Management-Reihe Corporate Social Responsibility, Springer Nature, 2019-03-13) [Book Chapter]
    In this chapter, we discuss main notions related to inconsistent decision tables, and three approaches to handle inconsistency in decision tables: decision tables with many-valued decisions (MVD approach), decision tables with generalized decisions (GD approach), and decision tables with most common decisions (MCD approach). After that, we compare complexity and classification accuracy of decision trees constructed by greedy heuristics in the frameworks of these approaches.
  • Decision and Inhibitory Rules and Systems of Rules

    Alsolami, Fawaz; Azad, Mohammad; Chikalov, Igor; Moshkov, Mikhail (Management-Reihe Corporate Social Responsibility, Springer Nature, 2019-03-13) [Book Chapter]
    In this chapter, we consider various types of decision and inhibitory rules and systems of rules. We discuss the notion of cost function for rules, the notion of decision rule uncertainty, and the notion of inhibitory rule completeness. Similar notions are introduced for systems of decision and inhibitory rules.

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