Identification of a periodic time series from an environmental proxy record

The past environment is often reconstructed by measuring a certain proxy (e.g. δ¹⁸O) in an environmental archive, i.e. a species that gradually accumulates mass and records the current environment during this mass formation (e.g. corals, shells, trees, etc.). When such an environmental proxy is measured, its values are known on a distance grid. However, to relate the data to environmental variations, the date associated with each measurement has to be known too. This transformation from distance to time is not straightforward to solve, since species usually do not grow at constant or known rates. In this paper, we investigate this problem for environmental archives exhibiting a certain periodicity. In practice, the method will be applicable to most annually resolved archives because these contain a seasonal component, e.g. clams, corals, sediment cores or trees. Due to variations in accretion rate the data along the distance axis have a disturbed periodic profile. In this paper, a method is developed to extract information about the accretion rate, such that the original (periodic, but further unknown) signal as a function of time can be recovered. The final methodology is quasi-independent of choices made by the investigator and is designed to deliver the most precise and accurate result. Every step in the procedure is described in detail, the results are tested on a Monte-Carlo simulation, and finally the method is exemplified on a real world example.     

An optimality criteria based method for discrete design optimization taking into account buildability constraints

This paper presents a heuristic design optimization method specifically developed for practicing structural engineers. Practical design optimization problems are often governed by buildability constraints. The majority of optimization methods that have recently been proposed for design optimization under buildability constraints are based on evolutionary computing. While these methods are generally easy to implement, they require a large number of function evaluations (finite element analyses), and they involve algorithmic parameters that require careful tuning. As a consequence, both the computation time and the engineering time are high. The discrete design optimization algorithm presented in this paper is based on the optimality criteria method for continuous optimization. It is faster than an evolutionary algorithm and it is free of tuning parameters. The algorithm is successfully applied to two classical benchmark problems (the design of a ten-bar truss and an eight-story frame) and to a practical truss design optimization problem.     

The Conversion of UDP-Glc to UDP-Man: In Silico and Biochemical Exploration To Improve the Catalytic Efficiency of CDP-Tyvelose C2-Epimerases

A promiscuous CDP-tyvelose 2-epimerase (TyvE) from Thermodesulfatator atlanticus (TaTyvE) belonging to the nucleotide sugar active short-chain dehydrogenase/reductase superfamily (NS-SDRs) was recently discovered. TaTyvE performs the slow conversion of NDP-glucose (NDP-Glc) to NDP-mannose (NDP-Man). Here, we present the sequence fingerprints that are indicative of the conversion of UDP-Glc to UDP-Man in TyvE-like enzymes based on the heptagonal box motifs. Our data-mining approach led to the identification of 11 additional TyvE-like enzymes for the conversion of UDP-Glc to UDP-Man. We characterized the top two wild-type candidates, which show a 15- and 20-fold improved catalytic efficiency, respectively, on UDP-Glc compared to TaTyvE. In addition, we present a quadruple variant of one of the identified enzymes with a 70-fold improved catalytic efficiency on UDP-Glc compared to TaTyvE. These findings could help the design of new nucleotide production pathways starting from a cheap sugar substrate like glucose or sucrose.     

Top-down kinetic modeling from power law to elementary steps using KASTER: A methane steam reforming case study

A top-down methodology for kinetic model construction including regression against experimental data is proposed using “KASTER.” As a case study, it is applied in the assessment of methane steam reforming (MSR) including water–gas shift (WGS) on a Ni catalyst at 923 K. The degree of detail in the reaction mechanism and the corresponding model is gradually enhanced, typically ranging from a simple power law to a microkinetic model. The reactor equations are solved transiently, preventing the numerical challenges encountered in the steady-state solution, particularly for microkinetic models. The microkinetic variant indicated that CH₄ dissociative adsorption and CO formation are kinetically relevant steps in MSR, while COOH formation is rate-determining in WGS. However, the model providing the best balance between detail accounted for and parameter significance corresponded to a Langmuir–Hinshelwood–Hougen–Watson (LHHW) mechanism accounting for dissociative adsorption, with CO formation and COOH formation as rate-determining steps for MSR and WGS, respectively.     

Identification of Biologically Relevant Compounds in Aboveground and Belowground Induced Volatile Blends

Plants under attack by aboveground herbivores emit complex blends of volatile organic compounds (VOCs). Specific compounds in these blends are used by parasitic wasps to find their hosts. Belowground induction causes shifts in the composition of aboveground induced VOC blends, which affect the preference of parasitic wasps. To identify which of the many volatiles in the complex VOC blends may explain parasitoid preference poses a challenge to ecologists. Here, we present a case study in which we use a novel bioinformatics approach to identify biologically relevant differences between VOC blends of feral cabbage (Brassica oleracea L.). The plants were induced aboveground or belowground with jasmonic acid (JA) and shoot feeding caterpillars (Pieris brassicae or P. rapae). We used Partial Least Squares—Discriminant Analysis (PLSDA) to integrate and visualize the relation between plant-emitted VOCs and the preference of female Cotesia glomerata. Overall, female wasps preferred JA-induced plants over controls, but they strongly preferred aboveground JA-induced plants over belowground JA-induced plants. PLSDA revealed that the emission of several monoterpenes was enhanced similarly in all JA-treated plants, whereas homoterpenes and sesquiterpenes increased exclusively in aboveground JA-induced plants. Wasps may use the ratio between these two classes of terpenes to discriminate between aboveground and belowground induced plants. Additionally, it shows that aboveground applied JA induces different VOC biosynthetic pathways than JA applied to the root. Our bioinformatic approach, thus, successfully identified which VOCs matched the preferences of the wasps in the various choice tests. Additionally, the analysis generated novel hypotheses about the role of JA as a signaling compound in aboveground and belowground induced responses in plants.     

Metal-ion-induced formation and stabilization of protein cages based on the cowpea chlorotic mottle virus

The cowpea chlorotic mottle virus (CCMV) is a versatile building block for the construction of nanoreactors and functional materials. Upon RNA removal, the capsid can be reversibly assembled and disassembed by adjusting the pH. At pH 5.0 the capsid is in the native assembled conformation, while at pH 7.5 it disassembles into 90 capsid protein dimers. This special property enables the encapsulation of various molecules, such as protein and enzymes, but only at low pH. It is possible to stabilize the capsid at pH 7.5 by addition of negatively charged polyelectrolytes or negatively charged particles, but these methods all fill the interior of the capsid, leaving little or no space for other cargo molecules. This pH restriction therefore severely limits the range of enzymes that can be encapsulated, and hampers the investigation of the CCMV capsid as a nanoreactor for the study of enzymes in confined spaces. Herein, the interaction of N-terminal histidine-tag-modified capsid proteins with several metal ions is reported. Depending on the conditions used, nanometer-sized protein particles or capsidlike architectures are formed that are stable at pH 7.5. This metal-mediated stabilization methodology is employed to form stable capsids containing multiple proteins at pH 7.5, thereby greatly expanding the scope of the CCMV capsid as a nanoreactor.     

Physicochemical properties and amylopectin chain profiles of cowpea,chickpea and yellow pea starches

Starches from cowpea and chickpea seeds were isolated and their properties were compared with those of commercial yellow pea starch. Amylose contents were 25.8%, 27.2%, and 31.2%, and the volume mean diameter of granules, determined in the dry state, were 15.5, 17.9, and 33.8 μm for cowpea, chickpea and yellow pea starches, respectively. All three legume starches showed a C-type X-ray diffraction pattern and two-stage swelling pattern. Amylopectin populations were isolated and the unit chain profiles were analyzed by HPLC after debranching with pullulanase. The degree of polymerization (DP) of short chain populations was about 6–50 and the populations of long chain had a DP of 50–80. Cowpea showed a lower weight ratio of short:long chains than chickpea and yellow pea starches. The larger portion of long side chains in cowpea amylopectin can be correlated with a higher gelatinization temperature, greater pasting peak and a slight difference in crystalline structure found for cowpea starch. Chickpea and yellow pea starches exhibited similarity in unit chain profile of amylopectin as well as in gelatinization temperature and pasting profile, while they differed in amylose content, particle size and syneresis. It is assumed that the chain length distribution of amylopectin has a large influence on starch properties.