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At least 109 records · Page 6

Formation of oligonucleotide-PNA-chimeras by template-directed ligation

DNA sequences have previously been reported to act as templates for the synthesis of PNA, and vice versa. A continuous evolutionary transition from an informational replicating system based on one polymer to a system based on the other would be facilitated if it were possible to form chimeras, that is molecules that contain monomers of both types. Here we show that ligation to form chimeras proceeds efficiently both on PNA and on DNA templates. The efficiency of ligation is primarily determined by the number of backbone bonds at the ligation site and the relative orientation of template and substrate strands. The most efficient reactions result in the formation of chimeras with ligation junctions resembling the structures of the backbones of PNA and DNA and with antiparallel alignment of both components of the chimera with the template, that is, ligations involving formation of 3'-phosphoramidate and 5'-ester bonds. However, double helices involving PNA are stable both with antiparallel and parallel orientation of the two strands. Ligation on PNA but not on DNA templates is, therefore, sometimes possible on templates with reversed orientation. The relevance of these findings to discussions of possible transitions between genetic systems is discussed.

NASA Discipline Exobiology↗

Representations of mechanical assembly sequences

Five types of representations for assembly sequences are reviewed: the directed graph of feasible assembly sequences, the AND/OR graph of feasible assembly sequences, the set of establishment conditions, and two types of sets of precedence relationships. (precedence relationships between the establishment of one connection between parts and the establishment of another connection, and precedence relationships between the establishment of one connection and states of the assembly process). The mappings of one representation into the others are established. The correctness and completeness of these representations are established. The results presented are needed in the proof of correctness and completeness of algorithms for the generation of mechanical assembly sequences.

Homem De Mello, Luiz S.↗

Iterative pass optimization of sequence data

The problem of determining the minimum-cost hypothetical ancestral sequences for a given cladogram is known to be NP-complete. This "tree alignment" problem has motivated the considerable effort placed in multiple sequence alignment procedures. Wheeler in 1996 proposed a heuristic method, direct optimization, to calculate cladogram costs without the intervention of multiple sequence alignment. This method, though more efficient in time and more effective in cladogram length than many alignment-based procedures, greedily optimizes nodes based on descendent information only. In their proposal of an exact multiple alignment solution, Sankoff et al. in 1976 described a heuristic procedure--the iterative improvement method--to create alignments at internal nodes by solving a series of median problems. The combination of a three-sequence direct optimization with iterative improvement and a branch-length-based cladogram cost procedure, provides an algorithm that frequently results in superior (i.e., lower) cladogram costs. This iterative pass optimization is both computation and memory intensive, but economies can be made to reduce this burden. An example in arthropod systematics is discussed. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

NASA Discipline Evolutionary Biology↗

Linear Prediction Of Stationary Sequences Of Vectors

Report discusses direct approach to linear prediction of stationary sequence of vectors. Derives set of equations constituting minimal-order linear predictor. Using this approach, it proposes two specific computationally efficient schemes to predict vectors in sequence.

Baram, Yoram↗

Towards Digital and Performance-Based Supervisory HVAC Control Delivery

Upgrading supervisory HVAC control in commercial buildings is one of the most attractive decarbonization tools at our disposal. Modern controls are software programs and can in theory be deployed at scale and with a low up-front carbon "pulse". In practice, however, control delivery is a disjointed and inefficient process, dominated by manual handoffs of imprecise English language documents. A particularly high barrier exists between control implementation and building energy modeling (BEM) which results in control sequences typically not being tested for correctness or performance before implementation. Together with industry partners, DOE and the national labs are developing an ecosystem of tools and standards that can support fully digital performance-based control delivery workflows. This paper describes this ecosystem, which consists of three mutually supportive efforts. Semantic models of buildings and their systems enable automatic configuration and installation of control software. Platform-neutral control descriptions separate control algorithms from control platforms and enable the creation of libraries of reference control implementations. Dynamic whole-building energy-control simulation that can execute physically realistic control sequences makes it possible to test and evaluate the performance of control sequences and then directly compile them for installation and execution in control systems. In addition to digitizing and streamlining project-level control delivery, these standards and related software support benchmarking of control algorithms, both rule-based and optimization-based, and help to both advance the state of the art and to implement ratings and programs that encourage the adoption of high-performance control.

building controls↗

Time-Sequenced Flow Field Prediction in an Optima Spark-Ignition Direct-Injection Engine Using Bidirectional Recurrent Neural Network (bi-RNN) with Long Short-Term Memory

To further improve the energy conversion efficiency of internal combustion engine, the transient and complex air flow movement inside the cylinder needs to be better understood and controlled. Although the in-cylinder flow fields are highly stochastic with strong cycle-to-cycle fluctuations, machine learning can still provide an efficient way to learn and regress the complex flow movement process inside the cylinder. In this work, a bidirectional recurrent neural network (bi-RNN) model with long short-term memory was applied to predict the in-cylinder flow fields at different time steps using training data from mull-cycle particle image velocimetry (PIV) measurements. To evaluate the agreement between the true and predicted flow fields, structure and magnitude comparison indices are calculated both globally and locally. The comparison results show that the bi-RNN model can accurately predict the bulk flow and vortex motions from early intake stroke to compression stroke. This work demonstrates that the machine learning model has the potential to predict the underlying dynamics of the interaction between in-cylinder flows and provides a reliable way to improve temporal resolution in PIV flow data to better reveal transient in-cylinder flow features.

Bi-RNN model↗

How should Fitts' Law be applied to human-computer interaction?

The paper challenges the notion that any Fitts' Law model can be applied generally to human-computer interaction, and proposes instead that applying Fitts' Law requires knowledge of the users' sequence of movements, direction of movement, and typical movement amplitudes as well as target sizes. Two experiments examined a text selection task with sequences of controlled movements (point-click and point-drag). For the point-click sequence, a Fitts' Law model that used the diagonal across the text object in the direction of pointing (rather than the horizontal extent of the text object) as the target size provided the best fit for the pointing time data, whereas for the point-drag sequence, a Fitts' Law model that used the vertical size of the text object as the target size gave the best fit. Dragging times were fitted well by Fitts' Law models that used either the vertical or horizontal size of the terminal character in the text object. Additional results of note were that pointing in the point-click sequence was consistently faster than in the point-drag sequence, and that pointing in either sequence was consistently faster than dragging. The discussion centres around the need to define task characteristics before applying Fitts' Law to an interface design or analysis, analyses of pointing and of dragging, and implications for interface design.

NASA Program Space Human Factors↗

One-Pot Self-Assembly of Sequence-Controlled Mesoporous Heterostructures via Structure-Directing Agents

Multimaterial heterostructures have led to characteristics surpassing the individual components. Nature controls the architecture and placement of multiple materials through biomineralization of nanoparticles (NPs); however, synthetic heterostructure formation remains limited and generally departs from the elegance of self-assembly. Here, in this study, a class of block polymer structure-directing agents (SDAs) are developed containing repeat units capable of persistent (covalent) NP interactions that enable the direct fabrication of nanoscale porous heterostructures, where a single material is localized at the pore surface as a continuous layer. This SDA binding motif (design rule 1) enables sequence-controlled heterostructures, where the composition profile and interfaces correspond to the synthetic addition order. This approach is generalized with 5 material sequences using an SDA with only persistent SDA-NP interactions (“P-NP 1 –NP 2 ”; NP i = TiO 2 , Nb 2 O 5 , ZrO 2 ). Expanding these polymer SDA design guidelines, it is shown that the combination of both persistent and dynamic (noncovalent) SDA-NP interactions (“PD-NP 1 –NP 2 ”) improves the production of uniform interconnected porosity (design rule 2). The resulting competitive binding between two segments of the SDA (P- vs D-) requires additional time for the first NP type (NP 1 ) to reach and covalently attach to the SDA (design rule 3). The combination of these three design rules enables the direct self-assembly of heterostructures that localize a single material at the pore surface while preserving continuous porosity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design of laminated plates for maximum buckling load

The buckling load of laminated plates having midplane symmetry is maximized for a given total thickness. The thicknesses of the layers are taken as the design variables. Buckling analysis is carried out using the finite element method. The optimality equations are solved by a homotopy method which permits tracing optima as a function of total thickness. It is shown that for any design with a given stacking sequence of ply orientations, there exists a design associated with any other stacking sequence which possesses the same bending stiffness matrix and same total thickness. Hence, from the optimum design for a given stacking sequence, one can directly determine the optimum design for any rearrangement of the ply orientations, and the optimum buckling load is independent of the stacking sequence.

Shin, Yung S.↗

Solar System Escape Trajectories Using Outer Planetary Gravity Assists

A broad search of outer planet gravity assist sequences reveals flyby conditions that are naturally amenable for solar system escape. The optimal flyby conditions depend on the arrival velocity at the final body and provide the maximum possible escape speed for purely ballistic sequences. Trajectories in the 2030-2060 time frame are categorized by their encounter year with an emphasis on solar system escape speed and direction. All resulting sequences require a Jupiter gravity assist, and a considerable increase in escape speed is found in trajectories that utilize an additional Saturn, Uranus, or Neptune flyby. However, these solutions are limited by their availability and range of right ascensions. All cataloged trajectories are able to escape the solar system at least 3 au/year, and the highest energy sequences are in excess of 5.5 au/year. The search space is then used to find outer planet gravity assist trajectories to Kuiper Belt Objects (KBOs), and several cases are optimized.

Lam, Try↗

Aircraft stress sequence development: A complex engineering process made simple

Development of stress sequences for critical aircraft structure requires flight measured usage data, known aircraft loads, and established relationships between aircraft flight loads and structural stresses. Resulting cycle-by-cycle stress sequences can be directly usable for crack growth analysis and coupon spectra tests. Often, an expert in loads and spectra development manipulates the usage data into a typical sequence of representative flight conditions for which loads and stresses are calculated. For a fighter/trainer type aircraft, this effort is repeated many times for each of the fatigue critical locations (FCL) resulting in expenditure of numerous engineering hours. The Aircraft Stress Sequence Computer Program (ACSTRSEQ), developed by Southwest Research Institute under contract to San Antonio Air Logistics Center, presents a unique approach for making complex technical computations in a simple, easy to use method. The program is written in Microsoft Visual Basic for the Microsoft Windows environment.

Schrader, K. H.↗

Sequences of correlated hard X-ray and type III bursts during solar flares

Acceleration and injection of electron beams in solar flares can be traced from radio type III (or type U) bursts and correlated hard X-ray pulses with similar timescales and nonthermal spectra. We perform a systematic survey of such correlated radio and hard X-ray (HXR) pulses with timescales of less than or approximately 2 s in flares simultaneously observed with the radio spectrometer Ikarus and the Hard X-Ray Burst Spectrometer (HXRBS) on solar maximum mission (SMM). We applied an epoch-folding technique to enhance correlated time patterns in burst sequences at the two wavelengths. We present the results from the strongest (10) flares with a HXRBS count rate greater than or = 3000 counts/s, which have a satisfactory signal-to-noise ratio for subsecond pulses. The major findings of this study are presented. These observations strongly suggest that particle acceleration in solar flares occurs in a pulsed mode where electron beams are simultaneously injected in upward and downward directions. Since the sequences of correlated HXR and radio bursts show identical durations and intervals at the two wavelengths, they are believed to reflect most directly the temporal dynamics of the underlying common accelerator. As a consequence, thick-target models should be reconsidered under the aspect of electron injection with pulse durations of 0.2-2.0 s and duty cycles of approximately = 50%.

Aschwanden, Markus J.↗

Enhanced Modeling of First-Order Plant Equations of Motion for Aeroelastic and Aeroservoelastic Applications

A methodology is described for generating first-order plant equations of motion for aeroelastic and aeroservoelastic applications. The description begins with the process of generating data files representing specialized mode-shapes, such as rigid-body and control surface modes, using both PATRAN and NASTRAN analysis. NASTRAN executes the 146 solution sequence using numerous Direct Matrix Abstraction Program (DMAP) calls to import the mode-shape files and to perform the aeroelastic response analysis. The aeroelastic response analysis calculates and extracts structural frequencies, generalized masses, frequency-dependent generalized aerodynamic force (GAF) coefficients, sensor deflections and load coefficients data as text-formatted data files. The data files are then re-sequenced and re-formatted using a custom written FORTRAN program. The text-formatted data files are stored and coefficients for s-plane equations are fitted to the frequency-dependent GAF coefficients using two Interactions of Structures, Aerodynamics and Controls (ISAC) programs. With tabular files from stored data created by ISAC, MATLAB generates the first-order aeroservoelastic plant equations of motion. These equations include control-surface actuator, turbulence, sensor and load modeling. Altitude varying root-locus plot and PSD plot results for a model of the F-18 aircraft are presented to demonstrate the capability.

Pototzky, Anthony S.↗

Mutations in the putative calcium-binding domain of polyomavirus VP1 affect capsid assembly

Calcium ions appear to play a major role in maintaining the structural integrity of the polyomavirus and are likely involved in the processes of viral uncoating and assembly. Previous studies demonstrated that a VP1 fragment extending from Pro-232 to Asp-364 has calcium-binding capabilities. This fragment contains an amino acid stretch from Asp-266 to Glu-277 which is quite similar in sequence to the amino acids that make up the calcium-binding EF hand structures found in many proteins. To assess the contribution of this domain to polyomavirus structural integrity, the effects of mutations in this region were examined by transfecting mutated viral DNA into susceptible cells. Immunofluorescence studies indicated that although viral protein synthesis occurred normally, infective viral progeny were not produced in cells transfected with polyomavirus genomes encoding either a VP1 molecule lacking amino acids Thr-262 through Gly-276 or a VP1 molecule containing a mutation of Asp-266 to Ala. VP1 molecules containing the deletion mutation were unable to bind 45Ca in an in vitro assay. Upon expression in Escherichia coli and purification by immunoaffinity chromatography, wild-type VP1 was isolated as pentameric, capsomere-like structures which could be induced to form capsid-like structures upon addition of CaCl2, consistent with previous studies. However, although VP1 containing the point mutation was isolated as pentamers which were indistinguishable from wild-type VP1 pentamers, addition of CaCl2 did not result in their assembly into capsid-like structures. Immunogold labeling and electron microscopy studies of transfected mammalian cells provided in vivo evidence that a mutation in this region affects the process of viral assembly.

Non-NASA Center↗

Exploring Connectivity in Sequence Space of Functional RNA

Emergence of replicable genetic molecules was one of the marking points in the origin of life, evolution of which can be conceptualized as a walk through the space of all possible sequences. A theoretical concept of fitness landscape helps to understand evolutionary processes through assigning a value of fitness to each genotype. Then, evolution of a phenotype is viewed as a series of consecutive, single-point mutations. Natural selection biases evolution toward peaks of high fitness and away from valleys of low fitness. whereas neutral drift occurs in the sequence space without direction as mutations are introduced at random. Large networks of neutral or near-neutral mutations on a fitness landscape, especially for sufficiently long genomes, are possible or even inevitable. Their detection in experiments, however, has been elusive. Although a few near-neutral evolutionary pathways have been found, recent experimental evidence indicates landscapes consist of largely isolated islands. The generality of these results, however, is not clear, as the genome length or the fraction of functional molecules in the genotypic space might have been insufficient for the emergence of large, neutral networks. Thorough investigation on the structure of the fitness landscape is essential to understand the mechanisms of evolution of early genomes. RNA molecules are commonly assumed to play the pivotal role in the origin of genetic systems. They are widely believed to be early, if not the earliest, genetic and catalytic molecules, with abundant biochemical activities as aptamers and ribozymes, i.e. RNA molecules capable, respectively, to bind small molecules or catalyze chemical reactions. Here, we present results of our recent studies on the structure of the sequence space of RNA ligase ribozymes selected through in vitro evolution. Several hundred thousands of sequences active to a different degree were obtained by way of deep sequencing. Analysis of these sequences revealed several large clusters defined such that every sequence in a cluster can be reached from any other sequence in the same cluster through a series of single point mutations. Sequences in a single cluster appear to adopt more than one secondary structure. The mechanism of refolding within a single cluster was examined. To shed light on possible evolutionary paths in the space of ribozymes, the connectivity between clusters was investigated. The effect of length of RNA molecules on the structure of the fitness landscape and possible evolutionary paths was examined by way of comparing functional sequences of 20 and 80 nucleobases in length. It was found that sequences of different lengths shared secondary structure motifs that were presumed responsible for catalytic activity, with increasing complexity and global structural rearrangements emerging in longer molecules.

Wei, Chenyu↗

Crabtree/Warburg-like aerobic xylose fermentation by engineered Saccharomyces cerevisiae

Bottlenecks in the efficient conversion of xylose into cost-effective biofuels have limited the widespread use of plant lignocellulose as a renewable feedstock. The yeast Saccharomyces cerevisiae ferments glucose into ethanol with such high metabolic flux that it ferments high concentrations of glucose aerobically, a trait called the Crabtree/Warburg Effect. In contrast to glucose, most engineered S. cerevisiae strains do not ferment xylose at economically viable rates and yields, and they require respiration to achieve sufficient xylose metabolic flux and energy return for growth aerobically. Here, we evolved respiration-deficient S. cerevisiae strains that can grow on and ferment xylose to ethanol aerobically, a trait analogous to the Crabtree/Warburg Effect for glucose. Through genome sequence comparisons and directed engineering, we determined that duplications of genes encoding engineered xylose metabolism enzymes, as well as TKL1, a gene encoding a transketolase in the pentose phosphate pathway, were the causative genetic changes for the evolved phenotype. Reengineered duplications of these enzymes, in combination with deletion mutations in HOG1, ISU1, GRE3, and IRA2, increased the rates of aerobic and anaerobic xylose fermentation. Importantly, we found that these genetic modifications function in another genetic background and increase the rate and yield of xylose-to-ethanol conversion in industrially relevant switchgrass hydrolysate, indicating that these specific genetic modifications may enable the sustainable production of industrial biofuels from yeast. We propose a model for how key regulatory mutations prime yeast for aerobic xylose fermentation by lowering the threshold for overflow metabolism, allowing mutations to increase xylose flux and to redirect it into fermentation products.

59 BASIC BIOLOGICAL SCIENCES↗

Machine learning prediction of enzyme optimum pH

The relationship between pH and enzyme catalytic activity, especially the optimal pH (pH opt ) at which enzymes function, is critical for biotechnological applications. Hence, computational methods to predict pH opt will enhance enzyme discovery and design by facilitating accurate identification of enzymes that function optimally at specific pH levels, and by elucidating sequence-function relationships. Here, in this study, we proposed and evaluated various machine learning methods for predicting pH opt , conducting extensive hyperparameter optimization and training over 11,000 model instances. Our results demonstrate that models utilizing language model embeddings markedly outperform other methods in predicting pHopt. We present EpHod, the best-performing model, to predict pHopt, making it publicly available to researchers. From sequence data, EpHod directly learns structural and biophysical features that relate to pH opt , including proximity of residues to the catalytic centre and the accessibility of solvent molecules. Overall, EpHod presents a promising advancement in pH opt prediction and will potentially speed up the development of enzyme technologies.

97 MATHEMATICS AND COMPUTING↗