Representative Set Of Examples Research Articles

Isopointal intermetallics: the cP24, dca phases as a representative set of examples, along with their vacancy-ordered variants β-Mn and SrSi2

Abstract The crystal-chemical relationship of the cubic Laves phase MgCu2 (space group F d 3 ‾ $d\overline{3}$ m, cF24) with the ternary phases Cd2Cu3In, Na2Au3Al, Mg2Rh3P, Li2Pd3B, Ag2Pd3S, Cu3Pt2B, Mo3Al2C, Mo3Ni2N, and V3Ga2N (subgroup P4132, cP24, dca) is discussed based on a group-subgroup scheme. The course of the lattice parameters and the free positional parameters show substantially different distortions and thus clear differences in chemical bonding, classifying these phases as isopointal rather than isotypic (usually they are all assigned to the Mo3Al2C type). The group-subgroup scheme further shows that the β-Mn and SrSi2 structures are vacancy-ordered variants of the cP24, dca phases. The structures of Mn3IrSi and LaIrSi (space group types P213; translationengleiche subgroups) are their ternary ordered versions.

Commutativity Simplifies Proofs of Parameterized Programs

Commutativity has proven to be a powerful tool in reasoning about concurrent programs. Recent work has shown that a commutativity-based reduction of a program may admit simpler proofs than the program itself. The framework of lexicographical program reductions was introduced to formalize a broad class of reductions which accommodate sequential (thread-local) reasoning as well as synchronous programs. Approaches based on this framework, however, were fundamentally limited to program models with a fixed/bounded number of threads. In this paper, we show that it is possible to define an effective parametric family of program reductions that can be used to find simple proofs for parameterized programs , i.e., for programs with an unbounded number of threads. We show that reductions are indeed useful for the simplification of proofs for parameterized programs, in a sense that can be made precise: A reduction of a parameterized program may admit a proof which uses fewer or less sophisticated ghost variables . The reduction may therefore be within reach of an automated verification technique, even when the original parameterized program is not. As our first technical contribution, we introduce a notion of reductions for parameterized programs such that the reduction R of a parameterized program P is again a parameterized program (the thread template of R is obtained by source-to-source transformation of the thread template of P ). Consequently, existing techniques for the verification of parameterized programs can be directly applied to R instead of P . Our second technical contribution is that we define an appropriate family of pairwise preference orders which can be effectively used as a parameter to produce different lexicographical reductions. To determine whether this theoretical foundation amounts to a usable solution in practice, we have implemented the approach, based on a recently proposed framework for parameterized program verification. The results of our preliminary experiments on a representative set of examples are encouraging.

Understanding and bridging the energy performance gap in building retrofit

On the basis of a representative set of examples, we tackle following issues concerning the energy performance gap which is commonly observed in retrofit of multifamily buildings: quantification of the main factors behind the gap, in relation with simulation; decomposition of the gap, by combination of the most sensitive parameters, in relation with observed values; exploration of how to bridge the gap, on the basis of two best practice examples. The results show that the gap consists of: (i) the difference between optimal yet realistic conditions of use, and standard values used in the simulation process; (ii) the difference between actual and optimal conditions of use, which corresponds to the optimization potential. It proves that significant reduction of the performance gap is possible through building optimization and responsible behavior.

Crowdsourcing the El Reno 2013 Tornado: A New Approach for Collation and Display of Storm Chaser Imagery for Scientific Applications

Abstract The 31 May 2013 El Reno, Oklahoma, tornado is used to demonstrate how a video imagery database crowdsourced from storm chasers can be time-corrected and georeferenced to inform severe storm research. The tornado’s exceptional magnitude (∼4.3-km diameter and ∼135 m s−1 winds) and the wealth of observational data highlight this storm as a subject for scientific investigation. The storm was documented by mobile research and fixed-base radars, lightning detection networks, and poststorm damage surveys. In addition, more than 250 individuals and groups of storm chasers navigating the tornado captured imagery, constituting a largely untapped resource for scientific investigation. The El Reno Survey was created to crowdsource imagery from storm chasers and to compile submitted materials in a quality-controlled, open-access research database. Solicitations to storm chasers via social media and e-mail yielded 93 registrants, each contributing still and/or video imagery and metadata. Lightning flash interval is used for precise time calibration of contributed video imagery; when combined with georeferencing from open-source geographical information software, this enables detailed mapping of storm phenomena. A representative set of examples is presented to illustrate how this standardized database and a web-based visualization tool can inform research on tornadoes, lightning, and hail. The project database offers the largest archive of visual material compiled for a single storm event, accessible to the scientific community through a registration process. This approach also offers a new model for poststorm data collection, with instructional materials created to facilitate replication for research into both past and future storm events.

An introduction to learning algorithms and potential applications in geomorphometry and Earth surface dynamics

Abstract. “Learning algorithms” are a class of computational tool designed to infer information from a data set, and then apply that information predictively. They are particularly well suited to complex pattern recognition, or to situations where a mathematical relationship needs to be modelled but where the underlying processes are not well understood, are too expensive to compute, or where signals are over-printed by other effects. If a representative set of examples of the relationship can be constructed, a learning algorithm can assimilate its behaviour, and may then serve as an efficient, approximate computational implementation thereof. A wide range of applications in geomorphometry and Earth surface dynamics may be envisaged, ranging from classification of landforms through to prediction of erosion characteristics given input forces. Here, we provide a practical overview of the various approaches that lie within this general framework, review existing uses in geomorphology and related applications, and discuss some of the factors that determine whether a learning algorithm approach is suited to any given problem.

Knowledge discovery in data sets with graded attributes

We present a knowledge discovery method for graded attributes that is based on an interactive determination of implications (if-then-rules) holding between the attributes of a given data-set. The corresponding algorithm queries the user in an efficient way about implications between the attributes. The result of the process is a representative set of examples for the entire theory and a set of implications from which all implications that hold between the attributes can be deduced. In many instances, the exploration process may be shortened by the usage of the user’s background knowledge. That is, a set of of implications the user knows beforehand. The method was successfully applied in different real-life applications for discrete data. In this paper, we show that attribute exploration with background information can be generalized for graded attributes.

3-D Crack Detection in Anisotropic Layered Media Through a Sparseness-Regularized Solver

An innovative 3-D imaging technique is proposed for the detection of cracks in anisotropic layered media. Toward this end, a fast approach to compute the 3-D method-of-moments (MoM) matrices is combined with a Bayesian Compressive Sensing solver to retrieve the unknown equivalent currents corresponding to sparse crack profiles. The proposed approach is numerically validated in a representative set of examples.

Improvement of Structure-Based Potentials for Protein Folding by Native and Nonnative Hydrogen Bonds

Pure Gō models (where every native interaction equally stabilizes the folded state) have widely proved their convenience in the computational investigation of protein folding. However, a chemistry-based description of the real interactions also provides a desirable tune in the analysis of the folding process, and thus some hybrid Gō potentials that combine both aspects have been proposed. Among all the noncovalent interactions that contribute to protein folding, hydrogen bonds are the only ones with a partial covalent character. This feature makes them directional and, thus, more difficult to model as part of the coarse-grained descriptions that are typically employed in Gō models. Thanks to a simplified but rigorous representation of backbone hydrogen bonds that we have recently proposed, we present in this article a combined potential (Gō + backbone hydrogen bond) to study the thermodynamics of protein folding in the frame of very simple simulation models. We show that the explicit inclusion of hydrogen bonds leads to a systematic improvement in the description of protein folding. We discuss a representative set of examples (from two-state folders to downhill proteins, with different types of native structures) that reveal a relevant agreement with experimental data.

Computer performance analysis and the Pi Theorem

This paper applies the Pi Theorem of dimensional analysis to a representative set of examples from computer performance analysis. It is a survey paper that takes a different look at problems involving latency, bandwidth, cache-miss ratios, and the efficiency of parallel numerical algorithms. The Pi Theorem is the fundamental tool of dimensional analysis, and it applies to problems in computer performance analysis just as well as it does to problems in other sciences. Applying it requires the definition of a system of measurement appropriate for computer performance analysis with a consistent set of units and dimensions. Then a straightforward recipe for each specific problem reduces the number of independent variables to a smaller number of dimensionless parameters. Two machines with the same values of these parameters are self-similar and behave the same way. Self-similarity relationships emphasize how machines are the same rather than how they are different. The Pi Theorem is simple to state and simple to prove, using purely algebraic methods, but the results that follow from it are often surprising and not simple at all. The results are often unexpected but they almost always reveal something new about the problem at hand.

Letterplace ideals and non-commutative Gröbner bases

In this paper we propose a 1-to-1 correspondence between graded two-sided ideals of the free associative algebra and some class of ideals of the algebra of polynomials, whose variables are double-indexed commuting ones. We call these ideals the “letterplace analogues” of graded two-sided ideals. We study the behaviour of the generating sets of the ideals under this correspondence, and in particular that of the Gröbner bases. In this way, we obtain a new method for computing non-commutative homogeneous Gröbner bases via polynomials in commuting variables. Since the letterplace ideals are stable under the action of a monoid of endomorphisms of the polynomial algebra, the proposed algorithm results in an example of a Buchberger procedure “reduced by symmetry”. Owing to the portability of our algorithm to any computer algebra system able to compute commutative Gröbner bases, we present an experimental implementation of our method in Singular. By means of a representative set of examples, we show finally that our implementation is competitive with computer algebra systems that provide non-commutative Gröbner bases from classical algorithms.

An expansion method for irregular oscillatory integrals

Many current problems in applied mathematics require the numerical integration of irregular oscillatory integrals. Few methods have been specifically found for these problems. An alternative method based on expansion is presented here and this method is compared with other approaches. Tests are carried out on a representative set of examples, and the algorithms are applied to problems with large oscillatory factors.

An alternative method for irregular oscillatory integrals over a finite range

Many current problems in applied mathematics require the numerical integration of irregular oscillatory integrals. Few methods have been specifically found for these problems. An alternative method based on substitution is presented here and this method is compared with other approaches. Tests are carried out on a representative set of examples, and the algorithms are applied to problems with large oscillatory factors.

Parameter set for the prediction of the 13C-NMR chemical shifts of sp 2- and sp-hybridized carbon atoms in organic compounds

A parameter set was compiled for the prediction of the carbon-13 chemical shifts of sp 2- and sp-hybridized carbon atoms based on simple linear additivity relationships. Extensive tests were done against 80 115 known chemical shifts. Many of the previously reported parameters are amended and new parameters are added. Statistical measures of the quality of the prediction are given in cases for which a representative set of examples was available. The parameter set together with previously published increments for sp 3-hybridized carbon atoms could predict 97% of the 150 000 chemical shifts investigated, with a standard deviation of 5.5 ppm. The additivity rules reported can be used alone or in connection with a recently published computer program for the estimation of carbon-13 chemical shifts. This program automatically selects and applies the addivity rules appropriate to the individual carbon atoms of the chemical constitution entered.

Sulfur Extrusion Reactions - Scope and Mechanistic Aspects

Abstract This review details a significant and representative set of examples in the literature where one of the products in a chemical reaction is elemental sulfur. While the mechanism of such extrusions is not clearly understood, several mechanistic possibilities have been considered including the likelihood of thiosulfoxide intermediates, the concatenation of sulfur atoms and the elimination of singlet diatomic sulfur as a discrete species. Details of the mechanistic efforts that have been uncovered in the literature are included as well as our own work in this area. In order to help avoid confusion for the reader, the nomenclature (although sometimes inconsistent) is in most cases that which appeared in the original articles.

Artinian, non-Noetherian rings

The structure of the rings of the title is studied with an eye to giving a representative set of examples. A uniqueness theorem is proved for the components appearing in Peirce decompositions with respect to a principal idempotent, and a Krull-Schmidt-type theorem is proved for the direct sum decompositions of these rings.