Neighbor Parameters Research Articles

Energy Efficient and Stable Weight Based Clustering for Mobile Ad Hoc Networks

Recently several weighted clustering algorithms have been proposed, however, to the best of our knowledge; there is none that propagates weights to other nodes without weight message for leader election, normalizes node parameters and considers neighboring node parameters to calculate node weights. In this paper, we propose an Energy Efficient and Stable Weight Based Clustering (EE-SWBC) algorithm that elects cluster heads without sending any additional weight message. It propagates node parameters to its neighbors through neighbor discovery message (HELLO Message) and stores these parameters in neighborhood list. Each node normalizes parameters and efficiently calculates its own weight and the weights of neighboring nodes from that neighborhood table using Grey Decision Method (GDM). GDM finds the ideal solution (best node parameters in neighborhood list) and calculates node weights in comparison to the ideal solution. The node(s) with maximum weight (parameters closer to the ideal solution) are elected as cluster heads. In result, EE-SWBC fairly selects potential nodes with parameters closer to ideal solution with less overhead. Different performance metrics of EE-SWBC and Distributed Weighted Clustering Algorithm (DWCA) are compared through simulations. The simulation results show that EE-SWBC maintains fewer average numbers of stable clusters with minimum overhead, less energy consumption and fewer changes in cluster structure within network compared to DWCA.

Thermodynamic Characterization of Naturally Occurring RNA Single Mismatches with G-U Nearest Neighbors

Due to their prevalence and roles in biological systems, single mismatches adjacent to G-U pairs are important RNA structural elements. Since there are only limited experimental values for the stability of single mismatches adjacent to G-U pairs, current algorithms using free energy minimization to predict RNA secondary structure from sequence assign predicted thermodynamic values to these types of single mismatches. Here, thermodynamic data are reported for frequently occurring single mismatches adjacent to at least one G-U pair. This experimental data can be used in place of predicted thermodynamic values in algorithms that predict secondary structure from sequence using free energy minimization. When predicting the thermodynamic contributions of previously unmeasured single mismatches, most algorithms apply the same thermodynamic penalty for an A-U pair adjacent to a single mismatch and a G-U pair adjacent to a single mismatch. A recent study, however, suggests that the penalty for a G-U pair adjacent to a tandem mismatch should be 1.2 +/- 0.1 kcal/mol, and the penalty for an A-U pair adjacent to a tandem mismatch should be 0.5 +/- 0.2 kcal/mol [Christiansen, M. E. and Znosko, B. M. (2008) Biochemistry 47, 4329-4336]. Therefore, the data reported here are combined with the existing thermodynamic dataset of single mismatches, and nearest neighbor parameters are derived for an A-U pair adjacent to a single mismatch (1.1 +/- 0.1 kcal/mol) and a G-U pair adjacent to a single mismatch (1.4 +/- 0.1 kcal/mol).

Thermodynamic Characterization of RNA Duplexes Containing Naturally Occurring 1 × 2 Nucleotide Internal Loops

Thermodynamic data for RNA 1 x 2 nucleotide internal loops are lacking. Thermodynamic data that are available for 1 x 2 loops, however, are for loops that rarely occur in nature. In order to identify the most frequently occurring 1 x 2 nucleotide internal loops, a database of 955 RNA secondary structures was compiled and searched. Twenty-four RNA duplexes containing the most common 1 x 2 nucleotide loops were optically melted, and the thermodynamic parameters DeltaH degrees , DeltaS degrees , DeltaG degrees 37, and TM for each duplex were determined. This data set more than doubles the number of 1 x 2 nucleotide loops previously studied. A table of experimental free energy contributions for frequently occurring 1 x 2 nucleotide loops (as opposed to a predictive model) is likely to result in better prediction of RNA secondary structure from sequence. In order to improve free energy calculations for duplexes containing 1 x 2 nucleotide loops that do not have experimental free energy contributions, the data collected here were combined with data from 21 previously studied 1 x 2 loops. Using linear regression, the entire dataset was used to derive nearest neighbor parameters that can be used to predict the thermodynamics of previously unmeasured 1 x 2 nucleotide loops. The DeltaG degrees 37,loop and DeltaH degrees loop nearest neighbor parameters derived here were compared to values that were published previously for 1 x 2 nucleotide loops but were derived from either a significantly smaller dataset of 1 x 2 nucleotide loops or from internal loops of various sizes [Lu, Z. J., Turner, D. H., and Mathews, D. H. (2006) Nucleic Acids Res. 34, 4912-4924]. Most of these values were found to be within experimental error, suggesting that previous approximations and assumptions associated with the derivation of those nearest neighbor parameters were valid. DeltaS degrees loop nearest neighbor parameters are also reported for 1 x 2 nucleotide loops. Both the experimental thermodynamics and the nearest neighbor parameters reported here can be used to improve secondary structure prediction from sequence.

Thermodynamic Characterization of Single Mismatches Found in Naturally Occurring RNA

Many naturally occurring RNA structures contain single mismatches. However, the algorithms currently used to predict RNA structure from sequence rely on a minimal set of data for single mismatches, most of which occur rather infrequently in nature. As a result, several approximations and assumptions are used to predict the stability of RNA duplexes containing the most common single mismatches. Therefore, the relative frequency of single mismatches was determined by compiling and searching a database of 955 RNA secondary structures. Thermodynamic parameters for duplex formation, derived from optical melting experiments, are reported for 28 oligoribonucleotides containing frequently occurring single mismatches. These data were then combined with previous data to construct a dataset of 64 single mismatches, including the 30 most common in the database. Because of this increase in experimental thermodynamic parameters for single mismatches that occur frequently in nature, more accurate free energy calculations have resulted. To improve the prediction of the thermodynamic parameters for duplexes containing single mismatches that have not been experimentally measured, single mismatch-specific nearest neighbor parameters were derived. The free energy of an RNA duplex containing a single mismatch that has not been thermodynamically characterized can be calculated by: DeltaG degrees 37,single mismatch = DeltaG degrees 37,mismatch nt + DeltaG degrees 37,mismatch-NN interaction + DeltaG degrees 37,AU/GU. Here, DeltaG degrees 37,mismatch is -0.4, -2.1, and -0.3 kcal/mol for A.G, G.G, and U.U mismatches, respectively; DeltaG degrees 37,mismatch-NN interaction is 0.7, -0.5, 0.4, -0.4, and -1.0 kcal/mol for 5'YRR3'/3'RRY5', 5'RYY3'/3'YYR5', 5'YYR3'/3'RYY5', 5'YRY3'/3'RYR5', and 5'RRY3'/3'YYR5' mismatch-nearest neighbor combinations, respectively, when A and G are categorized as purines (R) and C and U are categorized as pyrimidines (Y); and DeltaG degrees 37,AU/GU is a penalty of 1.2 kcal/mol for replacing a G-C base pair with either an A-U or G-U base pair. Similar predictive models were also derived for DeltaH degrees single mismatch and DeltaS degrees single mismatch. These new predictive models, in conjunction with the reported thermodynamics for frequently occurring single mismatches, should allow for more accurate calculations of the free energy of RNA duplexes containing single mismatches and, furthermore, allow for improved prediction of secondary structure from sequence.

Financial distress prediction based on OR-CBR in the principle of k-nearest neighbors

Financial distress prediction including bankruptcy prediction has called broad attention since 1960s. Various techniques have been employed in this area, ranging from statistical ones such as multiple discriminate analysis (MDA), Logit, etc. to machine learning ones like neural networks (NN), support vector machine (SVM), etc. Case-based reasoning (CBR), which is one of the key methodologies for problem-solving, has not won enough focus in financial distress prediction since 1996. In this study, outranking relations (OR), including strict difference, weak difference, and indifference, between cases on each feature are introduced to build up a new feature-based similarity measure mechanism in the principle of k-nearest neighbors. It is different from traditional distance-based similarity mechanisms and those based on NN, fuzzy set theory, decision tree (DT), etc. Accuracy of the CBR prediction method based on OR, which is called as OR-CBR, is determined directly by such four types of parameters as difference parameter, indifference parameter, veto parameter, and neighbor parameter. It is described in detail that what the model of OR-CBR is from various aspects such as its developed background, formalization of the specific model, and implementation of corresponding algorithm. With three year's real-world data from Chinese listed companies, experimental results indicate that OR-CBR outperforms MDA, Logit, NN, SVM, DT, Basic CBR, and Grey CBR in financial distress prediction, under the assessment of leave-one-out cross-validation and the process of Max normalization. It means that OR-CBR may be a preferred model dealing with financial distress prediction in China.

Nucleic Acid Unwinding by Hepatitis C Virus and Bacteriophage T7 Helicases Is Sensitive to Base Pair Stability

Helicases are motor enzymes that convert the chemical energy of NTP hydrolysis into mechanical force for motion and nucleic acid strand separation. Within the cell, helicases process a range of nucleic acid sequences. It is not known whether this composite rate of moving and opening the strands of nucleic acids depends on the base sequence. Our presteady state kinetic studies of helicases from two classes, the ring-shaped T7 helicase and two forms of non-ring-shaped hepatitis C virus (HCV) helicase, show that both the unwinding rate and processivity depend on the sequence and decrease as the nucleic acid stability increases. The DNA unwinding activity of T7 helicase and the RNA unwinding activity of HCV helicases decrease steeply with increasing base pair stability. On the other hand, the DNA unwinding activity of HCV helicases is less sensitive to base pair stability. These results predict that helicases will fall into a spectrum of modest to high sensitivity to base pair stability depending on their biological role in the cell. Modeling of the dependence provided the degree of the active involvement of helicase in base pair destabilization during the unwinding process and distinguished between passive and active mechanisms of unwinding.

Nearest Neighbor Parameters for Inosine·Uridine Pairs in RNA Duplexes

An enzyme family known as adenosine deaminases that act on RNA (ADARs) catalyzes adenosine deamination in RNA. ADARs act on RNA that is largely double-stranded and convert adenosine to inosine, resulting, in many cases, in an I x U pair. Thermodynamic parameters derived from optical melting studies are reported for a series of 14 oligoribonucleotides containing single I x U pairs adjacent to Watson-Crick pairs. In order to determine unique linearly independent nearest neighbor parameters for I x U pairs, four duplexes containing 3'-terminal I x U pairs and four duplexes containing 5'-terminal I x U pairs have also been thermodynamically characterized. This data was combined with previously published data of seven duplexes containing internal, terminal, or tandem I x U pairs from Strobel et al. [Strobel, S. A., Cech, T. R., Usman, N., and Beigelman, L. (1994) Biochemistry 33, 13824-13838] and Serra et al. [Serra, M. J., Smolter, P. E., and Westhof, E. (2004) Nucleic Acids Res. 32, 1824-1828]. On average, a duplex with an internal I x U pair is 2.3 kcal/mol less stable than the same duplex with an A-U pair, however, a duplex with a terminal I x U pair is 0.8 kcal/mol more stable than the same duplex with an A-U pair. Although isosteric with a G-U pair, on average, a duplex with an internal I x U pair is 1.9 kcal/mol less stable than the same duplex with a G-U pair, however, a duplex with a terminal I x U pair is 0.9 kcal/mol more stable than the same duplex with a G-U pair. Duplexes with tandem I x U pairs are on average 5.9 and 3.8 kcal/mol less stable than the same duplex with tandem A-U or tandem G-U pairs, respectively. Using the combined thermodynamic data and a complete linear least-squares fitting routine, nearest neighbor parameters for all nearest neighbor combinations of I x U pairs and an additional parameter for terminal I x U pairs have been derived.

A set of nearest neighbor parameters for predicting the enthalpy change of RNA secondary structure formation

A complete set of nearest neighbor parameters to predict the enthalpy change of RNA secondary structure formation was derived. These parameters can be used with available free energy nearest neighbor parameters to extend the secondary structure prediction of RNA sequences to temperatures other than 37°C. The parameters were tested by predicting the secondary structures of sequences with known secondary structure that are from organisms with known optimal growth temperatures. Compared with the previous set of enthalpy nearest neighbor parameters, the sensitivity of base pair prediction improved from 65.2 to 68.9% at optimal growth temperatures ranging from 10 to 60°C. Base pair probabilities were predicted with a partition function and the positive predictive value of structure prediction is 90.4% when considering the base pairs in the lowest free energy structure with pairing probability of 0.99 or above. Moreover, a strong correlation is found between the predicted melting temperatures of RNA sequences and the optimal growth temperatures of the host organism. This indicates that organisms that live at higher temperatures have evolved RNA sequences with higher melting temperatures.

Nearest neighbor parameters for Watson-Crick complementary heteroduplexes formed between 2'-O-methyl RNA and RNA oligonucleotides

Results from optical melting studies of Watson–Crick complementary heteroduplexes formed between 2′-O-methyl RNA and RNA oligonucleotides are used to determine nearest neighbor thermodynamic parameters for predicting the stabilities of such duplexes. The results are consistent with the physical model assumed by the individual nearest neighbor-hydrogen bonding model, which contains terms for helix initiation, base pair stacking and base pair composition. The sequence dependence is similar to that for Watson–Crick complementary RNA/RNA duplexes, which suggests that the sequence dependence may also be similar to that for other backbones that favor A-form RNA conformations.

Free Energy Simulations of Uncatalyzed DNA Replication Fidelity: Structure and Stability of T·G and dTTP·G Terminal DNA Mismatches Flanked by a Single Dangling Nucleotide

A reference system for DNA replication fidelity was studied by free energy perturbation (FEP) and linear interaction energy (LIE) methods. The studied system included a hydrated duplex DNA with the 5'-CG dangling end of the templating strand, and dCTP4-.Mg2+ or dTTP4-.Mg2+ inserted opposite the dangling G to form a correct (i.e., Watson-Crick) or incorrect (i.e., wobble) base pair, respectively. The average distance between the 3'-terminal oxygen of the primer strand and the alpha-phosphorus of dNTP was found to be 0.2 A shorter for the correct base pair than for the incorrect base pair. Binding of the incorrect dNTP was found to be disfavored by 0.4 kcal/mol relative to the correct dNTP. We estimated that improved binding and more near-attack configurations sampled by the correct base pair should translate in aqueous solution and in the absence of DNA polymerase into a six times faster rate for the incorporation of the correct dNTP into DNA. The accuracy of the calculated binding free energy difference was verified by examining the relative free energy for melting duplex DNA containing GC and GT terminal base pairs flanked by a 5' dangling C. The calculated LIE and FEP free energies of 1.7 and 1.1 kcal/mol, respectively, compared favorably with the experimental estimate of 1.4 kcal/mol obtained using the nearest neighbor parameters. To decompose the calculated free energies into additive electrostatic and van der Waals contributions and to provide a set of rigorous theoretical data for the parametrization of the LIE method, we suggested a variant of the FEP approach, for which we coined a binding-relevant free energy (BRFE) acronym. BRFE approach is characterized by its unique perturbation pathway and by its exclusion of the intramolecular energy of a rigid part of the ligand from the total potential energy.

Analysis of the secondary structure of a ribozyme that requires His as a cofactor

A novel ribozyme that requires L-histidine for expression of the function was revealed from an in vitro selection experiment. Here, we report the secondary structural analysis of the ribozyme. Several deletion and point mutants were designed based on the possible secondary structures predicted by a thermodynamic method with nearest neighbor parameters. As a result, formation of two important stems was essential for folding into the active structure.

Using an RNA secondary structure partition function to determine confidence in base pairs predicted by free energy minimization.

A partition function calculation for RNA secondary structure is presented that uses a current set of nearest neighbor parameters for conformational free energy at 37 degrees C, including coaxial stacking. For a diverse database of RNA sequences, base pairs in the predicted minimum free energy structure that are predicted by the partition function to have high base pairing probability have a significantly higher positive predictive value for known base pairs. For example, the average positive predictive value, 65.8%, is increased to 91.0% when only base pairs with probability of 0.99 or above are considered. The quality of base pair predictions can also be increased by the addition of experimentally determined constraints, including enzymatic cleavage, flavin mono-nucleotide cleavage, and chemical modification. Predicted secondary structures can be color annotated to demonstrate pairs with high probability that are therefore well determined as compared to base pairs with lower probability of pairing.

Damage characterization and damage percolation modelling in aluminum alloy sheet

Tessellation methods have been applied to characterize second-phase particle fields and the degree of clustering present in AA5754 and AA5182 automotive sheet alloys. A model of damage development within these materials has been developed using a damage percolation approach based on measured particle distributions. The model accepts tessellated particle fields in order to capture the spatial distributions of particles, as well as nearest neighbour and cluster parameter data. The model demonstrates that damage initiates and percolates within particle clusters in a stable fashion for the majority of the deformation history. Macrocracking leading to final failure occurs as a chain reaction with catastrophic void linkage triggered once linkage beyond three or more clusters of voids takes place. A parametric study has been undertaken considering subfields of larger particle fields in order to study the effect of choice of representative volume element (RVE) on ductility predictions.

Long Range Interactions and the Sense of Molecular Long Axis in Ferroelectric Smectics

The successive phase transitions in the ferro- and antiferro-electric smectics have been described by the Ising model with competing interactions. The additional pseudo-spins are introduced newly to represent the sense of the molecular long axis. By taking the sum over the whole states of these pseudo-spins in the partition function, not only the nearest neighbour parameter of the Ising model are renormalized but additional long range interactions and many-body forces are shown to be induced. The effective second nearest neighbour interaction is shown to be antiferroelectric kind and the third nearest neighbour one is ferroelectric in some cases. In the ferroelectric phase and main antiferroelectric one the sense of the molecules is arranged such that the ordering is absent even in the ordered region in agreement with the symmetry of these phases, while in the other intermediate phases this ordering is proved to exist because of the bias due to the stacking of layer-orders.

Direct observation of second neighbor interactions for Cr4+ doped forsterite by resonance Raman scattering

Fifteen Cr4+ local modes are observed using resonance Raman scattering in a Cr:Mg<thin>2SiO4 crystal, instead of a maximum of nine internal vibrations predicted by first neighbor interactions. The larger-than-predicted number of modes is explained in terms of second neighbor interactions for the Cr4+ ion. The frequency dependence of the two tetrahedral stretching modes measured at 361 and 765 cm−1 on second neighbor parameters shows a different degree of localization at the Cr<thin>4+ site for these modes.

Application of the Thermodynamic Parameters of DNA Stability Prediction to Double-Helix Formation of Deoxyribooligonucleotides

Abstract The energetics of a double helix formation of deoxyribooligonucleotides has been studied by measuring optical melting curves and calculating thermodynamic values based on the nearest neighbor model and parameters. The results show that, though the model is valid, the values of the nearest-neighbor thermodynamic parameters reported previously should be improved for some base pairs in order to predict more precisely the stability of the double helix of the oligomers by the parameters.

Relationship between Structure and Function of Nucleic Acids: The Study Using Nearest Neighbor Parameters.

Structure and function of nucleic acids are well known to be dependent on their base sequences. Current predictions of the structure stability of nucleic acids from thermodynamic parameters for formation of base pairs depend largely on a nearest neighbor model. However, it has not been tested whether the published values of the nearest neighbor parameters for DNA are valid. In this paper, the published parameters are discussed, new parameters are present, and the new ones are applied to the prediction of the mechanism of the recombination and dissociation of DNA double helices.

Improvement of the shape-memory effect properties of copper alloys by optimization of the heat-treatment regimen

Review of engineering methods for the heat treatment of copper alloys with a thermoelastic martensitic transformation, particularly alloys belonging to the Cu-Al-Zn, Cu-Al-Mn, and Cu-Al-Ni systems. The effectiveness of utilizing a multifactor experiment based on the mathematical theory of experimental design in order to determine the optimum heat-treatment regimen for copper alloys possessing the shape-memory effect (SME) with neighboring martensitic transformation parameters is shown. The basic structural and phase changes produced by heat treatment which lead to a strengthening of the SME are elucidated. 20 refs., 1 fig., 3 tabs.

Magnetic susceptibility and electron spin resonance of Cd 1−zMn zTe 1−ySe y alloys with z⩾0.85

Cd 1− z Mn z Te 1− y Se y alloys which exhibit antiferromagnetic behaviour (in the region z ⩾ 0.85, 0 ⩽ y ⩽ 1.0) are studied as a function of temperature by means of magnetic susceptibility and electron spin resonance (ESR). For y ⩾ 0.6 the low temperature susceptibility results are interpreted in terms of structural phase transitions from cubic NaCl type phase to hexagonal NiAs type. The transitions in the Cd 1− z Mn z Se alloys are strongly influenced by the substitution of Cd for Mn. The susceptibility and ESR results obtained in the MnTe 1− y Se y alloys allow the phase diagram of Panson and Johnston to be extended to low temperatures. In the resonance work the Mn 2+ ESR linewidth Δ H is measured in the range T N ⩽ T ⩽ 500 K. The Δ H vs. T curves for y⩾0.6 are analyzed in terms of a critical effect near T N and a paramagnetic effect at high temperature. The variation with alloy composition of T N and the Curie-Weiss temperature θ are interpreted in terms of a nearest neighbour (90° interaction) exchange parameters J 1 and next-nearest neighbour (180° interaction) parameter J 2. It is found that ¦ J 2¦ > ¦ J 1¦ in the samples with y ⩾ 0.6, and that J 1 changes sign when the results for MnTe 1− y Se y are extrapolated to a hypothetical MnTe in the NaCl type structure.

Phase stability investigations of the palladium-cadmium system: part i. thermodynamic studies

The vapor pressure of cadmium in palladium-cadmium alloys was determined between 830 and 1350 K and between 33 and 65 at. pct Cd by two different isopiestic methods. An analysis of the resulting partial molar quantities of Cd in the β1-phase in terms of Chang's theoretical model for the Ll0-structure yielded a disorder parameter α= 7 × 10-4 and a second-nearest neighbor parameter η = 0.75 at 1073 K. Available literature data for the thermodynamic activities of Cd in the α-phase (solid solution of Cd in Pd) were evaluated using a subregular solution model. By combining these values with the present experimental data, all relevant partial and integral thermodynamic properties for the α- and β1-phase could be derived. At the stoichiometric composition of the β1-phase, values of ΔG = -38.0 kJ(g-atom)-1 and ΔH = -53.7 kJ(g-atom)-1, referred to Pd(s) and Cd(l), were obtained for a temperature of 1073 K.