Number Of Backbones Research Articles

Innovation Model of College Education Based on Nonlinear Random Matrix Organization and Management

At present, the scientific research and innovation team in colleges and universities has become an important carrier for the development of science and technology and personnel training in China, but in terms of its development status, the role of the scientific research and innovation team has not been really brought into play. Most colleges and universities only have the organizational form of scientific research and innovation teams. Too many scientific research tasks still rely on a small number of backbones. The cohesion of the team is not enough, and the combined force of the team is not manifested. In production practice, more and more high-dimensional data with dimension p approaching or even exceeding the number of samples n are collected and stored. Unlike traditional data analysis, high-dimensional data analysis is more complex and difficult. Layer of scientific research and innovation teams in colleges and universities is often ignored by managers, which is manifested by ignoring the cultural construction of the team. In the eyes of team managers, the time spent on building a team culture is far less than the time it takes to do a few more scientific experiments. University scientific research and innovation team is a multi-level network system. The asymptotic and nonasymptotic theories of random matrices break the framework of classical multivariate statistical analysis and are very suitable for the study of statistical characteristics of high-dimensional data, which can help machine learning algorithms to complete the analysis of high-dimensional data and expand its application range. The research and innovation team in colleges and universities is deeply analyzed from the perspective of nonlinearity. It is believed that the scientific research and innovation team in colleges and universities is a complex nonlinear system in terms of scientific research objects-interdisciplinary research, or from the perspective of personnel composition. Correspondingly, the construction should be considered from a nonlinear perspective in the process, following the systematic, integral, and multi-dimensional characteristics of nonlinear systems. Specifically applied to the construction of the team, first, from a macro perspective, three principles should be paid attention to at the beginning of the creation of the team, and then the specific application should be explained in detail. It is hoped that a new perspective will be put forward in the construction of scientific research innovation teams in colleges and universities to better promote the development of teams.

Energy Density Enhancement of Stacked Switched Capacitor Energy Buffers Through Capacitance Ratio Optimization

The recently proposed stacked switched capacitor (SSC) energy buffer architecture can extend the lifetime of single-phase ac–dc converters by replacing the electrolytic capacitors needed for twice-line-frequency energy storage with film or ceramic capacitors, while maintaining comparable effective energy density. This paper presents a methodology for further increasing the effective energy density of SSC energy buffers by optimizing the capacitance ratios of the capacitors used in the energy buffer. It is systematically shown that the relative enhancement in effective energy density depends on the required ripple ratio and the number of backbone and supporting capacitors in the energy buffer. The proposed approach can substantially increase the effective energy density of the energy buffer. For example, the effective energy density of a 1-10 enhanced unipolar SSC energy buffer, designed for a 10% ripple ratio, can be increased by 100% as a result of this capacitance ratio optimization. The presented methodology is validated using a 1-2 enhanced unipolar SSC energy buffer designed for an 8-W offline LED driver.

Combs and Bottlebrushes in a Melt

We use a combination of the coarse-grained molecular dynamics simulations and scaling analysis to study conformations of bottlebrush and comb-like polymers in a melt. Our analysis shows that a crossover between comb and bottlebrush regimes is controlled by the crowding parameter, Φ, describing overlap between neighboring macromolecules. In comb-like systems characterized by a sparse grafting of side chains (Φ < 1), the side chains and backbones belonging to neighboring macromolecules interpenetrate. However, in bottlebrushes with densely grafted side chains (Φ ≥ 1), the interpenetration between macromolecules is suppressed by steric repulsion between side chains. In this regime, bottlebrush macromolecules can be viewed as filaments with diameter proportional to size of the side chains. For flexible side chains, the crowding parameter is given by Φ ≈ [v/(lb)3/2][(nsc/ng + 1)/nsc1/2], which depends on both the architectural parameters (degree of polymerization of the side chains, nsc, and number of backbone...

Research on the Solution Space of 2-SAT and Max-2-SAT

We study the properties of 2-SAT and Max-2-SAT problems by analyzing the node adding process on the factor graph. Two important structures, backbones and mutual-determinations are investigated, and the reduced solution graph for the expression of solution space of 2-SAT and Max-2-SAT is defined. For 2-SAT problem, a complete evolution process for the reduced graph is discussed and corresponding algorithm is obtained. For the Max-2-SAT problem, the analysis shows it’s backbone number can evolve in a much harder way by which it can increase or decrease. The research in this paper provide a new view point for understanding the solution space of 2-SAT and Max-2-SAT, which will be benefit for recognizing the complexity nature of the NP-hard problems.

Enumeration of RNA complexes via random matrix theory

In the present article, we review a derivation of the numbers of RNA complexes of an arbitrary topology. These numbers are encoded in the free energy of the Hermitian matrix model with potential V(x)=x2/2-stx/(1-tx), where s and t are respective generating parameters for the number of RNA molecules and hydrogen bonds in a given complex. The free energies of this matrix model are computed using the so-called topological recursion, which is a powerful new formalism arising from random matrix theory. These numbers of RNA complexes also have profound meaning in mathematics: they provide the number of chord diagrams of fixed genus with specified numbers of backbones and chords as well as the number of cells in Riemann's moduli spaces for bordered surfaces of fixed topological type.

Identifying Factors Controlling Protein Release from Combinatorial Biomaterial Libraries via Hybrid Data Mining Methods

Polyanhydrides are a class of degradable biomaterials that have shown much promise for applications in drug and vaccine delivery. Their properties can be tailored for controlled drug release, drug/protein stability, and immune regulation (adjuvant effect). Identifying the relationship between the molecular structures of the polymers and the drug release kinetics profiles would help understand the release mechanism and aid in the accurate prediction of drug release and the rational design of polymer-based drug carrier systems. The molecular structure descriptors that had the most impact on the release kinetics were identified using a prediction/optimization data mining approach. Using this new approach for modeling nonlinear release kinetics behavior, we determined that the descriptors which had the greatest effect on the release kinetics were the number of backbone -COO- nonconjugated bonds, the number of aromatic rings, and the number of -CH₂- bonds.

Acid-Induced Equilibrium Folding Intermediate of Human Platelet Profilin

The acid-induced unfolding of human platelet profilin (HPP) can be minimally modeled as a three-state process. Equilibrium unfolding studies have been performed on human platelet profilin1 (HPP) and monitored by far-UV circular dichroism, tryptophan fluorescence, ANS binding, and NMR spectroscopy. Far-UV CD measurements obtained by acid titration demonstrate that HPP unfolds via a three-state mechanism (N --> I --> U), with a highly populated intermediate between pH 4 and 5. Approximately 80% of native helical secondary structural content remains at pH 4, as indicated by monitoring the CD signal at 222 nm. The stability (DeltaGH2O) of the native conformation at pH 7.0 (obtained by monitoring the change in tryptophan signal as a function of urea concentration) is 5.56 +/- 0.51 kcal mol-1; however, the DeltaGH2O for the intermediate species at pH 4 is 2.01 +/- 0.47 kcal mol-1. The calculated m-values for the pH 7.0 and pH 4.0 species were 1.64 +/- 0.15 and 1.34 +/- 0.17 kcal mol-1 M-1, respectively, which is an indication that the native and intermediate species are similarly compact. Additionally, translational diffusion measurements obtained by NMR spectroscopy and ANS binding studies are consistent with a globular and compact conformation at both pH 7.0 and 4.0. The pKa values for the two histidine (His) residues located on helix 4 of HPP were determined to be 5.6 and 5.7 pH units. These pKa values coincide with the midpoint of the far-UV CD acid titration curve and suggest that the protonation of one or both His residues may play a role in the formation of the unfolding intermediate. Stable intermediate species populate the 2D 1H-15N HSQC NMR spectra between pH 4 and 5. A number of backbone and side-chain resonances show significant perturbations relative to the native spectrum; however, considerable nativelike tertiary contacts remain. Interestingly, the residues on HPP that are significantly altered at low pH coincide with segments of the G-actin binding surface and poly-l-proline binding interface. The earlier reports that a decrease in pH below 6.0 induces structural alterations in profilin, favoring dissociation of the profilin-actin complex, corresponds with the structural alterations observed in the partially unfolded species. Our findings suggest that a novel mechanism for pH induced disruption of the profilin-G-actin complex involve a nativelike unfolding intermediate of profilin.

Identification of Quantitative Traits Loci (QTL) Affecting Growth Traits in Pigs

Molecular genetic markers were used to detect chromosomal regions which contain economically important traits such as growth, carcass, and meat quality traits in pigs. A three generation resource population was constructed from a cross between Korean native boars and Landrace sows. A total of 240 F2 animals from intercross of F1 was produced. Phenotypic data on 17 traits, birth weight, body weights at 3, 5, 12, and 30 weeks of age, teat number, carcass weight, backfat thickness, body fat, backbone number, muscle pH, meat color, drip loss, cooking loss, water holding capacity, shear force, and intramuscular fat content were collected for F2 animals. Animals including grandparents (F0), parents (F1), and offspring (F2) were genotyped for 80 microsatellite markers covering from chromosome 1 to 10. Least squares regression interval mapping was used for quantitative trait loci (QTL) identification. Significance thresholds were determined by permutation tests. A total of 10 QTL were detected at 5% chromosome-wide significance levels for growth traits on SSCs 2, 4, 5, 6, and 8. (Asian-Aust. J. Anim. Sci. 2005. Vol 18, No. 11 : 1524-1528)