The H\"older-Poincar\'e Duality for Lq,pL_{q,p}-cohomology

We prove the following version of Poincare duality for reduced $L_{q,p}$-cohomology: For any $1<q,p<\infty$, the $L_{q,p}$-cohomology of a Riemannian manifold is in duality with the interior $L_{p',q'}-cohomology for$1/p+1/p'=1$,$1/q+1/q'=1$.Comment: 21 page

Transport anomaly at the ordering transition for adatoms on graphene

We analyze a manifestation of the partial ordering transition of adatoms on graphene in resistivity measurements. We find that Kekule mosaic ordering of adatoms increases sheet resistance of graphene, due to a gap opening in its spectrum, and that critical fluctuations of the order parameter lead to a non-monotonic temperature dependence of resistivity, with a cusp-like minimum at T=T_c.Comment: 4 pages, 1 figur

Effect of &sigma;-Phase on the Strength, Stress Relaxation Behavior, and Corrosion Resistance of an Ultrafine-Grained Austenitic Steel AISI 321

This paper reported the results of research into the effect of Equal Channel Angular Pressing (ECAP) temperature and 1-h annealing temperature on mechanical properties, stress-relaxation resistance, and corrosion resistance of austenitic steel AISI 321L with strongly elongated thin &delta;-ferrite particles in its microstructure. The formation of &alpha;&prime;-martensite and fragmentation of austenite grains takes place during ECAP. Ultrafine-grained (UFG) steels demonstrate increased strength. However, we observed a reduced Hall&ndash;Petch coefficient as compared with coarse-grained (CG) steels due to the fragmentation of &delta;-ferrite particles. UFG steel specimens were found to have 2&ndash;3 times higher stress-relaxation resistance as compared with CG steels. For the first time, the high stress-relaxation resistance of UFG steels was shown to stem from a internal stress-relaxation mechanism, i.e., the interaction of lattice dislocations with non-equilibrium grain boundaries. Short-time 1-h annealing of UFG steel specimens at 600&ndash;800 &deg;C was found to result in the nucleation of &sigma;-phase nanoparticles. These nanoparticles affect the grain boundary migration, raise strength, and stress-relaxation resistance of steel but reduce the corrosion resistance of UFG steel. Lower corrosion resistance of UFG steel was shown to be related to the formation of &alpha;&prime;-martensite during ECAP and the nucleation of &sigma;-phase particles during annealing

Developing high strain rate superplasticity in Al-Mg-Sc-Zr alloys using equal-channel angular pressing

The processing of metallic alloys through the procedure of equal-channel angular pressing (ECAP) provides an opportunity for achieving superplastic ductilities at very high strain rates. This paper reports experimental data from an investigation of a series of Al---Mg---Sc---Zr alloys processed by ECAP. The results show the occurrence of high tensile ductilities at testing strain rates above 10?2 s?1. <br/

High Performance Fine-Grained Biodegradable Mg-Zn-Ca Alloys Processed by Severe Plastic Deformation

The tensile strength, fatigue, and corrosion fatigue performance of the magnesium alloy ZX40 benefit strongly from hybrid deformation processing involving warm equal-channel angular pressing (ECAP) at the first step and room temperature rotary swaging at the second. The general corrosion resistance improved as well, though to a lesser extent. The observed strengthening is associated with a combined effect of substantial microstructure refinement down to the nanoscale, reducing deformation twinning activity, dislocation accumulation, and texture transformation. The ultimate tensile strength and the endurance limit in the ultrafine-grained material reached or exceeded 380 and 120 MPa, respectively, which are remarkable values for this nominally low strength alloy

High Performance Fine-Grained Biodegradable Mg-Zn-Ca Alloys Processed by Severe Plastic Deformation

The tensile strength, fatigue, and corrosion fatigue performance of the magnesium alloy ZX40 benefit strongly from hybrid deformation processing involving warm equal-channel angular pressing (ECAP) at the first step and room temperature rotary swaging at the second. The general corrosion resistance improved as well, though to a lesser extent. The observed strengthening is associated with a combined effect of substantial microstructure refinement down to the nanoscale, reducing deformation twinning activity, dislocation accumulation, and texture transformation. The ultimate tensile strength and the endurance limit in the ultrafine-grained material reached or exceeded 380 and 120 MPa, respectively, which are remarkable values for this nominally low strength alloy

High strength and fatigue properties of Mg-Zn-Ca alloys after severe plastic deformation

Magnesium alloys are the lightest metallic structural materials with an outstanding specific strength. This makes them appealing for a wide range of applications in “green” transportation where weight saving is of major concern. Another emerging application area for modern Mg-based alloys is in the biomedical domain where they are considered as bioabsorbable temporary implants, and where the worldwide market is expanding particularly rapidly in parallel with the surging research. Requirements for mechanical properties - strength, ductility and fatigue resistance - of implants in orthopaedics are stringent. Therefore, a broad variety of processing routes have been proposed in the past decade to tailor the microstructure in order to optimize the properties. In the present brief communication, we demonstrate that using a hybrid deformation processing schedule involving warm equal-channel angular pressing (ECAP) on the first stage and cold rotary swaging on the second dramatically improves the tensile and fatigue properties of the magnesium alloy ZX40. Due to a combined effect of significant grain refinement and dislocation storage after rotary swaging, the ultimate tensile strength and the conventional fatigue limit achieved very high values (for this class of alloys) of 380 MPa and 115 MPa, respectively. Preliminary results of the microstructural investigations are discussed briefly

Current Approaches in Supersecondary Structures Investigation

Proteins expressed during the cell cycle determine cell function, topology, and responses to environmental influences. The development and improvement of experimental methods in the field of structural biology provide valuable information about the structure and functions of individual proteins. This work is devoted to the study of supersecondary structures of proteins and determination of their structural motifs, description of experimental methods for their detection, databases, and repositories for storage, as well as methods of molecular dynamics research. The interest in the study of supersecondary structures in proteins is due to their autonomous stability outside the protein globule, which makes it possible to study folding processes, conformational changes in protein isoforms, and aberrant proteins with high productivity

Effect of Sc, Hf, and Yb Additions on Superplasticity of a Fine-Grained Al-0.4%Zr Alloy

This research was undertaken to study the way deformation behaves in ultrafine-grained (UFG)-conducting Al-Zr alloys doped with Sc, Hf, and Yb. All in all, eight alloys were studied with zirconium partially replaced by Sc, Hf, and/or Yb. Doping elements (X = Zr, Sc, Hf, Yb) in the alloys totaled 0.4 wt.%. The choice of doping elements was conditioned by the possible precipitation of Al3X particles with L12 structure in the course of annealing these alloys. Such particles provide higher thermal stability of a nonequilibrium UFG microstructure. Initial coarse-grained samples were obtained by induction casting. A UFG microstructure in the alloys was formed by equal-channel angular pressing (ECAP) at 225 °C. Superplasticity tests were carried out at temperatures ranging from 300 to 500 °C and strain rates varying between 3.3 × 10−4 and 3.3 × 10−1 s−1. The highest values of elongation to failure are observed in Sc-doped alloys. A UFG Al-0.2%Zr-0.1%Sc-0.1%Hf alloy has maximum ductility: at 450 °C and a strain rate of 3.3 × 10−3 s−1, relative elongation to failure reaches 765%. At the onset of superplasticity, stress (σ)–strain (ε) curves are characterized by a stage of homogeneous (uniform) strain and a long stage of localized plastic flow. The dependence of homogeneous (uniform) strain (εeq) on test temperature in UFG Sc-doped alloys is increasing uniformly, which is not the case for other UFG alloys, with εeq(T) dependence peaking at 350–400 °C. The strain rate sensitivity coefficient of flow stress m is small and does not exceed 0.26–0.3 at 400–500 °C. In UFG alloys containing no Sc, the m coefficient is observed to go down to 0.12–0.18 at 500 °C. It has been suggested that lower m values are driven by intensive grain growth and pore formation in large Al3X particles, which develop specifically at an ingot crystallization stage

Managing of Unassigned Mass Spectrometric Data by Neural Network for Cancer Phenotypes Classification

Mass spectrometric profiling provides information on the protein and metabolic composition of biological samples. However, the weak efficiency of computational algorithms in correlating tandem spectra to molecular components (proteins and metabolites) dramatically limits the use of “omics” profiling for the classification of nosologies. The development of machine learning methods for the intelligent analysis of raw mass spectrometric (HPLC-MS/MS) measurements without involving the stages of preprocessing and data identification seems promising. In our study, we tested the application of neural networks of two types, a 1D residual convolutional neural network (CNN) and a 3D CNN, for the classification of three cancers by analyzing metabolomic-proteomic HPLC-MS/MS data. In this work, we showed that both neural networks could classify the phenotypes of gender-mixed oncology, kidney cancer, gender-specific oncology, ovarian cancer, and the phenotype of a healthy person by analyzing ‘omics’ data in ‘mgf’ data format. The created models effectively recognized oncopathologies with a model accuracy of 0.95. Information was obtained on the remoteness of the studied phenotypes. The closest in the experiment were ovarian cancer, kidney cancer, and prostate cancer/kidney cancer. In contrast, the healthy phenotype was the most distant from cancer phenotypes and ovarian and prostate cancers. The neural network makes it possible to not only classify the studied phenotypes, but also to determine their similarity (distance matrix), thus overcoming algorithmic barriers in identifying HPLC-MS/MS spectra. Neural networks are versatile and can be applied to standard experimental data formats obtained using different analytical platforms