Search

High-entropy alloys are promising materials for novel thin-film resistors since they have high resistivity and a low-temperature coefficient of resistivity (TCR). In this work, a new high-entropy thin-film CoCrFeNiTix was deposited on a Si/SiO2 substrate by means of magnetron sputtering of the multi-component target produced by hot pressing of the powder mixture. The samples possessed a thickness of 130–230 nm and an amorphous atomic structure with nanocrystallite traces. This structure persisted after being annealed up to 400 °C, which was confirmed using X-ray and electron diffraction. The film had a single-phase structure with a smooth surface and a uniform distribution of all elements. The obtained film served for microresistor elaboration, which was produced using the lithography technique and tested in a temperature range from −60 °C up to 200 °C. Resistivity at room temperature was estimated as 2.37 μOhm·m. The results have demonstrated that TCR depends on temperature according to the simple linear law in a range from −60 °C up to 130 °C, changing its value from −78 ppm/°C at low temperatures to −6.6 ppm/°C at 130 °C. Such characteristics show the possibility of using these high-entropy alloy films for resistive elements in contemporary and future micro-electronic devices.

The ordered Ca3TaGa3Si2O14 and disordered La3Ga5SiO14 crystals of the lantangallium silicate family were grown by the Czochralski method. The independent coefficients of thermal expansion of crystals αc and αa were determined by X-ray powder diffraction based on the analysis of X-ray diffraction spectra measured in the temperature range of 25÷1000°C. It is shown that in the temperature range of 25÷800°C the thermal expansion coefficients are linear. At temperatures above 800°C there is a nonlinear character of the thermal expansion coefficients associated with a decrease in the Ga content in the crystal lattice of the lantangallium silicate family crystals.

Social stressors produce neurobiological and emotional consequences in social species. Environmental interventions, such as environmental enrichment and exercise, may modulate physiological and behavioral stress responses. The present study investigated the benefits of environmental enrichment and exercise against social stress in the socially monogamous prairie vole. Female prairie voles remained paired with a sibling (control) or were isolated from a sibling for 4 weeks. The isolated groups were separated into isolated sedentary, isolated with environmental enrichment, and isolated with both enrichment and exercise conditions. Behaviors related to depression, anxiety, and sociality were investigated using the forced swim test (FST), elevated plus maze (EPM), and a social crowding stressor (SCS), respectively. cFos expression was evaluated in stress-related circuitry following the SCS. Both enrichment and enrichment with exercise protected against depression-relevant behaviors in the FST and social behavioral disruptions in the SCS, but only enrichment with exercise protected against anxiety-related behaviors in the EPM and altered cFos expression in the hypothalamic paraventricular nucleus in isolated prairie voles. Enrichment may alleviate emotion-related and social behaviors, however physical exercise may be an important component of environmental strategies for protecting against anxiety-related behaviors and reducing neural activation as a function of social stress.

With increasing rates of anxiety and mood disorders across the world, there is an unprecedented need for preclinical animal models to generate translational results for humans experiencing disruptive emotional symptoms. Considering that life events resulting in a perception of loss are correlated with depressive symptoms, the enrichment-loss rodent model offers promise as a translational model for stress-initiated psychiatric disorders. Additionally, predisposed temperament characteristics such as coping styles have been found to influence an individual's stress response. Accordingly, male rats were profiled as either consistent or flexible copers and assigned to one of three environments: standard laboratory housing, enriched environment, or enriched environment exposure followed by downsizing to standard laboratory cages (i.e., enrichment-loss group). Throughout the study, several behaviors were assessed to determine stress, social, and reward-processing responses. To assess recovery of the stress response, fecal samples were collected following the swim stress in 3-h increments to determine the recovery trajectory of corticosterone (CORT) and dehydroepiandrosterone (DHEA) metabolite levels. Upon death, neural markers of neuroplasticity including doublecortin, glial fibrillary acidic factor, and brain-derived neurotrophic factor were assessed via immunohistochemistry. Results indicated the flexible coping animals in the continuous enriched group had higher DHEA/CORT ratios (consistent with adaptive responses in past research); furthermore, the enrichment-loss animals exhibited a blunted CORT response throughout the assessments and enriched flexible copers had faster CORT recovery rates than consistent copers. Standard housed animals exhibited less exploratory behavior in the open field task and continuous enriched, flexible rats consumed more food rewards than the other groups. No differences in neuroplasticity neural markers were observed. In sum, the results of the present study support past research indicating the disruptive consequences of enrichment-loss, providing evidence that the model represents a valuable approach for the investigation of neurobiological mechanisms contributing to interindividual variability in responses to changing experiential landscapes.

Zinc plant residue (ZPR) is a secondary material generated during hydrometallurgical zinc production that contains considerable contents of valuable elements such as Zn, Cu, Fe, Pb, Cd, Ag, In, Ga, Tl. Zinc, copper and accompanying elements in ZPR are in different minerals, mainly in the ferrites. A promising approach for recycling ZPR is the sulfating roasting using iron sulfates followed by water leaching. In this study, the composition of ZPR and the obtained products were thoroughly investigated by various methods including X-ray diffraction analysis (XRD), chemical phase analysis and Mössbauer spectroscopy. The effect of temperature, amount of iron sulfates and roasting time on the conversion of valuable metals into a water-soluble form was thermodynamically and experimentally studied both using pure ferrites and ZPR. Based on the results of time-resolved XRD analysis and synchronous thermal analysis (STA), a mechanism of the sulfation roasting was elucidated. The rate-controlling step of zinc and copper sulfation process during the ZPR roasting was estimated. The sulfating roasting at 600 °C during 180 min with the optimal Fe2(SO4)3∙9H2O addition followed by water leaching enables to recover 99% Zn and 80.3% Cu, while Fe, Pb, Ag, In, Ga retained almost fully in the residue.

One of the first steps during the investigation of geological objects is the interwell correlation. It provides information on the structure of the objects under study, as it comprises the framework for constructing geological models and assessing hydrocarbon reserves. Today, the detailed interwell correlation relies on manual analysis of well-logging data. Thus, it is time-consuming and of a subjective nature. The essence of the interwell correlation constitutes an assessment of the similarities between geological profiles. There were many attempts to automate the process of interwell correlation by means of rule-based approaches, classic machine learning approaches, and deep learning approaches in the past. However, most approaches are of limited usage and inherent subjectivity of experts. We propose a novel framework to solve the geological profile similarity estimation based on a deep learning model. Our similarity model takes well-logging data as input and provides the similarity of wells as output. The developed framework enables (1) extracting patterns and essential characteristics of geological profiles within the wells and (2) model training following the unsupervised paradigm without the need for manual analysis and interpretation of well-logging data. For model testing, we used two open datasets originating in New Zealand and Norway. Our data-based similarity models provide high performance: the accuracy of our model is $0.926$ compared to $0.787$ for baselines based on the popular gradient boosting approach. With them, an oil\&gas practitioner can improve interwell correlation quality and reduce operation time.

The article deals with the concept of a smart city, a conceptual scheme of the advanced system of environmental management of the city is given, features of geographic information systems in solving problems of environmental monitoring are presented.

In this work we consider Monteiro - Svaiter accelerated hybrid proximal extragradient (A-HPE) framework and accelerated Newton proximal extragradient (A-NPE) framework. The last framework contains an optimal method for rather smooth convex optimization problems with second-order oracle. We generalize A-NPE framework for higher order derivative oracle (schemes). We replace Newtons type step in A-NPE that was used for auxiliary problem by Newtons regularized (tensor) type step (Yu. Nesterov, 2018). Moreover we generalize large step A-HPE/A-NPE framework by replacing Monteiro - Svaiters large step condition so that this framework could work for high-order schemes. The main contribution of the paper is as follows: we propose optimal highorder methods for convex optimization problems. As far as we know for that moment there exist only zero, first and second order optimal methods that work according to the lower bounds. For higher order schemes there exists a gap between the lower bounds (Arjevani, Shamir, Shiff, 2017) and existing high-order (tensor) methods (Nesterov - Polyak, 2006; Yu.Nesterov, 2008; M. Baes, 2009; Yu.Nesterov, 2018). Asymptotically the ratio of the rates of convergences for the best existing methods and lower bounds is about 1.5. In this work we eliminate this gap and show that lower bounds are tight. We also consider rather smooth strongly convex optimization problems and show how to generalize the proposed methods to this case. The basic idea is to use restart technique until iteration sequence reach the region of quadratic convergence of Newton method and then use Newton method. One can show that the considered method converges with optimal rates up to a logarithmic factor. Note, that proposed in this work technique can be generalized in the case when we cant solve auxiliary problem exactly, moreover we cant even calculate the derivatives of the functional exactly. Moreover, the proposed technique can be generalized to the composite optimization problems and in particular to the constraint convex optimization problems. We also formulate a list of open questions that arise around the main result of this paper (optimal universal method of high order e.t.c.).

Decentralized optimization methods have been in the focus of optimization community due to their scalability, increasing popularity of parallel algorithms and many applications. In this work, we study saddle point problems of sum type, where the summands are held by separate computational entities connected by a network. The network topology may change from time to time, which models real-world network malfunctions. We obtain lower complexity bounds for algorithms in this setup and develop near-optimal methods which meet the lower bounds.

We study the problem of decentralized optimization with strongly convex smooth cost functions. This paper investigates accelerated algorithms under time-varying network constraints. In our approach, nodes run a multi-step gossip procedure after taking each gradient update, thus ensuring approximate consensus at each iteration. The outer cycle is based on accelerated Nesterov scheme. Both computation and communication complexities of our method have an optimal dependence on global function condition number \(\kappa _g\). In particular, the algorithm reaches an optimal computation complexity \(O(\sqrt{\kappa _g}\log (1/\varepsilon ))\).

Ferroelectric LiNb

BackgroundBacillus anthracis is a causal agent of a zoonotic disease relevant for many countries, and is an agent of bioterrorism. Meanwhile, the reasons for the dependence on tryptophan of some strains with altered virulence have not been established with an almost complete absence of information on the tryptophan operon of this pathogen. In this study, we report gene variability and the structure of the tryptophan operon in B. anthracis strains of the three main lineages.ResultsFor in silico analysis we used 112 B. anthracis genomes, including 68 of those available at the GenBank database and 44 sequenced at our institute. The B. anthracis tryptophan operon has an ancestral structure with a complete set of seven partially overlapping genes. The results show that the variability of all seven tryptophan operon genes is determined by the presence of single nucleotide polymorphisms and InDels. The trpA genes of strains of the main lineage B and trpG genes of strains of the C lineage are pseudogenes and the proteomes lack the corresponding enzymes of the biosynthetic pathway, which may explain the dependence of the strains of line B on tryptophan. ConclusionIn this study, the differences in tryptophan operon genes for B. anthracis strains belonging to different main lineages were demonstrated for the first time. Mutation in the gene of the tryptophan synthase subunit alpha can explain the dysfunction of this enzyme and the dependence on tryptophan in strains of the main lineage B. Identified features suggest a further study of the dependence on tryptophan in B. anthracis strains of the main lineage B and may be of interest from the point of view of intraspecific evolution of the anthrax pathogen.

In this paper we discuss lower bounds for convergence of convex optimization methods of high order and attainability of this bounds. We formulate a hypothesis that covers all the cases. It is noticeable that we provide this statement without a proof. Newton method is the most famous method that uses gradient and Hessian of optimized function. However, it converges locally even for strongly convex functions. Global convergence can be achieved with cubic regularization of Newton method [Nesterov, Polyak, 2006], whose iteration cost is comparable with iteration cost of Newton method and is equivalent to inversion of Hessian of optimized function. Yu.Nesterov proposed accelerated variant of Newton method with cubic regularization in 2008 [Nesterov, 2008]. R.Monteiro and B. Svaiter managed to improve global convergence of cubic regularized method in 2013 [Monteiro, Svaiter, 2013]. Y.Arjevani, O. Shamir and R. Shiff showed that convergence bound of Monteiro and Svaiter is optimal (cannot be improved by more than logarithmic factor with any second order method) in 2017 [Arjevani et al., 2017]. They also managed to find bounds for convex optimization methods of p-th order for $p 2$. However, they got bounds only for first and second order methods for strongly convex functions. In 2018 Yu.Nesterov proposed third order convex optimization methods with rate of convergence that is close to this lower bounds and with similar to Newton method cost of iteration [Nesterov, 2018]. Consequently, it was showed that high order methods can be practical. In this paper we formulate lower bounds for p-th order methods for $p 3$ for strongly convex unconstrained optimization problems. This paper can be viewed as a little survey of state of the art of high order optimization methods.

Summary Background: marker assisted selection methods of sheep require the identification of genes that positively and negatively affect meat quality. Genes with high expression levels could have the greatest impact on growth and structure of muscle fibers. Objective: this study evaluated the expression of genes in the loin muscle of Dzhalginsky Merino sheep. Methods: reverse transcription-quantitative real-time PCR (RT-qPCR) was used to investigate the expression of 48 genes in the loin muscle of Dzhalginsky Merino sheep bred in Russia. Results: genes GAPDH, PYGM, CAST, ATP5G1, CAPN3, SOD1, VEGFA, CALM2, YWHAZ, ASIP, MYOD1, CAPN1, GHR, OXTR, BEGAIN, SLC2A3, and SS18L2 showed the highest expression. The group of genes with a medium level of expression included ATOX1, BAMBI, TLR6, IGF2, FOS, FST, GGTA2P, C-MET, FGF5, ACVR2A, CAPN2, GH, DGAT1, and IGF1. Low levels of expression were identified for genes ABCG2, SPP2, PYGL, PPARG2, TGFB1, CXCR4, MSTN, CYP2J, LEPR, CDKN1A, IGFBP4, and SERT. Trace expression was detected in genes SST, TSHR, GDF9, FGF7 and BMP15. Significant correlation between expression level and live weight was observed for most of the investigated genes. Conclusion: our results demonstrate the feasibility of using these newly identified candidate genes as genetic markers in sheep. Keywords: growth traits, marker assisted selection (MAS), microarray analysis, transcription. Resumen Antecedentes: los metodos de seleccion asistida de ovejas a traves de marcadores requieren la identificacion de los genes que afectan positiva o negativamente la calidad de la carne. Los genes con niveles mas altos de expresion podrian tener mayor impacto en el crecimiento y estructura de las fibras musculares. Objetivo: evaluar la expresion de los genes en el musculo del lomo de carneros de la raza Dzhalginsky Merino. Metodos: se utilizo RT-PCR cuantitativa en tiempo real (RT-qPCR) para investigar la expresion de 48 genes en el musculo del lomo de ovejos raza Merino Dzhalginsky criados en Rusia. Resultados: los genes GAPDH, PYGM, CAST, ATP5G1, CAPN3, SOD1, VEGFa, CALM2, YWHAZ, ASIP, MYOD1, CAPN1, GHR, OXTR, BEGAIN, SLC2A3 y SS18L2 mostraron la mas alta expresion. El grupo de genes con un nivel medio de expresion incluyo ATOX1, BAMBI, TLR6, IGF2, FOS, FST, GGTA2P, C-MET, FGF5, ACVR2A, CAPN2, GH, DGAT1 y IGF1. Se identificaron bajos niveles de expresion en los genes ABCG2, SPP2, PYGL, PPARG2, TGFB1, CXCR4, NTCR, CYP2J, LEPR, CDKN1A, IGFBP4 y SERT. Expresion traza fue detectada en los genes SST, TSHR, GDF9, FGF7 y BMP15. Para la mayoria de los genes investigados hubo una correlacion significativa entre el nivel de expresion y el peso vivo de los carneros. Conclusion: los resultados demuestran la factibilidad del uso de estos genes candidatos identificados recientemente como marcadores geneticos en ovejas. Palabras clave: analisis de micromatrices, caracteristicas de crecimiento, seleccion asistida por marcadores (MAS), transcripcion. Resumo Antecedentes: metodos que utilizam marcadores de selecao assistida em ovelhas exigem a identificacao de novos genes que afetam a qualidade da carne. Genes com maiores niveis de expressao podem ter maior impacto sobre o crescimento e a estrutura das fibras musculares. Objetivo: avaliar a expressao de genes no musculo lombar de ovinos da raca Merino Dzhalginsky. Metodos: foi utilizada a reacao em cadeia da polimerase-transcriptase reversa e em tempo real (RT-qPCR) para investigar a expressao de 48 genes em musculo do lombo da raca de ovinos Merino Dzhalginsky, que foram criados na Russia. Resultados: os genes GAPDH, PYGM, CAST, ATP5G1, CAPN3, SOD1, VEGFA, CALM2, YWHAZ, ASIP, MYOD1, CAPN1, GHR, OXTR, BEGAIN, SLC2A3 e SS18L2 apresentaram a maior expressao. O grupo de genes com um nivel medio de expressao incluiram ATOX1, BAMBI, TLR6, IGF2, FOS, FST, GGTA2P, C-MET, FGF5, ACVR2A, CAPN2, GH, DGAT1 e IGF1. Foram identificados baixos niveis de expressao para os genes ABCG2, SPP2, PYGL, PPARG2, TGFB1, CXCR4, MSTN, CYP2J, LEPR, CDKN1A, IGFBP4 e SERT. Foi detectado rastreamento de expressao nos genes SST, TSHR, GDF9, FGF7 e BMP15. Para a maioria dos genes investigados, houve uma correlacao significativa entre o nivel de expressao e o peso vivo dos carneiros Dzhalginsky Merino. Conclusao: os resultados demonstram a viabilidade do uso desses genes candidatos recentemente identificados como marcadores geneticos no desenvolvimento de novas racas de ovinos. Palavras chave: caracteristicas de crescimento, microarray analise, selecao assistida por marcadores (MAS), transcricao.

The efficiency of singlet oxygen photosensitization by porous silicon is compared with that of a conventional dye photosensitizer tetraphenylporphine by means of singlet oxygen-mediated photooxidation of α-terpinene. Based on photoluminescence measurements it was concluded that the efficiency of porous silicon as a sensitizer is much lower than that of the conventional organic dye. The main reasons for this are the low quantum yield of long living photoinduced electronic excitations (excitones) confined in silicon nanocrystals and deactivation of singlet oxygen by H-terminated internal surface of porous silicon powder. Efficient quenching of excitons in porous silicon by 1,3-diphenylisobenzofuran via the direct energy transfer was demonstrated. This process is believed to be responsible for photobleaching of 1,3-diphenylisobenzofuran at its millimolar concentrations.

An annular flow photochemical reactor illuminated by UV and green (524 nm) light emitting diodes (LEDs) was characterised by a chemical actinometer. Very high efficiency of absorption of photons, most likely promoted by the specific orientation of LED elements in the reactor, was calculated based on the measured actinometry results. Generation of singlet oxygen mediated by nanoporous silicon under illumination by Ar+ laser, UV and green LEDs was demonstrated by indirect measurement of suppression of porous Si photoluminescence, and by direct measurements of singlet oxygen luminescence. The efficiency of reactor in singlet oxygen mediated reactions was tested using reaction of decomposition of diphenylbenzofuran. Estimated quantum yield of chemical reaction is about 34%.

Silicon nanoparticles of three types (oxide-terminated silicon nanospheres, micron-sized hydrogen-terminated porous silicon grains and micron-size oxide-terminated porous silicon grains) were incorporated into silica aerogels at the gel preparation stage. Samples with a wide range of concentrations were prepared, resulting in aerogels that were translucent (but weakly coloured) through to completely opaque for visible light over sample thicknesses of several millimetres. The photoluminescence of these composite materials and of silica aerogel without silicon inclusions was studied in vacuum and in the presence of molecular oxygen in order to determine whether there is any evidence for non-radiative energy transfer from the silicon triplet exciton state to molecular oxygen adsorbed at the silicon surface. No sensitivity to oxygen was observed from the nanoparticles which had partially H-terminated surfaces before incorporation, and so we conclude that the silicon surface has become substantially oxidised. Finally, the FTIR and Raman scattering spectra of the composites were studied in order to establish the presence of crystalline silicon; by taking the ratio of intensities of the silicon and aerogel Raman bands, we were able to obtain a quantitative measure of the silicon nanoparticle concentration independent of the degree of optical attenuation.

Periodic solid state structures exhibit transmission stop bands for waves of certain frequencies. We report the realization and direct measurement of acoustic band gaps in porous silicon multilayer structures which exhibit similar to 50 dB stop bands for longitudinal acoustic waves in the gigahertz range. Furthermore, realization of an acoustic microcavity structure in porous silicon is demonstrated.

We report on the synthesis of freestanding silicon spheres having sizes in the range of 3–10 nm. As-prepared luminescent silicon nanocrystals have H-passivated surface. Therefore, energy transfer from excitons confined in Si nanocrystals to oxygen molecules is found to be efficient. It is demonstrated that a termination of silicon nanocrystal H-passivated hydrophobic surface by lipids provides their water solubility. We found that this procedure preserves photosensitizing ability of silicon nanocrystals. Therefore, this material system can potentially be employed for a variety of biomedical applications.

Can silicon ever be a true direct-bandgap semiconductor? The first observation of a new, short-lived photoluminescence band from silicon nanocrystals offers fresh hope.

We report on the light emitting properties of freestanding hydrogen-terminated spherical silicon nanocrystals. The nanocrystals exhibit size-dependent tunable light emission properties. Many light emission properties of this system are found to be very similar to those known for other systems containing silicon nanocrystals. However, we found specific emission properties of this system ascribed to the spherical shape of silicon nanocrystals and their spatial separation. We attributed all observations to the spatial confinement of excitons within the crystalline core of the indirect band gap silicon nanocrystals.

not Available.

not Available.