bluuebunny/crossref_metadata_2025 huggingface dataset:
Floristic evidence for alternative biome states in tropical Africa
Authors: Aleman J. C. , Fayolle A. , Favier C. , Staver A. C. , Dexter K. G. , Ryan C. M. , Azihou A. F. , Bauman D. , te Beest M. , Chidumayo E. N. , Comiskey J. A. , Cromsigt J. P. G. M. , Dessard H. , Doucet J.-L. , Finckh M. , Gillet J.-F. , Gourlet-Fleury S. , Hempson G. P. , Holdo R. M. , Kirunda B. , Kouame F. N. , Mahy G. , Gonçalves F. Maiato P. , McNicol I. , Quintano P. Nieto , Plumptre A. J. , Pritchard R. C. , Revermann R. , Schmitt C. B. , Swemmer A. M. , Talila H. , Woollen E. , Swaine M. D.
Published: October 2020

Significance

We develop a biogeographic approach to analyzing the presence of alternative stable states in tropical biomes. Whilst forest–savanna bistability has been widely hypothesized and modeled, empirical evidence has remained scarce and controversial, and here, applying our method to Africa, we provide large-scale evidence that there are alternative states in tree species composition of tropical vegetation. Furthermore, our results have produced more accurate maps of the forest and savanna distributions in Africa, which take into account differences in tree species composition, and a complex suite of determinants. This result is not only important for understanding the biogeography of the continent but also, to guide large-scaled tree planting and restoration efforts planned for the region.
USP7 regulates ALS-associated proteotoxicity and quality control through the NEDD4L–SMAD pathway
Authors: Zhang Tao , Periz Goran , Lu Yu-Ning , Wang Jiou
Published: October 2020

Significance

Protein homeostasis is fundamental to the functioning of all living cells. Perturbation of the homeostasis, or proteotoxicity, plays an important role in the pathogenesis of amyotrophic lateral sclerosis and related neurodegenerative diseases. To guard against proteotoxicity, cells have evolved sophisticated quality-control mechanisms that make adaptations including enhanced turnover of misfolded proteins. However, how the quality-control systems are coordinated through higher-order regulatory pathways is not fully understood. We have discovered a unique suppressor of proteotoxicity, the ubiquitin-specific protease USP7, whose action is conserved from invertebrate to mammalian systems and mediated by a substrate cascade involving NEDD4L and SMAD2. These findings reveal a previously unknown regulatory pathway for protein quality control and provide new strategies for developing interventions for neurodegenerative diseases.
A far-red cyanobacteriochrome lineage specific for verdins
Authors: Moreno Marcus V. , Rockwell Nathan C. , Mora Manuel , Fisher Andrew J. , Lagarias J. Clark
Published: October 2020

Significance

Cyanobacteriochrome (CBCR) photoreceptors leverage light-triggered photoisomerization of bound bilin chromophores to regulate gene expression, directional movement, and cell–cell communication in cyanobacteria. CBCRs responding to far-red light provide an emerging class of small reagents for applications in synthetic biology. We have found CBCRs that use 18
1
,18
2
-dihydrobiliverdin or biliverdin chromophore precursors to sense far-red light. This lineage is distinguished from others by exclusion of phycobilins, the normal CBCR chromophores. Owing to the deep penetrance of far-red light in mammalian tissue and availability of biliverdin therein, this lineage of CBCRs holds great potential for developing synthetic biology tools of biomedical interest.
An allosteric peptide inhibitor of HIF-1α regulates hypoxia-induced retinal neovascularization
Authors: Usui-Ouchi Ayumi , Aguilar Edith , Murinello Salome , Prins Mitchell , Gantner Marin L. , Wright Peter E. , Berlow Rebecca B. , Friedlander Martin
Published: October 2020

Significance

Retinal ischemia causes hypoxia-induced neovascularization that stimulates production of proangiogenic cytokines such as VEGF by the hypoxia-inducible transcription factors HIF-1 and HIF-2. Current therapies for ischemic retinal diseases target circulating VEGF but do not modulate the activity of the transcription factors that control its production. We demonstrate that inhibiting HIF-mediated transcription with a peptide derived from the intrinsically disordered protein CITED2, a negative feedback regulator of HIF-1α, reduces pathological angiogenesis in a mouse model of ischemic retinopathy. Combining the CITED2 peptide with the VEGF-Trap aflibercept causes potent suppression of neovascularization and promotes revascularization of the ischemic retina, an outcome not observed for anti-VEGF agents alone, suggesting that dual targeting of the HIF transcription factors and VEGF may be advantageous.
Genome-wide mapping of spontaneous genetic alterations in diploid yeast cells
Authors: Sui Yang , Qi Lei , Wu Jian-Kun , Wen Xue-Ping , Tang Xing-Xing , Ma Zhong-Jun , Wu Xue-Chang , Zhang Ke , Kokoska Robert J. , Zheng Dao-Qiong , Petes Thomas D.
Published: October 2020

Significance

Although geneticists often emphasize diversity generated during sexual reproduction, genomic alterations that occur during vegetative growth are an important source of genetic diversity. In the current study, we have measured the rate and location of single-base mutations, large deletions/duplications, ploidy alterations, and mitotic recombination events in extensively subcultured diploid isolates of the yeast
Saccharomyces cerevisiae
. We were able to determine the relative frequency of these events and to predict the frequency of loss of heterozygosity of allelic markers resulting from mitotic recombination. This analysis is relevant to understanding of genomic evolution, as well as the mitotic recombination events in humans that predispose cells to form tumors.
Nfkb2 variants reveal a p100-degradation threshold that defines autoimmune susceptibility
Authors: Wirasinha Rushika C. , Davies Ainsley R. , Srivastava Monika , Sheridan Julie M. , Sng Xavier Y.X. , Delmonte Ottavia M. , Dobbs Kerry , Loh Khai L. , Miosge Lisa A. , Lee Cindy Eunhee , Chand Rochna , Chan Anna , Yap Jin Yan , Keller Michael D. , Chen Karin , Rossjohn Jamie , La Gruta Nicole L. , Vinuesa Carola G. , Reid Hugh H. , Lionakis Michail S. , Notarangelo Luigi D. , Gray Daniel H.D. , Goodnow Christopher C. , Cook Matthew C. , Daley Stephen R.
Published: October 2020

NF-κB2/p100 (p100) is an inhibitor of κB (IκB) protein that is partially degraded to produce the NF-κB2/p52 (p52) transcription factor. Heterozygous NFKB2 mutations cause a human syndrome of immunodeficiency and autoimmunity, but whether autoimmunity arises from insufficiency of p52 or IκB function of mutated p100 is unclear. Here, we studied mice bearing mutations in the p100 degron, a domain that harbors most of the clinically recognized mutations and is required for signal-dependent p100 degradation. Distinct mutations caused graded increases in p100-degradation resistance. Severe p100-degradation resistance, due to inheritance of one highly degradation-resistant allele or two subclinical alleles, caused thymic medullary hypoplasia and autoimmune disease, whereas the absence of p100 and p52 did not. We inferred a similar mechanism occurs in humans, as the T cell receptor repertoires of affected humans and mice contained a hydrophobic signature of increased self-reactivity. Autoimmunity in autosomal dominant NFKB2 syndrome arises largely from defects in nonhematopoietic cells caused by the IκB function of degradation-resistant p100.
Primordial black holes as a dark matter candidate
Authors: Green Anne M , Kavanagh Bradley J
Published: October 2020

The detection of gravitational waves from mergers of tens of Solar mass black hole binaries has led to a surge in interest in primordial black holes (PBHs) as a dark matter candidate. We aim to provide a (relatively) concise overview of the status of PBHs as a dark matter candidate, circa Summer 2020. First we review the formation of PBHs in the early Universe, focussing mainly on PBHs formed via the collapse of large density perturbations generated by inflation. Then we review the various current and future constraints on the present day abundance of PBHs. We conclude with a discussion of the key open questions in this field.
Anisotropic reduced diffusion in dilute liquid 3He–4He mixture in ordered aerogel
Authors: Safiullin K , Kuzmin V , Stanislavovas A , Alakshin E , Klochkov A , Tagirov M
Published: October 2020

We report on the first observation of 3He diffusion anisotropy in 3He–4He liquid mixture confined in ordered aerogels at 1.5–4.2 K temperatures. The used aerogels are arrays of long Al2O3 parallel 8 nm strands. The possible origins of diffusion anisotropy are considered and the changes of roton properties introduced by parallel aerogel strands are discussed. Among the responsible mechanisms we account for Knudsen diffusion, potential anisotropy of layer mode excitations or of bulklike excitations, and helium vortices. The observed reduced 3He diffusion in aerogels is discussed and suggested to appear due to helium excitations at strong confinement conditions. These observations pave the way for future experiments to gain insight into the crossover regime expected at lower temperatures (below 1 K) for which roton density is lower and 3He collisions with strands play significant role.
Evaluation of CBCT scatter correction using deep convolutional neural networks for head and neck adaptive proton therapy
Authors: Lalonde Arthur , Winey Brian , Verburg Joost , Paganetti Harald , Sharp Gregory C
Published: October 2020

Adaptive proton therapy (APT) is a promising approach for the treatment of head and neck cancers. One crucial element of APT is daily volumetric imaging of the patient in the treatment position. Such data can be acquired with cone-beam computed tomography (CBCT), although scatter artifacts make uncorrected CBCT images unsuitable for proton therapy dose calculation. The purpose of this work is to evaluate the performance of a U-shape deep convolutive neural network (U-Net) to perform projection-based scatter correction and enable fast and accurate dose calculation on CBCT images in the context of head and neck APT. CBCT projections are simulated for a cohort of 48 head and neck patients using a GPU accelerated Monte Carlo (MC) code . A U-Net is trained to reproduce MC projection-based scatter correction from raw projections. The accuracy of the scatter correction is experimentally evaluated using CT and CBCT images of an anthropomorphic head phantom. The potential of the method for head and neck APT is assessed by comparing proton therapy dose distributions calculated on scatter-free, uncorrected and scatter-corrected CBCT images. Finally, dose calculation accuracy is estimated in experimental patient images using a previously validated empirical scatter correction as reference. The mean and mean absolute HU differences between scatter-free and scatter-corrected images are -0.8 and 13.4 HU, compared to -28.6 and 69.6 HU for the uncorrected images. In the head phantom, the root-mean square difference of proton ranges calculated in the reference CT and corrected CBCT is 0.73 mm. The average 2%/2 mm gamma pass rate for proton therapy plans optimized in the scatter free images and re-calculated in the scatter-corrected ones is 98.89%. In experimental CBCT patient images, a 3%/3 mm passing rate of 98.72% is achieved between the proposed method and the reference one. All CBCT projection volume could be corrected in less than 5 seconds.
Measurements of the energy distribution of W atoms sputtered by low energy Ar ions using high-resolution Doppler spectroscopy
Authors: Ertmer S , Marchuk O , Dickheuer S , Brezinsek S , Boerner P , Schmitz J , Kreter A
Published: October 2020

Emission spectra of neural tungsten (W) sputtered by impact of argon (Ar) ions in a weakly magnetized (<0.1 T) Ar plasma were measured using a high resolution spectrometer at normal incidence angle to the surface. The measurements were performed for the mono-energetic impact energies between 70 and 150 eV using the neutral tungsten (W I) line at 4982.593 Å. The line shape of this line was simulated using a Doppler-shifted emission model to determine the energy distribution. Additional broadening mechanisms were taken into account: instrumental broadening, Zeeman effect and finally the photon or light reflectance at the W surface.

The obtained energy distribution was found in a very good agreement with the Thompson distribution, even though deviations for lower impact energies are observed, e.g. the high-energy tail of sputtered particles demonstrates a faster drop compared to 1/E
2 at energies below 100 eV. Moreover, the standard cosine (Knudsen cosine law) distribution provides a rather good description of emission spectra in the energy range of study. Finally, the energy distribution was also compared with simulations carried out with the binary collision approximation (BCA) based Monte-Carlo code SDTrimSP. It shows a marginally worse description at low energies and better description of the high energy tail compared to the Thompson one. Furthermore, the model was used to determine in-situ the degree of light reflection at the W surface. The results are in excellent agreement with the literature data.
Multi-source domain adaptation for decoder calibration of intracortical brain-machine interface
Authors: Li Wei , Ji Shaohua , Chen Xi , Kuai Bo , He Jiping , Zhang Peng , Li Qiang
Published: October 2020

Objective. For nonstationarity of neural recordings, daily retraining is required in the decoder calibration of intracortical brain-machine interfaces (iBMIs). Domain adaptation (DA) has started to be applied in iBMIs to solve the problem of daily retraining by taking advantage of historical data. However, previous DA studies used only a single source domain, which might lead to performance instability. In this study, we proposed a multi-source DA algorithm, by fully utilizing the historical data, to achieve a better and more robust decoding performance while reducing the decoder calibration time. Approach. The neural signals were recorded from two rhesus macaques using intracortical electrodes to decode the reaching and grasping movements. A principal component analysis (PCA)-based multi-source domain adaptation (PMDA) algorithm was proposed to apply the feature transfer to diminish the disparities between the target domain and each source domain. Moreover, the multiple weighted sub-classifiers based on multi-source domain data and small current sample set were constructed to accomplish the decoding. Main results. Our algorithm was able to make use of the multi-source domain data and achieve better and more robust decoding performance compared with other methods. Only a small current sample set was needed by our algorithm in order for the decoder calibration time to be effectively reduced. Significance. (1) The idea of the multi-source DA was introduced into the iBMIs to solve the problem of time consumption in the daily decoder retraining. (2) Instead of using only single-source domain data in the previous study, our algorithm made use of multi-day historical data, resulting in better and more robust decoding performance. (3) Our algorithm could be accomplished with only a small current sample set, and it can effectively reduce the decoder calibration time, which is important for further clinical applications.
The theory of open localized quantum systems in representation of the effective Hamiltonian
Authors: Basharov A M
Published: October 2020

The paper substantiates the necessity of using the effective Hamiltonian in describing open optical systems.
Polymorphic uncertainty in met-ocean conditions and the influence on fatigue loads
Authors: Hübler Clemens , Müller Franziska , Rolfes Raimund
Published: October 2020

An accurate numerical simulation of the structural lifetime of offshore wind turbines is a challenging task due to several reasons. One of them is the uncertainty of met-ocean conditions acting on a turbine, e.g. wind and waves. This uncertainty can be divided into two kinds of uncertainty: aleatory and epistemic uncertainty. If both types of uncertainty occur, this is called polymorphic uncertainty. According to the state of the art, for met-ocean conditions, mainly aleatory uncertainty is considered or both types of uncertainty are modelled using a single probability density function. This leads to a simplification of the actual uncertainty, whose effect on the lifetime estimation has not been analysed so far. In that sense, in this work, the influence of various uncertainty models for met-ocean conditions on long-term damage equivalent loads (DELs) - representing the wind turbine fatigue lifetime - is investigated. For this purpose, different uncertainty models for met-ocean conditions are derived using real measurement data. Not only purely probabilistic models are applied, but imprecise probabilities - here interval random variables - as well. It is shown that the uncertainty models have a considerable influence on the fatigue life of offshore wind turbines. Especially, the large fatigue load intervals, which are determined, clarify the importance of a well-founded decisions regarding uncertainty modelling of met-ocean conditions.
The dynamic response of offshore wind turbines and their sensitivity to wind field models
Authors: Myrtvedt Maylinn Haaskjold , Nybø Astrid , Nielsen Finn Gunnar
Published: October 2020

As the rotor diameter of offshore wind turbines increases, an improved understanding of the structure of the turbulent wind field approaching the rotor is important. Present standards for computing wind loads are resting upon assumptions of neutral atmospheric conditions and a simplistic formulation of the coherence of the turbulence. In the present work, various formulations of the wind field are applied and the dynamic responses of a bottom fixed and a floating wind turbine are computed to investigate the sensitivity to the formulation of the wind field. Focus is on wind situations with above average turbulence intensity as these are expected to have a significant contribution to fatigue damage of the structure. It is observed that choice of wind spectrum, coherence formulation as well as assumptions related to atmospheric stability conditions significantly influences the dynamic loads in tower bending moment, yaw moment and blade flap moment. The differences are significant in particular in the low frequency range. This implies that in particular floaters are sensitive to the formulation of the wind field.
Evaluation of Gaussian wake models under different atmospheric stability conditions: Comparison with large eddy simulation results
Authors: Krutova Maria , Paskyabi Mostafa Bakhoday , Nielsen Finn Gunnar , Reuder Joachim
Published: October 2020

The calculation of the velocity deficit in the wake of individual wind turbines is a fundamental part of the wind farm analysis. A good approximation of the wake deficit behind a single wind turbine will improve the power estimation for downwind turbines. Large-eddy simulation (LES) is a research tool widely used in studying the velocity deficit and turbulence intensity in the wake. However, the computational cost of the LES prevents its application in wind farm performance analysis and control. Existing analytical wake models provide a fast estimation of the velocity deficit and the wake expansion rate downstream from the rotor. The Gaussian wake models use a Gaussian distribution to improve the prediction of the wake velocity deficit. With the number of analytical models available, an extensive evaluation of their performance under different flow parameters is needed. In this work, we simulate a wake of a single wind turbine using the LES code PALM (Parallelized LES Model) combined with an actuator disc model with rotation. We compare the computed flow field with the predictions made by Gaussian models and fit their parameters to obtain the best possible fit for the wake field data as computed by LES.
Predictive Analysis of Machine Learning Schemes in Forecasting Offshore Wind Speed
Authors: Bakhoday-Paskyabi Mostafa
Published: October 2020

High variability of wind in the farm areas causes a drastic instability in the energy markets. Therefore, precise forecast of wind speed plays a key role in the optimal prediction of offshore wind power. In this study, we apply two deep learning models, i.e. Long Short-Term Memory (LSTM) and Nonlinear Autoregressive EXogenous input (NARX), for predicting wind speed over long-range of dependencies. We use a four-month-long wind speed/direction, air temperature, and atmospheric pressure time series (all recorded at 10 m height) from a meteorological mast (Vigra station) in the close vicinity of the Havsul-I offshore area near Ålesund, Norway. While both predictive methods could efficiently predict the wind speed, the LSTM with update generally outperforms the NARX. The NARX suffers from vanishing gradient issue and its performance declines by abrupt variability inherited in the input data during training phase. It is observed that this sensitivity will significantly decrease by integrating, for example, the wind direction at low frequencies in the learning process. Generally, the results showed that the predictive models are robust and accurate in short-term and somewhat long-term forecasting of wind.
Splipy: B-Spline and NURBS Modelling in Python
Authors: Johannessen K. A. , Fonn E.
Published: October 2020

Splipy is a pure Python library for the creation, evaluation and manipulation of B-spline and NURBS geometries. It supports n-variate splines of any dimension, but emphasis is placed on the use of curves, surfaces and volumes. The library is designed primarily for analysis use, and therefore allows fine-grained control over many aspects which cannot be achieved with conventional CAD tools. It is packaged and distributed through Python Package Index: PyPi which gives easy installation.
Modern methods of intensification of heat exchange processes in plate apparatuses
Authors: Savvin N Yu , Kushchev L A , Alifanova A I
Published: October 2020

The heat supply system of the Russian Federation is characterized by significant wear and tear of equipment: heating networks and boilers. At the same time, an important element of heat supply systems equipment is heat exchangers of various designs, which are used in boilers, IHP, thermal power plants, and nuclear power plants. Various heat exchange equipment used in modern heat power engineering is considered. It is established that the use of plate heat exchangers is a more appropriate engineering solution than shell-and-tube heat exchangers, due to economic factors and operational advantages. The method of intensification of heat transfer of the heated liquid by means of technological depressions of spherical shape located according to the linear law is considered.
Features of mathematical formulation and solution of the problem of optimal division of funds in the construction business
Authors: Chernyaev A P , Meerson A Yu , Sukhorukova I V , Fomin G P
Published: October 2020

The paper considers a microeconomic model of the construction business economy, assuming that it is a stable object in a crisis. The paper presents the distinctive features of the microeconomic formulation of the problem of finding a method for optimal separation of construction materials into consumed and accumulated parts. This area is constantly paid attention to and described in the media, sometimes with much unexpected outcome for investors. It is quite natural that consumption is optimized, just as in macroeconomics, but not in its pure form. The integral discounted utility of consumption is maximized. The communication equation in this paper differs from the similar macroeconomic equation, as the construction business exists and survives even in crisis conditions not in the same way as it does in social environments.
One of the approaches to the concrete strength mathematical model
Authors: Nikonorov V M , Nikonorov V V
Published: October 2020

The importance of concrete as a structural material is undeniable. The key indicator of concrete as a construction material is strength. Creating and solving a concrete strength mathematical model will allow optimizing raw material costs, increasing the financial result of concrete production, and managing the concrete strength at the stage of its production. The authors reviewed existing concrete strength mathematical models. In the considered models, the concrete strength was influenced by various factors – water-cement ratio, C3S hardness, etc. The authors used the kinetic theory of solid destruction as the basis for their mathematical model of concrete strength. The process of destruction of the sample is considered without deformation. Applying the concept of strained and broken bonds, the authors constructed and solved a concrete strength mathematical model. The main parameters of the model are the speed formation coefficient of the stressed bonds and the speed formation coefficient of destroyed bonds. The model allows estimating the time required for sample destruction at a given load. This is a non-trivial conclusion.
Innovative structural and technological developments of pile foundation engineering
Authors: Kocherzhenko Vladimir , Suleymanova Lyudmila , Kolesnikov Maksim
Published: October 2020

The paper considers innovative structural and technological solutions for precast piles, which significantly increase their load-bearing capacity: a transformable pile and a pile with “pockets” (recesses) on the side surface for use in loose soils. In the first case, in the manufacture of precast reinforced concrete piles in the center they set plastic cone-shaped cruciform brake detail with length 0.75 of the pile length, in which after driving the piles destructive non-explosive substance is poured, that increasing in volume in 2-3 times, transforms prismatic pile into a pyramid one. In the second case, when making precast concrete piles, they provide for the arrangement along the side faces of “pockets” (recesses). The liquid hardening compound located in the “pockets” penetrates into the soil of the pile during the driving process and secures it, which significantly increases the lateral friction force of the pile and its load-bearing capacity and reduces the energy of the pile sinking. The considered design and technological solutions allow reducing the energy of pile driving, while increasing their load-bearing capacity.
Method for predicting the remaining life of the ball mill support axle based on changes in the design stresses of the external surface of the axle
Authors: Bondarenko J A , Duyun T A , Bestuzheva O V
Published: October 2020

The article considers a method for predicting the residual life of the ball mill support axle based on changes in the calculated stresses of the external surface of the axle. The main terms of forecasting the remaining life of large-sized equipment are considered. The task is set and controlled parameters are selected for the development of the methodology. An algorithm for implementing a method for predicting the residual life of the ball mill support axle based on external surface stresses is presented. A method has been developed for predicting the residual life of ball mill support axles based on changes in the design stresses of the external surface of the trunnion, which allows you to set parameters that affect the duration of the residual life without stopping the mill and to adequately calculate the residual life of the trunnion, including from the start of operation of the mill. The homogeneity of the obtained data is estimated. The parameters of the stress distribution of the external surface of the trunnion are determined, indicating that the obtained distribution corresponds to the theoretical Weibull distribution and the validity of using this method for predicting the resource of the ball mill support trunnion. The values of the guaranteed residual life of the ball mill trunnion are calculated according to the developed method. The analytical dependence of the residual life of the ball mill trunnion on the equivalent stresses occurring on the external surface of the trunnion is given.
Design process of executive elements in stroke mechanisms based on rammer’s deformations and stress modeling
Authors: Chepchurov M S , Voronenko V P , Chirkov A V
Published: October 2020

The article deals with the strength calculation issues of products by example of rammer under short-term loads in hammer drill. Based on finite element analysis’ results of the rammer geometrical model, it is proposed to select a material with a strength limit significantly exceeding the allowable residual stresses inside the rammer. The harmonic analysis allows us to estimate the rammer’s strength. The dynamic coefficient may be calculated by the use of Vibran 2.0 device (amplitude and signal frequency) and by calculation results of the maximum displacement. The FreeCAD software package was used for this. It allows to create internal scripts to automatically search for the optimal design parameters. A method of determining mechanism’s static load and its dynamic coefficient under periodic impact loads has been developed. Static loads calculations and harmonic analysis according to the developed method allow to determine structural strength of the product, to select the rammer’s material and to find the dynamic coefficient (which takes into account the stroke loads in calculations). The pro-posed calculation method may be used not only to solve the describing problem, but also for a whole class of problems related to stroke loading, where such parameters as application time of force or duration time of force’s impulse are important.
Nanodispersed additive for composite binders based on technogenic raw materials of Iraq
Authors: Ahmed Ahmed Ahmed Anees
Published: October 2020

The economic development of the Arab states is characterized by such trends as industrialization and urbanization, population concentration in large cities, saving land, increasing the number of storeys of buildings. Population growth in developing countries is causing acute housing needs. One of the most promising modern building materials is concrete and re-inforced concrete. The main components of concrete, as it is known, are a binder (cement), large and small aggregates. The creation of comfortable conditions is provided by the optimization of the “man-material-environment” system. The theoretical basis for the development of materials science is knowledge about geological processes and the genesis of rocks. The evolution of the development of binders goes along the way of complicating their composition and structure. In the development of materials science there is the process of controlling the structure formation of binders using nanodispersed additives. Nanodispersed additive is produced by grinding in various grinding aggregates of the silica-containing component, the cement, the carbonate constituents, superplasticizers, air-entraining additives, etc. The result is a very complex system. After we introduce a nanodispersed modifier in cements in an amount of 3 to 12%, they absolutely change the processes of structure formation. Thus, it was found that when adding a superplasticizer and a nanodispersed modifier, the compressive strength increases to 47% and the bending strength increases to 27%. The nature of the influence of the nanodispersed modifier on the properties of binders is established. Maintaining a nanodispersed modifier in the composition of Portland cement allows optimizing the process of structure formation of the component of a nanodispersed modifier and has a multifunctional value.
The influence of additives of dehydrated clay on the properties of unburned binders and concrete on their basis
Authors: Sarsenbayev N B , Kurbaniyazov S K , Saktaganova N A , Karshygayev R O
Published: October 2020

The purpose is development of technological bases of production of unburned alkaline binders and concrete on their basis from metallurgical and electro-thermo-phosphoric slags with an additive of the dehydrated clay with high operational properties.

In this regard the increased indicators of physical mechanical properties of unburned alkaline binders and concrete on their basis were researched with addition of 25% - dehydrated clay mixing alkalis.

The influences of fineness grinding, a type of slag and an alkaline component, curing conditions on properties unburned alkaline binders and concrete on their basis, namely on changes of average density, water absorption, strength characteristics were researched.

Thus, as a result of the conducted researches are received depending on a type of slag, an alkaline component, conditions of curing and fineness grinding of unburned alkaline binders and concrete on their basis with an additive of the ground dehydrated clay of grade from M300 to M1200.
Investigation of ground and foundation vibrations of an existing building during impact pile driving
Authors: Veshnyakov V A
Published: October 2020

Pile driving technology remains the most common in Arkhangelsk where the presence of soft soils is an engineering-geological feature. New construction is mainly carried out in the conditions of existing urban development. During pile driving dynamic effects that propagate in the ground can have a negative impact on existing buildings. In common conditions, a distance of more than 25 m is considered safe. Sometimes driving piles by hammer is safe for neighboring buildings at a shorter distance. Often such buildings have pile foundations. The monitoring of pile driving by diesel hammer was carried out at one of the sites in Arkhangelsk. Vertical vibration velocities were measured by a vibration analyzer with independent channels. One vibration sensor was installed on the ground surface, the other one on the foundation of a 5-storey building. Continuous recordings of vibrations allowed a detailed analysis of the driving process of each pile. The level of dynamic effects propagating in the ground changed with the penetration of the driven pile. The highest values were observed when pile foots passed through a layer of glacial deposits. Change in soil resistance to pile driving also affected the operation of diesel hammer. The level of dynamic effects increased as the distance to the driven pile decreased both on the ground surface and on the foundation of the building, while the values on the ground surface were higher. The ratio of the highest vertical peak vibration velocities on the ground surface and on the building foundation was determined by field studies.
Method of forming technological parameters in the design of vibrating cone crushers
Authors: Gerasimov M D , Chetverikov B S , Lubimyi N S , Ridvan I
Published: October 2020

The paper deals with issues related to expanding the possibility of using a promising direction for improving vibrating cone crushers of secondary and fine crushing. The paper deals with two major issues that need to be solved at designing and creating vibrating cone crushers. First question: the value of the ratio of the crushing force in the standard design of a cone crusher of secondary or fine crushing. The second question is the frequency of forced oscillations of the additional vibration device. The choice of the ratio of the crushing force and the value of the driving force of the vibrator is based on the output of the rational frequency of forced oscillations of the unbalanced vibration device. For the first time in this paper for this type of machine the method of dividing the circular crushing chamber into separate sections is used. Each section is a zone of wave displacement of the compressive stress in the material from the action of the crushing force. The length of the section is considered in the range of the current action of the crushing force, in which the stress in the crushed material changes from zero to maximum and again to zero. This section of the action of the crushing force is an elementary section of the force effect of the crushing force on the material. The paper contains some new terms that are caused by the need to apply a more accurate description of the kinetics of the process. The paper forms new approaches to the process of calculating the parameters of vibrating cone crushers, so it can be considered in the “in order of discussion” format.
Use of chestnut sheel (Castánea) as adsorption material for removing pollutants from natural and sewage waters: a review
Authors: Sverguzova S V , Shaikhiev I G , Fomina E V , Galimova R Z
Published: October 2020

The literature data on the use of grinded chestnut shells as a sorption material for removing heavy metal ions, dyes and some organic compounds from aqueous media are summarized. It is shown that a large number of publications are devoted to the study of the adsorption of ions of heavy metals with the shell of chestnut fruits. Information on the chemical composition of the chestnut shell is given. It was shown that the chestnut fruit contains cellulose, lignin and sugars in the shell most of all. It is indicated that the adsorption of many metal ions is carried out by functional groups that is a part of the biopolymers contained in the shell of chestnut fruits. It was revealed that the acidity of the medium influences the degree of extraction of metal ions from aqueous solutions, while the temperature has little effect on the sorption capacity of the shell of chestnut fruits. It is shown that it is possible to increase the sorption characteristics of pollutants by chemical modification of the chestnut shells. It has been determined that sorption isotherms in most cases are more fully described by the Langmuir model, and the kinetics of the process in all cases obeys the pseudo-second order model.
Technopark and its role in improving the competitiveness of the country’s economy: current issues in Russia and Iran
Authors: Safaie Nasser , Romanovich M A , Romanovich L G , Yarmolenko I V
Published: October 2020

This article presents the recent problems of infrastructure support for innovative enterprises that topical for scientists, public authorities and business representatives. The authors consider modern innovation policy as a regulator of innovation processes, consider the experience of organizing technoparks in foreign countries and the features of Russian technoparks, give the dynamics of their creation in Russia, and analyze the structure of domestic technoparks depending on their specialization and affiliation. The structure of technoparks is analyzed depending on its specialization, as well as depending on the owners. Actual problems of the organization and activity of technoparks in Russia, including on the basis of higher education institutions, are highlighted and generalized. Noting the important role of new-generation technoparks in improving the competitiveness of the country’s economy, practical recommendations for their development in modern conditions are given. The recommendations are universal and can be applied in the practical activities of authority, representatives of technoparks, universities and subjects of innovative business in Russia, Iran and other states, aimed at developing their own developments and their introduction into production. It can contribute to increase the competitiveness of the country’s economy.
Development of an algorithm for managing a multi-robot system for cargo transportation based on reinforcement learning in a virtual environment
Authors: Rybak L A , Behera L , Averbukh M A , Sapryka A V
Published: October 2020

This paper is devoted to the study of varieties of the Q-Learning algorithm – deep Q-networks and dueling Q-networks. These algorithms belong to the group of reinforcement learning algorithms. Neural network architectures are selected. The process of modeling the robot’s operation in the problem of cargo delivery from a random point A to the green zone is described. The method of obtaining information about the environment by the robot using the Raycast method is described. A block diagram for controlling the robot movement has been developed, which consists of a block of positioning and state sensors, a neural network module, and a block for constructing a trajectory. The last two blocks together form a system for automatically controlling the agent’s movement in the external environment. Modeling was performed in the Unity development environment. To work with ml agents, the special Unity ML-Agents tool is used. This tool is implemented using a modern DRL servo motor, which is based on the model of the optimization algorithm proximal policy optimization (PPO). A constructive simplification of the agent and environment to facilitate the reproduction of training scenes is implemented. An algorithm for training a robot in a random environment is presented. The optimal parameters of the algorithms under consideration are selected. Suggestions are made to improve the performance of algorithms for this problem.
Analysis of the Steel Structural Reliability under the Big Data
Authors: Yongfeng Fang , Li Wang , Kong Fah TEE
Published: October 2020

In this paper, the reliability of steel roof under the big data loads is analyzed. Firstly, the roof of steel structure is shown. The relationship between roof span and stress composed of hollow steel joist beam is obtained, and the parameters of the structure of the open web steel joists that is made by the wide flange steel is given. Secondly, according to the random distribution parameters of steel roof and the big data loads, the limit state function of steel roof structural calculation is given. The function is an implicit function. Monte Carlo method is used to calculate reliability index of the steel structural roof with considering the dead loads and the big data loads. Finally, the reasonable suggestions for the reliability and safe operation of the steel structural roof are given from the reliability of the calculated of the steel structural roof.
Learnability Factors for Investigating the Effectiveness of Augmented Reality Smart Glasses in Smart Campus
Authors: Hafsa Sayera , Abdul Majid Mazlina
Published: October 2020

Augmented Reality (AR) has become an emerging platform in the field of learning either in education or industry. Wearable AR smart glasses are the example of new wearable technology devices in AR. AR smart glasses has been introduced as another alternative to enhance the user’s experience in the real world rather than replacing the principle of learning. In education, AR smart glasses is seen as a possible technology to be embedded in the teaching and learning among lecturers and students for achieving smart campus environment. The effectiveness of AR smart glasses in education is a prospect for further study. Thus, this paper aims to identify the factors for investigating the learnability of students while learning using AR smart glasses. Various existing learning factors were reviewed through literature exploration and potential AR smart glasses learning factors are suggested. The results are significance for the development of the AR smart glasses learnability model that will further investigate in the future work.
The experience of uncertainty for patients, families and healthcare providers in post-stroke palliative and end-of-life care: a qualitative meta-synthesis
Authors: Connolly Teresa , Coats Heather , DeSanto Kristen , Jones Jacqueline
Published: October 2020

Purpose

recent data show that there is limited evidence and guidance regarding the best practices for the integration of palliative care (PC) and end-of-life (EOL) post-stroke. The purpose of this meta-synthesis is to understand the PC/EOL experiences after a stroke.

Methods

a meta-synthesis was conducted to answer the following research question—What are post-stroke PC/EOL experiences from the perspectives of patients, families and healthcare professionals (HCPs)? This approach was completed through two main phases—a systematic search and appraisal of the literature and reciprocal translation with interpretive triangulation of the extracted data. Databases searched were MEDLINE, EMBASE, PsycINFO, Joanna Briggs Institute and CINAHL databases (from their inception to April 2020). After data were extracted, a qualitative exploratory design was used to evaluate the PC/EOL in post-stroke experiences.

Results

the search identified 696 studies. A total of 14 studies were included in this meta-synthesis as they satisfied our eligibility criteria. Uncertainty post-stroke was the overarching main theme that emerged across post-stroke PC/EOL experiences. Within this theme of uncertainty, opportunities to decrease uncertainty emerged from two interdependent themes—presence of cohesive communication and shared dynamic decision process for both families and HCPs.

Conclusions

to mitigate the degree of uncertainty post-stroke, HCPs should be present, provide clear direct communication and incorporate the value-based goals of care within their medical treatment plan. These findings suggest that future research is needed to focus on how PC approaches can be integrated into stroke care programmes.
Retrospective Hair Cortisol Concentrations from Pretreatment to Early Recovery in Alcohol Use Disorder
Authors: Price Julianne L , Nixon Sara Jo
Published: October 2020

Cortisol profiles are known to vary across phases of alcohol use disorder (AUD; e.g. chronic use, withdrawal and early/sustained recovery). These patterns have largely been established through between-subjects contrasts. Using a segmental hair cortisol concentrations (HCC) approach, retrospective longitudinal analyses are feasible. Here, we examine monthly cortisol secretion in treatment-seekers with AUD from alcohol use to abstinence. At ~6 weeks of recovery we collected hair samples from individuals with moderate-to-severe AUD. We examined HCC from three consecutive segments; proximal to the scalp representing the most recent month (sustained abstinence from alcohol), the midsegment representing the previous month in which abstinence was attained, and the distal segment representing 2 months prior during active drinking. Analyses examined main and interactive effects of segment and sex, controlling for monthly alcohol consumption. Best fit by a quadratic shape, within-subject change was significant (F1,15 = 5.27, P = 0.04, ηpartial2 = 0.26). The distal and midsegments did not differ from one another (P = 0.51). The proximal segment was significantly lower than both the distal (M∆ = 0.200, P = 0.004) and mid (M∆ = 0.175, P < 0.001) segments. An effect of sex approached significance suggesting women had modestly higher HCC than men (MWOMEN = 1.37 vs. MMEN = 1.02, P = 0.10). Consistent with previous cross-sectional reports, these data confirm nonlinear patterns of cortisol accumulation with elevations apparent during periods of alcohol consumption and a decrease in abstinence. Capturing these within-subject patterns via HCC trajectories may serve as a valuable resource in identifying profiles associated with increased risk and post-treatment outcomes.