Hypereutectic al-ca-mn-(Ni) alloys as natural eutectic composites

Data Availability Statement: Data are available from the corresponding author on reasonable request.In the present paper, Natural Metal-Matrix Composites (NMMC) based on multicomponent hypereutectic Al-Ca-(Mn)-(Ni) alloys were studied in as-cast, annealed and rolled conditions. Thermo-Calc software and microstructural observations were utilised for analysing the equilibrium and actual phase composition of the alloys including correction of the Al-Ca-Mn system liquidus projection and the solid phase distribution in the Al-Ca-Mn-Ni system. A previously unknown Al10CaMn2 was discovered by both electron microprobe analysis and X-ray studies. The Al-6Ca-3Mn, Al-8Ca-2Mn, Al-8Ca-2Mn-1Ni alloys with representative NMMC structure included ultrafine Ca-rich eutectic and various small-sized primary crystals were found to have excellent feasibility of rolling as compared to its hypereutectic Al-Si counterpart. What is more, Al-Ca alloys showed comparable Coefficient of Thermal Expansion values due to enormous volume fraction of Al-based eutectic and primary intermetallics. Analysis of tensile samples’ fracture surfaces revealed that primary intermetallics may act either as stress raisers or malleable particles depending on their stiffness under deformation. It is shown that a compact morphology can be achieved by conventional casting without using any refining agents. Novel hypereutectic Al-Ca NMMC materials solidifying with the formation of Al10Mn2Ca primary compound have the best ductility and strength. We reasonably propose these materials for high-load pistons.Russian Science Foundation (project no. 20–19–00746)

CALCULATION OF THE DIGITAL TWIN OF THE SALES FUNNEL

Commercial activity has always been influenced by the competitive environment and its spread to the online space is the next stage of development and a defining trend for the nearest time horizon. The changes in the business landscape influenced by COVID19 pose new challenges for marketers and entrepreneurs. It is necessary to use the forced sharp increase in online interaction with consumers. The course towards the digital economy determines the use of scientific, mathematical methods to optimize the target indicators of economic activity. These global shifts in business interactions are generating innovative tools for measuring business results and transforming old practices to meet new market realities. This is the basic condition for the sustainability of doing business in any industry. This study is devoted to the development of a theoretical description of the process of multi-stage interaction with a consumer pool. To solve this problem, a mathematical model has been developed, the basis of which is digital information interaction, starting from the stage of determining the target audience and ending with the complete completion of a commercial transaction. This article presents the results of modeling sales funnel, as the basis for the software of a modern market analyst, using a cross-system approach. In contrast to the classical sales funnel, the presented algorithms allow using the multidimensional conversion funnel not only for assessing business results for the reporting period. Thanks to the flow of model arguments in real time, it becomes possible to optimize the business process by moving to the concept of leading economic indicators.In practice, this means the ability to implement effective business planning on digital platforms. The arguments of the mathematical model are Internet statistics, the dynamics of consumer preferences, the history of the business process accumulated in the big data system. At the same time, the means of queuing theory, differential calculus, economic and mathematical modeling are involved, based on indicators such as KPI (Key Performance Indicators), CTR (click-through rate), CR (Conversion rate). This made it possible to formulate the concept of a digital twin of a commercial process and its transformation, convenient for practical applications, into a conversion funnel for embedding into algorithms implemented on a computer

РАСЧЕТ ЦИФРОВОГО ДВОЙНИКА ВОРОНКИ ПРОДАЖ

Commercial activity has always been influenced by the competitive environment and its spread to the online space is the next stage of development and a defining trend for the nearest time horizon. The changes in the business landscape influenced by COVID19 pose new challenges for marketers and entrepreneurs. It is necessary to use the forced sharp increase in online interaction with consumers. The course towards the digital economy determines the use of scientific, mathematical methods to optimize the target indicators of economic activity. These global shifts in business interactions are generating innovative tools for measuring business results and transforming old practices to meet new market realities. This is the basic condition for the sustainability of doing business in any industry. This study is devoted to the development of a theoretical description of the process of multi-stage interaction with a consumer pool. To solve this problem, a mathematical model has been developed, the basis of which is digital information interaction, starting from the stage of determining the target audience and ending with the complete completion of a commercial transaction. This article presents the results of modeling sales funnel, as the basis for the software of a modern market analyst, using a cross-system approach. In contrast to the classical sales funnel, the presented algorithms allow using the multidimensional conversion funnel not only for assessing business results for the reporting period. Thanks to the flow of model arguments in real time, it becomes possible to optimize the business process by moving to the concept of leading economic indicators.In practice, this means the ability to implement effective business planning on digital platforms. The arguments of the mathematical model are Internet statistics, the dynamics of consumer preferences, the history of the business process accumulated in the big data system. At the same time, the means of queuing theory, differential calculus, economic and mathematical modeling are involved, based on indicators such as KPI (Key Performance Indicators), CTR (click-through rate), CR (Conversion rate). This made it possible to formulate the concept of a digital twin of a commercial process and its transformation, convenient for practical applications, into a conversion funnel for embedding into algorithms implemented on a computer.Коммерческая деятельность всегда испытывала воздействие конкурентной среды, и онлайн-торговля является следующей ступенью развития и определяющим трендом на ближайшее время. Произошедшие под влиянием COVID-19 изменения в бизнес-ландшафте ставят перед маркетологами и предпринимателями новые задачи. Необходимо использовать вынужденный резкий рост онлайн-взаимодействия с потребителями. Курс на цифровую экономику обуславливает применение научных, математических методов для оптимизации целевых показателей экономической деятельности. Такие глобальные перемены в бизнес-взаимодействии порождают инновационные инструменты для оценки результатов коммерции и трансформируют прежние методики для соответствия новым реалиям рынка. Это является базовым условием устойчивости ведения бизнеса в любой отрасли. Настоящее исследование посвящено разработке теоретического описания процесса многоступенчатого взаимодействия с потребительским пулом. Для решения задачи формализации данного процесса разработана математическая модель, основу которой составляет информационное цифровое взаимодействие от этапа определения целевой аудитории до полного завершения коммерческой сделки.В предлагаемой статье изложены результаты работы по моделированию sales funnel как основы программного обеспечения современного аналитика рынка с применением кросс-системного подхода. В отличие от классической sales funnel, представленные алгоритмы позволяют использовать многомерную conversion funnel не только для оценки результатов работы бизнеса за отчетный период: благодаря потоку аргументов модели в режиме реального времени становится возможным оптимизировать коммерческий процесс за счет перехода к концепции опережающих экономических показателей.На практике это означает возможность реализации на цифровых платформах эффективного планирования коммерческой деятельности. Аргументами математической модели служат интернет-статистика, динамика потребительских предпочтений, история бизнес-процесса, аккумулированная в системе больших данных. При этом задействованы средства queuing theory, дифференциального исчисления, экономико-математического моделирования с опорой на такие показатели, как KPI (Key Performance Indicators), CTR (click-through rate), CR (Conversion rate). Это позволило сформулировать концепцию цифрового двойника коммерческого процесса. Нами разработаны математические формализмы, удобные для практических приложений. Это позволяет обеспечить приемлемую для программирования на ЭВМ реализацию алгоритмов, описывающих conversion funnel

Na,K-ATPase Acts as a Beta-Amyloid Receptor Triggering Src Kinase Activation

Beta-amyloid (Aβ) has a dual role, both as an important factor in the pathology of Alzheimer’s disease and as a regulator in brain physiology. The inhibitory effect of Aβ42 oligomers on Na,K-ATPase contributes to neuronal dysfunction in Alzheimer’s disease. Still, the physiological role of the monomeric form of Aβ42 interaction with Na,K-ATPase remains unclear. We report that Na,K-ATPase serves as a receptor for Aβ42 monomer, triggering Src kinase activation. The co-localization of Aβ42 with α1- and β1-subunits of Na,K-ATPase, and Na,K-ATPase with Src kinase in SH-SY5Y neuroblastoma cells, was observed. Treatment of cells with 100 nM Aβ42 causes Src kinase activation, but does not alter Na,K-ATPase transport activity. The interaction of Aβ42 with α1β1 Na,K-ATPase isozyme leads to activation of Src kinase associated with the enzyme. Notably, prevention of Na,K-ATPase:Src kinase interaction by a specific inhibitor pNaKtide disrupts the Aβ-induced Src kinase activation. Stimulatory effect of Aβ42 on Src kinase was lost under hypoxic conditions, which was similar to the effect of specific Na,K-ATPase ligands, the cardiotonic steroids. Our findings identify Na,K-ATPase as a Aβ42 receptor, thus opening a prospect on exploring the physiological and pathological Src kinase activation caused by Aβ42 in the nervous system

Studying the Effects of Mechanical Loads and Environmental Conditions on the Drive-Axle Performance

© 2019 IOP Publishing Ltd. All rights reserved. The paper discusses the problem of achieving the required output parameters of a truck drive under various operating conditions. The authors enumerate the final-drive and differential mechanical efficiency, the pre-load torque in the final-drive bearing assembly, the friction coefficient, and the differential locking factor as the most significant technical parameters of the drive axle and its components. The main factors that affect these parameters during operation are: (i) mechanical loads that transmission is exposed to when transmitting the torque from the engine to the drive wheels; (ii) the effects of external thermal and dynamic loads when driving on an uneven surface or in cold/hot climates. The paper describes the main dependences between the final-drive processes and the inter-wheel differential processes; it also demonstrates how the aforementioned factors affect the output parameters of the component. The assumptions hereof are based on the results of bench and field truck tests, including adverse-climate tests. We herein propose a method for estimating the drive-axle load, which is based on the weighted values of the aforementioned factors. We prove it feasible to use auto-adjusted heating of the drive-axle components. The degree of thermal exposure shall be determined with due account of environmental conditions, surface conditions, engine and transmission parameters. The control algorithm is supposed to automatically take into account any change in one or more factors. This approach to controlling the output parameters helps improve the efficiency and the longevity of the drive axle and truck as a whole

Studying the Effects of Mechanical Loads and Environmental Conditions on the Drive-Axle Performance

© 2019 IOP Publishing Ltd. All rights reserved. The paper discusses the problem of achieving the required output parameters of a truck drive under various operating conditions. The authors enumerate the final-drive and differential mechanical efficiency, the pre-load torque in the final-drive bearing assembly, the friction coefficient, and the differential locking factor as the most significant technical parameters of the drive axle and its components. The main factors that affect these parameters during operation are: (i) mechanical loads that transmission is exposed to when transmitting the torque from the engine to the drive wheels; (ii) the effects of external thermal and dynamic loads when driving on an uneven surface or in cold/hot climates. The paper describes the main dependences between the final-drive processes and the inter-wheel differential processes; it also demonstrates how the aforementioned factors affect the output parameters of the component. The assumptions hereof are based on the results of bench and field truck tests, including adverse-climate tests. We herein propose a method for estimating the drive-axle load, which is based on the weighted values of the aforementioned factors. We prove it feasible to use auto-adjusted heating of the drive-axle components. The degree of thermal exposure shall be determined with due account of environmental conditions, surface conditions, engine and transmission parameters. The control algorithm is supposed to automatically take into account any change in one or more factors. This approach to controlling the output parameters helps improve the efficiency and the longevity of the drive axle and truck as a whole