Sequential Transformation Research Articles

Allyl 4-Chlorophenyl Sulfone as a Versatile 1,1-Synthon for Sequential α-Alkylation/Cobalt-Catalyzed Allylic Substitution

Despite their unique potential as rare 1,1-dipole synthons, allyl sulfones are rarely used in target-oriented syntheses, likely due to the lack of a general catalytic method for their branch-selective allylic substitution. Herein, we identified allyl 4-chlorophenyl sulfone as a versatile linchpin for both base-mediated α-derivatization and subsequent cobalt-catalyzed allylic substitution. The sequential transformations allow for highly regioselective access to branched allylic substitution products with a variety of aliphatic side chains. The photoredox-enabled­ ­cobalt catalysis is indispensable for achieving high yields and regioselectivity­ for the desulfonylative substitution in contrast to traditional metal-catalyzed protocols, which lead to inferior outcomes in the corresponding transformations.

Greyhound racing ideal trajectory path generation for straight to bend based on jerk rate minimization

This paper presents methods for modelling and designing an ideal path trajectory between straight and bend track path segments for racing greyhounds. To do this, we numerically generate clothoid and algebraic curve segments for racing quadrupeds using a sequential vector transformation method as well as using a helper equation for approaching ideal clothoid segments that would respect greyhound kinematic parameters and boundary conditions of the track. Further, we look into the limitations of using a clothoid curve for racing dog track path design and propose a smooth composite curve for track transition design which roughly maintains G3 curvature continuity for smooth jerk to overcome limitations of a clothoid transition. Finally, we show results from race data modelling and past injury data, which provide a strong indication of clothoid curve segments improving the dynamics and safety of racing greyhounds while reducing injuries.

Multi-phase transformation kinetics of HSLA steels during continuous cooling: experiments and cellular automaton (CA) simulation

ABSTRACT Kinetics of multiply ferrite/bainite phase transformation of HSLA steels is investigated by experiments and cellular automaton (CA) simulation. Peak-differentiation method to elucidate the sequential ferrite and bainite phase transformation individually, which is verified by the CA simulation. Such CA modelling executed using classic JMAK theory, but also gives an insight of microstructure evolution of the multi-phase transformation routine on different cooling rate. From that, it enables classic JMAK modelling to capture the detached phase transformation with different growth models and interface-migration mechanisms. Also, we find that the final phase constitution is sensitive to the cooling rate. With increasing the cooling rate, bainite sheaves nucleated at prior austenite boundaries and ferrite/austenite interfaces are significantly facilitated, which seriously inhibits the growth of prior ferrites. The scenario can be interpreted by the CA simulation and the influence of the cooling rate on sequential multi-phase transformation can be also obtained.

Functional outlier detection and taxonomy by sequential transformations

Functional data analysis can be seriously impaired by abnormal observations, which can be classified as either magnitude or shape outliers based on their way of deviating from the bulk of data. Identifying magnitude outliers is relatively easy, while detecting shape outliers is much more challenging. We propose turning the shape outliers into magnitude outliers through data transformation and detecting them using the functional boxplot. Besides easing the detection procedure, applying several transformations sequentially provides a reasonable taxonomy for the flagged outliers. A joint functional ranking, which consists of several transformations, is also defined here. Simulation studies are carried out to evaluate the performance of the proposed method using different functional depth notions. Interesting results are obtained in several practical applications.

Atomic Disordering and BCC → FCC Transformation in the Heusler Compound Ni54Mn20Fe1Ga25 Subject to High-Pressure Torsional Megaplastic Deformation

The Heusler compound with the L21 Ni54Mn20Fe1Ga25 structure subject to high-pressure torsional megaplastic deformation was first systematically studied by in situ methods of X-ray phase analysis and transmission and scanning electron microscopy. It was established that the torsional shear deformation at room temperature reduces the polycrystalline structure of the compound to a nanocrystalline and partially amorphous state. It was revealed that, as the pressure increases from 3 to 5 GPa and the degree of deformation increases from 2 to 5 revolutions, total atomic disordering and sequential structural-phase transformation according to the scheme B2(bcc) → A2(bcc) → A1(fcc) occur. It is shown that annealing at a temperature of 570 K and below causes devitrification of the amorphous phase and annealing at a temperature of 620 K and above causes the restoration of the L21 structure. The dimensional effect of suppressing the thermoelastic martensitic transformation is revealed in the nanostructured austenitic L21 alloy with grains smaller than 80 nm when cooled to 120 K. The capability of the thermoelastic martensitic transformation and of the shape memory is restored in a submicrocrystalline ultrafine-grained alloy after its recrystallization annealing at temperatures above 600 K.

Block diagrams of a doubly fed inductor motor as a control object

To design the electric drives with the doubly fed inductor motor it is required to have the mathematical models of these motors. For this, one should have the mathematical models in the transfer functions form. The basic motor model is non-linear therefore, it should be linearized using the Taylor series. A block diagram is created according to the obtained system of linearized equations. Then the sequential transformation of this block diagram is performed with a gradual decrease in the number of contours. The block diagrams can be used to obtain the motor transfer functions with the arbitrary combination of input quantities (the amplitude, voltages, the frequencies of two voltages) and output quantities (the speed and the rotation angle).

MATERIAL FLOWS IN LOGISTICS ACTIVITIES OF THE ENTERPRISE: TEORETICAL ASPECT

Topicality. In today's economic environment, logistic activity of enterprises requires transformation of approaches to material flow management. Constant changes in the market situation require enterprises to analyze the market conditions, improve inventory management processes, introduce qualitatively new forms of work with suppliers of material resources, as well as mechanisms for selling finished products to different categories of consumers. Solving the above problems causes the need to develop a set of measures to improve the management of material flows at enterprises in order to increase the level of logistics services to consumers and reduce the cost of logistics activities as a result of lowering the costs of logistics and marketing activities. In the scientific literature on logistics, there is a variety of definitions of the term �material flow�, which is proposed by scientists from different scientific schools. Some scientists understand the material flow as a set of inventory; others � products; the third � the flow of different types of resources; fourth � the process of sequential formation and transformation in space and time of objects of labor, etc. In this connection, it became necessary to generalize and systematize theoretical approaches to the essence and content of the concept of �material flow�. Aim and tasks. The aim of this study is to substantiate the application of a comprehensive approach to the definition of the meaning of the term �material flow of the enterprise�. To achieve this goal, the following scientific tasks have been defined: to analyze, summarize and systematize existing scientific approaches to determining the essence of material flow of the enterprise; provide an author's interpretation of the concept. Methods of analysis and synthesis, critical analysis and comparison, generalization, classification, structural-logical method, system approach were used to solve the set scientific problems. Research results. Generalized various scientific views to formulate the material flow of the enterprise, which is conditionally systematized according to 10 classification features: a key category of logistics management theory; the object of logistics management; set of inventory; set of elements (resources, materials, equipment, finished goods, waste); a set of different goods moving from suppliers to consumers; production in kind; a set of inventories; flow of different types of resources; set of logistic operations, processes, links; objects of work. The feasibility of applying a comprehensive approach to the definition of the term �material flow�, which makes it possible to reflect the continuous movement of the set of necessary types of resources (material resources, production of work in progress, production and inventory, finished products, industrial waste) at the enterprise in the consistent implementation of the entire list of processes logistic activities (logistical support, storage of material resources, production of products, formation of production and commodity stocks, serve different customer categories, transportation and marketing of finished products, recycling of industrial waste). Conclusion. The novelty of the author's interpretation of the material flow is that this definition is quite complex and reflects the continuous movement of the set of necessary types of resources at an industrial enterprise with the consistent implementation of the entire list of processes of logistics activities. It is established that it will help to obtain synergetic effect by reducing the costs of organizing logistics activities, improving the quality of logistics services and the level of service of different categories of consumers, optimizing the level of inventories and increasing the level of profitability of the enterprise from the sale of finished products.

Type synthesis of 90°/180° dual-function upenders for large shell units of nuclear reactor

In this paper, unit vectors collinear with the axes of large shell units of nuclear reactors were used to represent the poses of the workpieces. Based on the motion operator interpretation of the rotation matrix, 60 kinds of rotation matrix permutations with 90° turns as the step length to achieve 180° flipping of the workpiece were obtained. After eliminating invalid permutations and merging homogenous permutations, class I, II, and III flipping motion models were obtained. By calculating the Lie algebra of each step of rigid body motion in the flipping motion model, the twist and the motion pair property for each step were obtained. By means of the permutation and combination theory, the sequence of the motion pairs for different configurations was determined, and the rules between sequential transformations and axis changes of the motion pairs under the initial configuration were stipulated. Three classes of 19 initial configurations of 90°/180° dual-function upenders were constructed. For three of them, taking into account the characteristics of the axial dimension variation of workpieces, prismatic pairs were added along the workpiece’s axis (vector), and 15 overall configurations of 90°/180° dual-function upenders were synthesized. This provides the basic theoretical support for the innovative design of upenders with independent intellectual property rights.

Unsymmetrical 1,1-Bisboryl Species: Valuable Building Blocks in Synthesis.

Unsymmetrical 1,1-bis(boryl)alkanes and alkenes are organo-bismetallic equivalents, which are synthetically important because they allow for sequential selective transformations of C–B bonds. We reviewed the synthesis and chemical reactivity of 1,1-bis(boryl)alkanes and alkenes to provide information for the synthetic community. In the first part of this review, we disclose the synthesis and chemical reactivity of unsymmetrical 1,1-bisborylalkanes. In the second part, we describe the synthesis and chemical reactivity of unsymmetrical 1,1-bis(boryl)alkenes.

Wavelet‐based deep learning for skin lesion classification

Skin lesions can be in malignant or benign forms. Benign skin lesion types are not deadly; however, malignant types of skin lesions can be fatal. Lethal forms are known as skin cancer. These types require urgent clinical treatment. Fast detection and diagnosis of malignant types of skin lesions might prevent life-threatening scenarios. This work presents two methods for the automatic classification of malignant melanoma and seborrhoeic keratosis lesions. The first method builds on modelling skin images together with wavelet coefficients. Approximate, horizontal, and vertical wavelet coefficients are obtained using the wavelet transform, and then deep learning (DL) models are generated for each of the representations and skin images. The second method builds on modelling skin images together with three approximate coefficients. This method utilises a sequential wavelet transformation to produce approximation coefficients. Then DL models are generated for each of the representations and skin images. Transfer learning-based ResNet-18 and ResNet-50 DL models provide model images and wavelet coefficients. Then skin lesion detection is achieved by fusing model output probabilities. Both proposed models outperform the methods only based on image data and other previously proposed methods.

Quantum‐chemical models of KOH(KOBut)/DMSO superbasic systems and mechanisms of base‐promoted acetylene reactions

AbstractThe mechanisms of fundamental base‐promoted acetylene reactions, namely, nucleophilic addition to the triple C ≡ C bond (vinylation) and nucleophilic addition of acetylenic carbanion to a carbonyl group (ethynylation), are addressed using three models of different complexity—pentasolvate, monosolvate, and anionic—which describe the catalytic superbasic systems MOH(OBut)/DMSO (suspensions of alkali hydroxides or tert‐butoxides in dimethyl sulfoxide). The above acetylene reactions and sequential transformations of reagents arranged by the superbasic center are modeled within the framework of the most complete pentasolvate model, in which the superbase is represented by the KOH·5DMSO (KOBut·5DMSO) complexes. We have developed approaches to the construction of simplified models (monosolvate and anionic) to describe transformations in complex systems. The mechanisms of cascade assemblies of 6,8‐dioxabicyclo[3.2.1]octanes, cyclopentenones, and furan cycles from ketones and acetylenes in the superbasic environment are investigated using a uniform B2PLYP/6‐311+G**//B3LYP/6‐31+G* approach, and the energy profiles of these different carbo‐ and heterocycles are analyzed.

Design, Synthesis, and In Vitro Evaluation of Benzofuro[3,2-c]Quinoline Derivatives as Potential Antileukemia Agents.

Herein, we design and synthesize an array of benzofuro[3,2-c]quinolines starting from 3-(2-methoxyphenyl)quinolin-4(1H)ones via a sequential chlorination/demethylation, intramolecular cyclization pathway. This sequential transformation was efficient, conducted under metal-free and mild reaction conditions, and yielded corresponding benzofuro[3,2-c]quinolines in high yields. In vitro biological evaluation indicated that such type of compounds showed excellent antileukemia activity and selectivity, and therefore may offer a promising hit compound for developing antileukemia compounds.

Sequential Motion of 4D Printed Photopolymers with Broad Glass Transition

AbstractThe term “4D printing” refers to the development of stimulus‐responsive structures through 3D printing of active smart materials, typically shape memory polymers. A noteworthy aim of this research field is to obtain objects able to display complex shape‐shifting motions, such as sequential transformations over time. In this work, this peculiar response is studied on a commercial photopolymer, printed by stereolithography and featuring, on the basis of its inherent broad glass transition, the so‐called “temperature‐memory effect” (TME). The TME, that is, a response in which the shape memory effect occurs on a region controlled by the deformation temperature, is studied in shape memory cycles where the deformation temperature is systematically varied, so to provide a correlation between deformation and recovery temperatures. This also allows to properly select two temperatures at which deforming a specimen along a multistep history, so as to finally separate each recovery process on the temperature and time scales. This sequential recovery is studied in double folded bars, with arms deformed at different temperatures, and on a properly designed self‐locking clamp. The obtained results are promising for the realization of smart temperature‐responsive structures printed with one single polymer and capable of multiple shape transformations.

Investigation of Phase Portraits Belonging to Polynomial Dynamic Systems in a Poincare Disk

The paper describes especially developed research methods and results for some original study of a broad dynamic systems’ family, which is characterized with the reciprocal polynomials in the right parts of differential equations which compose a system. The goal of this work is to obtain and analyze all the existing (and different in the topological meaning) phase portraits in a Poincare disk, as well as to indicate the criteria of each topological type of phase portraits appearance. Poincare methods of sequential transformations and displays have been successfully used along with a whole set of new research techniques developed for the purposes of this study. Over than 250 of different portraits were obtained and depicted eventually for different subsystems belong to the dynamic systems’ family under consideration. All portraits were described up to each the so-called invariant cell of the phase portrait, a boundary of it, and features of a phase flow in it, including it’s a source and a sink. Results of dynamic systems’ behavior research are useful for a wide spectrum of applications such as the mathematical modeling of physical processes, vital problems of civil engineering, for example, in the consideration of seismic stability of buildings etc., computing and producing systems, biological phenomena, and of sociological events.

Numerical modelling of bender element test in soils

Shear and compression wave velocities (Vs and Vp, respectively) are considered to be very useful for determining various dynamic properties of soils such as small strain shear modulus, Gmax, elastic modulus, Emax and the Poisson’s ratio, ν. Moreover, the index as well as engineering properties of the soil mass can be directly or indirectly correlated to Vs and Vp. However, the bender-extender element and soil interaction during wave propagation stage is difficult to monitor due to various sequential transformations as an electromechanical system. The experimental analysis is unable to reveal the hidden phenomena of wave propagation, boundary wall reflections etc. which otherwise facilitate to understand the complex and highly non-linear behavior at a certain level. The numerical analysis of bender element test simulation is less focused and very few researchers have studied the different aspects such as non-linear dynamics of element-soil system using different numerical approaches. In present study, a numerical code Abaqus™ based on finite element method (FEM) was used to simulate the bender element tests. Shear wave velocity was determined experimentally for six different types of soils and the results were compared with that obtained from numerical modeling. The objective of FE analysis in this research is to arrive at an accurate approximation of laboratory shear wave velocity in different soil materials modelled at varying input frequencies.

Development of the method of forecasting the atmospheric air pollution parameters based on error correction by neural-like structures of the model of successive geometric transformations

The article describes the importance of improving existing and exploring new algorithms for predicting environmental parameters to improve the quality of environmental monitoring. Because the organization and management of production require the development of new approaches to the problem of control and management of industrial sources of harmful substances based on new information technologies. One of the most problematic places in industrial air quality control and management systems is the development of advanced prospective air pollution forecasting algorithms. These algorithms must take into account t situational changes in data distribution and do not require retraining of atmospheric air pollution parameters. With the advent of neural-like structures, there is a need for their study, including the task of predicting the parameters of air pollution. The object of research is the neural-like structures of the Model of Successive Geometric Transformations. A method for predicting the parameters of atmospheric air pollution based on error correction with the help of a committee of different types of neural-like structures is proposed. In the course of the study, three methods for predicting the parameters of atmospheric air pollution were analyzed: a Generalized Regression Neural Network, a Radial Basis Function, and a neural-like structure of Sequential Geometric Transformations Model. A combination of these methods was performed and the results of the three methods were compared. It is experimentally determined that the prediction of atmospheric air pollution parameters based on the error correction using the committee of neural-like structures of the Sequential Geometric Transformations Model provides a prediction error reduction by 7 % of the General Regression Neural Network and by 2.6 % of the Radial Basis Function with extended General Regression Network. The obtained results increase the reliability and speed of forecasting of atmospheric air parameters to improve the quality of monitoring of emissions of harmful impurities in production and to make environmental management decisions.

Triple decomposition of velocity gradient tensor in homogeneous isotropic turbulence

The triple decomposition of a velocity gradient tensor is studied with direct numerical simulations of homogeneous isotropic turbulence, where the velocity gradient tensor ∇u is decomposed into three components representing an irrotational straining motion (∇u)EL, a rigid-body rotation (∇u)RR, and a shearing motion (∇u)SH. Strength of these motions can be quantified with the decomposed components. A procedure of the triple decomposition is proposed for three-dimensional flows, where the decomposition is applied in a basic reference frame identified by examining a finite number of reference frames obtained by three sequential rotational transformations of a Cartesian coordinate. Even though more than one basic reference frame may be available for the triple decomposition, the results of the decomposition depend little on the choice of basic reference frame. In homogeneous isotropic turbulence, regions with strong rigid-body rotations or straining motions are highly intermittent in space, while most flow regions exhibit moderately strong shearing motions in the absence of straining motions and rigid-body rotations. In the classical double decomposition, the velocity gradient tensor is decomposed into a rate-of-rotation tensor Ωij and a rate-of-strain tensor Sij. Regions with large ω2=2ΩijΩij can be associated with rigid-body rotations and shearing motions while those with large s2=2SijSij can be associated with irrotational straining motions and shearing motions. Therefore, vortices with rigid-body rotations and shear layers in turbulence cannot be detected solely by thresholding ω or s while they can be identified simply with (∇u)RR and (∇u)SH in the triple decomposition, respectively. The thickness of the shear layer detected in the triple decomposition is about 8 times of Kolmogorov scale, while the velocity parallel to the layer changes rapidly across the layer, in which the velocity difference across the shear layer is of the order of the root-mean-squared velocity fluctuation.

Automated Detection and Classification of the Diatom Microscopic Photo Images

The diatoms (Bacillariophyta) are a species-rich and extremely widespread microalgae. Many diatom species require a fairly narrow range of ecological conditions (temperature, pH, salinity, saprobity, trophic level of the water etc.). They are very sensitive to changes of different water chemical parameters that allows to use of the diatoms as the indicators in monitoring of water quality as well as for the ecological reconstruction using bottom sediments. Different methods of the diatom analysis are based on the species composition and species amount in the preparations of plankton, benthos and epyphyton. However this analysis requires highly qualified staff and the manual processing of hundreds samples. The development of the computer tools for the automatic diatom species detection and identification is an actual task to improve the effectiveness of ecological studies and simplify the time-consuming routine work of the researchers. The image processing methods were investigated for the diatom species automatic identification in the light microscopic photos of the samples that were collected for the routine monitoring. The methods of segmentation of the images based on the threshold processing and morphological differentiation of the images were studied. The two-steps segmentation of the diatom photos was proposed. The method of artificially expanding the training dataset by sequential image transformation was applied. Based on the prepared training dataset, two realizations of convolutional neural networks were trained and their accuracy evaluated.

Багатокрокове прогнозування тренду показників забруднення атмосферного повітря

Наявність величезної кількості джерел небезпеки, спричинених діяльністю людини, становить реальну загрозу для самої людини і навколишнього середовища. Сучасний рівень організації та моніторингу забруднення навколишнього середовища висуває вимоги до розроблення нових підходів щодо вирішення проблеми контролю якості атмосферного повітря, прогнозування його забруднення та управління джерелами викидів шкідливих речовин на основі нових інформаційних технологій. Тому створення інтегрованих автоматизованих систем контролю та управління якістю атмосферного повітря, розроблення перспективних моделей і алгоритмів прогнозування забруднення повітря є актуальною проблемою. Одночасно розроблювані алгоритми прогнозування повинні бути простими та зрозумілими у використанні, тому у дослідженні описано та проаналізовано такі методи прогнозування параметрів забруднення атмосферного повітря: метод наївного прогнозу та методи прогнозування на основі лінійної нейроподібної структури моделі послідовних геометричних перетворень. Оскільки метод наївного прогнозу є найпростішим серед всіх існуючих методів, було виконано порівняння методу прогнозування на основі лінійної нейроподібної структури моделі послідовних геометричних перетворень (НС МПГП) саме зі згаданим методом, з ціллю визначення який метод результує з кращими показниками. Експериментально доведено, що метод прогнозування тренду шкідливої домішки CO на основі лінійної нейроподібної структури моделі послідовних геометричних перетворень є ефективним методом, оскільки показує точніші результати, ніж метод наївного прогнозу. Тому за допомогою розроблюваного методу виконано короткочасне багатокрокове прогнозування тренду забруднення атмосферного повітря.

Temporal Dynamics of the Soil Metabolome and Microbiome During Simulated Anaerobic Soil Disinfestation.

Significant interest exists in engineering the soil microbiome to attain suppression of soil-borne plant diseases. Anaerobic soil disinfestation (ASD) has potential as a biologically regulated disease control method; however, the role of specific metabolites and microbial community dynamics contributing to ASD mediated disease control is mostly uncharacterized. Understanding the trajectory of co-evolutionary processes leading to syntrophic generation of functional metabolites during ASD is a necessary prelude to the predictive utilization of this disease management approach. Consequently, metabolic and microbial community profiling were used to generate highly dimensional datasets and network analysis to identify sequential transformations through aerobic, facultatively anaerobic, and anaerobic soil phases of the ASD process and distinct groups of metabolites and microorganisms linked with those stages. Transient alterations in abundance of specific microbial groups, not consistently accounted for in previous studies of the ASD process, were documented in this time-course study. Such events initially were associated with increases and subsequent diminution in highly labile metabolites conferred by the carbon input. Proliferation and dynamic compositional changes in the Firmicutes community continued throughout the anaerobic phase and was linked to temporal changes in metabolite abundance including accumulation of small chain organic acids, methyl sulfide compounds, hydrocarbons, and p-cresol with antimicrobial properties. Novel potential modes of disease control during ASD were identified and the importance of the amendment and “community metabolism” for temporally supplying specific classes of labile compounds were revealed.