Use of a computer for the optimal results of treatment of diabetes mellitus with insulin

The authors present material on the optimization of diabetes mellitus treatment, with the aid of a computer. There were 320 patients under observation. Mathematical models describing the process of the patients treatment and permitting to pronosticate the blood and urine sugar level during the treatment were developed. The use of the imitation experiment on a computer permitted to test several therapeutic variants for the given patient and to choose the optimum one, leading to the most rapid compensation. The second task consisted in the maintenance in the patients of blood glucose variations within definite limits, in the course of 24 hours. An individual model of blood glucose dynamics in the course of 24 hours is set on the computer, and then the optimal scheme of insulin treatment is chosen. Practical testing of such scheme showed its efficacy.     

Neuroscience and architecture: What does the brain tell to an emotional experience of architecture via a functional MR study?

Environment psychologically affects individuals. According to the base of cognitive psychology, there is a direct relationship between human behavior, environment, and emotional process. Assuming that pleasantness and unpleasantness are associated with peripheral nervous system activation, the current study aims to explore if the pleasant or unpleasant architectural places can stimulate the brain regions engaged in emotions or not. As the main contribution, we used functional magnetic resonance imaging (fMRI) measuring blood oxygenation level-dependent (BOLD) changes to effectively detect the brain's region that mainly responds to the emotional-perceptual processes. Based on the results of examining the emotional assessment model of “Pleasure-Arousal” applied to 140 students, 30 most-rated images representing 15 pleasant and 15 unpleasant places were shown to 32 participants in a 1.5-T MRI scanner. After applying standard preprocessing steps (re-alignment, slice-timing, co-registration, segmentation, normalization, and smoothing) to functional MR images, first-level analysis was applied to each subject. The results were evaluated using statistical corrections at different levels for female and male participants with the second-level analysis. In conclusion, it has been shown that there is a significant linkage between environmental experience and brain activation so that the architectural qualities can change blood flow in specific brain regions.     

Evaluation of Non-Ambiguous Critical Micelle Concentration of Surfactants in Relation to Solution Behaviors of Pure and Mixed Surfactant Systems: A Physicochemical Documentary and Analysis

Critical micelle concentration (CMC) is a fundamental physical parameter of surfactant aggregation in solution. The CMC is determined by different methods, tensiometry, conductometry, microcalorimetry, fluorimetry, and so on. However, it is known that though CMC is reported as a single value, in reality, micelle formation occurs over a narrow range of concentration for different experimental procedures produce different results. We shall discuss about a unique procedure of measuring correct CMC applicable to all potential methods used in practice. This is essential for the evaluation of thermodynamic properties of the micelle forming process in pure and mixed states in terms of solution theories. As we in this short documentary want to deal with various aspects of Milton Rosen's research—wherein we have also worked—a few other facets of surfactant chemistry research, besides the micelle formation, are also briefly discussed. In mixed surfactant systems, synergistic effects in various surfactant properties like detergency, foaming, solubilization, and so on are found whereas in some others non-synergistic effects are observed. Dehydration of micelles with an increase in temperature or by the addition of hydrophilic substances may cause clouding to the system. Soluble amphiphilic systems produce Gibbs monolayer at the air/water interface; insoluble amphiphiles form Langmuir monolayers. A documentary of the above aspects will be herein presented and discussed. We mention that this article is neither an original research article nor a review article. This is a mixture of the two: a documentary of both original research and some review of our works presented in memory of Prof. Milton Rosen.     

Adaptive control of unactuated dynamical systems through interconnections: Stability and performance guarantees

This article studies control and performance enforcement for a class of uncertain dynamical systems that consist of actuated and unactuated portions physically interconnected to each other. The proposed approach stabilizes the overall interconnected system in the presence of unknown physical interconnections as well as system uncertainties. Performance guarantees are enforced, individually, on the actuated as well as unactuated portions of the interconnected system via this approach. For enforcing these performance guarantees, a set-theoretic model reference adaptive control approach is used, in conjunction with linear matrix inequalities, to restrict the respective system error trajectories of the actuated and unactuated dynamics inside a priori, user-defined compact sets. The efficacy of the proposed approach is demonstrated using simulations.     

Multicriteria decision-making using Archimedean aggregation operators in Pythagorean hesitant fuzzy environment

In multicriteria decision-making (MCDM), the existing aggregation operators are mostly based on algebraic t-conorm and t-norm. But, Archimedean t-conorms and t-norms are the generalized forms of t-conorms and t-norms which include algebraic, Einstein, Hamacher, Frank, and other types of t-conorms and t-norms. From that view point, in this paper the concepts of Archimedean t-conorm and t-norm are introduced to aggregate Pythagorean hesitant fuzzy information. Some new operational laws for Pythagorean hesitant fuzzy numbers based on Archimedean t-conorm and t-norm have been proposed. Using those operational laws, Archimedean t-conorm and t-norm-based Pythagorean hesitant fuzzy weighted averaging operator and weighted geometric operator are developed. Some of their desirable properties have also been investigated. Afterwards, these operators are applied to solve MCDM problems in Pythagorean hesitant fuzzy environment. The developed Archimedean aggregation operators are also applicable in Pythagorean fuzzy contexts also. To demonstrate the validity, practicality, and effectiveness of the proposed method, a practical problem is considered, solved, and compared with other existing method.     

Integration of machine learning and first principles models

Model building and parameter estimation are traditional concepts widely used in chemical, biological, metallurgical, and manufacturing industries. Early modeling methodologies focused on mathematically capturing the process knowledge and domain expertise of the modeler. The models thus developed are termed first principles models (or white-box models). Over time, computational power became cheaper, and massive amounts of data became available for modeling. This led to the development of cutting edge machine learning models (black-box models) and artificial intelligence (AI) techniques. Hybrid models (gray-box models) are a combination of first principles and machine learning models. The development of hybrid models has captured the attention of researchers as this combines the best of both modeling paradigms. Recent attention to this field stems from the interest in explainable AI (XAI), a critical requirement as AI systems become more pervasive. This work aims at identifying and categorizing various hybrid models available in the literature that integrate machine-learning models with different forms of domain knowledge. Benefits such as enhanced predictive power, extrapolation capabilities, and other advantages of combining the two approaches are summarized. The goal of this article is to consolidate the published corpus in the area of hybrid modeling and develop a comprehensive framework to understand the various techniques presented. This framework can further be used as the foundation to explore rational associations between several models.     

Optimal position and rating of DG in distribution networks by ABC–CS from load flow solutions illustrated by fuzzy-PSO

In this work, load flow problems of both radial distribution networks (RDNs) and mesh distribution networks (MDNs) have been solved using hybrid fuzzy-PSO algorithm. A new voltage stability index (VSI) is also indicated. Based on the suggested load flow, distributed generation (DG) is ready to conduct through the requirement; and with the support of inserting the optimal-sized DG unit in an exact way, the distribution system’s stability is also studied. The exact position of each DG unit has been computed using “loss sensitivity analysis,” whereas the optimal sizing of each DG unit has been done with the help of hybrid artificial bee colony and Cuckoo search algorithm. The suggested method is tested in the regular 33-node and 69-node RDNs as well as in 85-node and 119-node MDNs. The transcendence of the proposed operation has been centered with the aid of comparison to the other existing methods. The suggested VSI is also correlated with other two existing VSIs before and after placement of DG unit(s).

     

Social‐based reputation‐aware data forwarding for improved multicast delivery in the presence of selfish nodes in DTNs

Delay/disruption tolerant networks (DTNs) are potentially applicable in the challenged scenarios like post‐disaster environments. In such networks, data forwarding generally relies on the mutual cooperation of the nodes. However, in reality, despite the availability of necessary resources for data forwarding, a node could misbehave by dropping messages received from other nodes with whom it has no strong social ties. Such a node is called a socially selfish node, which would cause a poor delivery ratio in the network. In this paper, we aim to address the problem of multicast data forwarding in the presence of such selfish nodes, by means of efficient relay selection in DTNs. First, we define a realistic reputation model, in contrast to existing models, to define the socially selfish/misbehaving nodes in the network. Further, a game‐theoretic analysis is carried out that implies data forwarding cost is also an influential parameter in handling selfishness/misbehavior. Subsequently, the problem is formulated as a constrained optimization problem, which is NP hard. Therefore, a heuristic is proposed by combining the reputation of a node and the cost of message forwarding to appropriately identify relay nodes, thus improve the performance of the multicast message delivery in the network. We utilize a social metric, centrality to minimize the message forwarding cost in terms of the number of relay nodes. Finally, the comparative performance evaluation in ONE simulator with practical scenarios shows the superiority of the proposed scheme over the other prominent schemes.     

Highly birefringent large negative dispersion-flattened photonic crystal fibre for broadband residual dispersion compensation

A triangular lattice photonic crystal fibre is presented in this paper for residual dispersion compensation. The fibre exhibits a flattened negative dispersion of ?992.01 ± 6.93 ps/(nm-km) over S+C+L wavelength bands and ?995.83 ± 0.42 ps/(nm-km) over C-band. The birefringence is about 4.4 × 10^?2 at the excitation wavelength of 1550 nm which is also very high. Full vector finite element method (FEM) with a perfectly matched absorbing layer (PML) boundary condition is applied to numerically investigate the guiding properties of this PCF. The fibre operates at fundamental mode only. All these properties endorse this fibre as a suitable candidate for compensating residual dispersion and polarization maintaining applications.     

Novel analysis of the size and orientation dependent resonance phenomenon of the microstrip line coupled complementary split‐ring resonator

The purpose of this article is to provide a comprehensive investigation on the resonance phenomenon of microstrip line coupled complementary split‐ring resonator (CSRR) with different orientation and relative size. It is shown that when the relative size of the CSRR is smaller than the host line, the CSRR with its slit oriented orthogonal to the line axis will not excite effectively and show weak resonance behavior. However, when the slit is positioned along the line axis, the cross‐polarization effect comes into play, which excites the CSRR through the mixed coupling. To ensure the correctness, several numerical simulations are carried out for different substrate height and relative permittivity. Finally, a prototype is fabricated and measured for the experimental validation.