Dominant Properties Research Articles

A Review on Adsorption and Desorption of Different Pesticides in Various Soil

Pesticides are important to the success of agriculture as well as an inevitable factor to maintain good public health. Over the years, the consumption of pesticides has increased manifold, particularly during the past two decades. However, this increase has caused great concern over the presence of residues or leftover pesticides in the environment. The understanding of adsorption and desorption behavior of different pesticides is an important phenomenon to describe the fate of pesticide in soil and other environmental compartment like water and sediment. The soil is considered as ultimate sink of pesticide as these were reached to soil directly or indirectly from the point/non-point sources. Adsorption–desorption processes are necessary in understanding pesticides retention behavior and its potential mobility within the soil. The behavior of pesticides in the soil depends on factors such as the physico-chemical properties of pesticides, the active surface of mineral, organic components and the amount of the pesticide applied. Henceforth, adsorption and desorption of soil applied pesticides needed to deal with greater sincerity. This review primarily ascertains dominant properties of pesticides including surface area, pH, surface functional groups, carbon content and aromatic structure and evaluate the adsorption and desorption of pesticide in agricultural soils. In addition, a vision for future research prospects has been anticipated by considering the pesticide bioavailability as residues in soil, influence of soil organic matter, clay content, pH and soil temperature on pesticide removal, pesticide properties and its behavior in soils.

Eigenmeasures and stochastic diagonalization of bilinear maps

A new stochastic approach is presented to understand general spectral type problems for (not necessarily linear) functions between topological spaces. In order to show its potential applications, we construct the theory for the case of bilinear forms acting in couples of a Banach space and its dual. Our method consists of using integral representations of bilinear maps that satisfy particular domination properties, which is shown to be equivalent to having a certain spectral structure. Thus, we develop a measure‐based technique for the characterization of bilinear operators having a spectral representation, introducing the notion of eigenmeasure, which will become the central tool of our formalism. Specific applications are provided for operators between finite and infinite dimensional linear spaces.

Highly Durable and Easily Integrable Triboelectric Foam for Active Sensing and Energy Harvesting Applications

AbstractTriboelectric nanogenerators (TENGs) have potential applications as active sensors or energy harvesters in self‐powered sensors and systems as they enable harvesting and conversion of mechanical energy into electrical energy. TENG development allows high‐efficiency energy harvesting capability and outstanding sensing characteristics, such as excellent output performance, high durability, reliable stability, easy integration, and convenient fabrication, among others. A triboelectric foam (T‐Foam) composed of a foam material with an embedded soft electrode is proposed in this study. The T‐Foam inherits the dominant mechanical properties of the foam material, which allows it to be freely folded, compressed, and kneaded, as well as immediate recovery upon stimulus withdrawal. The durability and stability of the T‐Foam are tested for a 0.1842 g sample; after stamping 14 times with a 158.6 lb tester, its output performance remained nearly identical. These properties indicate that the T‐Foam can be easily integrated into products, such as insoles, schoolbags, and seat mats, to build smart applications for motion, health, and safety monitoring. When driven by a polytetrafluoroethylene plate, a T‐Foam sample of 135 × 135 × 25 mm3 exhibits considerable energy harvesting capability, with the output power as high as 5.46 mW.

Properties of double Roman domination on cardinal products of graphs

Double Roman domination is a stronger version of Roman domination that doubles the protection. The areas now have 0 , 1 , 2 or 3 legions. Every attacked area needs 2 legions for its defence, either their own, or borrowed from 1 or 2 neighbouring areas, which still have to keep at least 1 legion to themselves. The minimal number of legions in all areas together is equal to the double Roman domination number. In this paper we determine an upper bound and a lower bound for double Roman domination numbers on cardinal product of any two graphs. Also we determine the exact values of double Roman domination numbers on P 2 × G (for many types of graph G ). Also, the double Roman domination number is found for P 2 × P n , P 3 × P n , P 4 × P n , while upper and lower bounds are given for P 5 × P n and P 6 × P n . Finally, we will give a case study to determine the efficiency of double protection. We will compare double Roman domination versus Roman domination by running a simulation of a battle.

Feature Extraction Based on Non-Subsampled Shearlet Transform (NSST) with Application to SAR Image Data

Considering the defaults in synthetic aperture radar (SAR) image feature extraction, an SAR target recognition method based on non-subsampled Shearlet transform (NSST) was proposed with application to target recognition. NSST was used to decompose an SAR image into multilevel representations. These representations were translation-invariant, and they could well reflect the dominant and detailed properties of the target. During the machine learning classification stage, the joint sparse representation was employed to jointly represent the multilevel representations. The joint sparse representation could represent individual components independently while considering the inner correlations between different components. Therefore, the precision of joint representation could be enhanced. Finally, the target label of the test sample was determined according to the overall reconstruction error. Experiments were conducted on the MSTAR dataset to examine the proposed method, and the results confirmed its validity and robustness under the standard operating condition, configuration variance, depression angle variance, and noise corruption.

Additional Properties of Frame Domination in Graphs

The generalization of frame domination concept on graphs is the main aims of this work. In addition, some advanced properties on frame domination have been presented. Some corresponding theorems related to delete, add edges or delete vertices have been proved. Also, the relationship between the original graph and a graph getting from contraction edges has been addressed. Finally, the upper and lower bounds of frame domination number for some special different graphs have been compared and determined.

Transports and Net Fluxes of Surface Wave Energy and Momentum inside Tropical Cyclones: Spectrum Computation and Modeling

AbstractTransports and net fluxes of surface wave energy and momentum inside tropical cyclones (TCs) are analyzed with wave spectra acquired by hurricane hunters. Previous analyses of dominant wave properties show a primary feature of sinusoidal azimuthal variation. Transports calculated from directional wave spectra are also primarily sinusoidal, which is modeled as a harmonic series. The result reveals that forward transport peaks are in the right-front quarter relative to the TC heading, and somewhat weaker valleys of backward transports are in the left-back quarter. Rightward transport peaks are in the right-back quarter and stronger leftward transport valleys are in the left-front quarter. Net fluxes are derived analytically from the gradients of transports. Their azimuthal variations are primarily biharmonic with forward trend confined in a slightly left-tilted parallel channel about a width two to three radius of maximum wind (RMW) on each side of the TC center. Leftward net fluxes are in a parallel channel of similar size and normal to that of the forward net fluxes. In vectors, the right-back quarter is a region of net influxes of energy and momentum. The TC central region has strong local fluxes that lead to bifurcation of the flux lines into leftward and forward paths. This may play a role in stabilizing the TC propagation. The net fluxes are a small fraction of the expected energy and momentum inputs from local wind except near the eye region. Within about 30 km from the TC center the local wind speed may exceed 30 m s−1 and the net fluxes can exceed 50% of the expected local wind input.

A Hybrid Genetic Algorithm for Integrated Production and Distribution Scheduling Problem with Outsourcing Allowed

In this paper, we studied a new integrated production scheduling, vehicle routing, inventory and outsourcing problem. The production phase considers parallel machine scheduling including setup times with outsourcing allowed and the distribution phase considered batch delivery by a fleet of homogenous vehicles with respect to holding cost of completed jobs. The objective of the Mixed Integer Linear Programming (MILP) formulated model is to minimize the total costs including production, outsourcing, holding, tardiness and distribution fixed and variable costs. Due to the nondeterministic polynomial time (Np)-hardness of the problem, we derive a number of dominance properties for the optimal solution and combine them with a Genetic Algorithm (GA) to solve the problem. To assess the efficiency and effectiveness of the proposed hybrid algorithm, we conduct the computational study on randomly generated instances. Sensitivity analyses showed the impacts of the parameters on the objective function were incorporated. In order to evaluate the significance of the differences among the results obtained by GA and GADP one-tailed paired t tests were performed and interval plots were depicted.

The central core and the mid-central core as novel set-valued and point-valued solution concepts for transferable utility coalitional games

This paper proposes two new solution concepts for transferable utility coalitional games that are Core selections, the Central Core and the Mid-central Core, with the first being set-valued and the latter point-valued. The basic idea at the root of the Central Core is to allow such Core elements that grant to each player at least the pay-off obtained from the centroid of the extreme points of the Core of the same game but with the worth of the grand coalition reduced to the minimum value such that the game remains balanced. The Mid-central Core is defined as the centroid of the extreme points of the Central Core.Some basic geometrical properties of the Central Core are then analysed, showing that it is a convex polytope that coincides with the Core under particular circumstances, or it is a strict subset of the Core. It is further shown that almost all fundamental axiomatic properties of the Core are preserved by these solutions.Finally, an axiomatization of the Mid-central Core is provided through the adaptation of the mid-point domination property to a coalitional setting. The Mid-central Core is the only solution satisfying individual and group rationality together with aggregate monotonicity and a version of mid-point domination whose reference set is shaped according to the mentioned axioms.

Cubic silicon carbide/zinc oxide heterostructure fuel cells

Multifunctional semiconductor cubic silicon carbide (3C-SiC) is employed for fuel cell electrolyte, which has never been used before. n-type 3C-SiC can be individually employed as the electrolyte in fuel cells, but delivers insufficient open circuit voltage and minuscule current density due to its electronic dominant property. By introducing n-type ZnO to form an n–n 3C-SiC/ZnO heterostructure, significant enhancements in the ionic conductivity of 0.12 S/cm and fuel cell performance of 270 mW cm−2 are achieved at 550 °C. It is found that the energy band bending and build-in electric field of the heterostructure play the pivotal role in the ionic transport and suppressing the electronic conduction of 3C-SiC, leading to a markable material ionic property and fuel cell performance. These findings suggest that 3C-SiC can be tuned to ionic conducting electrolyte for fuel cell applications through the heterostructure approach and energy band alignment methodology.

Research article game theory problems using interval parameters

In this paper, we consider a game with imprecise values in the payoff matrix. All the imprecise values are taken as intervals. Here, we solve anintervalgame problem based on pure strategy, mixed strategy and using dominance property. A graphical method is also given for solving 2 x n and m x 2interval game problem.To illustrate this, numerical examples are provided.

Highly Robust Tetranuclear Cobalt-Based 3D Framework for Efficient C2H2/CO2 and C2H2/C2H4Separations

A novel noninterpenetrated tetranuclear cobalt(II)-based metal-organic framework, (NH4)2·[Co4(μ3-OH)2(ina)2(pip)3]·4EtOH·H2O (simplified as NbU-10·S), constructed by mix linkers was synthesized by a hydrothermal method. Interestingly, the presence of a hydrophobic benzene ring in the organic linker makes NbU-10·S exhibit high stability in high temperature and even in aqueous solution over a wide pH range of about 4-13. Magnetic studies showed that the tetranuclear cobalt(II) units in NbU-10·S show dominant antiferromangetic properties. However, in the absence of Lewis basic functional sites and open metal sites in the material, NbU-10 still displays high C2H2/CO2 and C2H2/C2H4 selectivity in ideal adsorbed solution theory calculations and dynamic breakthrough experiments. Moreover, density functional theory calculations were performed to identify the adsorption characteristics of different gas molecules.

Low-complexity and fast-convergence linear precoding based on modified SOR for massive MIMO systems

Linear zero forcing (ZF) precoding can obtain near-optimal performance as the number of base station (BS) antennas increases, but involve complex matrix inversion calculations whose computational complexity is cubic with respect to the number of user equips (UEs) in massive multiple-input multiple-output (MIMO) systems. In this paper, a low-complexity modified successive over-relaxation-based ZF (MSOR-ZF) linear precoding is proposed, in which complicated matrix inversion is directly avoided through the use of MSOR iteration. Moreover, to further increase the convergence rate, the proposed MSOR-ZF precoding exploits the diagonal dominant property of the matrix instead of the original zero vector solution to achieve a satisfactory performance with a reduced iteration number. The proposed precoding is superior in convergence rate and reduces the computational complexity by approximately one order of magnitude, which is indicated by theoretical analysis. Simulation results demonstrate that the proposed precoding can achieve better achievable sum-rate and bit-error-ratio (BER) performance than some existing iterative-based precoding schemes with lower complexity.

Uncovering New Drug Properties in Target-Based Drug–Drug Similarity Networks

Despite recent advances in bioinformatics, systems biology, and machine learning, the accurate prediction of drug properties remains an open problem. Indeed, because the biological environment is a complex system, the traditional approach—based on knowledge about the chemical structures—can not fully explain the nature of interactions between drugs and biological targets. Consequently, in this paper, we propose an unsupervised machine learning approach that uses the information we know about drug–target interactions to infer drug properties. To this end, we define drug similarity based on drug–target interactions and build a weighted Drug–Drug Similarity Network according to the drug–drug similarity relationships. Using an energy-model network layout, we generate drug communities associated with specific, dominant drug properties. DrugBank confirms the properties of 59.52% of the drugs in these communities, and 26.98% are existing drug repositioning hints we reconstruct with our DDSN approach. The remaining 13.49% of the drugs seem not to match the dominant pharmacologic property; thus, we consider them potential drug repurposing hints. The resources required to test all these repurposing hints are considerable. Therefore we introduce a mechanism of prioritization based on the betweenness/degree node centrality. Using betweenness/degree as an indicator of drug repurposing potential, we select Azelaic acid and Meprobamate as a possible antineoplastic and antifungal, respectively. Finally, we use a test procedure based on molecular docking to analyze Azelaic acid and Meprobamate’s repurposing.

Rheological properties of carboxymethyl hydroxypropyl cellulose and its application in high quality reactive dye inkjet printing on wool fabrics

In this paper, the effect of rheological properties of pretreatment solutions, using carboxymethyl hydroxypropyl cellulose (CMHPC), sodium carboxymethyl cellulose (CMC), and sodium alginate (SA) as thickeners, on inkjet printing performance of wool with reactive dye inks was examined. Rheological, FESEM, and thickness results showed that fabrics treated with CMHPC solution, which exhibited superior fluidity, dominant elasticity property, and the largest zero-shear viscosity, produced the most continuous films and the lowest fabric thickness. Optical microscopy and XPS analyses confirmed that when compared with SA and CMC treated fabrics, CMHPC treated fabric controlled the excessive spread and penetration of ink droplets at higher effectiveness and produced the highest color strength (K/S value) and sharpest edge. In contrast to this, SA solution exhibited the worst fluidity, the most obvious viscous behavior, and lowest zero-shear viscosity. This resulted in the most discontinuous film, highest fabric thickness, and worst printing performance. Furthermore, wettability analysis demonstrated that the film structure dependent on the rheological property was the main factor that affected the inkjet printing performance of wool fabrics. CMHPC treatment of wool fabric provides an environment-friendly method with lower CMHPC concentration, less urea consumption, and shorter steaming time for higher K/S value.

Facile Synthesis of Aryl-Substituted Cycloarenes via Bismuth(III) Triflate-Catalyzed Cyclization of Vinyl Ethers

Cycloarenes are an essential class of polycyclic aromatic hydrocarbons with unique electronic structure, but their synthesis is very challenging. Herein, we report a facile synthetic strategy prima...

Decision-Making Analysis Based on Fermatean Fuzzy Yager Aggregation Operators with Application in COVID-19 Testing Facility

This research article is devoted to establish some general aggregation operators, based on Yager’s t-norm and t-conorm, to cumulate the Fermatean fuzzy data in decision-making environments. The Fermatean fuzzy sets (FFSs), an extension of the orthopair fuzzy sets, are characterized by both membership degree (MD) and nonmembership degree (NMD) that enable them to serve as an excellent tool to represent inexact human opinions in the decision-making process. In this article, the valuable properties of the FFS are merged with the Yager operator to propose six new operators, namely, Fermatean fuzzy Yager weighted average (FFYWA), Fermatean fuzzy Yager ordered weighted average (FFYOWA), Fermatean fuzzy Yager hybrid weighted average (FFYHWA), Fermatean fuzzy Yager weighted geometric (FFYWG), Fermatean fuzzy Yager ordered weighted geometric (FFYOWG), and Fermatean fuzzy Yager hybrid weighted geometric (FFYHWG) operators. A comprehensive discussion is made to elaborate the dominant properties of the proposed operators. To verify the importance of the proposed operators, an MADM strategy is presented along with an application for selecting an authentic lab for the COVID-19 test. The superiorities of the proposed operators and limitations of the existing operators are discussed with the help of a comparative study. Moreover, we have explained comparison between the proposed theory and the Fermatean fuzzy TOPSIS method to check the accuracy and validity of the proposed operators. The influence of various values of the parameter in the Yager operator on decision-making results is also examined.

Some Properties of Double Roman Domination

A double Roman dominating function on a graph G is a function f:VG⟶0,1,2,3 satisfying the conditions that every vertex u for which fu=0 is adjacent to at least one vertex v for which fv=3 or two vertices v1 and v2 for which fv1=fv2=2 and every vertex u for which fu=1 is adjacent to at least one vertex v for which fv≥2. The weight of a double Roman dominating function f is the value fV=∑u∈Vfu. The minimum weight of a double Roman dominating function on a graph G is called the double Roman domination numberγdRG of G. A graph with γdRG=3γG is called a double Roman graph. In this paper, we study properties of double Roman domination in graphs. Moreover, we find a class of double Roman graphs and give characterizations of trees with γdRT=γRT+k for k=1,2.

Predicting Thioflavin Fluorescence of Retinal Amyloid Deposits Associated With Alzheimer's Disease from Their Polarimetric Properties.

PurposeTo use machine learning in those with brain amyloid to predict thioflavin fluorescence (indicative of amyloid) of retinal deposits from their interactions with polarized light.MethodsWe imaged 933 retinal deposits in 28 subjects with post mortem evidence of brain amyloid using thioflavin fluorescence and polarization sensitive microscopy. Means and standard deviations of 14 polarimetric properties were input to machine learning algorithms. Two oversampling strategies were applied to overcome data imbalance. Three machine learning algorithms: linear discriminant analysis, supporting vector machine, and random forest (RF) were trained to predict thioflavin positive deposits. For each method; accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve were computed.ResultsFor the polarimetric positive deposits, using 1 oversampling method, RF had the highest area under the receiver operating characteristic curve (0.986), which was not different from that with the second oversampling method. RF had 95% accuracy, 94% sensitivity, and 97% specificity. After including deposits with no polarimetric signals, polarimetry correctly predicted 93% of thioflavin positive deposits. Linear retardance and linear anisotropy were the dominant polarimetric properties in RF with 1 oversampling method, and no polarimetric properties were dominant in the second method.ConclusionsThioflavin positivity of retinal amyloid deposits can be predicted from their images in polarized light. Polarimetry is a promising dye-free method of detecting amyloid deposits in ex vivo retinal tissue. Further testing is required for translation to live eye imaging.Translational RelevanceThis dye-free method distinguishes retinal amyloid deposits, a promising biomarker of Alzheimer's disease, in human retinas imaged with polarimetry.

Supervised framework for top-down color interest point detection

Selective attention is one of the dominant properties of the biological visual system to locate regions of interest in the scene. This article presents a local feature detector based on selective attention. Most previous approaches are bottom-up and do not consider prior information for known object categories. They detect feature points using spatial information present in the image. In contrast, this article presents an attention inspired algorithm that encapsulates the second-moment matrix-based detector to identify feature points based on some color information selectively. The intuition is to use skin color as a top-down cue to generate interest points, finding a high similarity to known spectra. It has applications in a variety of real-time applications such as image retrieval, gesture classification, virtual reality, etc. The technique is inspired by the human visual perception to gain cognizance of regions based on selective boosting of colors. The properties of color models are used to form a distinctiveness function to suppress unwanted background clutter. A relationship between interest points and salient colors in the image is computed using partial correlations in color derivative space. The system is evaluated on the MSRA dataset commonly used for saliency detection. The experiments are based on finding distinct regions having an affinity towards skin color. The robustness of the algorithm is tested in a realistic scenario by separate training and testing datasets. Experimental results show a high level of repeatability for different noise variations, image compression, and blur. The simplicity, robustness, and efficiency of the technique to locate color interest points make it appropriate for real-time vision systems.