The Multifunctional Role of Herbal Products in the Management of Diabetes and Obesity: A Comprehensive Review

Obesity and diabetes are the most demanding health problems today, and their prevalence, as well as comorbidities, is on the rise all over the world. As time goes on, both are becoming big issues that have a big impact on people’s lives. Diabetes is a metabolic and endocrine illness set apart by hyperglycemia and glucose narrow-mindedness because of insulin opposition. Heftiness is a typical, complex, and developing overall wellbeing worry that has for quite some time been connected to significant medical issues in individuals, all things considered. Because of the wide variety and low adverse effects, herbal products are an important hotspot for drug development. Synthetic compounds are not structurally diverse and lack drug-likeness properties. Thus, it is basic to keep on exploring herbal products as possible wellsprings of novel drugs. We conducted this review of the literature by searching Scopus, Science Direct, Elsevier, PubMed, and Web of Science databases. From 1990 until October 2021, research reports, review articles, and original research articles in English are presented. It provides top to bottom data and an examination of plant-inferred compounds that might be utilized against heftiness or potentially hostile to diabetes treatments. Our expanded comprehension of the systems of activity of phytogenic compounds, as an extra examination, could prompt the advancement of remedial methodologies for metabolic diseases. In clinical trials, a huge number of these food kinds or restorative plants, as well as their bioactive compounds, have been shown to be beneficial in the treatment of obesity.     

CT and MRI Medical Image Fusion Using Noise-Removal and Contrast Enhancement Scheme with Convolutional Neural Network

Medical image fusion (MIF) has received painstaking attention due to its diverse medical applications in response to accurately diagnosing clinical images. Numerous MIF methods have been proposed to date, but the fused image suffers from poor contrast, non-uniform illumination, noise presence, and improper fusion strategies, resulting in an inadequate sparse representation of significant features. This paper proposes the morphological preprocessing method to address the non-uniform illumination and noise by the bottom-hat–top-hat strategy. Then, grey-principal component analysis (grey-PCA) is used to transform RGB images into gray images that can preserve detailed features. After that, the local shift-invariant shearlet transform (LSIST) method decomposes the images into the low-pass (LP) and high-pass (HP) sub-bands, efficiently restoring all significant characteristics in various scales and directions. The HP sub-bands are fed to two branches of the Siamese convolutional neural network (CNN) by process of feature detection, initial segmentation, and consistency verification to effectively capture smooth edges, and textures. While the LP sub-bands are fused by employing local energy fusion using the averaging and selection mode to restore the energy information. The proposed method is validated by subjective and objective quality assessments. The subjective evaluation is conducted by a user case study in which twelve field specialists verified the superiority of the proposed method based on precise details, image contrast, noise in the fused image, and no loss of information. The supremacy of the proposed method is further justified by obtaining 0.6836 to 0.8794, 0.5234 to 0.6710, and 3.8501 to 8.7937 gain for QFAB, CRR, and AG and noise reduction from 0.3397 to 0.1209 over other methods for objective parameters.     

Isolation and Identification of Bioactive Compounds from Bidens spp. Using HPLC-DAD and GC-MS Analysis and Their Biological Activity as Anticancer Molecules

The genus Bidens a member of family Compositae, is widely documented as an ethno-medicinally important genus of plants. In the present study, anticancer potential of three ethno-medicinally important species i.e., B. bipinnata, B. biternata and B. pilosa were tested. For in-vitro evaluation, an MTT (Thiazolyl blue tetrazolium bromide) assay was performed against cervical cancer cells (HeLa), hepatocellular carcinoma (HepG), and adenocarcinoma human alveolar basal epithelial cells (A549). For in vivo evaluation, Artemia salina, Danio rerio, and Caenorhabditis elegans were used. Among all the tested extracts, the ethanol extract of B. biternata appeared to have highest anticancer activity, and the compounds responsible for this activity were identified to be Tris (2,4-di-tert-butylphenyl), 4-hydroxy-2,4′-dimethoxychalcone, and 2,4-di-tert-butylphenol. This is the first report of the isolation of Tris (2,4-di-tert-butylphenyl) phosphate from the genus Bidens and the first report of 4-hydroxy-2,4′-dimethoxychalcone and 2,4-di-tert-butylphenol from B. biternata. Among the isolated compounds, 4-hydroxy-2,4′-dimethoxychalcone showed the highest anticancer activity with an LD50 value of 236.7 µg/mL. Therefore, this compound carries promising potential for being established as a pharmaceutical for chemoprevention and chemotherapy.     

Phase diagrams of a spin-1 Ising superlattice

The three-dimensional spin-1 Ising superlattice consisting of two different ferromagnetic materials with two different crystal fields _Δ1${\Delta }_1$ and _Δ2${\Delta }_2$ is considered in the mean field approximation. The phase diagrams are considered in the (t,_d2$t,d_2$) plane for different ranges of variation of _d1(t=T/J,_d1=_Δ1/J$d_1(t=T/J,d_1={\Delta }_1/J$, _d2=_Δ2/J$d_2={\Delta }_2/J$ are the reduced temperature and crystal fields respectively). The phase diagrams exhibit a variety of multicritical points and reentrant and double reentrant behaviours. They are found to depend qualitatively and/or quantitatively on the thicknesses of the materials in a supercell. This has direct consequences on the nature of the magnetic states of superlattices with different thicknesses.     

The role of F A1:Ag+ defects in laser light generation and coadsorption of CO and halogen atoms at the KCl and KBr surface sites. First principles calculations

F _A1:Ag⁺ color center at the low coordination (100) and (110) surface sites of KCl and KBr thin films play an important role in providing tunable laser oscillation and adsorbatesubstrate interactions. Double-well potentials at this site are investigated using ab initio molecular electronic structure calculations. The calculated Stokes shifted (optical transition bands), opticaloptical conversion efficiencies, the probability of orientational destruction, exciton (energy) transfer and Glasner-Tompkins empirical rule suggest that laser light generation is sensitive to (i) the lattice anion, (ii) the coordination number of surface ions, and (iii) the choice of the basis set centered on the anion vacancy. The adsorbate-substrate interactions were found to be dependent on the electronegativity of the adatom and on the lattice anion. Optimised geometries and the coadsorption of CO and (F, Cl, Br, I) on KCl and KBr (100) crystals are presented. Calculated chemisorption energies for CO on the (halogen atom/defect free sites of KCl and KBr (100) crystals) showed that the coadsorption of halogen atom tends to block other adsorbate-substrate interactions at the nearest neighbour sites. Thus if halogen atom coverage increases, the CO prefers to be adsorbed on the K⁺ site of the KCl and KBr (100) surfaces and on KBr relative to KCl.      

Thermally Radiative Rotating Magneto-Nanofluid Flow over an Exponential Sheet with Heat Generation and Viscous Dissipation:A Comparative Study

This article examines a mathematical model to analyze the rotating flow of three-dimensional water based nanofluid over a convectively heated exponentially stretching sheet in the presence of transverse magnetic field with additional effects of thermal radiation,Joule heating and viscous dissipation.Silver(Ag),copper(Cu),copper oxide(Cu O),aluminum oxide(Al_2O_3)and titanium dioxide(Ti O_2)have been taken under consideration as the nanoparticles and water(H_2O)as the base fluid.Using suitable similarity transformations,the governing partial differential equations(PDEs)of the modeled problem are transformed to the ordinary differential equations(ODEs).These ODEs are then solved numerically by applying the shooting method.For the particular situation,the results are compared with the available literature.The effects of different nanoparticles on the temperature distribution are also discussed graphically and numerically.It is witnessed that the skin friction coefficient is maximum for silver based nanofluid.Also,the velocity profile is found to diminish for the increasing values of the magnetic parameter.     

Search for heavy particles decaying into electron-positron pairs in pp collisions

We present results of searches for technirho (rho(T)), techniomega (omega(T)), and Z' particles, using the decay channels rho(T),omega(T),Z'-->e(+)e(-). The search is based on 124.8 pb(-1) of data collected by the D0 detector at the Fermilab Tevatron during 1992-1996. In the absence of a signal, we set 95% C.L. upper limits on the cross sections for the processes pp-->rho(T),omega(T),Z'-->e(+)e(-) as a function of the mass of the decaying particle. For certain model parameters, we exclude the existence of degenerate rho(T) and omega(T) states with masses below about 200 GeV. We exclude a Z' with mass below 670 GeV, assuming that it has the same couplings to fermions as the Z boson.     

Dielectric behavior of hexaferrites BaCo2−xZnxFe16O27

The dielectric constant (′) and dielectric loss (tan δ) for hexaferrites BaCo_2−xZn_xFe₁₆O₂₇ have been studied as a function of frequency (f), temperature (T) and composition (x). The experimental results indicate that ′ and tan δ above the relaxation frequency only decrease as the frequency increases and as the temperature decreases. Tan δ shows the dielectric relaxation at certain critical frequencies which rise as temperature increases. The activation energy for the dielectric relaxation (E_D), ′, and tan δ are found to be minimum for x = 0.8.     

A stochastic programming approach for planning horizons of infinite horizon capacity planning problems

Planning horizon is a key issue in production planning. Different from previous approaches based on Markov Decision Processes, we study the planning horizon of capacity planning problems within the framework of stochastic programming. We first consider an infinite horizon stochastic capacity planning model involving a single resource, linear cost structure, and discrete distributions for general stochastic cost and demand data (non-Markovian and non-stationary). We give sufficient conditions for the existence of an optimal solution. Furthermore, we study the monotonicity property of the finite horizon approximation of the original problem. We show that, the optimal objective value and solution of the finite horizon approximation problem will converge to the optimal objective value and solution of the infinite horizon problem, when the time horizon goes to infinity. These convergence results, together with the integrality of decision variables, imply the existence of a planning horizon. We also develop a useful formula to calculate an upper bound on the planning horizon. Then by decomposition, we show the existence of a planning horizon for a class of very general stochastic capacity planning problems, which have complicated decision structure.