Microwave attenuation in isotopically disordered semiconductor crystals

110-114In an isotopically disordered semiconductor crystal , electrons interact with harmonic and localized phonon fields, which causes dramatic changes in the dynamical properties. In order to discuss these effects the double time thermodynamic Green's function has been evaluated using the equation of motion technique of quantum dynamics via a newly formulated Hamiltonian, which include selectron, harmonic phonon, electron-phonon and defect contributions. The expression for microwave attenuation so developed is found to depend chiefly on electron-phonon coupling, force constant changes and temperature.</span

Thermodynamics and kinetics to develop an analytical method for sensing of aqueous Hg(II) using caffeic acid decorated AgNPs

Mercury (Hg) and its compounds are exceptionally noxious and extensively distributed in the atmosphere. We have used caffeic acid decorated silver nanoparticles (CA–AgNPs) for the colorimetric detection of the Hg(II) ions in the aqueous systems. In this method, a paper strip was simply used as a dipstick type device for the fast and selective detection of the aqueous Hg(II) ions. The paper strip displays a color change within 50 seconds with superior selectivity after being dipped into the solution containing a concentration of Hg(II) ions in the range of 20–0.0001 ppm. The developed method allows us to detect Hg(II) through naked eyes with a LOD of 0.0001 ppm. The interaction between prepared CA–AgNPs and Hg(II) was also studied using reactive kinetics, thermodynamic parameters and density functional theory (DFT). The proposed method can be a cost-effective tool for field-level applications for on-site real-time detection of mercury

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Not AvailablePedotransfer functions (PTFs) for estimation of soil water retention at field capacity (θFC, -33 kPa) and permanent wilting point (θPWP, -1500 kPa) were developed under three soil categories (<20%, 20-40% and >40% clay) through linear, log-linear and stepwise-regression (SR) approach, using particle size distribution and bulk density data. Under <20% clay, the log-linear model was better than other models in predicting θFC, whereas SR model was better for predicting θPWP. Under 20-40% clay category, all the three approaches predicted θFC with equal efficiency, while SR was superior for θPWP. The log-linear models performed better in predicting both the θFC and θPWP with >40% soil clay.Not Availabl

Neuroinflammatory Markers: Key Indicators in the Pathology of Neurodegenerative Diseases

Neuroinflammation, a protective response of the central nervous system (CNS), is associated with the pathogenesis of neurodegenerative diseases. The CNS is composed of neurons and glial cells consisting of microglia, oligodendrocytes, and astrocytes. Entry of any foreign pathogen activates the glial cells (astrocytes and microglia) and overactivation of these cells triggers the release of various neuroinflammatory markers (NMs), such as the tumor necrosis factor-&alpha; (TNF-&alpha;), interleukin-1&beta; (IL-1&beta;), interleukin-1&beta; (IL-10), nitric oxide (NO), and cyclooxygenase-2 (COX-2), among others. Various studies have shown the role of neuroinflammatory markers in the occurrence, diagnosis, and treatment of neurodegenerative diseases. These markers also trigger the formation of various other factors responsible for causing several neuronal diseases including Alzheimer&rsquo;s disease (AD), Parkinson&rsquo;s disease (PD), Huntington&rsquo;s disease (HD), multiple sclerosis (MS), ischemia, and several others. This comprehensive review aims to reveal the mechanism of neuroinflammatory markers (NMs), which could cause different neurodegenerative disorders. Important NMs may represent pathophysiologic processes leading to the generation of neurodegenerative diseases. In addition, various molecular alterations related to neurodegenerative diseases are discussed. Identifying these NMs may assist in the early diagnosis and detection of therapeutic targets for treating various neurodegenerative diseases

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Not AvailableSoil field capacity (FC) and permanent wilting point (PWP) are important input parameters in many biophysical models. Although these parameters can be measured directly, their measurement is quite difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. A study has been conducted to evaluate PTFs of FC and PWP created using artificial neural networks (ANNs). A total of 721 different sampling locations spread all over India are selected to develop PTFs using ANN. Results indicate that six neurons in hidden layers are best suited for prediction of FC and PWP. The statistical criteria (value of R2, RMSE, MBE, ME, and d) is used to evaluate ANN, indicated an unbiased and higher predictability of developed models.Not Availabl

Electronic heat capacity of crystalline solids

288-293<span style="font-size:14.0pt;line-height: 115%;font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" color:black;mso-ansi-language:en-in;mso-fareast-language:en-in;mso-bidi-language:="" hi"="" lang="EN-IN">The expressions for the electron density of states (EDOS) and electronic heat capacity (EHC) have been obtained for an isotopically disordered anharmonic crystal. The quantum dynamics of the crystal has been discussed in the light of an almost complete Hamiltonian consisting of (i) harmonic and anharmonic phonon fields, (ii) electrons, (iii) electron-phonon interaction and (iv) localized fields. It is observed that the electron-phonon coupling plays a crucial role in determining EDOS and EHC. The temperature dependence of EDOS is the remarkable feature of the present formulation</span

An Evaluation of Regression Algorithms Performance for the Chemical Process of Naphthalene Sublimation

Part 5: Machine Learning - Regression - ClassificationInternational audienceDifferent regression algorithms are applied for predicting the sublimation rate of naphthalene in various working conditions: time, temperature, trainer rate and shape of the sample. The original Large Margin Nearest Neighbor Regression (LMNNR) algorithm is applied and its performance is compared to other well-established regression algorithms, such as support vector regression, multilayer perceptron neural networks, classical k-nearest neighbor, random forest, and others. The experimental results obtained show that the LMNNR algorithm provides better results than the other regression algorithms

Myricetin bioactive effects: moving from preclinical evidence to potential clinical applications

Several flavonoids have been recognized as nutraceuticals, and myricetin is a good example. Myricetin is commonly found in plants and their antimicrobial and antioxidant activities is well demonstrated. One of its beneficial biological effects is the neuroprotective activity, showing preclinical activities on Alzheimer, Parkinson, and Huntington diseases, and even in amyotrophic lateral sclerosis. Also, myricetin has revealed other biological activities, among them as antidiabetic, anticancer, immunomodulatory, cardiovascular, analgesic and antihypertensive. However, few clinical trials have been performed using myricetin as nutraceutical. Thus, this review provides new insights on myricetin preclinical pharmacological activities, and role in selected clinical trials