Lyapunov-type inequalities for fractional difference operators with discrete Mittag-Leffler kernel of order 2 &lt; <Emphasis Type="Italic">α</Emphasis> &lt; 5/2

Fractional difference operators with discrete-Mittag-Leffler kernels of order α > 1 are defined and their corresponding fractional sum operators are confirmed. We prove existence and uniqueness theorems for the discrete fractional initial value problems in the frame of discrete Caputo (ABC) and Riemann (ABR) operators by using Banach contraction theorem. Then, we prove Lyapunov type inequality for a Riemann type fractional difference boundary value problem of order 2 < α < 5∕2 within discrete Mittag-Leffler kernels, where the limiting case α → 2⁺ results in the ordinary difference Lyapunov inequality. Examples are given to clarify the applicability of our results and an application about the discrete fractional Sturm-Liouville eigenvalue problem is analyzed.     

Interfacial Compatibilization into PLA/Mg Composites for Improved In Vitro Bioactivity and Stem Cell Adhesion

The present work highlights the crucial role of the interfacial compatibilization on the design of polylactic acid (PLA)/Magnesium (Mg) composites for bone regeneration applications. In this regard, an amphiphilic poly(ethylene oxide-b-L,L-lactide) diblock copolymer with predefined composition was synthesised and used as a new interface to provide physical interactions between the metallic filler and the biopolymer matrix. This strategy allowed (i) overcoming the PLA/Mg interfacial adhesion weakness and (ii) modulating the composite hydrophilicity, bioactivity and biological behaviour. First, a full study of the influence of the copolymer incorporation on the morphological, wettability, thermal, thermo-mechanical and mechanical properties of PLA/Mg was investigated. Subsequently, the bioactivity was assessed during an in vitro degradation in simulated body fluid (SBF). Finally, biological studies with stem cells were carried out. The results showed an increase of the interfacial adhesion by the formation of a new interphase between the hydrophobic PLA matrix and the hydrophilic Mg filler. This interface stabilization was confirmed by a decrease in the damping factor (tanδ) following the copolymer addition. The latter also proves the beneficial effect of the composite hydrophilicity by selective surface localization of the hydrophilic PEO leading to a significant increase in the protein adsorption. Furthermore, hydroxyapatite was formed in bulk after 8 weeks of immersion in the SBF, suggesting that the bioactivity will be noticeably improved by the addition of the diblock copolymer. This ceramic could react as a natural bonding junction between the designed implant and the fractured bone during osteoregeneration. On the other hand, a slight decrease of the composite mechanical performances was noted.     

Simplified Method the Determination of Multiple Pesticides Residues in Water by Capillary Column Chromatography

Pesticides occur trace levels in water. The determination of pesticide residues involves complex methodologies composed of different analytical steps. Multiresidue analysis has been applied successfully to analyses for Pyrethroids, Organohalogens, Organophosphates, and Carbamatesl561 in agricultural products.     

GC-MS and GC-FID analyses of the volatile constituents of Brachychiton rupestris and Brachychiton discolor,their biological activities and their differentiation using multivariate data analysis

Abstract

The volatile constituents of the leaves and flowers of Brachychiton rupestris and Brachychiton discolor (Malvaceae) were characterized by GC-FID and GC-MS. A total of 92 compounds were identified. The major component of B. rupestris leaves was α-farnesene (34.57%) while in the flowers it was n-heptacosane (29.5%). (8Z, 11Z, 14Z)-heptadecatrienal (21.2%) in the leaves and palmitic acid (83.49%) in the flowers represent the abundant ingredients of B. discolor. Unsupervised pattern recognition techniques of multivariate data analysis exemplified by hierarchical cluster analysis (HCA) and principle component analysis (PCA) relying upon chromatographic results effectively discriminate the two related species. Also, both investigated species were assessed for their cytotoxic and antimicrobial efficacy. Results revealed that B. discolor flowers showed the highest cytotoxicity against human lung carcinoma (A-549) cell lines with IC₅₀ equals 7.98?μg/mL, whereas B. discolor leaves exhibited the highest antimicrobial potency against all tested microorganisms namely Streptococcus pneumonia, Bacillus subtilis, Escherichia coli as well as Aspergillus fumigatus and Geotrichum candidum (MICs between 0.98 and 15.63?µg/mL) except for Salmonella typhi.     

Using deep neural networks to diagnose engine pre-ignition

Engine downsizing and boosting have been recognized as effective strategies for improving engine efficiency. However, operating the engines at high load promotes abnormal combustion events, such as pre-ignition and potential superknock. Currently the most effective method for detecting pre-ignition is by using in-cylinder pressure sensors that have high precision and sensitivity, but also high cost. Due to rapid advances in automotive technology such as autonomous driving, computer-aided designs and future connectivity, we propose to use a complimentary data-driven strategy for diagnosing abnormal combustion events. To this end, a data-driven diagnostics approach for pre-ignition detection with deep neural networks is proposed. The success of convolutional neural networks (CNNs) in object detection and recurrent neural networks (RNNs) in sequence forecasting inspired us to develop these models for pre-ignition detection. For a cost-effective strategy, we use data from less expensive sensors, such as lambda and low-resolution exhaust back pressure (EBP), instead of high resolution in-cylinder pressure measurements. The first deep learning model is combined with a commonly used dimensionality reduction tool–Principal Component Analysis (PCA). The second model eliminates this step and directly processes time-series data. Results indicate that the first model with reduced input dimensions, and correspondingly smaller size of the network, shows better performance in detecting pre-ignition cycles with an F1 score of 79%. Overall, the proposed deep learning approach is a promising alternative for abnormal combustion diagnostics using data from low resolution sensors.     

Hamiltonian Formulation of Singular Lagrangians on Time Scales

The Hamiltonian formulation of Lagrangian on time scale is investigated and the equivalence of Hamilton and Euler-Lagrange equations is obtained. The role of Lagrange multipliers is discussed.     

Full-Energy peak efficiency of an NaI(Tl) detector with coincidence summing correction showing the effect of the source-to-detector distance

The coincidence summing effect is considered to be one of the most important problems in γ-ray spectrometry. It has played an important role in the detector calibration process, especially at low source-to-detector distances, which are the typical conditions when the environmental samples have to be measured. In this work, the γ–γ coincidence summing correction factors (CSCF) for a 3″×?3″ NaI(Tl) γ-ray detector have been calculated at different distances from the detector end cap. These factors with NaI(Tl) γ-ray detectors have rarely been discussed in the previous literature, due to the lack of the separation process of the close gamma energy lines in the scintillation detector spectrum. The γ–γ CSCF were calculated for ⁶⁰Co, ¹³³Ba and ¹⁵²Eu radioactive point sources, which show the simple and the complex decay scheme of several radionuclides. In order to obtain the CSCF, the following parameters must be estimated by the numerical simulation method (NSM): the total efficiency (ε_T), the full-energy peak efficiency (ε_P) and the effective solid angle (Ω_eff). These parameters were calculated numerically depending on the direct mathematical method and efficiency transfer method. The obtained CSCF was used to correct the measured efficiency curves, which were measured at different distances, then compared to the ETNA and EFFTRAN programs, as well as the CSCF. The results show a good agreement, especially at large source-to-detector distances.     

Design and Synthesis of Some New Analgesic Azole Derivatives Containing Tramadol Moiety

Some new triazole, thiadiazole, oxadiazole, thiazole, oxazole, and imidazole derivatives have been synthesized via the reaction of tramadol bearing a hydrazide, hydrazine carbodithioate, and/or acetic acid group with certain reagents. Molecular docking study had been carried out to demonstrate the reactivity of these synthetic compounds for interaction with Cytochrome P450 2D6 ( CYP2D6 ).