Synthesis of TiO(2)-PMMA nanocomposite: using methacrylic acid as a coupling agent

Inorganic-polymer nanocomposites are of significant interest for emerging materials due to their improved properties and unique combination of properties. Methacrylic acid (MA), a functionalization agent that can chemically link TiO2 nanomaterials (n-TiO2) and polymer matrix, was used to modify the surface of n-TiO2 using a Ti-carboxylic coordination bond. Then, the double bond in MA was copolymerized with methyl methacrylate (MMA) to form a n-TiO2-PMMA nanocomposite. The resulting n-TiO2-PMMA nanocomposite materials were characterized by using thermal analysis, electron microscopy, and elemental analysis. The dynamic mechanical properties (Young's and shear modulus) were measured using an ultrasonic pulse technique. The electron microscopy results showed a good distribution of the nanofillers in the polymer matrix. The glass transition temperature, thermal degradation temperature, and dynamic elastic moduli of the nanocomposites were shown to increase with an increase in the weight percentage of nanofibers in the composite. The resulting nanocomposites exhibited improved elastic properties and have potential application in dental composites and bone cements.     

Design,Synthesis, Biological Evaluation and In Silico Study of Benzyloxybenzaldehyde Derivatives as Selective ALDH1A3 Inhibitors

Aldehyde dehydrogenase 1A3 (ALDH1A3) has recently gained attention from researchers in the cancer field. Several studies have reported ALDH1A3 overexpression in different cancer types, which has been found to correlate with poor treatment recovery. Therefore, finding selective inhibitors against ALDH1A3 could result in new treatment options for cancer treatment. In this study, ALDH1A3-selective candidates were designed based on the physiological substrate resemblance, synthesized and investigated for ALDH1A1, ALDH1A3 and ALDH3A1 selectivity and cytotoxicity using ALDH-positive A549 and ALDH-negative H1299 cells. Two compounds (ABMM-15 and ABMM-16), with a benzyloxybenzaldehyde scaffold, were found to be the most potent and selective inhibitors for ALDH1A3, with IC₅₀ values of 0.23 and 1.29 µM, respectively. The results also show no significant cytotoxicity for ABMM-15 and ABMM-16 on either cell line. However, a few other candidates (ABMM-6, ABMM-24, ABMM-32) showed considerable cytotoxicity on H1299 cells, when compared to A549 cells, with IC₅₀ values of 14.0, 13.7 and 13.0 µM, respectively. The computational study supported the experimental results and suggested a good binding for ABMM-15 and ABMM-16 to the ALDH1A3 isoform. From the obtained results, it can be concluded that benzyloxybenzaldehyde might be considered a promising scaffold for further drug discovery aimed at exploiting ALDH1A3 for therapeutic intervention.     

On the crystallization of γ-isotactic polypropylene: A high pressure study

The non-parallel chain structure determined for γ-phase isotactic polypropylene (γ-iPP) is confirmed by Rietveld analysis for highly isotactic high molecular mass iPP crystallized at 200 MPa. The new refinement shows that: (i) stereoregularity or crystallization pressure do not significantly influence the lattice dimensions; (ii) defect inclusion in γ-iPP crystals is unlikely. The α and γ forms have nearly identical bulk internal energy and density, but α-iPP should be normally kinetically favored over γ-iPP which may in turn predominate due to its greater ability to host defects at the crystalline-amorphous interface.     

Statistics-Based Outlier Detection and Correction Method for Amazon Customer Reviews

People nowadays use the internet to project their assessments, impressions, ideas, and observations about various subjects or products on numerous social networking sites. These sites serve as a great source to gather data for data analytics, sentiment analysis, natural language processing, etc. Conventionally, the true sentiment of a customer review matches its corresponding star rating. There are exceptions when the star rating of a review is opposite to its true nature. These are labeled as the outliers in a dataset in this work. The state-of-the-art methods for anomaly detection involve manual searching, predefined rules, or traditional machine learning techniques to detect such instances. This paper conducts a sentiment analysis and outlier detection case study for Amazon customer reviews, and it proposes a statistics-based outlier detection and correction method (SODCM), which helps identify such reviews and rectify their star ratings to enhance the performance of a sentiment analysis algorithm without any data loss. This paper focuses on performing SODCM in datasets containing customer reviews of various products, which are (a) scraped from Amazon.com and (b) publicly available. The paper also studies the dataset and concludes the effect of SODCM on the performance of a sentiment analysis algorithm. The results exhibit that SODCM achieves higher accuracy and recall percentage than other state-of-the-art anomaly detection algorithms.     

The Effect of Wall Material Type on the Encapsulation Efficiency and Oxidative Stability of Fish Oils

Fish oil is the primary source of long-chain omega-3 fatty acids, which are important nutrients that assist in the prevention and treatment of heart disease and have many health benefits. It also contains vitamins that are lipid-soluble, such as vitamins A and D. This work aimed to determine how the wall material composition influenced the encapsulation efficiency and oxidative stability of omega fish oils in spray-dried microcapsules. In this study, mackerel, sardine waste oil, and sand smelt fish oil were encapsulated in three different wall materials (whey protein, gum Arabic (AG), and maltodextrin) by conventional spray-drying. The effect of the different wall materials on the encapsulation efficiency (EE), flowability, and oxidative stability of encapsulated oils during storage at 4 °C was investigated. All three encapsulating agents provided a highly protective effect against the oxidative deterioration of the encapsulated oils. Whey protein was found to be the most effective encapsulated agent comparing to gum Arabic and maltodextrin. The results indicated that whey protein recorded the highest encapsulation efficiency compared to the gum Arabic and maltodextrin in all encapsulated samples with EE of 71.71%, 68.61%, and 64.71% for sand smelt, mackerel, and sardine oil, respectively. Unencapsulated fish oil samples (control) recorded peroxide values (PV) of 33.19, 40.64, and 47.76 meq/kg oil for sand smelt, mackerel, and sardine oils after 35 days of storage, while all the encapsulated samples showed PV less than 10 in the same storage period. It could be concluded that all the encapsulating agents provided a protective effect to the encapsulated fish oil and elongated the shelf life of it comparing to the untreated oil sample (control). The results suggest that encapsulation of fish oil is beneficial for its oxidative stability and its uses in the production of functional foods.     

Formation of 3-Sulfonyl-Substituted Benzo[a]heptalene-2,4-diols from Heptalene-1,2-dicarboxylates and Lithiomethyl Phenyl Sulfones

On treatment with 6 mol-equiv. of lithiomethyl phenyl sulfone at −78° in THF, dimethyl 5,6,8,10-tetramethylheptalene-1,2-dicarboxylate ( 1′b ) gives, after raising the temperature to −10° and addition of 6 mol-equiv. of BuLi, followed by further warming to ambient temperature, the corresponding 3-(phenylsulfonyl)benzo[a]heptalene-2,4-diol 2b in yields up to 65% (cf. Scheme 6 and Table 2), in contrast to its double-bond-shifted (DBS) isomer 1b which gave 2b in a yield of only 6% [1]. The bisanion [ 9 ]²⁻ of the cyclopenta[a]heptalen-1(1H)-one 9 (cf. Fig. 1), carrying a (phenylsulfonyl)methyl substituent at C(11b), seems to be a key intermediate on the reaction path to 2b , because 9 is transformed in high yield into 2b in the presence of 6 mol-equiv. of BuLi in the temperature range of −10° to room temperature (cf. Scheme 7). Heptalene-dicarboxylate 1′b was also transformed into benzo[a]heptalene-2,4-diols 2c – g by a number of lithiated methyl X-phenyl sulfones and BuLi (cf. Scheme 9 and Table 3).     

Constraining chameleon field driven warm inflation with Planck 2018 data

The European Physical Journal C - We study the Yukawa model with one scalar and one axial scalar fields, coupled to N copies of Dirac fermions, in curved spacetime background. The theory possesses...     

Synthesis and Molecular Structure Investigation by DFT and X-Ray Diffraction of ARNO

Abstract  

We report here the synthesis of (Z)-5-(4-nitrobenzyliden)-3-N(2-ethoxyphenyl)-2-thioxo-thiazolidin-4-one (ARNO) compound. The crystal structure has been determined by X-ray diffraction. The compound crystallizes in the triclinic system with space group P[`1] P\bar{1} and cell parameters: a = 9.1289(19), b = 9.3717(7), c = 12.136(3) ?, α = 102.133(11)°, β = 90.99(2)°, γ = 117.165(9)°, V = 895.4(3) ?³ and Z = 2. The structure has been refined to a final R = 0.05 for 2591 observed reflections. The refined structure was found to be significantly non planar. The molecule exhibits intermolecular hydrogen bond of type C–H⋯O and C–H⋯S. ab initio calculations were also were performed at Hartree–Fock and density functional theory levels. The full HF and DFT geometry optimization was carried out using LANL2DZ, 6-31G* and B3LYP/6-31+G** basis sets. The optimized geometry of the title compound was found to be consistent structure determined by X-ray diffraction. The minimum energy of geometrical structure is obtained by using level HF/LANL2DZ basis sets.     

Qualitative possibilistic influence diagrams based on qualitative possibilistic utilities

This paper proposes a new approach for decision making under uncertainty based on influence diagrams and possibility theory. The so-called qualitative possibilistic influence diagrams extend standard influence diagrams in order to avoid difficulties attached to the specification of both probability distributions relative to chance nodes and utilities relative to value nodes. In fact, generally, it is easier for experts to quantify dependencies between chance nodes qualitatively via possibility distributions and to provide a preferential relation between different consequences. In such a case, the possibility theory offers a suitable modeling framework. Different combinations of the quantification between chance and utility nodes offer several kinds of possibilistic influence diagrams. This paper focuses on qualitative ones and proposes an indirect evaluation method based on their transformation into possibilistic networks. The proposed approach is implemented via a possibilistic influence diagram toolbox (PIDT).