Synthesis and characterization of cellulose acetate from cellophane industry residues. Application as acetaminophen controlled-release membranes

Journal of Thermal Analysis and Calorimetry - Cellophane film production generates cellulosic residues from scraps, edges, and low-quality films. In this work, cellophane was used as a raw material...     

Topology optimization of composite hyperelastic material using SPIMFO-method

Meccanica - Fiber reinforced materials are used in assorted engineering application and for this reason, new additive manufacturing technologies have been developed for this type of materials. With...     

One Spot Microwave Synthesis and Characterization of Nitrogen-Doped Carbon Dots with High Oxygen Content for Fluorometric Determination of Banned Sudan II Dye in Spice Samples

Journal of Fluorescence - A simple microwave-assisted synthesis of nitrogen-doped carbon dots with high oxygen content (O-N-CDs) was carried out with citric acid as a carbon source and...     

Co-Training for Visual Object Recognition Based on Self-Supervised Models Using a Cross-Entropy Regularization

Automatic recognition of visual objects using a deep learning approach has been successfully applied to multiple areas. However, deep learning techniques require a large amount of labeled data, which is usually expensive to obtain. An alternative is to use semi-supervised models, such as co-training, where multiple complementary views are combined using a small amount of labeled data. A simple way to associate views to visual objects is through the application of a degree of rotation or a type of filter. In this work, we propose a co-training model for visual object recognition using deep neural networks by adding layers of self-supervised neural networks as intermediate inputs to the views, where the views are diversified through the cross-entropy regularization of their outputs. Since the model merges the concepts of co-training and self-supervised learning by considering the differentiation of outputs, we called it Differential Self-Supervised Co-Training (DSSCo-Training). This paper presents some experiments using the DSSCo-Training model to well-known image datasets such as MNIST, CIFAR-100, and SVHN. The results indicate that the proposed model is competitive with the state-of-art models and shows an average relative improvement of 5% in accuracy for several datasets, despite its greater simplicity with respect to more recent approaches.     

Two algorithms for the exchange lemma

Numerical Algorithms - In this note, we present two new algorithms for the Steinitz Exchange Lemma. They are grounded on a single application of a procedure (finding either a row echelon form or a...     

The use of dilatometry aiming to evaluate the metallurgical aspect of coil slump in a hot-rolled medium carbon steel

Journal of Thermal Analysis and Calorimetry - The hot coil slump is a recurrent problem in the manufacturing process of medium and high equivalent carbon steel plates. Even with the success of the...     

Comparative bioavailability of two zolpidem hemitartrate formulations in healthy human Brazilian volunteers using high-performance liquid chromatography coupled to tandem mass spectrometry

To assess the bioequivalence of two zolpidem hemitartrate formulations in 30 healthy volunteers. Plasma samples were obtained over a 24 h period. Plasma concentrations of zolpidem were analyzed by liquid chromatography coupled to tandem mass spectrometry with positive ion electrospray ionization using multiple reaction monitoring. Values of peak concentration (C_max), area under curve (AUC), half-life, elimination constant, volume of distribution and clearance showed statistically significant differences when comparing women (604.34 ng h/ml, 127.36 ng/ml, 4.4 h, 0.18 1/h, 50.56 L and 8.55 L/h, respectively) and men (276.1 ng h/ml, 70.9 ng/ml, 3.3 h, 0.26 1/h, 91.42 L and 24.34 L/h, respectively), receiving the same dose (5 mg), respectively. The geometric means with corresponding 90% confidence interval for Test/Reference percentage ratios were 99.73% (CI 93.69–106.16) for C_max, 97.44% (90% CI = 91.85–103.37%) for area under curve of plasma concentration until the last concentration observed (AUC_last) and 98.30% (90% CI = 92.48–104.49) for the area under curve between the first sample (pre-dosage) and infinity (AUC_0–inf). Since the 90% CI for AUC_last, AUC_0–inf and C_max ratios were within the 80–125% interval proposed by the US Food and Drug Administration, it was concluded that zolpidem hemitartrate formulation (5 mg orodispersible tablet) is bioequivalent to the zolpidem hemitartrate formulation (Patz SL 5 mg sublingual tablet) with regard to both the rate and the extent of absorption. A new formulation of zolpidem 2.5 mg may be useful in women for the same clinical benefits as the 5 mg formulation in men.     

Shaping metal–organic framework (MOF) powder materials for CO2 capture applications—a thermogravimetric study

Journal of Thermal Analysis and Calorimetry - The paper presents the effect of the tabletting pressure and time on the chemical structure and crystallinity of the CuBTC and MIL-53(Al)...     

An unexpected Pummerer rearrangement in the synthetic route to ethyl (2′-hydroxy-4′,5′-methylenedioxyphenyl)acetate: An alternative approach to 2,3-dimethylthio benzofurans

The synthesis of ethyl (2′-hydroxy-4′,5′-methylendioxophenyl)acetate, a fragment of the antihyperglycemic natural coumarin subcoriacin, is reported. We found an expeditious route to the title compound in five steps. Final metal catalyzed acid ethanolysis of the vinylic 1,1-methylthio methylsulfoxide derivative afforded the required aryl acetic ester, but in the absence of metal catalyst, an unexpected Pummerer rearrangement produced the 2,3-dimethylthiofuran derivative as the major product. This last result provides an alternative entry to 2,3-dimethlythiobenzofurans.