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This paper presents experimental and numerical results of butt friction stir welding of high density polyethylene. The FSW designed tool insulates the welded samples and preserves the heat gained from friction thus avoiding the appearance of blisters and splits after welding. The experimental tests, conducted according to combinations of process factors such as rotation speed, welding speed, pin diameter and hold time at beginning welding, were carried out according the Taguchi orthogonal table L27 in randomized way. Temperatures in the joint during the welding operation and flow stresses from the tensile tests of welded samples were measured and variances were analyzed. Identified models were used to simulate, by finite elements, the tensile tests performed on specimens having a weld cordon in their active area. The results show coherence between the numerical predictions and experimental observations in different cases of weld cordon mechanical behaviour.

2-Amino[2.2]paracyclophane reacts with salicylaldehyde or 2-hydroxyacetophenone to yield imines that then give access to a new series of boranils (8b-d) upon complexation with BF 2 . These novel boron-containing compounds display both planar and axial chiralities and were examined experimentally and computationally. In particular, their photophysical and chiroptical properties were studied and compared to newly prepared, simpler boranils (9a-d) exhibiting axial chirality only. Less sophisticated chiral architectures were shown to demonstrate overall stronger circularly polarized luminescence (CPL) activity., (© 2023 The Authors. Chirality published by Wiley Periodicals LLC.)

Mono- and di-boranil-substituted helicenes were prepared by BF 2 -borylation of the corresponding anils, readily synthesized by condensation of 2-amino- and 2,15-diamino-helicenes with 4-(diethylamino)salicylaldehyde. After enantiomeric resolution using HPLC, their chiroptical properties including circularly polarized fluorescence in solution and in PMMA films were investigated and rationalized with the help of NMR, X-ray and quantum-chemical calculations., (© 2021 Wiley-VCH GmbH.)

Background and Objective: Accurate mass segmentation in mammographic images is a critical requirement for computer-aided diagnosis systems since it allows accurate feature extraction and thus improves classification precision., Methods: In this paper, a novel automatic breast mass segmentation approach is presented. This approach consists of mainly three stages: contour initialization applied to a given region of interest; construction of fuzzy contours and estimation of fuzzy membership maps of different classes in the considered image; integration of these maps in the Chan-Vese model to get a fuzzy-energy based model that is used for final delineation of mass., Results: The proposed approach is evaluated using mass regions of interest extracted from the mini-MIAS database. The experimental results show that the proposed method achieves an average true positive rate of 91.12% with a precision of 88.08%., Conclusions: The achieved results show high accuracy in breast mass segmentation when compared to manually annotated ground truth and to other methods from the literature., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Medical imaging modalities such as computed tomography (CT) combined with computer-aided diagnostic processing have already become important part of clinical routine specially for pleural diseases. The segmentation of the thoracic cavity represents an extremely important task in medical imaging for different reasons. Multiple features can be extracted by analyzing the thoracic cavity space and these features are signs of pleural diseases including the malignant pleural mesothelioma (MPM) which is the main focus of our research. This paper presents a method that detects the MPM in the thoracic cavity and plans the photodynamic therapy in the preoperative phase. This is achieved by using a texture analysis of the MPM region combined with a thoracic cavity segmentation method. The algorithm to segment the thoracic cavity consists of multiple stages. First, the rib cage structure is segmented using various image processing techniques. We used the segmented rib cage to detect feature points which represent the thoracic cavity boundaries. Next, the proposed method segments the structures of the inner thoracic cage and fits 2D closed curves to the detected pleural cavity features in each slice. The missing bone structures are interpolated using a prior knowledge from manual segmentation performed by an expert. Next, the tumor region is segmented inside the thoracic cavity using a texture analysis approach. Finally, the contact surface between the tumor region and the thoracic cavity curves is reconstructed in order to plan the photodynamic therapy. Using the adjusted output of the thoracic cavity segmentation method and the MPM segmentation method, we evaluated the contact surface generated from these two steps by comparing it to the ground truth. For this evaluation, we used 10 CT scans with pathologically confirmed MPM at stages 1 and 2. We obtained a high similarity rate between the manually planned surface and our proposed method. The average value of Jaccard index was about 0.79 and we obtained a value of 0.88 using the Dice index., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

A series of new (E) and (Z)-benzoyl-homoquinones have been prepared in good yield by the parent quinone-electrogenerated base (EGB) in the presence of α-bromoacetophenones or α-bromopropiophenone. The EGB, obtained when electrolysis of p-benzoquinone, or 1,4-naphthoquinone, is carried out at the reduction potential of their first voltammetric peak, conducted to electrogenerated phenacyl carbenes after halide evolution on the first obtained bromo-enolates. The stereoselectivity of the [2 + 2]cycloaddition of the carbene to the quinoid substrate is highly dependent on the electrode nature. Reaction mechanism proposal is discussed.

Female breast cancer is the second most common cancer in the world. Several efforts in artificial intelligence have been made to help improving the diagnostic accuracy at earlier stages. However, the identification of breast abnormalities, like masses, on mammographic images is not a trivial task, especially for dense breasts. In this paper we describe our novel mass detection process that includes three successive steps of enhancement, characterization and classification. The proposed enhancement system is based mainly on the analysis of the breast texture. First of all, a filtering step with morphological operators and soft thresholding is achieved. Then, we remove from the filtered breast region, all the details that may interfere with the eventual masses, including pectoral muscle and galactophorous tree. The pixels belonging to this tree will be interpolated and replaced by the average of the neighborhood. In the characterization process, measurement of the Gaussian density in the wavelet domain allows the segmentation of the masses. Finally, a comparative classification mechanism based on the Bayesian regularization back-propagation networks and ANFIS techniques is proposed. The tests were conducted on the MIAS database. The results showed the robustness of the proposed enhancement method., (Copyright © 2016. Published by Elsevier Ireland Ltd.)