ANIL KUMAR VEERAPANENI¹, CHANDRASEKAR KUPPAN^2,*, MURTHY CHAVALI^3,*

Journal of Polymer Materials, Vol.37, No.3-4, pp. 121-130, 2020, DOI:10.32381/JPM.2020.37.3-4.1

Abstract The mechanical properties of hybrid nanocomposites made of epoxy/glass fibre dispersed with nano-α-Al₂ O₃ powder at different weight percentages were studied.The effect of nano-α- Al₂O₃ size and wt% on mechanical properties like tensile, flexural, interlaminar shear stress and hardness enhanced because of their higher surface area and interfacial polymer-metal interaction. The nanoparticle embedded laminates have shown improvement in flexural strength,and hardness when compared to laminate without nano-α-Al₂ O₃. The properties varied with the loading and size of the nanoparticles. The tensile strength was highest for 0.5 wt% of 200nm nano-α-Al₂O₃, which is 167.80 N/m₂.The highest flexural strength was observed for… More >

ELIF ANT BURSALI^1,*, DILER ABACI¹, MURAT KIZIL², MURUVVET YURDAKOC¹

Journal of Polymer Materials, Vol.38, No.3-4, pp. 231-245, 2021, DOI:10.32381/JPM.2021.38.3-4.5

Abstract Genipin cross-linked/boron doped starch/polyvinily alcohol (PVA) based hydrogel (SH-GNP-B) was synthesized as a new material having antimicrobial and antioxidant activity. The prepared hydrogel was characterized by X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Thermal Gravimetric Analysis (TGA) and Scanning Electron Microscope (SEM) methods and evaluated for in vitro antimicrobial activities against selected organisms by disc diffusion tests. The antioxidant activity of the prepared hydrogels was evaluated using 2,2-diphenyl-1- picrylhydrazyl radical scavenging assays. Swelling behavior of the hydrogel was also investigated. The synthesized hydrogel was thermally stable and showed pH independent swelling tendency. SH-GNP-B hydrogel was found to have antimicrobial… More >

SOBHA KOTA^*, RATNAKUMARI ANANTHA, VAYUNANDANA RAO GOVADA, PRADEEP DUMPALA

Journal of Polymer Materials, Vol.40, No.3-4, pp. 285-303, 2023, DOI:10.32381/JPM.2023.40.3-4.10

Abstract The exoskeleton of marine shrimp contains a natural, biocompatible polymer chitin, which is dumped as a waste. The study proposes the sustainable single-pot-extraction of chitosan from the waste and its use in the fabrication of wound-dressings, and thus leverage its piezoelectric, antioxidant, hypoglycaemic and medicinal properties in wound-healing. The Fourier transform infrared spectrum revealed that marine chitosan contains functional groups with N-O, O-H, and CO stretching. Scanning electron micrographs demonstrated the spherical and mesoporous structures of the extracted chitosan. X-ray diffraction analysis showed a semi-crystalline phase of chitosan particles with a mean size of 28.9 nm. The film prepared with… More >

PARSOTAM H. PARSANIA^1,*, JIGNESH V. PATEL², JIGNESH P. PATEL³

Journal of Polymer Materials, Vol.40, No.3-4, pp. 271-284, 2023, DOI:10.32381/JPM.2023.40.3-4.9

Abstract Bisphenol-C epoxy crotonate resin was synthesized by reacting 8.09g epoxy resin of bisphenolC, and 2.15g crotonic acid using 25 mL 1,4-dioxane as a solvent, and 1 mL triethylamine as a catalyst at reflux temperature for 1-6 h. Solid epoxy crotonate (ECCR) is highly soluble in common organic solvents. ECCR was characterized by its acid (24.5-1.5 mg KOH/g) and hydroxyl (504.5-678.4 mg KOH/g) values. The structure of ECCR is supported by FTIR and 1 HNMR spectroscopic methods. A DSC endothermic transition at 229o C indicated melting followed by thermal polymerization of ECCR. ECCR is thermally stable up to 320o C and… More >

K. KRISHNAMOORTHY^a,*, N. PRABHU^b

Journal of Polymer Materials, Vol.40, No.3-4, pp. 215-226, 2023, DOI:10.32381/JPM.2023.40.3-4.7

Abstract The acoustic emission monitoring with artificial neural networks predicts the ultimate strength of glass/epoxy composite laminates using Acoustic Emission Data. The ultimate loads of all the specimens were used to characterise the emission of hits during failure modes. The six layered glass fiber laminates were prepared (in woven mat form) with epoxy as the binding medium by hand lay-up technique. At room temperature, with a pressure of 30 kg/cm², the laminates were cured. The laminates of standard dimensions as per ASTM D3039 for the tensile test were cut from the lamina. The Acoustic Emission (AE) test was conducted on these… More >

Da Cai, Yinlong Song, Hao Jiang, Guangyao Li, Junjia Cui^*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 873-887, 2024, DOI:10.32604/fdmp.2023.025833

Abstract Aluminum alloy thin-walled structures are widely used in the automotive industry due to their advantages related to light weight and crashworthiness. They can be produced at room temperature by the electrohydraulic forming process. In the present study, the influence of the related parameters on the forming quality of a 6063 aluminum alloy sinusoidal corrugation tube has been assessed. In particular, the orthogonal experimental design (OED) and central composite design (CCD) methods have been used. Through the range analysis and variance analysis of the experimental data, the influence degree of wire diameter (WD) and discharge energy (DE) on the forming quality… More >

Zihao Song, Yan Zhou^*, Wei Cheng, Futai Liang, Chenhao Zhang

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3349-3376, 2024, DOI:10.32604/cmc.2024.047034

Abstract The frequent missing values in radar-derived time-series tracks of aerial targets (RTT-AT) lead to significant challenges in subsequent data-driven tasks. However, the majority of imputation research focuses on random missing (RM) that differs significantly from common missing patterns of RTT-AT. The method for solving the RM may experience performance degradation or failure when applied to RTT-AT imputation. Conventional autoregressive deep learning methods are prone to error accumulation and long-term dependency loss. In this paper, a non-autoregressive imputation model that addresses the issue of missing value imputation for two common missing patterns in RTT-AT is proposed. Our model consists of two… More >

Maria Inês Clara^1,2,3,*, Maria Cristina Canavarro^2,3, Ana Severina⁴, Susana Ramos⁴, Carla Rafael⁴, Ana Allen Gomes^1,2,3

Psycho-Oncologie, Vol.18, No.1, pp. 49-57, 2024, DOI:10.32604/po.2023.044320

Abstract Objectif: L’objectif de l’étude fut de comparer la fatigue ressentie par les patients du cancer par rapport à celle de la population en générale, ainsi que d’examiner les facteurs de risque psychobiologiques associés à la fatigue. Matériel et méthodes: Dans cette étude quantitative et transversale, nous avons analysé les indicateurs cliniques et sociodémographiques de 389 participants (68.38% de femmes) : 148 patients du cancer sous traitement actif, 55 patients dans l’après-traitement d’un cancer, 75 patients atteints d’une autre maladie chronique et 111 personnes en bonne santé. Résultats: La fatigue s’exprimait de manière différente chez les patients ayant des antécédents de… More >

Zhonghao Guo^*, Xinyue Xu, Xiangxian Chen

Computer Systems Science and Engineering, Vol.48, No.2, pp. 479-509, 2024, DOI:10.32604/csse.2023.043932

Abstract In software testing, the quality of test cases is crucial, but manual generation is time-consuming. Various automatic test case generation methods exist, requiring careful selection based on program features. Current evaluation methods compare a limited set of metrics, which does not support a larger number of metrics or consider the relative importance of each metric to the final assessment. To address this, we propose an evaluation tool, the Test Case Generation Evaluator (TCGE), based on the learning to rank (L2R) algorithm. Unlike previous approaches, our method comprehensively evaluates algorithms by considering multiple metrics, resulting in a more reasoned assessment. The… More >

Anas Bilal¹, Azhar Imran², Talha Imtiaz Baig^3,4, Xiaowen Liu^1,*, Haixia Long¹, Abdulkareem Alzahrani⁵, Muhammad Shafiq⁶

Computer Systems Science and Engineering, Vol.48, No.2, pp. 511-528, 2024, DOI:10.32604/csse.2023.039672

Abstract Artificial Intelligence (AI) is being increasingly used for diagnosing Vision-Threatening Diabetic Retinopathy (VTDR), which is a leading cause of visual impairment and blindness worldwide. However, previous automated VTDR detection methods have mainly relied on manual feature extraction and classification, leading to errors. This paper proposes a novel VTDR detection and classification model that combines different models through majority voting. Our proposed methodology involves preprocessing, data augmentation, feature extraction, and classification stages. We use a hybrid convolutional neural network-singular value decomposition (CNN-SVD) model for feature extraction and selection and an improved SVM-RBF with a Decision Tree (DT) and K-Nearest Neighbor (KNN)… More >