Yalin Li^1,*, Lei Liu¹, Wenbao Huang¹, Junpu Xie², Zhaoxia Song¹, Shuna Guo¹, Enci Wang¹

Journal of Renewable Materials, Vol.11, No.7, pp. 3001-3023, 2023, DOI:10.32604/jrm.2023.026604

Abstract To achieve optimal recovery and value-added utilisation of cellulose in peanut shells, the cellulose in peanut shells was first extracted using the sodium hydroxide-sodium chlorite method. Then, cellulose hydrogel was prepared by graft copolymerisation using N, N’-methylenebisacrylamide as the cross-linking agent, sodium persulfate as the initiator, and acrylic acid as the monomer. Orthogonal optimisation experiments were designed to obtain optimal process parameters for hydrogel preparation with the cellulose dosage of 0.40 g, initiator dosage of 0.20 g, polymerisation temperature of 70°C, cross-linking agent of 0.25 g, and monomer dosage of 3.0 mL. The effect of initiator dosage on hydrogel synthesis was… More > Graphic Abstract

Nadeem Jabbar Chaudhry^1,*, M. Bilal Khan², M. Javaid Iqbal¹, Siddiqui Muhammad Yasir³

Journal on Artificial Intelligence, Vol.4, No.4, pp. 245-259, 2022, DOI:10.32604/jai.2022.038875

Abstract Recently, outstanding identification rates in image classification tasks were achieved by convolutional neural networks (CNNs). to use such skills, selective CNNs trained on a dataset of well-known images of metal surface defects captured with an RGB camera. Defects must be detected early to take timely corrective action due to production concerns. For image classification up till now, a model-based method has been utilized, which indicated the predicted reflection characteristics of surface defects in comparison to flaw-free surfaces. The problem of detecting steel surface defects has grown in importance as a result of the vast range of steel applications in end-product… More >

S. Eliza Femi Sherley^1,*, J. M. Karthikeyan¹, N. Bharath Raj¹, R. Prabakaran², A. Abinaya¹, S. V. V. Lakshmi³

Journal on Artificial Intelligence, Vol.4, No.4, pp. 215-227, 2022, DOI:10.32604/jai.2022.034931

Abstract Semantic change detection is extension of change detection task in which it is not only used to identify the changed regions but also to analyze the land area semantic (labels/categories) details before and after the timelines are analyzed. Periodical land change analysis is used for many real time applications for valuation purposes. Majority of the research works are focused on Convolutional Neural Networks (CNN) which tries to analyze changes alone. Semantic information of changes appears to be missing, there by absence of communication between the different semantic timelines and changes detected over the region happens. To overcome this limitation, a… More >

Matthieu Noucher¹ , Françoise Gourmelon², Christophe Claramunt³

Revue Internationale de Géomatique, Vol.29, No.1, pp. 9-30, 2019, DOI:10.3166/rig.2019.00074

Abstract Extensive uses of geographic information generate a data deluge on many Web infrastructures. Monitoring and analyzing the content of these platforms is still a research challenge because these can be considered as very dynamic informational and algorithmic black boxes. The concept of “geographical information observatory” appears as an appropriate mean to monitor, analyze and then provide a better understanding of the evolution of the volume and flows of the spatial data available on a specific web infrastructure. Nevertheless, its implementation raises several methodological questions discussed in this paper, starting from the experimentation of a diachronic data observation of French Spatial… More >

Anh Tu Hoang¹ , Philippe Apparicio¹, Thi-Thanh-Hien Pham²

Revue Internationale de Géomatique, Vol.29, No.2, pp. 135-158, 2019, DOI:10.3166/rig.2019.00071

Abstract The objective of this article is to assess environmental equity regarding the accessibility of parks for four population groups (children, older people, low-education individuals, and highly-educated persons) in Ho Chi Minh City (HCMC). To achieve this, two accessibility measures calculated according to network distance in GIS: the distance to the nearest park (immediate proximity) and the enhanced two-step floating catchment area method (availability based on supply and demand). Several regression models were then constructed, with the accessibility measures as dependent variables and the percentages of the four groups as independent variables. The results show that the accessibility of parks in… More >

CHUYAO WANG^1,2,#, CHUAN LU^2,#, LUXIANG ZOU^2,*, DONGMEI HE^2,*

BIOCELL, Vol.47, No.6, pp. 1293-1306, 2023, DOI:10.32604/biocell.2023.028199

Abstract Background: Temporomandibular joint osteoarthritis (TMJOA) is an end-stage disease that seriously affects the patients’ quality of life. Molecular insights in advancing our understanding of TMJOA are the need of the hour. Methods: We performed RNA high-throughput sequencing and bioinformatics analysis of differentially expressed (DE) long non-coding RNA (lncRNAs), microRNAs (miRNAs), and messenger RNA (mRNAs) in human synovial TMJOA tissues. Firstly, synovium samples of TMJOA patients and non-TMJOA controls were collected for highthroughput sequencing of lncRNAs, miRNAs, and mRNAs. We then performed biological function analysis of the top 100 mRNAs with more than 2-fold differential expression, and their upstream regulated miRNAs… More >

WEI LIANG^1,2,*, ZONGWEI ZHANG^1,2, KEJU YANG^1,2,3, HONGTU HU^1,2, QIANG LUO^1,2, ANKANG YANG^1,2, LI CHANG⁴, YUANYUAN ZENG⁴

BIOCELL, Vol.47, No.6, pp. 1253-1263, 2023, DOI:10.32604/biocell.2023.027373

Abstract Background: Diabetic nephropathy (DN) is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide. Diagnostic biomarkers may allow early diagnosis and treatment of DN to reduce the prevalence and delay the development of DN. Kidney biopsy is the gold standard for diagnosing DN; however, its invasive character is its primary limitation. The machine learning approach provides a non-invasive and specific criterion for diagnosing DN, although traditional machine learning algorithms need to be improved to enhance diagnostic performance. Methods: We applied high-throughput RNA sequencing to obtain the genes related to DN tubular… More >

DER-JEU CHEN, CHENG-HUNG LAI^*

BIOCELL, Vol.47, No.6, pp. 1317-1327, 2023, DOI:10.32604/biocell.2023.028883

Abstract Background: Magnolol, a bioactive extract of the Chinese herb Magnolia officinalis has a protective effect against periodontitis. This study is aimed to explore the mechanisms involved in the functioning of magnolol against periodontitis and provide a basis for further research. Methods: Network pharmacology analysis was performed based on the identification of related targets from public databases. The Protein-protein interaction (PPI) network was constructed to visualize the significance between the targets of magnolol and periodontitis. Subsequently, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to predict the functions and the signal regulatory pathways involved in… More >

CHENHAO SHI¹, MAOHONG HUA², GUANHUA XU^3,*

BIOCELL, Vol.47, No.6, pp. 1329-1344, 2023, DOI:10.32604/biocell.2023.028381

Abstract Background: Ulcerative colitis (UC) is a chronic disease that often presents with abdominal pain, diarrhea, hematochezia, and significant morbidity. Gancao Xiexin decoction (GXD), a traditional Chinese medicine, has been applied for the clinical treatment of UC, while its action mechanisms are unclear. Methods: The active ingredients and their targets of GXD, and UC-related targets, were derived from public databases. Protein-protein interaction, Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the important active compounds, key targets, and signaling pathways. Then, molecular docking and animal experiments were performed to verify the findings. A total… More >

Dominique Badariotti, Cyril Meyer, Yasmina Ramrani

Revue Internationale de Géomatique, Vol.30, No.2, pp. 181-213, 2020, DOI:10.3166/rig.2021.00109

Abstract In this paper, we propose a model and a methodology for the analysis of urban fabrics, sets of built morphological units articulated together by urban networks. The core of the paper presents the MoGUS model (Model Generator & analyser for Urban Simulation) and its formalization. This model jointly represents the buildings and the viaires networks of a city in a graph, and allows a comparative analysis of the properties of different urban fabrics, using derived indicators. A study plan applied to four types of archetypal urban fabrics (Hippodamean, medieval, radio-concentric, Haussmannic) generated with the MoGUS tool is presented to illustrate… More >