YAN LI¹, HUZHI CAI², XIAOLING PENG³, YOUHUI LIU⁴, QINGYANG CHEN⁴, XIANGDONG LIN⁵, XINYU CHEN^6,*

BIOCELL, Vol.48, No.3, pp. 501-511, 2024, DOI:10.32604/biocell.2023.030854

Abstract Background: Renal fibrosis is an important process in the development of chronic kidney disease. Understanding the pathogenesis and finding effective treatments for renal fibrosis is crucial. This study aims to investigate whether a newly discovered long non-coding RNA (lncRNA) called LOC103694972 could be a potential target for treating fibrosis of NRK-49F cells. Methods:: LncRNA Chip was used to identify differentially expressed lncRNAs between TGF-β1-induced NRK-49F cells and normal cells. The dual-luciferase assay confirmed the binding between miR-29c-3p and signal transducer and activator of transcription (STAT3), as well as between miR-29c-3p and lncRNA LOC103694972. Si-LOC103694972 and miR-29c-3p mimic were then transfected… More > Graphic Abstract

FEI SHA¹, DAISHAN XIN², JUN XU³, ZHIWEI ZHENG¹, WENXIN LIN¹, XIAORUI CAI¹, FEI LIN³, MINGHAO ZHENG^1,*, JIAOLING CHEN^1,*

BIOCELL, Vol.48, No.3, pp. 443-451, 2024, DOI:10.32604/biocell.2023.029188

Abstract Background: Curcumin is a plant polyphenol with antitumor properties and inhibits the development of colorectal cancer (CRC). However, as the molecular mechanism associated is still unclear, our study aimed to explore the underlying molecular mechanisms by which curcumin inhibits CRC. Methods: HT29 and SW480 cells were treated with curcumin or/and Doxycycline (DOX), and cell viability, colony forming ability, migration and invasion were confirmed by cell counting kit-8 (CCK-8), colony forming, Transwell assays. And Yes-associated protein 1 (YAP) and PDZ-binding motif (TAZ) signaling-related genes or proteins were analyzed using reverse transcription quantitative real-time PCR (RT-qPCR), western blot, and immunofluorescence assays. Then… More > Graphic Abstract

P. K. Das^*, S. Chakraborty, S. Bhaduri

Frontiers in Heat and Mass Transfer, Vol.3, No.1, pp. 1-17, 2012, DOI:10.5098/hmt.v3.1.3008

Abstract A state of the art review of critical heat flux during flow boiling through mini and microchannels has been provided based on the open literature. This review mainly examines three aspects, namely the experimental investigations, the available correlations and the state of prediction using those correlations and finally the proposed physical mechanisms as well as the theoretical models. Before discussing the specific literature on microchannels, a brief overview of critical heat flux for pool and flow boiling is provided. The review has been concluded with a summary of the available information on this topic and the need for future research. More >

Sira Saisorn^a,b, Somchai Wongwises^b,c,∗

Frontiers in Heat and Mass Transfer, Vol.3, No.1, pp. 1-7, 2012, DOI:10.5098/hmt.v3.1.3007

Abstract Two-phase pressure drop during flow boiling has been studied for several decades. Obviously, the publications available on micro-channels are relatively small compared with those for ordinarily sized channels. Although the use of micro-channels yields several advantages, the pressure drop taking p lace in these extremely small channels is higher than that in the ordinarily sized channels because of the increased wall friction. The knowledge of the two-phase pressure drop characteristics in addition to heat transfer phenomena is essential to the design and evaluation of the micro-systems. In this paper, recent research on the flow boiling pressure drop in micro-scale channels… More >

Sira Saisorn^a,b, Somchai Wongwises^b,c,*

Frontiers in Heat and Mass Transfer, Vol.3, No.1, pp. 1-15, 2012, DOI:10.5098/hmt.v3.1.3006

Abstract A summary of recent research on flow boiling in micro-channels is provided in this article. This review aims to survey and identify new findings arising in this important area, which may contribute to optimum design and process control of high performance miniature devices comprising extremely small channels. Several criteria for defining a micro-channel are presented at first and the recent works on micro-scale flow boiling are subsequently described into two parts including flow visualization and two-phase heat transfer. The results obtained from a number of p revious studies show that the flow behaviours and heat transfer mechanisms in micro-channels deviate… More >

Bijon Mallik¹, Md Abdur Rahim¹, Abu Saleh Musa Miah², Keun Soo Yun^3,*, Jungpil Shin²

Computer Systems Science and Engineering, Vol.48, No.2, pp. 555-570, 2024, DOI:10.32604/csse.2023.045981

Abstract In the digital age, non-touch communication technologies are reshaping human-device interactions and raising security concerns. A major challenge in current technology is the misinterpretation of gestures by sensors and cameras, often caused by environmental factors. This issue has spurred the need for advanced data processing methods to achieve more accurate gesture recognition and predictions. Our study presents a novel virtual keyboard allowing character input via distinct hand gestures, focusing on two key aspects: hand gesture recognition and character input mechanisms. We developed a novel model with LSTM and fully connected layers for enhanced sequential data processing and hand gesture recognition.… 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 >

Hae Sung Park¹, Yong Suk Choi^2,*

Computer Systems Science and Engineering, Vol.48, No.2, pp. 451-477, 2024, DOI:10.32604/csse.2023.043245

Abstract Much like humans focus solely on object movement to understand actions, directing a deep learning model’s attention to the core contexts within videos is crucial for improving video comprehension. In the recent study, Video Masked Auto-Encoder (VideoMAE) employs a pre-training approach with a high ratio of tube masking and reconstruction, effectively mitigating spatial bias due to temporal redundancy in full video frames. This steers the model’s focus toward detailed temporal contexts. However, as the VideoMAE still relies on full video frames during the action recognition stage, it may exhibit a progressive shift in attention towards spatial contexts, deteriorating its ability… More >

Abdullah Alsaleh^1,2,*

Computer Systems Science and Engineering, Vol.48, No.2, pp. 431-449, 2024, DOI:10.32604/csse.2023.043107

Abstract With the increasing number of connected devices in the Internet of Things (IoT) era, the number of intrusions is also increasing. An intrusion detection system (IDS) is a secondary intelligent system for monitoring, detecting and alerting against malicious activity. IDS is important in developing advanced security models. This study reviews the importance of various techniques, tools, and methods used in IoT detection and/or prevention systems. Specifically, it focuses on machine learning (ML) and deep learning (DL) techniques for IDS. This paper proposes an accurate intrusion detection model to detect traditional and new attacks on the Internet of Vehicles. To speed… More >

Muhammad Ali, Minhaj Ahmad Khan^*

Computer Systems Science and Engineering, Vol.48, No.2, pp. 287-303, 2024, DOI:10.32604/csse.2023.043010

Abstract The Extensible Markup Language (XML) files, widely used for storing and exchanging information on the web require efficient parsing mechanisms to improve the performance of the applications. With the existing Document Object Model (DOM) based parsing, the performance degrades due to sequential processing and large memory requirements, thereby requiring an efficient XML parser to mitigate these issues. In this paper, we propose a Parallel XML Tree Generator (PXTG) algorithm for accelerating the parsing of XML files and a Regression-based XML Parsing Framework (RXPF) that analyzes and predicts performance through profiling, regression, and code generation for efficient parsing. The PXTG algorithm… More >