Yun Wang^1,2,#, Xin-Yu Li^1,3,#, Sheng-Li Wu^1,3, Pianchou Gongpan¹, Da-Hong Li², Chang-An Geng^1,3,*

Phyton-International Journal of Experimental Botany, Vol.94, No.8, pp. 2563-2574, 2025, DOI:10.32604/phyton.2025.068185 - 29 August 2025

Abstract Twelve lignans (1–12) isolated from Amomum tsao-ko leaves were evaluated for the inhibitory effects against α-glucosidase and PTP1B. Compounds 1−4 and 10 showed inhibition on α-glucosidase with inhibitory ratios ranging from 53.8% to 90.0%, while compound 10 demonstrated 56.1% inhibition on PTP1B at 200 μM. Notably, erythro-5-methoxy-dadahol A (2) and threo-5-methoxy-dadahol A (3) displayed obvious inhibition on α-glucosidase with IC₅₀ values of 33.3 μM and 22.1 μM, significantly outperforming acarbose (IC₅₀ = 344.0 μM). Kinetic study revealed that compound 3 maintained a mixed-type mode, engaging with both free enzyme and enzyme-substrate complex via non-competitive and uncompetitive mechanisms. Molecular docking simulations further clarified its More >

Iman S. Al-Mahdi¹, Saad M. Darwish^1,*, Magda M. Madbouly²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 875-909, 2025, DOI:10.32604/cmes.2025.061623 - 11 April 2025

Abstract Heart disease prediction is a critical issue in healthcare, where accurate early diagnosis can save lives and reduce healthcare costs. The problem is inherently complex due to the high dimensionality of medical data, irrelevant or redundant features, and the variability in risk factors such as age, lifestyle, and medical history. These challenges often lead to inefficient and less accurate models. Traditional prediction methodologies face limitations in effectively handling large feature sets and optimizing classification performance, which can result in overfitting poor generalization, and high computational cost. This work proposes a novel classification model for heart… More >

Ziao Han, Hui Li^*, Kai Lu, Shujuan Liu, Mingmei Ju

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5097-5113, 2025, DOI:10.32604/cmc.2025.059577 - 06 March 2025

Abstract Traditional quantum circuit scheduling approaches underutilize the inherent parallelism of quantum computation in the Noisy Intermediate-Scale Quantum (NISQ) era, overlook the inter-layer operations can be further parallelized. Based on this, two quantum circuit scheduling optimization approaches are designed and integrated into the quantum circuit compilation process. Firstly, we introduce the Layered Topology Scheduling Approach (LTSA), which employs a greedy algorithm and leverages the principles of topological sorting in graph theory. LTSA allocates quantum gates to a layered structure, maximizing the concurrent execution of quantum gate operations. Secondly, the Layerwise Conflict Resolution Approach (LCRA) is proposed.… More >

Jungyeon Kim¹, Lequn Chen¹, Seung Ki Moon^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.012511

Abstract Robotic Laser-Directed Energy Deposition (L-DED) offers significant advantages in terms of workplace size and kinematic flexibility for part fabrication. However, its potential is hindered by challenges such as toolpath precision and speed inconsistency compared to traditional CNC machines. These limitations critically affect melt pool dynamics, temperature consistency, and ultimately, the geometric integrity of fabricated parts, areas that are still not thoroughly understood or quantified.
This preliminary research aims to investigate the impact of these inaccuracies on melt pool morphology and part quality, utilizing in-situ collected speed/position data with a digital twin model, notably the Eagar-Tsai… More >

Xiaolu Qin^1,3, Xinyu Li^1,3, Yi Yang², Mei Huang², Shengli Wu¹, Pianchou Gongpan¹, Lianzhang Wu², Juncai He², Changan Geng^1,3,*

Phyton-International Journal of Experimental Botany, Vol.93, No.5, pp. 875-883, 2024, DOI:10.32604/phyton.2024.048192 - 28 May 2024

Abstract The fruits of Amomum tsao-ko (Cao-Guo) were documented in Chinese Pharmacopoeia for the treatment of abdominal pain, vomiting, and plague. In our previous study, a series of diarylheptanes and flavonoids with α-glucosidase and protein tyrosine phosphatase 1B (PTP1B) inhibitory activity have been reported from the middle-polarity part of A. tsao-ko, whereas the antidiabetic potency of the low-polarity constituents is still unclear. In this study, three new hydroxytetradecenals, (2E, 4E, 8Z, 11Z)-6R-hydroxytetradeca-2,4,8,11-tetraenal (1), (2E, 4E, 8Z)-6R-hydroxytetradeca-2,4,8-trienal (2) and (2E, 4E)-6R-hydroxytetradeca-2,4-dienal (3) were obtained from the volatile oils of A. tsao-ko. The structures of compounds 1–3 were determined using spectroscopic data involving 1D and 2D nuclear magnetic More >

Aravindh Madhavankutty Ambika^1,2,*, Aarjab Ghimire², Sreekumar Appukuttan²

Energy Engineering, Vol.119, No.4, pp. 1483-1499, 2022, DOI:10.32604/ee.2022.017618 - 23 May 2022

Abstract This paper explains the experimental performance evaluation of a Corrugated Type Solar Air Heater (CTSAH) for understanding its performance in a humid tropical climatic condition in Puducherry, India. This helps in understanding its effectiveness in using it for drying application of products like seafood, etc. Experiments were conducted at different mass flow rates and their effect on the heat gain, efficiency, friction factor heat transfer, etc., was analyzed. Experiments were carried out at different mass flow rates, i.e., M1 = 0.06 kg/s, M2 = 0.14 kg/s, M3 = 0.17 kg/s, M4 = 0.25 kg/s, M5 = 0.3 kg/s, More >

Mahmoud Ragab^1,2,3, Ehab Bahauden Ashary⁴, Maha Farouk S. Sabir⁵, Adel A. Bahaddad⁵, Romany F. Mansour^6,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5441-5457, 2022, DOI:10.32604/cmc.2022.024545 - 14 January 2022

Abstract This study presents a novel method to detect the medical application based on Quantum Computing (QC) and a few Machine Learning (ML) systems. QC has a primary advantage i.e., it uses the impact of quantum parallelism to provide the consequences of prime factorization issue in a matter of seconds. So, this model is suggested for medical application only by recent researchers. A novel strategy i.e., Quantum Kernel Method (QKM) is proposed in this paper for data prediction. In this QKM process, Linear Tunicate Swarm Algorithm (LTSA), the optimization technique is used to calculate the loss… More >

Supreet Singh^1,2, Nitin Mittal¹, Urvinder Singh², Rohit Salgotra², Atef Zaguia³, Dilbag Singh^4,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3445-3462, 2022, DOI:10.32604/cmc.2022.023004 - 07 December 2021

Abstract This paper provides a new optimization algorithm named as tunicate swarm naked mole-rat algorithm (TSNMRA) which uses hybridization concept of tunicate swarm algorithm (TSA) and naked mole-rat algorithm (NMRA). This newly developed algorithm uses the characteristics of both algorithms (TSA and NMRA) and enhance the exploration abilities of NMRA. Apart from the hybridization concept, important parameter of NMRA such as mating factor is made to be self-adaptive with the help of simulated annealing mutation operator and there is no need to define its value manually. For evaluating the working capabilities of proposed TSNMRA, it is More >

Adnan Alam Khan^1,2,*, Qamar-ul-Arfeen¹

Journal of Cyber Security, Vol.3, No.4, pp. 201-205, 2021, DOI:10.32604/jcs.2021.024614 - 09 February 2022

Abstract Technology is expanding like a mushroom, there are various benefits of technology, in contrary users are facing serious losses by this technology. Furthermore, people lost their lives, their loved ones, brain-related diseases, etc. The industry is eager to get one technology that can secure their finance-related matters, personal videos or pictures, precious contact numbers, and their current location. Things are going worst because every software has some sort of legacy, deficiency, and shortcomings through which exploiters gain access to any software. There are various ways to get illegitimate access but on the top is Linux More >

Uma K.V^1,*, Appavu alias Balamurugan S²

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 61-70, 2020, DOI:10.31209/2019.100000153

Abstract Real world data consists of lot of impurities. Entropy measure will help to handle impurities in a better way. Here, data selection is done by using Naïve Bayes’ theorem. The sample which has posterior probability value greater than that of the threshold value is selected. C5.0 decision tree classifier is taken as base and modified the Gain calculation function using Tsallis entropy and Association function. The proposed classifier model provides more accuracy and smaller tree for general and Medical dataset. Precision value obtained for Medical dataset is more than that of existing method. More >