Buchi Reddy Ramakantha Reddy, Ramasamy Lokesh Kumar^*

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4081-4107, 2024, DOI:10.32604/cmc.2024.057071 - 19 December 2024

Abstract Traditional e-commerce recommendation systems often struggle with dynamic user preferences and a vast array of products, leading to suboptimal user experiences. To address this, our study presents a Personalized Adaptive Multi-Product Recommendation System (PAMR) leveraging transfer learning and Bi-GRU (Bidirectional Gated Recurrent Units). Using a large dataset of user reviews from Amazon and Flipkart, we employ transfer learning with pre-trained models (AlexNet, GoogleNet, ResNet-50) to extract high-level attributes from product data, ensuring effective feature representation even with limited data. Bi-GRU captures both spatial and sequential dependencies in user-item interactions. The innovation of this study lies… More >

Yvonne Achieng Ouma¹, Supriti Sundari Nayak¹, Smrutirekha Mishra², Harekrishna Panigrahi^1,*

Journal of Polymer Materials, Vol.41, No.4, pp. 281-297, 2024, DOI:10.32604/jpm.2024.056470 - 16 December 2024

Abstract Fuller earth (FE) nanoclay is a naturally occurring mineral with a high surface area, is highly abundant, and has a low purchasing cost, making it an excellent candidate for nanocomposite production. The study highlights the novelty of using FE nanoclay in combination with polyvinyl alcohol (PVA) to create a bio-nanocomposite that meets the need for sustainable packaging solutions, underscoring its potential to reduce environmental impact while maintaining product quality in food packaging applications. The solvent casting process, a reliable way to evenly disperse nanofillers in polymer matrices, has been employed in this work to incorporate… More >

Alwa Widi Aisya¹, Erlina Ambarwati^1,*, Supriyanta¹, Taufan Alam¹, Rizky Pasthika Kirana¹, I Gusti Komang Dana Arsana², Vina Eka Aristya², Ardian Elonard Purba², Taryono¹

Phyton-International Journal of Experimental Botany, Vol.93, No.11, pp. 3073-3089, 2024, DOI:10.32604/phyton.2024.058098 - 30 November 2024

Abstract The breeding process involves developing techniques to create cultivars that thrive in the ever-changing global climate, allowing for early harvesting and high yield. This study aimed to screen rice genotypes with early harvesting and high yield to develop new-generation cultivars. The study was conducted in a field experiment at the Department of Agronomy, Faculty of Agriculture, Universitas Gadjah Mada, Special Region of Yogyakarta, Indonesia, from December 2022 to April 2023. Ten genotypes were laid out using an Augmented Randomized Complete Block Design (ARCBD) with three rows and six columns. The observations were macro and micro-climate,… More >

Djordje P. Božović^1,2, Anja Rimac³, Milorad M. Vujičić^1,4, Pragya Singh⁵, Michal Goga⁵, Mingai Li^2,6, Claudio Varotto^2,6, Aneta D. Sabovljević^1,4, Marko S. Sabovljević^1,4,5,*

Phyton-International Journal of Experimental Botany, Vol.93, No.11, pp. 2949-2961, 2024, DOI:10.32604/phyton.2024.057995 - 30 November 2024

Abstract Physcomitrium eurystomum Sendtn. is a very rare European ephemeral funaroid moss. The entire European population of this species is considered threatened and it is red-listed in many regions and countries. In addition to being recognized as threatened and included in nature conservation legislation, it also requires active protection measures. This study aims to contribute to effective conservation practices for P. eurystomum. Different conservation physiology tests were carried out to propagate this species to achieve a reliable procedure for biomass production and the potential reintroduction of germplasm. Ex situ tests, both in vitro and ex vitro, were carried out to determine… More >

Chao Meng^1,#, Ikram Ullah^2,#, Wenjin Wu³, Yiping Zhang¹, Ruixue Shi¹, Shaodan Luo³, Cuixia Luo³, Satyabrata Nanda⁴, Mahmoud F. Seleiman⁵, Yalian Jiang^1,*, Wangqi Huang^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.11, pp. 3029-3038, 2024, DOI:10.32604/phyton.2024.057857 - 30 November 2024

Abstract Marigolds (Tagetes spp.) are popular horticultural plants worldwide. The current study aimed to investigate the optimal mutagenic conditions for marigold seeds using EMS (ethyl methanesulfonate) mutagenesis. Different concentrations and treatment times of EMS were applied to investigate their effects on the marigold seed germination rate, growth traits, antioxidant enzyme activities (i.e., SOD and POD), and malondialdehyde (MDA) contents. Results indicated that with increasing the EMS treatment duration and concentration, the seed germination rate and growth treatments were reduced, accompanied by elevated MDA content. In addition, SOD and POD activities initially correlated positively with the growth tratis at More >

Oleh Koshovyi^1,2,*, Janne Sepp¹, Valdas Jakštas³, Vaidotas Žvikas³, Karina Tolmacheva⁴, Igor Kireyev⁴, Jyrki Heinämäki¹, Ain Raal^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.11, pp. 2909-2925, 2024, DOI:10.32604/phyton.2024.056536 - 30 November 2024

Abstract Pineappleweed (Matricaria discoidea DC., Asteraceae) herb is an essential oil containing raw material with spasmolytic and anti-inflammatory activity. It is also rich in phenolics, which may be used in pharmaceutical practice. This study aimed to investigate the phenolic and amino acid composition and the hyporific and analgesic effects of the M. discoidea aqueous-ethanolic extract and its amino acid modifications. In addition, we developed a polyethylene oxide gel formulation with M. discoidea extracts for the 3D-printed oral solid dosage preparations. In M. discoidea extracts, 16 phenolic substances and 14 amino acids were established. The extract and its amino acid preparations More >

Hexin Yue¹, Cian Vyas^1,2,*, Paulo Bartolo^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.011598

Abstract Peripheral nerve injury can result in significant motor or sensory impairment. Traditional treatments have certain drawbacks and often result in suboptimal clinical results. To overcome these limitations, tissue engineering and bioprinting technologies are promising approaches for manufacturing nerve guidance conduits (NGCs). NGCs are tubular biostructures that bridge the nerve injury site, provide an appropriate microenvironment, and promote peripheral nerve regeneration by guiding axonal growth. The architecture of NGCs needs to mimic the morphology of natural peripheral nerves by designing their topology to regulate nerve cell behaviours. Topographic guidance cues are an effective element in improving… More >

Xinwei Wang^1,2,*, Ming Li¹, Hankun Bing¹, Dongxing Zhang¹, Yuanshu Zhang¹

Energy Engineering, Vol.121, No.12, pp. 3875-3898, 2024, DOI:10.32604/ee.2024.056237 - 22 November 2024

Abstract After long-term operation, the performance of components in the GTCC system deteriorates and requires timely maintenance. Due to the inability to directly measure the degree of component malfunction, it is necessary to use advanced exergy analysis diagnosis methods to characterize the components’ health condition (degree of malfunction) through operation data of the GTCC system. The dissipative temperature is used to describe the degree of malfunction of different components in the GTCC system, and an advanced exergy analysis diagnostic method is used to establish a database of overall operating condition component malfunctions in the GTCC system.… More >

Tao Yan¹, Javed Rashid^2,3, Muhammad Shoaib Saleem^3,4, Sajjad Ahmad⁴, Muhammad Faheem^5,*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2685-2708, 2024, DOI:10.32604/cmc.2024.058186 - 18 November 2024

Abstract Electricity is essential for keeping power networks balanced between supply and demand, especially since it costs a lot to store. The article talks about different deep learning methods that are used to guess how much green energy different Asian countries will produce. The main goal is to make reliable and accurate predictions that can help with the planning of new power plants to meet rising demand. There is a new deep learning model called the Green-electrical Production Ensemble (GP-Ensemble). It combines three types of neural networks: convolutional neural networks (CNNs), gated recurrent units (GRUs), and… More >

Jeng-Shyang Pan^1,2, Wenda Li¹, Shu-Chuan Chu^1,*, Xiao Sui¹, Junzo Watada³

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3033-3062, 2024, DOI:10.32604/cmc.2024.056310 - 18 November 2024

Abstract The growth optimizer (GO) is an innovative and robust metaheuristic optimization algorithm designed to simulate the learning and reflective processes experienced by individuals as they mature within the social environment. However, the original GO algorithm is constrained by two significant limitations: slow convergence and high memory requirements. This restricts its application to large-scale and complex problems. To address these problems, this paper proposes an innovative enhanced growth optimizer (eGO). In contrast to conventional population-based optimization algorithms, the eGO algorithm utilizes a probabilistic model, designated as the virtual population, which is capable of accurately replicating the… More >