Article
Biochemistry & Molecular Biology
Monirul Islam, Yatao Huang, Serajul Islam, Bei Fan, Litao Tong, Fengzhong Wang
Summary: Soybean protein hydrolysates were prepared using Alcalase and Protamex, and their degree of hydrolysis and functional properties were evaluated. Protamex showed excellent solubility, emulsifying activity, and foaming capacity, while Alcalase had high water-holding capacity. Additionally, Protamex exhibited the strongest antioxidant activity. These findings indicate the potential of soybean protein hydrolysates in improving the functional properties, antioxidant activity, and nutritional values of soybeans.
Article
Food Science & Technology
Pedro Valencia, Karen Espinoza, Carolina Astudillo-Castro, Fernando Salazar
Summary: Systematic modeling of enzymatic hydrolysis of milk proteins was conducted in this study. The modeling tool, which combined logarithmic and polynomial equations, accurately predicted the changes in kinetic constants and hydrolysis curves of milk proteins. This model can be used to test the correlation between the degree of hydrolysis and the functional properties of milk hydrolysates.
Article
Computer Science, Artificial Intelligence
Junjie Shi, Jiang Bian, Jakob Richter, Kuan-Hsun Chen, Jorg Rahnenfuhrer, Haoyi Xiong, Jian-Jia Chen
Summary: The predictive performance of a machine learning model depends on hyper-parameter setting, making hyper-parameter tuning crucial. In distributed machine learning, collecting all data is challenging, thus the MODES framework is proposed to deploy MBO on resource-constrained distributed embedded systems to optimize combined prediction accuracy.
Article
Materials Science, Multidisciplinary
Jack G. Nedell, Jonah Spector, Adel Abbout, Michael Vogl, Gregory A. Fiete
Summary: Motivated by the improvement of deep learning techniques, we design a mixed input convolutional neural network to predict transport properties in deformed nanoscale materials using a height map of deformations as input. Our network achieves higher accuracy in conductance predictions by using redundant input of energy values, and it successfully predicts valley-resolved conductance.
Article
Chemistry, Multidisciplinary
Jinfu Lin, Hongxia Liu, Shulong Wang, Dong Wang, Lei Wu
Summary: This paper studies the hardware implementation of a fully connected neural network based on the 1T1R array and its application in handwritten digital image recognition. Experimental and simulation analysis show the relationship between the recognition accuracy of the network and the number of hidden neurons. The results indicate that the network has high recognition accuracy and the impact of failed devices on accuracy is minimal.
Article
Computer Science, Artificial Intelligence
Alejandro Moran, Vincent Canals, Fabio Galan-Prado, Christian F. Frasser, Dhinakar Radhakrishnan, Saeid Safavi, Josep L. Rossello
Summary: Edge artificial intelligence is a growing research field, and reservoir computing has attracted attention as a feasible alternative for edge intelligence. This study proposes a simple hardware-optimized circuit design for low-power edge intelligence applications and demonstrates its implementation in FPGA for low-power audio event detection. The results show significant accuracy and ultra-low energy consumption for the proposed approach.
COGNITIVE COMPUTATION
(2023)
Article
Food Science & Technology
Yi Zhang, Xin Rui, Romy Vaugeois, Benjamin K. Simpson
Summary: Seal meat hydrolysates have high nutritional value and antioxidant activity, rich in essential amino acids and nutritive minerals. This study provides important information for seal meat hydrolysates as a healthy food supplement.
LWT-FOOD SCIENCE AND TECHNOLOGY
(2022)
Article
Food Science & Technology
Matea Habus, Maja Benkovic, Damir Ivekovic, Tomislava Vukus Pavicic, Nikolina Cukelj Mustac, Bojana Voucko, Duska Curic, Dubravka Novotni
Summary: This work investigated the influence of oil content, xylanase activity, and resting time of the dough on its rheology, 3D printing precision, and snack quality. The study found that the rheological properties of the dough can be valuable predictors of shrinkage and color of 3D-printed snacks, facilitating product development.
JOURNAL OF CEREAL SCIENCE
(2022)
Article
Multidisciplinary Sciences
Xiangyan Meng, Guojie Zhang, Nuannuan Shi, Guangyi Li, Jose Azana, Jose Capmany, Jianping Yao, Yichen Shen, Wei Li, Ninghua Zhu, Ming Li
Summary: Convolutional neural networks are facing limitations in processing massive data due to electrical frequency and memory access time. Optical computing offers faster processing speeds and higher energy efficiency, but current schemes lack scalability. In this study, a compact on-chip optical convolutional processing unit is demonstrated on a low-loss silicon nitride platform, showing potential for large-scale integration.
NATURE COMMUNICATIONS
(2023)
Article
Food Science & Technology
Cristian Torres-Leon, Monica L. Chavez-Gonzalez, Ayerim Hernandez-Almanza, Gloria A. Martinez-Medina, Nathiely Ramirez-Guzman, Liliana Londono-Hernandez, Cristobal N. Aguilar
Summary: High generation of food waste can lead to serious pollution issues and high handling costs, but utilizing food processing waste to produce valuable bioproducts is an attractive approach. Microbiological and enzymatic methods have been described as sustainable solutions for obtaining these bioproducts, with progress being made in optimizing processes at the laboratory level. However, studies need to focus on scaling up bioprocesses to make further advancements in this field.
CURRENT OPINION IN FOOD SCIENCE
(2021)
Article
Multidisciplinary Sciences
Muhammad Asghar, Muhammad Faisal Javed, M. Ijaz Khan, Sherzod Abdullaev, Fuad A. Awwad, Emad A. A. Ismail
Summary: This study develops empirical models using GEP, ANN, and XG Boost to determine the CS and TS of BFRC. The results show that GEP can accurately forecast the CS and TS of BFRC. This study also investigates the ideal BF content for industrial-scale BFRC reinforcement.
SCIENTIFIC REPORTS
(2023)
Article
Multidisciplinary Sciences
Zhengcai Li, Xinmin Hu, Chun Chen, Chenyang Liu, Yalu Han, Yuanfeng Yu, Lizhi Du
Summary: This paper investigates the optimization algorithms based on machine learning for settlement prediction. By comparing the performance of different algorithms, the study finds that Sparrow Search Algorithm (SSA) significantly improves the optimization effect of the gradient descent model and enhances its stability to a certain degree.
SCIENTIFIC REPORTS
(2022)
Article
Food Science & Technology
Pedro Valencia, Silvana Valdivia, Suleivys Nunez, Reza Ovissipour, Marlene Pinto, Cristian Ramirez, Alvaro Perez, Manuel Ruz, Paula Garcia, Paula Jimenez, Sergio Almonacid
Summary: The study evaluated the hydrolysis of salmon frame proteins under different conditions, showing that reducing water content increases the concentration of released alpha-NH groups, but decreases nitrogen recovery. Changing the SF/water ratio has a more significant impact on hydrolysis performance.
Article
Computer Science, Artificial Intelligence
Nadezhda Semenova, Laurent Larger, Daniel Brunner
Summary: Deep neural networks have unlocked new applications previously reserved for higher human intelligence, leveraging computing power from special purpose hardware. However, the emulation of neural networks by binary computing leads to unsustainable energy consumption and slow speed. Research shows that noise accumulation in deep neural networks with noisy nonlinear neurons is generally limited, and noise can be completely suppressed when neuron activation functions have a slope smaller than unity.
Article
Physics, Multidisciplinary
Lea Fellner, Marian Kraus, Arne Walter, Frank Duschek, Thomas Bocklitz, Valentina Gabbarini, Riccardo Rossi, Alessandro Puleio, Andrea Malizia, Pasquale Gaudio
Summary: Research on using laser-induced fluorescence (LIF) technology to distinguish organic materials, proposing a simplified experimental design to address interference from other fluorophores in the environment, testing neural networks in identifying different fluorophore signals in mixed samples.
EUROPEAN PHYSICAL JOURNAL PLUS
(2021)
Article
Chemistry, Applied
Jose Maria Ruiz-Alvarez, Teresa del Castillo-Santaella, Julia Maldonado-Valderrama, Antonio Guadix, Emilia M. Guadix, Pedro J. Garcia-Moreno
Summary: The interfacial properties of whey protein (WPH) and blue whiting protein (BPH) hydrolysates are influenced by pH, with WPH showing higher interfacial activity at pH 8. This results in smaller oil droplets and a more resistant interfacial peptide layer for stable emulsions. BPH exhibits higher dilatational elasticity and viscosity at pH 2, leading to stable emulsions at this pH but not at pH 8.
FOOD HYDROCOLLOIDS
(2022)
Article
Food Science & Technology
Carmen Berraquero-Garcia, M. Carmen Almecija, Emilia M. Guadix, Raul Perez-Galvez
Summary: This study proposes the enzymatic hydrolysis of blood protein to produce hydrolysates rich in haemic iron and antioxidant peptides. Subtilisin and trypsin treatments were found to be effective in recovering haem iron as soluble peptides, while also producing hydrolysates with high levels of in vitro antioxidant activities. These findings suggest the potential use of blood protein hydrolysates as iron fortification supplements.
INTERNATIONAL JOURNAL OF FOOD SCIENCE AND TECHNOLOGY
(2022)
Article
Chemistry, Applied
Nor E. Rahmani-Manglano, Nykola C. Jones, Soren V. Hoffmann, Emilia M. Guadix, Raul Perez-Galvez, Antonio Guadix, Pedro J. Garcia-Moreno
Summary: The secondary structure of whey protein concentrate hydrolysate (WPCH) was investigated using Synchrotron Radiation Circular Dichroism (SRCD). The study found that enzymatic hydrolysis resulted in peptides with a highly unordered structure in solution. However, when adsorbed at the oil/water interface, WPCH increased the alpha-helical content and improved thermal stability. The encapsulating agents and drying technique did not significantly modify the conformation of WPCH at the interface, but electrospraying had an effect on the obtained spectra.
Article
Chemistry, Applied
Nor E. Rahmani-Manglano, Manuel Tirado-Delgado, Pedro J. Garcia-Moreno, Antonio Guadix, Emilia M. Guadix
Summary: The influence of emulsifier type and encapsulating agent on the bioaccessibility of microencapsulated fish oil was investigated. It was found that the WPCH-based interfacial layer prevented oil droplet coalescence better than TW20, resulting in a higher bioaccessibility of the microencapsulated oil.
Article
Biochemistry & Molecular Biology
Jeimmy Lizeth Ospina-Quiroga, Pedro J. Garcia-Moreno, Antonio Guadix, Emilia M. Guadix, Maria del Carmen Almecija-Rodriguez, Raul Perez-Galvez
Summary: This study evaluated the physical and oxidative stabilities of fish oil-in-water emulsions stabilized with plant-based protein hydrolysates. The results showed that these hydrolysates can be used as natural antioxidants in food emulsions and effectively inhibit lipid oxidation.
Review
Food Science & Technology
Carmen Berraquero-Garcia, Raul Perez-Galvez, F. Javier Espejo-Carpio, Antonio Guadix, Emilia M. Guadix, Pedro J. Garcia-Moreno
Summary: Bioactive peptides derived from enzymatic hydrolysis are gaining attention for their potential applications in supplements, pharmaceuticals, and functional foods. However, their high susceptibility to degradation during gastrointestinal digestion limits their inclusion in oral delivery systems. Encapsulation techniques, such as monoaxial spray-drying and electrospraying, can stabilize bioactive peptides, improving their bioaccessibility and potential for use in various industries.
Review
Biochemistry & Molecular Biology
Julia Rivera-Jimenez, Carmen Berraquero-Garcia, Raul Perez-Galvez, Pedro J. Garcia-Moreno, F. Javier Espejo-Carpio, Antonio Guadix, Emilia M. Guadix
Summary: Inflammation is the immune system's response to harmful stimuli, with the aim of eliminating irritants and promoting tissue repair. Current anti-inflammatory drugs have limitations and side effects, so researchers are looking for alternative and more selective therapies from natural products. Small peptides with low molecular weight and short amino acid chains are found to be highly active, and the presence of hydrophobic and positively charged amino acids is common. Interestingly, a large percentage of anti-inflammatory peptides can be found in sustainable protein sources. However, not all peptides with in vitro anti-inflammatory potential achieve good scores in in silico bioactivity predictors, highlighting the need for bioinformatics tools to complement in vitro experiments with prediction of potential bioactive peptides.
