Impact of physico-chemical properties of nanocellulose on rheology of aqueous suspensions and its utility in multiple fields: A review

Nanocellulose (NC), due to its sustainable nature, high aspect ratio, superior mechanical strength, and availability of functionalizable  OH groups, has been widely utilized as reinforcement in numerous fluids/plastics. The physico-chemical properties of NC, like surface characteristics, dimensions/aspect ratio and their concentration, significantly impact the interparticle interactions, such as the extent of hydrogen bonding, van der Waal forces, hydrophobicity, electrostatic attraction/repulsion, and cellulose entanglement, and have been found to play a critical role in regulating the overall rheological characteristics of fluids. The functionalized NC aqueous suspension exhibited unique shear thinning properties, thixotropic behavior, and quick steady-state viscosity recovery and viscoelastic properties. However, upon adding functionalized NC to other fluids, a different impact was noticed. For instance, it improved the viscosity, G′ and mechanical stability of bio-ink; the setting time and mechanical strength of cementitious fluids; increased the filtration performance and provided a unique thermo-thickening impact in case of water-based drilling-fluid; enhanced viscosity with time and heat in case of oil recovery, and so forth. Keeping in view the notable dependence of the rheology of fluids on NC additives, in the present review article, the impact of various physico-chemical properties of NC additives on the rheological behavior of NC aqueous suspension and its utility as a rheology modifier in multiple advanced fields has been explored. This review article, compared to previous studies, warrants an update on the impact of recent NC surface functionalization/blending techniques employed and NC aspect ratio on specific properties of multiple advanced fluids.     

Comparison of high pressure and thermal pasteurization on the quality parameters of strawberry products: a review

Food Science and Biotechnology - Strawberry (Fragaria ananassa) is rich in bioactive compounds with high antioxidant activity. High pressure processing (HPP) is an efficient alternative to preserve...     

Hill Matrix and Radix-64 Bit Algorithm to Preserve Data Confidentiality

There are many cloud data security techniques and algorithms available that can be used to detect attacks on cloud data, but these techniques and algorithms cannot be used to protect data from an attacker. Cloud cryptography is the best way to transmit data in a secure and reliable format. Various researchers have developed various mechanisms to transfer data securely, which can convert data from readable to unreadable, but these algorithms are not sufficient to provide complete data security. Each algorithm has some data security issues. If some effective data protection techniques are used, the attacker will not be able to decipher the encrypted data, and even if the attacker tries to tamper with the data, the attacker will not have access to the original data. In this paper, various data security techniques are developed, which can be used to protect the data from attackers completely. First, a customized American Standard Code for Information Interchange (ASCII) table is developed. The value of each Index is defined in a customized ASCII table. When an attacker tries to decrypt the data, the attacker always tries to apply the predefined ASCII table on the Ciphertext, which in a way, can be helpful for the attacker to decrypt the data. After that, a radix 64-bit encryption mechanism is used, with the help of which the number of cipher data is doubled from the original data. When the number of cipher values is double the original data, the attacker tries to decrypt each value. Instead of getting the original data, the attacker gets such data that has no relation to the original data. After that, a Hill Matrix algorithm is created, with the help of which a key is generated that is used in the exact plain text for which it is created, and this Key cannot be used in any other plain text. The boundaries of each Hill text work up to that text. The techniques used in this paper are compared with those used in various papers and discussed that how far the current algorithm is better than all other algorithms. Then, the Kasiski test is used to verify the validity of the proposed algorithm and found that, if the proposed algorithm is used for data encryption, so an attacker cannot break the proposed algorithm security using any technique or algorithm.     

Hierarchical 3D Flower-like Metal Oxides Micro/Nanostructures: Fabrication,Surface Modification,Their Crucial Role in Environmental Decontamination,Mechanistic Insights,and Future Perspectives

Hierarchical micro/nanostructures are constructed by micro-scaled objects with nanoarchitectures belonging to an interesting class of crystalline materials that has significant applications in diverse fields. Featured with a large surface-to-volume ratio, facile mass transportation, high stability against aggregation, structurally enhanced adsorption, and catalytical performances, three dimenisional (3D) hierarchical metal oxides have been considered as versatile functional materials for waste-water treatment. Due to the ineffectiveness of traditional water purification protocols for reclamation of water, lately, the use of hierarchical metal oxides has emerged as an appealing platform for the remediation of water pollution owing to their fascinating and tailorable physiochemical properties. The present review highlights various approaches to the tunable synthesis of hierarchical structures along with their surface modification strategies to enhance their efficiencies for the removal of different noxious substances. Besides, their applications for the eradication of organic and inorganic contaminants have been discussed comprehensively with their plausible mechanistic pathways. Finally, overlooked aspects in this field as well as the major roadblocks to the implementation of these metal oxide architectures for large-scale treatment of wastewater are provided here. Moreover, the potential ways to tackle these issues are also presented which may be useful for the transformation of current water treatment technologies.     

Deep learning and machine learning-based early survival predictions of glioblastoma patients using pre-operative three-dimensional brain magnetic resonance imaging modalities

To propose and implement an automated machine learning (ML) based methodology to predict the overall survival of glioblastoma multiforme (GBM) patients. In the proposed methodology, we used deep learning (DL) based 3D U-shaped Convolutional Neural Network inspired encoder-decoder architecture to segment the brain tumor. Further, feature extraction was performed on these segmented and raw magnetic resonance imaging (MRI) scans using a pre-trained 2D residual neural network. The dimension-reduced principal components were integrated with clinical data and the handcrafted features of tumor subregions to compare the performance of regression-based automated ML techniques. Through the proposed methodology, we achieved the mean squared error (MSE) of 87 067.328, median squared error of 30 915.66, and a SpearmanR correlation of 0.326 for survival prediction (SP) with the validation set of Multimodal Brain Tumor Segmentation 2020 dataset. These results made the MSE far better than the existing automated techniques for the same patients. Automated SP of GBM patients is a crucial topic with its relevance in clinical use. The results proved that DL-based feature extraction using 2D pre-trained networks is better than many heavily trained 3D and 2D prediction models from scratch. The ensembled approach has produced better results than single models. The most crucial feature affecting GBM patients' survival is the patient's age, as per the feature importance plots presented in this work. The most critical MRI modality for SP of GBM patients is the T2 fluid attenuated inversion recovery, as evident from the feature importance plots.     

Synthesis of NiO/Si Using Sol-Gel as a Photosensor

Silicon - Recent studies have indicated that that the application of nickel oxide (NiO) regulator nano-films is growing. The sol-gel method has become the primary method for preparing NiO thin...