Enhancing Mechanical and Antibacterial Performance of Tire Waste/Epoxidized Natural Rubber Blends Using Modified Zinc Oxide-Silica.

This study investigates the synergistic effects of incorporating modified zinc oxide-silica (ZnO-SiO) into tire waste (TW) and epoxidized natural rubber (ENR) blends, with a focus on crosslinking dynamics, mechanical reinforcement, and antibacterial activity. The addition of ZnO-SiO significantly enhanced crosslink density, as evidenced by increased torque and accelerated cure rates. An optimal concentration of 10 phr was found to yield the highest performance.

Extraction of diosgenin using different techniques from fenugreek seeds- A review.

Diosgenin, falls under the category of steroidal saponin present in fenugreek seeds (Trigonella foenum-graecum) in the amount of 0.2-09%. This compound possesses certain pharmacological characteristics like anti-inflammatory, anti-cancer, anti-oxidant etc.

A sustainable approach towards extraction of diosgenin from fenugreek seeds using polystyrene/divinyl benzene resin.

Diosgenin, a bioactive molecule; is one of the deeply explored saponin with a wide spectrum of benefits against various ailments. The extraction and yield enhancement of diosgenin from a wide range of naturally occurring medicinal products has always been a challenging task for its commercial usage. The current research work envisages the use of a novel resin to maximize the yield of diosgenin.

Rapid formation of carbon nanotubes-natural rubber films cured with glutaraldehyde for reducing percolation threshold concentration.

Carbon nanotubes (CNTs) filled natural rubber (NR) composites with various CNT contents at 0, 1, 2, 3, 4 and 5 phr were prepared by latex mixing method using glutaraldehyde as curing agent. This work aims to improve the electrical and mechanical properties of CNT filled NR vulcanizates. The CNT dispersion of NR composites was clarified using dispersion grader, optical microscopy and scanning electron microscopy.

Multimodal Biomedical Image Segmentation using Multi-Dimensional U-Convolutional Neural Network.

Deep learning recently achieved advancement in the segmentation of medical images. In this regard, U-Net is the most predominant deep neural network, and its architecture is the most prevalent in the medical imaging society. Experiments conducted on difficult datasets directed us to the conclusion that the traditional U-Net framework appears to be deficient in certain respects, despite its overall excellence in segmenting multimodal medical images.

The medicinal panorama of benzimidazoles and their scaffolds as anticancer and antithrombotic agents: A review.

Nitrogen-containing heterocyclic scaffolds have become a prospective pharmacophore with therapeutic importance due to their biological similarities with natural and synthetic drugs. Among all nitrogen heterocyclic compounds, benzimidazoles and their derivatives are privileged molecules structurally akin to naturally available nucleotides, enabling them to intercommunicate with numerous biopolymers in biological systems. This reason enlightens modern researchers worldwide to assess their potential significance in the context of synthetic and biological chemistry.

Development and Characterization of Unmodified and Modified Natural Rubber Composites Filled with Modified Clay.

Novel composite based on rubber and modified bentonite clay (Clay) was investigated. The modified bentonite clay was developed by dispersing in ethanol solutions (Et-OH) using ultrasonic method. The effect of Et-OH on the dispersion of bentonite clay at various mixing temperatures in case of different type of rubber matrix, i.

Hyperspectral Image Classification Model Using Squeeze and Excitation Network with Deep Learning.

In the domain of remote sensing, the classification of hyperspectral image (HSI) has become a popular topic. In general, the complicated features of hyperspectral data cause the precise classification difficult for standard machine learning approaches. Deep learning-based HSI classification has lately received a lot of interest in the field of remote sensing and has shown promising results.

Influence of Non-Rubber Components on the Properties of Unvulcanized Natural Rubber from Different Clones.

Natural rubber from different clones, namely RRIM600, RRIT251, PB235 and BPM24, exhibit unique properties. The influences of the various fresh natural rubber latex and cream concentrated latex on the non-rubber components related properties were studied. It was found that the fresh natural rubber latex exhibited differences in their particle size, which was attributed to the non-rubber and unique signature of clones which affect various properties.

Segmentation and Classification of Glaucoma Using U-Net with Deep Learning Model.

Glaucoma is the second most common cause for blindness around the world and the third most common in Europe and the USA. Around 78 million people are presently living with glaucoma (2020). It is expected that 111.

A Torn ACL Mapping in Knee MRI Images Using Deep Convolution Neural Network with Inception-v3.

The anterior cruciate ligaments (ACL) are the fundamental structures in preserving the common biomechanics of the knees and most frequently damaged knee ligaments. An ACL injury is a tear or sprain of the ACL, one of the fundamental ligaments in the knee. ACL damage most generally happens during sports, for example, soccer, ball, football, and downhill skiing, which include sudden stops or changes in direction, jumping, and landings.

Effect of plasma-polymerised acetylene-coated silica on the compound properties of natural rubber composites.

Silica-filled natural rubber (NR) encounters incompatibility problems, owing to the strong particle-particle interaction arising from the hydrogen bonds of hydroxyl groups, which generally leads to the formation of agglomerates. The addition of coupling agents, especially silane coupling agents, reduces the agglomeration. However, this has some disadvantages, such as toxicity, a risk of pre-curing, and the generation of ethanol during mixing.

Combination of Self-Healing Butyl Rubber and Natural Rubber Composites for Improving the Stability.

The self-healing composites were prepared from the combination of bromobutyl rubber (BIIR) and natural rubber (NR) blends filled with carbon nanotubes (CNT) and carbon black (CB). To reach the optimized self-healing propagation, the BIIR was modified with ionic liquid (IL) and butylimidazole (IM), and blended with NR using the ratios of 70:30 and 80:20 BIIR:NR. Physical and chemical modifications were confirmed from the mixing torque and attenuated total reflection-fourier transform infrared spectroscopy (ATR-FTIR).