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Antibacterial activity of homemade Indian tomato tamarind soup (rasam) against common pathogens

Eswaran et al. | Oct 04, 2024

Antibacterial activity of homemade Indian tomato tamarind soup (rasam) against common pathogens

Systematic consumption of traditional foods is a popular way of treating diseases in India. Rasam, a soup of spices and tomato with a tamarind base, is a home remedy for viral infections such as the common cold. Here, we investigate if rasam, prepared under household conditions, exhibits antibacterial activity against Escherichia coli and Staphylococcus aureus, two common pathogenic bacteria. Our results show rasam prepared under household conditions lacks antibacterial activity despite its ingredients possessing such properties.

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Digestion products of bread and cheese cause addictive behavior in a planaria model

Cochin et al. | Sep 26, 2024

Digestion products of bread and cheese cause addictive behavior in a planaria model

The authors looked at two peptides, gluteomorphin and casomorphin, that are present after the digestion of bread and cheese. As these peptides can bind opioid receptors the authors want to know if they could be addictive in the same way as conventional opioids (i.e., morphine) are known to be. Their results in a planaria model suggest that both of these peptides are addictive.

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Identifying shark species using an AlexNet CNN model

Sarwal et al. | Sep 23, 2024

Identifying shark species using an AlexNet CNN model

The challenge of accurately identifying shark species is crucial for biodiversity monitoring but is often hindered by time-consuming and labor-intensive manual methods. To address this, SharkNet, a CNN model based on AlexNet, achieved 93% accuracy in classifying shark species using a limited dataset of 1,400 images across 14 species. SharkNet offers a more efficient and reliable solution for marine biologists and conservationists in species identification and environmental monitoring.

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A meta-analysis on NIST post-quantum cryptographic primitive finalists

Benny et al. | Sep 21, 2024

A meta-analysis on NIST post-quantum cryptographic primitive finalists
Image credit: Benny et al. 2024

The advent of quantum computing will pose a substantial threat to the security of classical cryptographic methods, which could become vulnerable to quantum-based attacks. In response to this impending challenge, the field of post-quantum cryptography has emerged, aiming to develop algorithms that can withstand the computational power of quantum computers. This study addressed the pressing concern of classical cryptographic methods becoming vulnerable to quantum-based attacks due to the rise of quantum computing. The emergence of post-quantum cryptography has led to the development of new resistant algorithms. Our research focused on four quantum-resistant algorithms endorsed by America’s National Institute of Standards and Technology (NIST) in 2022: CRYSTALS-Kyber, CRYSTALS-Dilithium, FALCON, and SPHINCS+. This study evaluated the security, performance, and comparative attributes of the four algorithms, considering factors such as key size, encryption/decryption speed, and complexity. Comparative analyses against each other and existing quantum-resistant algorithms provided insights into the strengths and weaknesses of each program. This research explored potential applications and future directions in the realm of quantum-resistant cryptography. Our findings concluded that the NIST algorithms were substantially more effective and efficient compared to classical cryptographic algorithms. Ultimately, this work underscored the need to adapt cryptographic techniques in the face of advancing quantum computing capabilities, offering valuable insights for researchers and practitioners in the field. Implementing NIST-endorsed quantum-resistant algorithms substantially reduced the vulnerability of cryptographic systems to quantum-based attacks compared to classical cryptographic methods.

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