Browse Articles

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.

Read More...

Shortage of Black physicians: Florida Black medical student enrollment from 2013 to 2021

Khan et al. | Sep 18, 2024

Shortage of Black physicians: Florida Black medical student enrollment from 2013 to 2021

Black patients tend to have better health outcomes when cared for by Black physicians, yet Black doctors make up only 5% of U.S. physicians, despite Black people comprising 14% of the population. This analysis of data from Florida medical schools showed a higher enrollment of Black first-year students (13.5%) compared to the national average (9%), and a national increase from 6% in 2013 to 9% in 2021, aligning with the rise of social justice movements. Increasing Black medical student enrollment could reduce health disparities and improve outcomes for Black communities.

Read More...

Solubility of graphite and the efficacy of using its dissolved form as a conductive paste

Kirby et al. | Aug 23, 2024

Solubility of graphite and the efficacy of using its dissolved form as a conductive paste

This study explored the use of graphite's conductivity for circuit boards by creating a conductive paste through exfoliation with organic solvents and sonication. The combination of acetone and sonication was found to be the most effective, producing a high-conductivity paste with desirable properties such as a low boiling point. While not a replacement for wires, this conductive paste has potential applications in electronics and infrastructure, provided that key engineering challenges are addressed.

Read More...

Diagnosing hypertrophic cardiomyopathy using machine learning models on CMRs and EKGs of the heart

Kolluri et al. | Jul 29, 2024

Diagnosing hypertrophic cardiomyopathy using machine learning models on CMRs and EKGs of the heart
Image credit: Jesse Orrico

Here seeking to develop a method to diagnose, hypertrophic cardiomyopathy which can cause sudden cardiac death, the authors investigated the use of a convolutional neural network (CNN) and long short-term memory (LSTM) models to classify cardiac magnetic resonance and heart electrocardiogram scans. They found that the CNN model had a higher accuracy and precision and better other qualities, suggesting that machine learning models could be valuable tools to assist physicians in the diagnosis of hypertrophic cardiomyopathy.

Read More...

Analysis of electrodialysis as a method of producing potable water

Shen et al. | May 03, 2024

Analysis of electrodialysis as a method of producing potable water

Here, seeking a way to convert the vast quantity of seawater to drinking water, the authors investigated the purification of seawater to drinking water through electrodialysis. Using total dissolved solids (TDS) as their measure, they found that electrodialysis was able to produce deionized water with TDS values under the acceptable range for consumable water.

Read More...

Changing electronic use behavior in adolescents while studying: An interventional psychology experiment

Kumar et al. | Mar 02, 2024

Changing electronic use behavior in adolescents while studying: An interventional psychology experiment
Image credit: RAMSHA ASAD

Here, the authors investigated the effects of an interventional psychology on the study habits of high school students specifically related to the use of electronic distractions such as social media or texting, listening to music, or watching TV. They reported varying degrees of success between the control and intervention groups, suggesting that the methods of habit-breaking for students merits further study.

Read More...

Automated classification of nebulae using deep learning & machine learning for enhanced discovery

Nair et al. | Feb 01, 2024

Automated classification of nebulae using deep learning & machine learning for enhanced discovery

There are believed to be ~20,000 nebulae in the Milky Way Galaxy. However, humans have only cataloged ~1,800 of them even though we have gathered 1.3 million nebula images. Classification of nebulae is important as it helps scientists understand the chemical composition of a nebula which in turn helps them understand the material of the original star. Our research on nebulae classification aims to make the process of classifying new nebulae faster and more accurate using a hybrid of deep learning and machine learning techniques.

Read More...

Scientific project in physics "Carbonated liquids and carbonation level"

Irina et al. | Jan 21, 2024

Scientific project in physics "Carbonated liquids and carbonation level"

In our work we followed the formation of gas bubbles on the surface of the vessel walls in different carbonated liquids, over different time intervals, at different temperatures and in vessels made of different materials. Our results made it possible to identify patterns affecting the process of formation and disappearance of carbon dioxide bubbles.

Read More...