Examining the NEUROG2-lineage and associated-gene expression in human cortical organoids.

Proneural genes are conserved drivers of neurogenesis across the animal kingdom. How their functions have adapted to guide human-specific neurodevelopmental features is poorly understood. Here, we mined transcriptomic data from human fetal cortices and generated from human embryonic stem cell (hESC)-derived cortical organoids (COs) to show that NEUROG1 and NEUROG2 are most highly expressed in basal neural progenitor cells, with pseudotime trajectory analyses indicating that NEUROG1-derived lineages predominate early and NEUROG2 lineages later.

Machine learning based intrusion detection framework for detecting security attacks in internet of things.

The Internet of Things (IoT) consist of a network of interconnected nodes constantly communicating, exchanging, and transferring data over various network protocols. Intrusion detection systems using deep learning are a common method used for providing security in IoT. However, traditional deep learning IDS systems do not accurately classify the attack and also require high computation time.

Dual Multi Scale Attention Network Optimized With Archerfish Hunting Optimization Algorithm for Diabetics Prediction.

Diabetes is a chronic disease that occurs when the body cannot regulate blood sugar levels. Nowadays, the screening tests for diabetes are developed using multivariate regression methods. An increasing amount of data is automatically collected to provide an opportunity for creating challenging and accurate prediction modes that are updated constantly with the help of machine learning techniques.

Assessing the spatial scale of synchrony in forest tree population dynamics.

Populations of forest trees exhibit large temporal fluctuations, but little is known about the synchrony of these fluctuations across space, including their sign, magnitude, causes and characteristic scales. These have important implications for metapopulation persistence and theoretical community ecology. Using data from permanent forest plots spanning local, regional and global spatial scales, we measured spatial synchrony in tree population growth rates over sub-decadal and decadal timescales and explored the relationship of synchrony to geographical distance.