Remote sensing and nuclear techniques for high-resolution mapping and quantification of gully erosion in the highly erodible area of the Malčanska River Basin, Eastern Serbia.

Gully erosion leads to the formation of deep and wide channels that increase the risk of soil loss, flooding, and water pollution. In addition, this process reduces the productivity and viability of agricultural land and natural ecosystems. Preventing gully erosion is critical for maintaining ecological balance and preserving natural resources in certain areas.

Surgical teaching of the retropubic midurethral sling: a virtual reality training system.

Introduction And Hypothesis: The objective is to develop a low-risk, cost-effective method to teach procedures that require learning by feel and high-volume pattern recognition, starting with the midurethral sling.

Methods: This video describes the creation of a virtual reality model utilizing de-identified patient data, artificial intelligence algorithms and haptics; and demonstrates the use of the training system for trocar passage of the retropubic midurethral sling procedure.

Results: This innovative system overcomes the lack of visualization and "blind" nature of sling surgery.

An Interpretable Deep Learning Model for Speech Activity Detection Using Electrocorticographic Signals.

Numerous state-of-the-art solutions for neural speech decoding and synthesis incorporate deep learning into the processing pipeline. These models are typically opaque and can require significant computational resources for training and execution. A deep learning architecture is presented that learns input bandpass filters that capture task-relevant spectral features directly from data.

Nucleus Basalis of Meynert Stimulation for Dementia: Theoretical and Technical Considerations.

Deep brain stimulation (DBS) of nucleus basalis of Meynert (NBM) is currently being evaluated as a potential therapy to improve memory and overall cognitive function in dementia. Although, the animal literature has demonstrated robust improvement in cognitive functions, phase 1 trial results in humans have not been as clear-cut. We hypothesize that this may reflect differences in electrode location within the NBM, type and timing of stimulation, and the lack of a biomarker for determining the stimulation's effectiveness in real time.

FN-DFE: fuzzy-neural data fusion engine for enhanced resilient state-awareness of hybrid energy systems.

Resiliency and improved state-awareness of modern critical infrastructures, such as energy production and industrial systems, is becoming increasingly important. As control systems become increasingly complex, the number of inputs and outputs increase. Therefore, in order to maintain sufficient levels of state-awareness, a robust system state monitoring must be implemented that correctly identifies system behavior even when one or more sensors are faulty.