PostBP: A Python library to analyze outputs from wildfire growth models.

Wildfire is an important natural disturbance agent in Canadian forests, but it has also caused significant economic damage nationwide. Spatial fire growth models have emerged as important tools for representing wildfire dynamics across diverse landscapes, enabling the mapping of key wildfire hazard metrics such as location-specific burn probabilities or likelihoods of fire ignition. While these summary metrics have gained popularity, they often fall short in capturing the directional spread of wildfires and their potential spread distances.

A Dual Mode Adaptive Basal-Bolus Advisor Based on Reinforcement Learning.

Self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) are commonly used by type 1 diabetes (T1D) patients to measure glucose concentrations. The proposed adaptive basal-bolus algorithm (ABBA) supports inputs from either SMBG or CGM devices to provide personalised suggestions for the daily basal rate and prandial insulin doses on the basis of the patients' glucose level on the previous day. The ABBA is based on reinforcement learning, a type of artificial intelligence, and was validated in silico with an FDA-accepted population of 100 adults under different realistic scenarios lasting three simulated months.

Reinforcement learning: a novel method for optimal control of propofol-induced hypnosis.

Reinforcement learning (RL) is an intelligent systems technique with a history of success in difficult robotic control problems. Similar machine learning techniques, such as artificial neural networks and fuzzy logic, have been successfully applied to clinical control problems. Although RL presents a mathematically robust method of achieving optimal control in systems challenged with noise, nonlinearity, time delay, and uncertainty, no application of RL in clinical anesthesia has been reported.

Reinforcement learning versus proportional-integral-derivative control of hypnosis in a simulated intraoperative patient.

Background: Research has demonstrated the efficacy of closed-loop control of anesthesia using bispectral index (BIS) as the controlled variable. Model-based and proportional-integral-derivative (PID) controllers outperform manual control. We investigated the application of reinforcement learning (RL), an intelligent systems control method, to closed-loop BIS-guided, propofol-induced hypnosis in simulated intraoperative patients.

Paternal behavior increases testosterone levels in offspring of the California mouse.

Paternal care during early development influences pup survivorship in the monogamous and biparental California mouse, Peromyscus californicus. Moreover, paternal pup retrievals impact development of adult offspring aggression and the neuropeptide vasopressin, yet little is known about the underlying mechanisms of these developmental changes. Because testosterone can increase arginine vasopressin and aggression, we hypothesized that paternal pup retrievals increase testosterone levels in prepubertal male P.

Fuzzy control for closed-loop, patient-specific hypnosis in intraoperative patients: a simulation study.

Research has demonstrated the efficacy of closed-loop control of anesthesia using bispectral index (BIS) as the controlled variable, and the recent development of model-based, patient-adaptive systems has considerably improved anesthetic control. To further explore the use of model-based control in anesthesia, we investigated the application of fuzzy control in the delivery of patient-specific propofol-induced hypnosis. In simulated intraoperative patients, the fuzzy controller demonstrated clinically acceptable performance, suggesting that further study is warranted.

Structure and reactivity of TNT and related species: application of spectroscopic approaches and quantum-chemical approximations toward understanding transformation mechanisms.

This paper presents our latest findings regarding the structure and reactivity of the nitroaromatics, TNT and selected derivatives, within their environmental context. We also demonstrate the useful and proactive role of combined computational chemistry and spectroscopy tools in studying competing transformation mechanisms, particularly those with toxic potential. TNT and selected derivatives were reacted via alkaline hydrolysis as well as via free radical initiators through monochromatic irradiation and through Fenton reactions in complex competing transformation mechanisms.