Ultra-Short Pulses Laser Heating of Dielectrics: A Semi-Classical Analytical Model.

Femtosecond laser pulses are currently regarded as an emerging and promising tool for processing wide bandgap dielectric materials across a variety of high-end applications, although the associated physical phenomena are not yet fully understood. To address these challenges, we propose an original, fully analytical model combined with Two Temperatures Model (TTM) formalism. The model is applied to describe the interaction of fs laser pulses with a typical dielectric target (e.

A Robust Recurrent Neural Networks-Based Surrogate Model for Thermal History and Melt Pool Characteristics in Directed Energy Deposition.

In directed energy deposition (DED), accurately controlling and predicting melt pool characteristics is essential for ensuring desired material qualities and geometric accuracies. This paper introduces a robust surrogate model based on recurrent neural network (RNN) architectures-Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurrent Unit (GRU). Leveraging a time series dataset from multi-physics simulations and a three-factor, three-level experimental design, the model accurately predicts melt pool peak temperatures, lengths, widths, and depths under varying conditions.

The estrous cycle modulates hippocampal spine dynamics, dendritic processing, and spatial coding.

Histological evidence suggests that the estrous cycle exerts a powerful effect on CA1 neurons in mammalian hippocampus. Decades have passed since this landmark observation, yet how the estrous cycle shapes dendritic spine dynamics and hippocampal spatial coding remains a mystery. Here, we used a custom hippocampal microperiscope and two-photon calcium imaging to track CA1 pyramidal neurons in female mice over multiple cycles.

Robust variability of grid cell properties within individual grid modules enhances encoding of local space.

Although grid cells are one of the most well studied functional classes of neurons in the mammalian brain, whether there is a single orientation and spacing value per grid module has not been carefully tested. We analyze a recent large-scale recording of medial entorhinal cortex to characterize the presence and degree of heterogeneity of grid properties within individual modules. We find evidence for small, but robust, variability and hypothesize that this property of the grid code could enhance the encoding of local spatial information.

Effect of Pre-Heating on Residual Stresses and Deformation in Laser-Based Directed Energy Deposition Repair: A Comparative Analysis.

Laser-directed energy deposition (DED), a metal additive manufacturing method, is renowned for its role in repairing parts, particularly when replacement costs are prohibitive. Ensuring that repaired parts avoid residual stresses and deformation is crucial for maintaining functional integrity. This study conducts experimental and numerical analyses on trapezoidal shape repairs, validating both the thermal and mechanical models with experimental results.

Learning multi-agent cooperation.

Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscape of development environments is making powerful RL techniques more accessible for a growing community of researchers. However, most existing frameworks do not directly address the problem of learning in complex operating environments, such as dense urban settings or defense-related scenarios, that incorporate distributed, heterogeneous teams of agents.

Learning generalizable behaviors from demonstration.

Generalizing prior experiences to complete new tasks is a challenging and unsolved problem in robotics. In this work, we explore a novel framework for control of complex systems called Primitive Imitation for Control (). The approach combines ideas from imitation learning, task decomposition, and novel task sequencing to generalize from demonstrations to new behaviors.

Conceptual knowledge representation: A cross-section of current research.

How is conceptual knowledge encoded in the brain? This special issue of Cognitive Neuropsychology takes stock of current efforts to answer this question through a variety of methods and perspectives. Across this work, three questions recur, each fundamental to knowledge representation in the mind and brain. First, what are the elements of conceptual representation? Second, to what extent are conceptual representations embodied in sensory and motor systems? Third, how are conceptual representations shaped by context, especially linguistic context? In this introductory article we provide relevant background on these themes and introduce how they are addressed by our contributing authors.

Evaluation of the current radiofrequency ablation systems using axiomatic design theory.

This article evaluates current radiofrequency ablation systems using axiomatic design theory. Due to its minimally invasive procedure, short-time hospital stay, low cost, and tumour metastasis treatment, the radiofrequency ablation technique has been playing an important role in tumour treatment in recent decades. Although the radiofrequency ablation technique has many advantages, some issues still need to be addressed.

Online tuning of fuzzy inference systems using dynamic fuzzy Q-learning.

This paper presents a dynamic fuzzy Q-learning (DFQL) method that is capable of tuning fuzzy inference systems (FIS) online. A novel online self-organizing learning algorithm is developed so that structure and parameters identification are accomplished automatically and simultaneously based only on Q-learning. Self-organizing fuzzy inference is introduced to calculate actions and Q-functions so as to enable us to deal with continuous-valued states and actions.

Nondermatoscopic digital imaging of pigmented lesions.

Background/aims: Pigmented lesions are often difficult to evaluate clinically. Improvement of diagnostic accuracy by dermatoscopy has attracted much interet. With advanced digital imaging measurement of assymmetry, border irregularity and relative color as well as texture characteristics, lesional depth and changes in lesional area are now possible, the object of this review is to conclude the present status of these techniques and their potential.