Author(s): van den Bos W; Bruckner R; Nassar MR; Mata R; Eppinger B;

In recent years, the application of computational modeling in studies on age-related changes in decision making and learning has gained in popularity. One advantage of computational models is that they provide access to latent variables that cannot be directly observed from behavior. In combination with experimental manipulations, these latent variables c ...

Article GUID: 29066078

Author(s): Ndiaye NA; Shamleh SA; Casale D; Castaneda-Ouellet S; Laplante I; Robinson MJF; Samaha AN;

Rationale: When people with drug addiction encounter cues associated with drug use, this can trigger cravings and relapse. These cues can include conditioned stimuli (CSs) signaling drug delivery and discriminative stimuli (DSs) signaling drug availability. Compared to CS effects, DS effects are ...

Article GUID: 38767684

Author(s): Rebecca J Daniels

Bradykinesia, or slow movement, is a defining symptom of Parkinson's disease (PD), but the underlying neuromechanical deficits that lead to this slowness remain unclear. People with PD often have impaired rates of motor output accompanied by disruptions in neuromuscular excitation, causing abnormal, segmented, force-time curves. Previous investigation ...

Article GUID: 38507858

Author(s): W Spencer Murch

The post-reinforcement pause (PRP) is an operant effect in which response latencies increase on trials following the receipt and consumption of reward. Human studies demonstrate analogous effects in electronic gambling machines that utilise random ratio reinforcement schedules. We sought to identify moderators of the human PRP effect, hypothesising that t ...

Article GUID: 38429228

Author(s): Carter F; Cossette MP; Trujillo-Pisanty I; Pallikaras V; Breton YA; Conover K; Caplan J; Solis P; Voisard J; Yaksich A; Shizgal P;

Phasic dopamine activity is believed to both encode reward-prediction errors (RPEs) and to cause the adaptations that these errors engender. If so, a rat working for optogenetic stimulation of dopamine neurons will repeatedly update its policy and/or action values, thus iteratively increasing its ...

Article GUID: 38039083

Author(s): Moezi SA; Sedaghati R; Rakheja S;

In recent years, magnetoactive soft continuum robots (MSCRs) with multimodal locomotion capabilities have emerged for various biomedical applications. Developments in nonlinear dynamic models and effective control methods for MSCRs are deemed vital not only to gain a better understanding of their coupled magneto-mechanical behavior but also to accurately ...

Article GUID: 37932207

Author(s): Sartori I; Walnum HT; Skeie KS; Georges L; Knudsen MD; Bacher P; Candanedo J; Sigounis AM; Prakash AK; Pritoni M; Granderson J; Yang S; Wan MP;

The data presented here were collected independently for 6 real buildings by researchers of different institutions and gathered in the context of the IEA EBC Annex 81 Data-driven Smart Buildings, as a joint effort to compile a diverse range of datasets suitable for advanced control applications o ...

Article GUID: 37153123

Author(s): El-Kassabi HT; Serhani MA; Masud MM; Shuaib K; Khalil K;

Supporting security and data privacy in cloud workflows has attracted significant research attention. For example, private patients' data managed by a workflow deployed on the cloud need to be protected, and communication of such data across multiple stakeholders should also be secured. In general, security threats in cloud environments have been stud ...

Article GUID: 36691661

Author(s): Pan J; Huang J; Cheng G; Zeng Y;

This paper proposes, implements, and evaluates a reinforcement learning (RL)-based computational framework for automatic mesh generation. Mesh generation plays a fundamental role in numerical simulations in the area of computer aided design and engineering (CAD/E). It is identified as one of the critical issues in the NASA CFD Vision 2030 Study. Existing ...

Article GUID: 36375347

Author(s): Rjoub G; Wahab OA; Bentahar J; Cohen R; Bataineh AS;

In the context of distributed machine learning, the concept of federated learning (FL) has emerged as a solution to the privacy concerns that users have about sharing their own data with a third-party server. FL allows a group of users (often referred to as clients) to locally train a single machine learning model on their devices without sharing their ra ...

Article GUID: 35875592

Author(s): Sohrabi Kashani A; Larocque K; Piekny A; Packirisamy M;

In the present study, we investigate the mechanobiological responses of human lung cancer that may occur through their interactions with two different types of gold nanoparticles: nanostars and nanospheres. Hyperspectral images of nanoparticle-treated cells revealed different spatial distributions of nanoparticles in cells depending on their morphology, w ...

Article GUID: 35839330