Comparative analysis of surgically induced astigmatism following cataract surgery: influence of previous myopic correction and corneal parameters.

Purpose: This retrospective study investigated the impact of corneal parameters on surgically induced astigmatism (SIA) in eyes with prior myopic correction undergoing cataract surgery.

Setting: Department of Ophthalmology, San Marino Hospital, San Marino, Republic of San Marino.

Design: This case-control study analyzed existing data retrospectively, without randomization or masking.

Child and caregiver predictors of primary caregiver participation in families of school-aged Autistic children.

Engaging in meaningful activities (e.g., leisure, spiritual, fitness) significantly affects caregivers' quality of life (QoL), yet the determinants of participation in caregivers of Autistic children remain largely unknown.

Leisure, community, workforce participation and quality of life in primary and secondary caregivers of autistic children.

Parents of Autistic children often modify their participation in leisure, social, and employment activities to meet the caregiving needs of their child. However, few studies have examined the impact this has on caregiver quality of life (QoL). The aim in the current study was to examine the role of participation in a range of activities on QoL amongst primary and secondary caregivers of school-aged Autistic children.

Quantum discriminator for binary classification.

Quantum computers have the unique ability to operate relatively quickly in high-dimensional spaces-this is sought to give them a competitive advantage over classical computers. In this work, we propose a novel quantum machine learning model called the Quantum Discriminator, which leverages the ability of quantum computers to operate in the high-dimensional spaces. The quantum discriminator is trained using a quantum-classical hybrid algorithm in [Formula: see text] time, and inferencing is performed on a universal quantum computer in [Formula: see text] time.

Encoding integers and rationals on neuromorphic computers using virtual neuron.

Neuromorphic computers emulate the human brain while being extremely power efficient for computing tasks. In fact, they are poised to be critical for energy-efficient computing in the future. Neuromorphic computers are primarily used in spiking neural network-based machine learning applications.