Perioperative research into memory (PRiMe), part 2: Adult burns intensive care patients show altered structure and function of the default mode network.

Background: Long-term cognitive impairment (LTCI) is experienced by up to two thirds of patients discharged from burns intensive care units (BICUs), however little is known about its neurobiological basis. This study investigated if patients previously admitted to BICU showed structural and functional MRI changes of the Default Mode Network (DMN).

Methods: Fifteen patients previously admitted to BICU with a significant burns injury, and 15 matched volunteers, underwent structural and functional MRI scans.

Novel opportunities for clinical pharmacy research: development of a machine learning model to identify medication related causes of delirium in different patient groups.

The advent of artificial intelligence (AI) technologies has taken the world of science by storm in 2023. The opportunities of this easy to access technology for clinical pharmacy research are yet to be fully understood. The development of a custom-made large language model (LLM) (DELSTAR) trained on a wide range of internationally recognised scientific publication databases, pharmacovigilance sites and international product characteristics to help identify and summarise medication related information on delirium, as a proof-of-concept model, identified new facilitators and barriers for robust clinical pharmacy practice research.

Applications of Lasers for Sensing and Free Space Communications: introduction to the feature issue.

This feature issue highlights the latest developments in laser-based sensing and free space communications. In total, 15 papers were published in Applied Optics, including an invited review paper that celebrates the legacy of David L. Fried.

Object recognition using sparse, reduced-dimension point cloud data.

It has been shown that point separations as a feature derived from point clouds can be used to discriminate between two objects of similar class. Here we show that the same feature derived from sparse point clouds can maintain significant discrimination capability. Using the point-separation feature, templates created from random realizations of a point cloud are developed for several vehicles.

Forecasting atmospheric turbulence conditions from prior environmental parameters using artificial neural networks.

Atmospheric turbulence ( 2) modeling has been proposed by physics-based models, but they are unable to capture the many cases. Recently, machine learning surrogate models have been used to learn the relationship between local meteorological conditions and turbulence strength. These models predict 2 at time from weather at time .

Coherent sensing performance comparison of framed and asynchronous GMAPD arrays.

Single photon counting Geiger mode avalanche photodiode (GMAPD) arrays are typically used for high-resolution 3D ranging. These high-gain, high-bandwidth detectors are also feasible for coherent sensing. GMAPD arrays have two different readout architectures: asynchronous and synchronous (or framed).

Viewpoint-independent object recognition using reduced-dimension point cloud data.

Point cloud data offer the potential for viewpoint-independent object recognition based solely on the geometrical information about an object that they contain. We consider two types of one-dimensional data products extracted from point clouds: range histograms and point-separation histograms. We evaluate each histogram in terms of its viewpoint independence.

Attribution bias underlying burns-induced anxiety symptoms.

Introduction: Burn injuries are a debilitating cause of morbidity and mortality associated with the long-term impact of psychological factors on quality of life. Accurate assessment of the differential impact of burn sequelae and anxiety is often complicated by the overlap between psychological and somatic symptoms in burns patients. The Beck Anxiety Inventory (BAI) is one validated psychometric tool for anxiety assessment.

Perioperative Research into Memory (PRiMe): Cognitive impairment following a severe burn injury and critical care admission, part 1.

Introduction: An investigation into long-term cognitive impairment and Quality of Life (QoL) after severe burns.

Methods: A proof of principle, cohort design, prospective, observational clinical study. Patients with severe burns (>15% TBSA) admitted to Burns ICU for invasive ventilation were recruited for psychocognitive assessment with a convenience sample of age and sex-matched controls.

High resolution non-iterative aperture synthesis.

The maximum resolution of a multiple-input multiple-output (MIMO) imaging system is determined by the size of the synthetic aperture. The synthetic aperture is determined by a coordinate shift using the relative positions of the illuminators and receive apertures. Previous methods have shown non-iterative phasing for multiple illuminators with a single receive aperture for intra-aperture synthesis.

Camera phasing in multi-aperture coherent imaging.

The resolution of a diffraction-limited imaging system is inversely proportional to the aperture size. Instead of using a single large aperture, multiple small apertures are used to synthesize a large aperture. Such a multi-aperture system is modular, typically more reliable and less costly.

Three dimensional object recognition with photon counting imagery in the presence of noise.

Three dimensional (3D) imaging systems have been recently suggested for passive sensing and recognition of objects in photon-starved environments where only a few photons are emitted or reflected from the object. In this paradigm, it is important to make optimal use of limited information carried by photons. We present a statistical framework for 3D passive object recognition in presence of noise.

Three dimensional imaging with randomly distributed sensors.

As a promising three dimensional passive imaging modality, Integral Imaging (II) has been investigated widely within the research community. In virtually all of such investigations, there is an implicit assumption that the collection of elemental images lie on a simple geometric surface (e.g.

Three dimensional visualization by photon counting computational Integral Imaging.

In this paper, we present three dimensional (3D) object reconstruction using photon-counted elemental images acquired by a passive 3D Integral Imaging (II) system. The maximum likelihood (ML) estimator is derived to reconstruct the irradiance of the 3D scene pixels and the reliability of the estimator is described by confidence intervals. For applications in photon scarce environments, our proposed technique provides 3D reconstruction for better visualization as well as significant reduction in the computational burden and required bandwidth for transmission of integral images.

Photon-counting passive 3D image sensing for reconstruction and recognition of partially occluded objects.

In this paper, we discuss the reconstruction and the recognition of partially occluded objects using photon counting integral imaging (II). Irradiance scenes are numerically reconstructed for the reference target in three-dimensional (3D) space. Photon counting scenes are estimated for unknown input objects using maximum likelihood estimation (MLE) of Poisson parameter.

Performance of 3D integral imaging with position uncertainty.

We present the theoretical and simulation results on the analysis of Synthetic Aperture Integral Imaging (SAII) technique and its sensitivity to pickup position uncertainty. SAII is a passive three dimensional imaging technique based on multiple image acquisitions with different perspective of the scene under incoherent or natural illumination. In practical SAII applications, there is always an uncertainty associated with the position at which each sensor captures the elemental image.

Three-dimensional distortion-tolerant object recognition using photon-counting integral imaging.

This paper addresses three-dimensional distortion-tolerant object recognition using photon-counting integral imaging (II). A photon-counting linear discriminant analysis (LDA) is proposed for classification photonlimited images. In the photon-counting LDA, classical irradiance images are used to train the classifier.

Photon counting passive 3D image sensing for automatic target recognition.

In this paper, we propose photon counting three-dimensional (3D) passive sensing and object recognition using integral imaging. The application of this approach to 3D automatic target recognition (ATR) is investigated using both linear and nonlinear matched filters. We find there is significant potential of the proposed system for 3D sensing and recognition with a low number of photons.

Enhanced signal coupling into periodically poled lithium niobate with microlens arrays.

The return signal frequency of an eye-safe ladar system is upconverted from the infrared to the visible through sum-frequency generation by incorporation of periodically poled LiNbO3 into the receiver. A quantitative analysis of the angular acceptance and the quantum efficiency is then presented for a single macroscopic receiver optic and a multiaperture microlens array. Comparing both results, a 6x increase in the receiver field of regard and an 18% increase in beam coupling were realized for the microlens design over the macroscopic system.

Space-bandwidth product enhancement of a monostatic, multiaperture infrared image upconversion ladar receiver incorporating periodically poled liNbO3.

We investigate the space-bandwidth product of a ladar system incorporating an upconversion receiver. After illuminating a target with an eye-safe beam, we direct the return into a piece of periodically poled LiNbO3 where it is upconverted into the visible spectrum and detected with a CCD camera. The theoretical and experimental transfer functions are then found.