Realistic evaluation

Brain segmentation from neonatal MRI images is a very challenging task due to large changes in the shape of cerebral structures and variations in signal intensities reflecting the gestational process. In this context, there is a clear need for segmentation techniques that are robust to variations in image contrast and to the spatial configuration of anatomical structures. In this work, we evaluate the potential of synthetic learning, a contrast-independent model trained using synthetic images generated from the ground truth labels of very few subjects...

BACKGROUND: Substantial work has been done to update or create evidence-based practices (EBPs) in the changing health care landscape. However, the success of these EBPs is limited by low levels of clinician implementation. OBJECTIVE: The goal of this study is to describe the use of standardized/simulated patient/person (SP) methodology as a framework to develop implementation bundles to increase the effectiveness, sustainability, and reproducibility of EBPs across health care clinicians...

PURPOSE: We examined magnetic field dependent SNR gains and ability to capture them with multichannel receive arrays for human head imaging in going from 7 T, the most commonly used ultrahigh magnetic field (UHF) platform at the present, to 10.5 T, which represents the emerging new frontier of >10 T in UHFs. METHODS: Electromagnetic (EM) models of 31-channel and 63-channel multichannel arrays built for 10.5 T were developed for 10...

BACKGROUND: Addressing increasing patient demand and improving ED patient flow is a key ambition for NHS England. Delivering general practitioner (GP) services in or alongside EDs (GP-ED) was advocated in 2017 for this reason, supported by £100 million (US$130 million) of capital funding. Current evidence shows no overall improvement in addressing demand and reducing waiting times, but considerable variation in how different service models operate, subject to local context...

Correlating transcriptional profiles with imaging-derived phenotypes has the potential to reveal possible molecular architectures associated with cognitive functions, brain development and disorders. Competitive null models built by resampling genes and self-contained null models built by spinning brain regions, along with varying test statistics, have been used to determine the significance of transcriptional associations. However, there has been no systematic evaluation of their performance in imaging transcriptomics analyses...

Under laboratory conditions, the toxicological effects of pesticides tend to be less variable and realistic than under field conditions, limiting their usefulness in environmental risk assessment. In the current study, the earthworm Eisenia fetida was selected as a bioindicator for assessing glyphosate toxic effects in two different trials to solve this dilemma. In Trial 1, the worms were exposed for 7 and 14 days to concentrations of a commercial glyphosate formulation (1 to 500 mg a.i. kg-1 ) currently used in the field...

BACKGROUND: In order to ensure adequate radiation protection of critical groups such as staff, caregivers and the general public coming into proximity of nuclear medicine (NM) patients, it is necessary to consider the impact of the radiation emitted by the patients during their stay at the hospital or after leaving the hospital. Current risk assessments are based on ambient dose rate measurements in a single position at a specified distance from the patient and carried out at several time points after administration of the radiopharmaceutical to estimate the whole-body retention...

Artificial neural networks have emerged as computationally plausible models of human language processing. A major criticism of these models is that the amount of training data they receive far exceeds that of humans during language learning. Here, we use two complementary approaches to ask how the models' ability to capture human fMRI responses to sentences is affected by the amount of training data. First, we evaluate GPT-2 models trained on 1 million, 10 million, 100 million, or 1 billion words against an fMRI benchmark...

UNLABELLED: Across all electrical stimulation (neuromodulation) domains, conventional analysis of cell polarization involves two discrete steps: i) prediction of macroscopic electric field, ignoring presence of cells and; ii) prediction of cell polarization from tissue electric fields. The first step assumes that electric current flow is not distorted by the dense tortuous network of cell structures. The deficiencies of this assumption have long been recognized, but - except for trivial geometries - ignored, because it presented intractable computation hurdles...

The study of the expressive power of neural networks has investigated the fundamental limits of neural networks. Most existing results assume real-valued inputs and parameters as well as exact operations during the evaluation of neural networks. However, neural networks are typically executed on computers that can only represent a tiny subset of the reals and apply inexact operations, i.e., most existing results do not apply to neural networks used in practice. In this work, we analyze the expressive power of neural networks under a more realistic setup: when we use floating-point numbers and operations as in practice...

Teaching microsurgery is limited by the availability of appropriate training models. In-vivo models, such as rats, remain the gold standard, but ethical and economic limitations restrict their use for initial training. This study investigated the feasibility of using egg membrane as an inert model, an accessible and economical alternative for introduction to microsurgery. The specifications for inert models include ease of access, low cost, high reproducibility and realistic reproduction of relevant characteristics...

PURPOSE: Specular reflections in endoscopic images not only disturb visual perception but also hamper computer vision algorithm performance. However, the intricate nature and variability of these reflections, coupled with a lack of relevant datasets, pose ongoing challenges for removal. METHODS: We present EndoSRR, a robust method for eliminating specular reflections in endoscopic images. EndoSRR comprises two stages: reflection detection and reflection region inpainting...

X-Ray Photoelectron Spectroscopy (XPS) has been utilized to extract local electrical potential profiles by recording core-level binding energy shifts upon application of the AC [square-wave (SQW)] bias with different frequencies. An electrochemical system consisting of a coplanar capacitor with a polyethylene membrane (PEM) coated with the Ionic Liquid (IL) N , N -diethyl- N -methyl- N -(2-methoxyethyl) ammonium bis(trifluoromethanesulfonyl)imide (DEME-TFSI) as the electrolyte is investigated. Analyses are carried out in operando , such that XPS measurements are recorded simultaneously with current measurements...

Indoxacarb is one of the most extensively used oxadiazine insecticides worldwide, but it may exert detrimental effects on ecosystems, population dynamics, and health. Due to the lack of knowledge on the ecotoxicity of indoxacarb, it is still challenging to assess whether this insecticide poses an ecotoxicological impact on terrestrial environments. Therefore, our study aims to provide novel data on the toxic effects of 28-day dietary exposure to commercial grade indoxacarb at two environmentally relevant concentrations, 0...

BACKGROUND: It is known that heel offloading devices are widely used in clinical practice for the prevention of heel pressure ulcers, even though there is a lack of robust, good quality evidence to inform their use. OBJECTIVE: To explore how and why heel offloading devices are used (or not used) and reasoning behind their use in population at high risk of developing heel pressure ulcers. METHODS: An ethnographic study was conducted as part of a realist evaluation in three orthopaedic wards in a large English hospital...

BACKGROUND AND OBJECTIVE: Mechanical ventilation is a life-saving treatment for critically-ill patients. During treatment, patient-ventilator asynchrony (PVA) can occur, which can lead to pulmonary damage, complications, and higher mortality. While traditional detection methods for PVAs rely on visual inspection by clinicians, in recent years, machine learning models are being developed to detect PVAs automatically. However, training these models requires large labeled datasets, which are difficult to obtain, as labeling is a labour-intensive and time-consuming task, requiring clinical expertise...

OBJECTIVE: Cleft lip and palate is the most common craniofacial birth anomaly and requires surgery in the first year of life. However, craniofacial surgery training opportunities are limited. The aim of this study was to present and evaluate an open-source cleft lip and palate hybrid (casting and three-dimensional (3D) printing) simulation model which can be replicated at low cost to facilitate the teaching and training of cleft surgery anatomy and techniques. DESIGN: The soft tissue component of the cleft surgery training model was casted using a 3D printed 5-component mold and silicone...

In stroke rehabilitation, simple robotic devices hold the potential to increase the training dosage in group therapies and to enable continued therapy at home after hospital discharge. However, we identified a lack of portable and cost-effective devices that not only focus on improving motor functions but also address sensory deficits. Thus, we designed a minimally-actuated hand training device that incorporates active grasping movements and passive pronosupination, complemented by a rehabilitative game with meaningful haptic feedback...

This paper presents a general framework for simulating plot data in multi-environment field trials with one or more traits. The framework is embedded within the R package FieldSimR, whose core function generates plot errors that capture global field trend, local plot variation, and extraneous variation at a user-defined ratio. FieldSimR's capacity to simulate realistic plot data makes it a flexible and powerful tool for a wide range of improvement processes in plant breeding, such as the optimisation of experimental designs and statistical analyses of multi-environment field trials...

Three-dimensional (3D)-cultured cells have attracted the attention of researchers in tissue engineering- and drug screening-related fields. Among them, 3D cellular fibers have attracted significant attention because they can be stacked to prepare more complex tissues and organs. Cellular fibers are widely fabricated using extrusion 3D bioprinters. For these applications, it is necessary to evaluate cellular activities, such as the oxygen consumption rate (OCR), which is one of the major metabolic activities...