Proof-of-concept for a segmented composite diving suit offering depth-independent thermal protection.

Heat loss is a major health hazard for divers. It can lead to hypothermia, organ damage, unconsciousness, and eventually death. Hence, thermal protection is essential for diver safety. Typically, protection is provided by wetsuits made of bubbled neoprene. However, neoprene shrinks with depth and loses thermal insulation capability, while thick neoprene suits make swimming exhausting. Herein, a proof-of-concept is presented for a solution to both problems: a 'K-suit' made of thermally-resistive composite segments attached to a thin neoprene suit. The segments are made of hollow glass microspheres embedded in carrier polymer thermally cured in 3D-printed molds based on 3D-scans of the diver's body. The K-suit was compared in field trials with a 7 mm commercial neoprene suit by diving in pairs, while automated dataloggers registered pressure and temperature inside and outside both suits. The K-suit demonstrated +4ºC higher temperature difference than the 7 mm neoprene. Also, divers reported that the K-suit had the ergonomics of a 3 mm neoprene suit. These preliminary results represent a proof-of-concept for the K-suit and promise further improvements with potential impact on diver safety.

High-Normal Adolescent Fasting Plasma Glucose Is Associated With Poorer Midlife Brain Health: Bogalusa Heart Study.

CONTEXT: It is unclear how adolescent glycemic status relates to brain health in adulthood. OBJECTIVE: To assess the association between adolescent fasting plasma glucose (FPG) and MRI-based brain measures in midlife. DESIGN: Between 1973 and 1992, the Bogalusa Heart Study (BHS) collected FPG from children, 3 to 18 years old, and followed up between 1992 and 2018. Cognitive tests and brain MRI were collected in 2013 to 2016 and 2018. SETTING: Observational longitudinal cohort study. PARTICIPANTS: Of 1298 contacted BHS participants, 74 completed screening, and 50 completed MRI. MAIN OUTCOME MEASURES: Mean FPG per participant at ages <20, 20 to 40, and over 40 years old; brain white matter hyperintensity (WMH) volume, gray matter volume, and functional MRI (fMRI) activation to a Stroop task; tests of logical and working memory, executive function, and semantic fluency. RESULTS: At MRI, participants were middle aged (51.3 ± 4.4 years) and predominantly female (74%) and white (74%). Mean FPG was impaired for zero, two, and nine participants in pre-20, 20 to 40, and over-40 periods. The pre-20 mean FPG above the pre-20 median value (i.e., above 83.5 mg/dL) was associated with greater WMH volume [mean difference: 0.029% of total cranial volume, CI: (0.0059, 0.052), P = 0.015] and less fMRI activation [-1.41 units (-2.78, -0.05), P = 0.043] on midlife MRI compared with below-median mean FPG. In controlling for over-40 mean FPG status did not substantially modify the associations. Cognitive scores did not differ by pre-20 mean FPG. CONCLUSIONS: High-normal adolescent FPG may be associated with preclinical brain changes in midlife.

Mental effort and discomfort: Testing the peak-end effect during a cognitively demanding task.

We applied the peak-end paradigm that was first introduced in the pain literature to examine the experience of effort and discomfort during a cognitively demanding working memory task. A total of 401 participants were asked to rate their effort and discomfort during and after the administration of a working memory task, which systematically varied task difficulty within participants and task duration between participants. Over the course of the task, participants reported a decrease in reported effort and an increase in reported discomfort. Peak and end real-time ratings were significant predictors of retrospective ratings for effort and discomfort; average and initial ratings predicted a small amount of additional variance. The regression analyses with effort and discomfort were largely consistent, with some exceptions. End discomfort significantly predicted willingness to do the task again, but not end effort. These findings highlight the ways in which the experience of effort and discomfort are integrally related, yet importantly separate, during a cognitively demanding task.

BRIDGE OVER TROUBLED WATERS? THE MOST "CENTRAL" MEMBERS OF PSYCHOLOGY AND PHILOSOPHY ASSOCIATIONS CA. 1900.

There are many different ways to assess the significance of historical figures. Often we look at the influence of their writings, or at the important offices they held with disciplinary institutions such as universities, journals, and scholarly societies. In this study, however, we took a novel approach: we took the complete memberships, ca. 1900, of four organizations-the American Psychological Association, the Western Philosophical Association, the American Philosophical Association, and the Southern Society for Philosophy and Psychology-and visualized them as a network. We then identified individuals who "bridged" between two or more of these groups and considered what might be termed their "centrality" to the psychological-philosophical community of their time. First, we examined these figures qualitatively, briefly describing their lives and careers. Then we approached the problem mathematically, considering several alternative technical realizations of "centrality" and then explaining our reasons for choosing eigenvector centrality as the best for our purposes. We found a great deal of overlap among the results of the qualitative and quantitative approaches, but also some telling differences. J. Mark Baldwin, Edward Buchner, Christine Ladd Franklin, and Frank Thilly consistently emerged as highly central figures. Some more marginal figures such as Max Meyer, and Frederick J. E. Woodbridge, Edward A. Pace, Edward H. Griffin played interesting roles as well.

Double-dorsal versus single-volar digital subcutaneous anaesthetic injection for finger injuries in the emergency department: A randomised controlled trial.

OBJECTIVE: The objective of this present study is to compare pain associated with the double-dorsal versus a single-volar subcutaneous injection in the provision of digital anaesthesia for finger injuries presenting to the ED. METHODS: A randomised controlled trial from November 2012 to January 2014 at a single adult tertiary-referral hospital. ED patients with finger injuries requiring digital anaesthesia was randomised to either the double-dorsal or a single-volar subcutaneous injection technique. The primary outcome was patient reported injection pain measured on a 100 mm visual analogue scale with the assessor blinded to the injection technique. The secondary outcome was success of anaesthesia defined as ability to perform the assessment and treatment without further anaesthetic supplementation after 5 min. RESULTS: Eighty-six patients were enrolled. Median (IQR) age was 34 (24-47) years and 79% were men. The majority (66.3%) had distal phalanx injuries. Forty patients were randomised to the double-dorsal and 46 to a single-volar subcutaneous injection technique. The mean (standard deviation) pain score of the double-dorsal injection was 39.1 (24.2) and a single-volar injection was 37.3 (24.5) with a difference of 1.8 (95% CI -8.8 to 12.3). Digital anaesthesia was successful in 64.9% of the double-dorsal and 71.7% of the single-volar subcutaneous injections, a difference of 6.8% (95% CI -12.7 to 26.3). CONCLUSION: In ED patients with finger injuries requiring digital anaesthesia, both the double-dorsal or single-volar subcutaneous injection techniques have similar pain of injection and success rates of anaesthesia. Single-volar injection appears suitable alternative to the commonly performed double-dorsal injection in the ED.

Automatic Classification of Free-Text Radiology Reports to Identify Limb Fractures using Machine Learning and the SNOMED CT Ontology.

OBJECTIVE: To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. MATERIALS AND METHODS: 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. RESULTS: Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. DISCUSSION: Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. CONCLUSION: This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.

Automated classification of limb fractures from free-text radiology reports using a clinician-informed gazetteer methodology.

BACKGROUND: Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. AIMS: The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. METHOD: A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. RESULTS: The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. CONCLUSION: While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.