The consequences of an increase in heavy goods vehicles for passenger car drivers' mental workload and behaviour:A simulator study

The effects of an increase in Heavy Goods Vehicles (HGVs) on merging behaviour and on mental workload of motorists during filtering in and out of traffic were studied. Participants drove in a driving simulator in a total of 12 conditions; twice in each of two weather conditions and in three traffic conditions. The weather conditions were clear weather and foggy weather. The traffic conditions were without HGVs (i.e. only private cars), the current mix of HGVs and private cars, and a condition with a 70% increase of HGVs leading to an HGV column in the slow lane. The focus of the study was on assessing effects on behaviour and mental workload during filtering into traffic, and during exiting from the motorway. During the experiment driving performance was registered, behaviour was observed, self reports were collected, and the participant's heart rate was recorded. The results showed that directly after filtering into traffic the variation in driving speed increased and the minimum time headway decreased with an increase in the proportion of HGVs. Joining motorway traffic was considered to involve greater effort and risk in the condition with a column of HGVs. The effects of the conditions on heart rate are less clear, although the moment when the participants joined the traffic is clearly visible. The effects of weather conditions were limited, drivers adapting their driving behaviour in adverse weather by reducing speed. To exit the motorway is not a difficult manoeuvre. For that reason the lane change from the left hand to the fight hand lane that preceded the exit was analysed. Although increased mental effort was reported and the lane change was visible in the heart rate record, no critical changes as a result of increase in proportion of HGVs were found for this manoeuvre. However, in the condition with a column of HGVs, the exit that had to be taken was most frequently missed as HGVs obstructed the view of the exit signs. It is concluded that an increase in HGVs will make merging into traffic more mentally demanding and will decrease safety margins

Pharmacological treatment for psychotic depression

Background Evidence is limited regarding the most effective pharmacological treatment for psychotic depression: monotherapy with an antidepressant, monotherapy with an antipsychotic, another treatment (e.g. mifepristone), or combination of an antidepressant plus an antipsychotic. This is an update of a review first published in 2005 and last updated in 2015. Objectives 1. To compare the clinical efficacy of pharmacological treatments for patients with an acute psychotic depression: antidepressant monotherapy, antipsychotic monotherapy, mifepristone monotherapy, and the combination of an antidepressant plus an antipsychotic versus placebo and/or each other. 2. To assess whether differences in response to treatment in the current episode are related to non-response to prior treatment. Search methods A search of the Cochrane Central Register of Controlled Trials (CENTRAL), in the Cochrane Library; the Cochrane Common Mental Disorders Controlled Trials Register (CCMDCTR); Ovid MEDLINE (1950-); Embase (1974-); and PsycINFO (1960-) was conducted on 21 February 2020. Reference lists of all included studies and related reviews were screened and key study authors contacted. Selection criteria All randomised controlled trials (RCTs) that included participants with acute major depression with psychotic features, as well as RCTs consisting of participants with acute major depression with or without psychotic features, that reported separately on the subgroup of participants with psychotic features. Data collection and analysis Two review authors independently extracted data and assessed risk of bias in the included studies, according to criteria from the Cochrane Handbook for Systematic Reviews of Interventions. Data were entered into RevMan 5.1. We used intention-to-treat data. Primary outcomes were clinical response for efficacy and overall dropout rate for harm/tolerance. Secondary outcome were remission of depression, change from baseline severity score, quality of life, and dropout rate due to adverse effects. For dichotomous efficacy outcomes (i.e. response and overall dropout), risk ratios (RRs) with 95% confidence intervals (CIs) were calculated. Regarding the primary outcome of harm, only overall dropout rates were available for all studies. If the study did not report any of the response criteria as defined above, remission as defined here could be used as an alternative. For continuously distributed outcomes, it was not possible to extract data from the RCTs. Main results The search identified 3947 abstracts, but only 12 RCTs with a total of 929 participants could be included in the review. Because of clinical heterogeneity, few meta-analyses were possible. The main outcome was reduction in severity (response) of depression, not of psychosis. For depression response, we found no evidence of a difference between antidepressant and placebo (RR 8.40, 95% CI 0.50 to 142.27; participants = 27, studies = 1; very low-certainty evidence) or between antipsychotic and placebo (RR 1.13, 95% CI 0.74 to 1.73; participants = 201, studies = 2; very low-certainty evidence). Furthermore, we found no evidence of a difference in overall dropouts with antidepressant (RR 1.24, 95% CI 0.34 to 4.51; participants = 27, studies = 1; very low-certainty evidence) or antipsychotic monotherapy (RR 0.79, 95% CI 0.57 to 1.08; participants = 201, studies = 2; very low-certainty evidence). No evidence suggests a difference in depression response (RR 2.09, 95% CI 0.64 to 6.82; participants = 36, studies = 1; very low-certainty evidence) or overall dropouts (RR 1.79, 95% CI 0.18 to 18.02; participants = 36, studies = 1; very low-certainty evidence) between antidepressant and antipsychotic. For depression response, low- to very low-certainty evidence suggests that the combination of an antidepressant plus an antipsychotic may be more effective than antipsychotic monotherapy (RR 1.83, 95% CI 1.40 to 2.38; participants = 447, studies = 4), more effective than antidepressant monotherapy (RR 1.42, 95% CI 1.11 to 1.80; participants = 245, studies = 5), and more effective than placebo (RR 1.86, 95% CI 1.23 to 2.82; participants = 148, studies = 2). Very low-certainty evidence suggests no difference in overall dropouts between the combination of an antidepressant plus an antipsychotic versus antipsychotic monotherapy (RR 0.79, 95% CI 0.63 to 1.01; participants = 447, studies = 4), antidepressant monotherapy (RR 0.91, 95% CI 0.55 to 1.50; participants = 245, studies = 5), or placebo alone (RR 0.75, 95% CI 0.48 to 1.18; participants = 148, studies = 2). No study measured change in depression severity from baseline, quality of life, or dropouts due to adverse events. We found no RCTs with mifepristone that fulfilled our inclusion criteria. Risk of bias is considerable: we noted differences between studies with regards to diagnosis, uncertainties around randomisation and allocation concealment, treatment interventions (pharmacological differences between various antidepressants and antipsychotics), and outcome criteria. Authors' conclusions Psychotic depression is heavily under-studied, limiting confidence in the conclusions drawn. Some evidence indicates that combination therapy with an antidepressant plus an antipsychotic is more effective than either treatment alone or placebo. Evidence is limited for treatment with an antidepressant alone or with an antipsychotic alone. Evidence for efficacy of mifepristone is lacking

Compressive 3D ultrasound imaging using a single sensor

Three-dimensional ultrasound is a powerful imaging technique, but it requires thousands of sensors and complex hardware. Very recently, the discovery of compressive sensing has shown that the signal structure can be exploited to reduce the burden posed by traditional sensing requirements. In this spirit, we have designed a simple ultrasound imaging device that can perform three-dimensional imaging using just a single ultrasound sensor. Our device makes a compressed measurement of the spatial ultrasound field using a plastic aperture mask placed in front of the ultrasound sensor. The aperture mask ensures that every pixel in the image is uniquely identifiable in the compressed measurement. We demonstrate that this device can successfully image two structured objects placed in water. The need for just one sensor instead of thousands paves the way for cheaper, faster, simpler, and smaller sensing devices and possible new clinical applications

Photoacoustic imaging of carotid artery atherosclerosis

We introduce a method for photoacoustic imaging of the carotid artery, tailored toward detection of lipidrich atherosclerotic lesions. A common human carotid artery was obtained at autopsy, embedded in a neck mimicking phantom and imaged with a multimodality imaging system using interstitial illumination. Light was delivered through a 1.25-mm-diameter optical probe that can be placed in the pharynx, allowing the carotid artery to be illuminated from within the body. Ultrasound imaging and photoacoustic signal detection is achieved by an external 8-MHz linear array coupled to an ultrasound imaging system. Spectroscopic analysis of photoacoustic images obtained in the wavelength range from 1130 to 1250 nm revealed plaque-specific lipid accumulation in the collagen structure of the artery wall. These spectroscopic findings were confirmed by histology

Information-theoretic active contour model for microscopy image segmentation using texture

High throughput technologies have increased the need for automated image analysis in a wide variety of microscopy techniques. Geometric active contour models provide a solution to automated image segmentation by incorporating statistical information in the detection of object boundaries. A statistical active contour may be defined by taking into account the optimisation of an information-theoretic measure between object and background. We focus on a product-type measure of divergence known as Cauchy-Schwartz distance which has numerical advantages over ratio-type measures. By using accurate shape derivation techniques, we define a new geometric active contour model for image segmentation combining Cauchy-Schwartz distance and Gabor energy texture filters. We demonstrate the versatility of this approach on images from the Brodatz dataset and phase-contrast microscopy images of cells

The international phase 4 validation study of the EORTC QLQ-SWB32: a stand-alone measure of spiritual wellbeing (SWB) for people receiving palliative care for cancer

The EORTC Quality of Life (QL) Group has just completed the final phase (field-testing and validation) of an international project to develop a stand-alone measure of spiritual wellbeing (SWB) for palliative cancer patients. Participants (n= 451) - from 14 countries on four continents; 54% female; 188 Christian, 50 Muslim, 156 with no religion - completed a provisional 36-item measure of SWB plus the EORTC QLQ-C15-PAL (PAL), then took part in a structured debriefing interview. All items showed good score distribution across response categories. We assessed scale structure using Principal Component Analysis and Rasch analysis, and explored construct validity, and convergent/divergent validity with the PAL. Twenty-two items in four scoring scales (Relationship with Self, Relationships with Others, Relationship with Something Greater, and Existential) explained 53% of the variance. The measure also includes a global SWB item and nine other items. Scores on the PAL global QL item and Emotional Functioning scale weakly-moderately correlated with scores on the global SWB item and two of the four SWB scales. This new validated 32-item SWB measure addresses a distinct aspect of QL, and is now available for use in research and clinical practice, with a role as both a measurement and an intervention tool

Development and technical validation of a smartphone-based cry detection algorithm

Introduction: The duration and frequency of crying of an infant can be indicative of its health. Manual tracking and labeling of crying is laborious, subjective, and sometimes inaccurate. The aim of this study was to develop and technically validate a smartphone-based algorithm able to automatically detect crying.Methods: For the development of the algorithm a training dataset containing 897 5-s clips of crying infants and 1,263 clips of non-crying infants and common domestic sounds was assembled from various online sources. OpenSMILE software was used to extract 1,591 audio features per audio clip. A random forest classifying algorithm was fitted to identify crying from non-crying in each audio clip. For the validation of the algorithm, an independent dataset consisting of real-life recordings of 15 infants was used. A 29-min audio clip was analyzed repeatedly and under differing circumstances to determine the intra- and inter- device repeatability and robustness of the algorithm.Results: The algorithm obtained an accuracy of 94% in the training dataset and 99% in the validation dataset. The sensitivity in the validation dataset was 83%, with a specificity of 99% and a positive- and negative predictive value of 75 and 100%, respectively. Reliability of the algorithm appeared to be robust within- and across devices, and the performance was robust to distance from the sound source and barriers between the sound source and the microphone.Conclusion: The algorithm was accurate in detecting cry duration and was robust to various changes in ambient settings.Perioperative Medicine: Efficacy, Safety and Outcome (Anesthesiology/Intensive Care