Linear Contraction Behavior of Low-Carbon, Low-Alloy Steels During and After Solidification Using Real-Time Measurements

A technique for measuring the linear contraction during and after solidification of low-alloy steel was developed and used for examination of two commercial low-carbon and low-alloy steel grades. The effects of several experimental parameters on the contraction were studied. The solidification contraction behavior was described using the concept of rigidity in a solidifying alloy, evolution of the solid fraction, and the microstructure development during solidification. A correlation between the linear contraction properties in the solidification range and the hot crack susceptibility was proposed and used for the estimation of hot cracking susceptibility for two studied alloys and verified with the real casting practice. The technique allows estimation of the contraction coefficient of commercial steels in a wide range of temperatures and could be helpful for computer simulation and process optimization during continuous casting. © 2013 The Minerals, Metals & Materials Society and ASM International

Social sensemaking with AI: Designing an open-ended AI experience with a blind child

AI technologies are often used to aid people in performing discrete tasks with well-defned goals (e.g., recognising faces in images). Emerging technologies that provide continuous, real-time information enable more open-ended AI experiences. In partnership with a blind child, we explore the challenges and opportunities of designing human-AI interaction for a system intended to support social sensemaking. Adopting a research-through-design perspective, we refect upon working with the uncertain capabilities of AI systems in the design of this experience. We contribute: (i) a concrete example of an open-ended AI system that enabled a blind child to extend his own capabilities; (ii) an illustration of the delta between imagined and actual use, highlighting how capabilities derive from the human-AI interaction and not the AI system alone; and (iii) a discussion of design choices to craft an ongoing human-AI interaction that addresses the challenge of uncertain outputs of AI systems

Perinatal death in a term fetal growth restriction randomized controlled trial:the paradox of prior risk and consent

BACKGROUND: The disproportionate intrauterine growth intervention trial at term was an intention to treat analysis and compared labor induction with expectant monitoring in pregnancies complicated by fetal growth restriction at term and showed equivalence for neonatal outcomes. OBJECTIVE: To evaluate trial participation bias and to examine the generalizability of the results of an obstetrical randomized trial. STUDY DESIGN: We used data from participants and nonparticipants of a randomized controlled trial-the disproportionate intrauterine growth intervention trial at term (n=1116) -to perform a secondary analysis. This study compared induction of labor and expectant management in women with term growth restriction. Data were collected in the same manner for both groups. Baseline characteristics and neonatal and maternal outcomes were compared. The primary outcome was a composite measure of adverse neonatal outcome. Secondary outcomes were delivery by cesarean delivery and instrumental vaginal delivery; length of stay in the neonatal intensive care, neonatal ward, and the maternal hospital; and maternal morbidity. RESULTS: Nonparticipants were older, had a lower body mass index, had a higher level of education, smoked less, and preferred expectant management. The time between study inclusion and labor onset was shorter in participants than in nonparticipants. Notably, 4 perinatal deaths occurred among nonparticipants and none among participants. Among nonparticipants, there were more children born with a birthweight below the third centile. The nonparticipants who had expectant management were monitored less frequently than the participants in both the intervention and the expectant arm. CONCLUSION: We found less favorable outcomes and more perinatal deaths in nonparticipants. Protocol-driven management, differences between participants and nonparticipants, or the fact that nonparticipants had a preference for expectant management might explain the findings

Multisite Comparison of MRI Defacing Software Across Multiple Cohorts

With improvements to both scan quality and facial recognition software, there is an increased risk of participants being identified by a 3D render of their structural neuroimaging scans, even when all other personal information has been removed. To prevent this, facial features should be removed before data are shared or openly released, but while there are several publicly available software algorithms to do this, there has been no comprehensive review of their accuracy within the general population. To address this, we tested multiple algorithms on 300 scans from three neuroscience research projects, funded in part by the Ontario Brain Institute, to cover a wide range of ages (3–85 years) and multiple patient cohorts. While skull stripping is more thorough at removing identifiable features, we focused mainly on defacing software, as skull stripping also removes potentially useful information, which may be required for future analyses. We tested six publicly available algorithms (afni_refacer, deepdefacer, mri_deface, mridefacer, pydeface, quickshear), with one skull stripper (FreeSurfer) included for comparison. Accuracy was measured through a pass/fail system with two criteria; one, that all facial features had been removed and two, that no brain tissue was removed in the process. A subset of defaced scans were also run through several preprocessing pipelines to ensure that none of the algorithms would alter the resulting outputs. We found that the success rates varied strongly between defacers, with afni_refacer (89%) and pydeface (83%) having the highest rates, overall. In both cases, the primary source of failure came from a single dataset that the defacer appeared to struggle with - the youngest cohort (3–20 years) for afni_refacer and the oldest (44–85 years) for pydeface, demonstrating that defacer performance not only depends on the data provided, but that this effect varies between algorithms. While there were some very minor differences between the preprocessing results for defaced and original scans, none of these were significant and were within the range of variation between using different NIfTI converters, or using raw DICOM files

Planned Cesarean or planned vaginal delivery for twins: secondary analysis of randomized controlled trial

Objective: To evaluate whether there is a differential benefit of planned Cesarean delivery (CD) over planned vaginal delivery (VD) in women with a twin pregnancy and the first twin in cephalic presentation, depending on prespecified baseline maternal and pregnancy characteristics, and/or gestational age (GA) at delivery. Methods: This was a secondary analysis of the Twin Birth Study, which included 2804 women with a twin pregnancy and the first twin (Twin A) in cephalic presentation between 32 + 0 and 38 + 6 weeks\u27 gestation at 106 centers in 25 countries. Women were assigned randomly to either planned CD or planned VD. The main outcome measure was composite adverse perinatal outcome, defined as the occurrence of perinatal mortality or serious neonatal morbidity in at least one twin. The baseline maternal and pregnancy characteristics (markers) considered were maternal age, parity, history of CD, use of antenatal corticosteroids, estimated fetal weight (EFW) of Twin A, EFW of Twin B, \u3e 25% difference in EFW between the twins, presentation of Twin B, chorionicity on ultrasound, method of conception, complications of pregnancy, ruptured membranes at randomization and GA at randomization. Separate logistic regression models were developed for each marker in order to model composite adverse perinatal outcome as a function of the specific marker, planned delivery mode and the interaction between these two terms. In addition, multivariable logistic regression analysis with backward variable elimination was performed separately in each arm of the trial. The association between planned mode of delivery and composite adverse perinatal outcome, according to GA at delivery, was assessed using logistic regression analysis. Results: Of the 2804 women initially randomized, 1391 were included in each study arm. None of the studied baseline markers was associated with a differential benefit of planned CD over planned VD in the rate of composite adverse perinatal outcome. GA at delivery was associated differentially with composite adverse perinatal outcome in the treatment arms (P for interaction \u3c 0.001). Among pregnancies delivered at 32 + 0 to 36 + 6 weeks, there was a trend towards a lower rate of composite adverse perinatal outcome in those in the planned-VD group compared with those in planned-CD group (29 (2.2%) vs 48 (3.6%) cases; odds ratio (OR) 0.62 (95% CI, 0.37–1.03)). In pregnancies delivered at or after 37 + 0 weeks, planned VD was associated with a significantly higher rate of composite adverse perinatal outcome, as compared with planned CD (23 (1.5%) vs 10 (0.7%) cases; OR, 2.25 (95% CI, 1.06–4.77)). Conclusion: The perinatal outcome of twin pregnancies with the first twin in cephalic presentation may differ depending on GA at delivery and planned mode of delivery. At 32–37 weeks, planned VD seems to be favorable, while, from around 37 weeks onwards, planned CD might be safer. The absolute risks of adverse perinatal outcomes at term are low and must be weighed against the increased maternal risks associated with planned CD. © 2019 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology