Predictors of orbital fractures in pediatric patients

OBJECTIVE: To determine risk factors and examination findings that are predictive of orbital fractures in pediatric patients, in the hope of using the findings to develop a rule for when to obtain a Computerized Tomography Scan (CT). Additionally, we will examine the treatments underwent by patients with confirmed orbital fractures. METHODS: A retrospective cohort study was conducted on patients below the age of 22 who were seen in the Emergency Department (ED) at Boston Children's Hospital (BCH) between January 2009 and May 2013, and underwent Computerized Tomography Scan (CT) for evaluation of orbital fracture. 326 cases were selected for inclusion in analysis. Electronic medical records (EMR) of cases were reviewed and data was collected about mechanism of injury, symptoms, physical exam (PE) findings, diagnosis of orbital fracture, and treatment. Data collected was analyzed using SPSS Statistical Software v.21. Frequency of variables was determined, and chi-square analysis was performed comparing frequencies for patients with orbital fractures to patients without orbital fractures. RESULTS: Of the 326 cases undergoing CT, 133 (40.8%) had radiographic evidence of an orbital fracture. Nausea/vomiting, orbital tenderness, orbital swelling, orbital ecchymosis, and limitation of extraocular movement (EOM) were all identified as statistically significant clinical indicators of orbital fractures. 22 (16.5%) of patients with confirmed orbital fractures underwent surgery, with an average time to surgery of 4.5 days. CONCLUSION: We found that 16.5% of cases with orbital fractures, and only 6.7% of all cases, underwent surgery. We have identified 5 factors that can be used for the development of an evidence-based algorithm for determining when to obtain a CT to rule out an orbital fracture in a pediatric population. We believe that we can use this to improve the evaluation of orbital fractures ED, which in turn will improve the utilization of ED resources, and reduce the exposure of pediatric patients to the risks associated with CT

Improving accountability reporting: How to make the best of journalism better for audiences

In this report, we want to explore a series of ideas people in news are working on that, taken together, will create a different approach to accountability journalism — work that encompasses fact-checking, explanatory and investigative reporting, but more generally applies to the journalistic work of holding the powerful accountable. Our proposals include recommendations about tools and technology, but also about format, tone and presentation

Error-resistant Single Qubit Gates with Trapped Ions

Coherent operations constitutive for the implementation of single and multi-qubit quantum gates with trapped ions are demonstrated that are robust against variations in experimental parameters and intrinsically indeterministic system parameters. In particular, pulses developed using optimal control theory are demonstrated for the first time with trapped ions. Their performance as a function of error parameters is systematically investigated and compared to composite pulses.Comment: 5 pages 5 figure

Label-Dependencies Aware Recurrent Neural Networks

In the last few years, Recurrent Neural Networks (RNNs) have proved effective on several NLP tasks. Despite such great success, their ability to model \emph{sequence labeling} is still limited. This lead research toward solutions where RNNs are combined with models which already proved effective in this domain, such as CRFs. In this work we propose a solution far simpler but very effective: an evolution of the simple Jordan RNN, where labels are re-injected as input into the network, and converted into embeddings, in the same way as words. We compare this RNN variant to all the other RNN models, Elman and Jordan RNN, LSTM and GRU, on two well-known tasks of Spoken Language Understanding (SLU). Thanks to label embeddings and their combination at the hidden layer, the proposed variant, which uses more parameters than Elman and Jordan RNNs, but far fewer than LSTM and GRU, is more effective than other RNNs, but also outperforms sophisticated CRF models.Comment: 22 pages, 3 figures. Accepted at CICling 2017 conference. Best Verifiability, Reproducibility, and Working Description awar

Regeneration of photon echoes with amplified photon echoes

Photon-echo-based devices have been proposed for many applications in data storage, image processing, and optical communications. Many of these applications would benefit if the output from the photon-echo process could be used as input in a second photon-echo process. We demonstrate the generation of such secondary echoes, using the amplified output from an initial photon-echo process. The amplification is performed with a Pr:ZBLAN fiber amplifier, which gives a gain of more than 300 at 606 nm when pumped with 320 mW of power at 476 nm

Refined saddle-point preconditioners for discretized Stokes problems

This paper is concerned with the implementation of efficient solution algorithms for elliptic problems with constraints. We establish theory which shows that including a simple scaling within well-established block diagonal preconditioners for Stokes problems can result in significantly faster convergence when applying the preconditioned MINRES method. The codes used in the numerical studies are available online