funcX: A Federated Function Serving Fabric for Science

Exploding data volumes and velocities, new computational methods and platforms, and ubiquitous connectivity demand new approaches to computation in the sciences. These new approaches must enable computation to be mobile, so that, for example, it can occur near data, be triggered by events (e.g., arrival of new data), be offloaded to specialized accelerators, or run remotely where resources are available. They also require new design approaches in which monolithic applications can be decomposed into smaller components, that may in turn be executed separately and on the most suitable resources. To address these needs we present funcX---a distributed function as a service (FaaS) platform that enables flexible, scalable, and high performance remote function execution. funcX's endpoint software can transform existing clouds, clusters, and supercomputers into function serving systems, while funcX's cloud-hosted service provides transparent, secure, and reliable function execution across a federated ecosystem of endpoints. We motivate the need for funcX with several scientific case studies, present our prototype design and implementation, show optimizations that deliver throughput in excess of 1 million functions per second, and demonstrate, via experiments on two supercomputers, that funcX can scale to more than more than 130000 concurrent workers.Comment: Accepted to ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC 2020). arXiv admin note: substantial text overlap with arXiv:1908.0490

Novel Moessbauer experiment in a rotating system and the extra-energy shift between emission and absorption lines

We present the results of a novel Mossbauer experiment in a rotating system, implemented recently in Istanbul University, which yields the coefficient k=0.69+/-0.02 within the frame of the expression for the relative energy shift between emission and absorption lines dE/E=ku2/c2. This result turned out to be in a quantitative agreement with an experiment achieved earlier on the subject matter (A.L. Kholmetskii et al. 2009 Phys. Scr. 79 065007), and once again strongly pointed to the inequality k>0.5, revealed originally in (A.L. Kholmetskii et al. 2008 Phys. Scr. 77, 035302 (2008)) via the re-analysis of Kundig experiment (W. Kundig. Phys. Rev. 129, 2371 (1963)). A possible explanation of the deviation of the coefficient k from the relativistic prediction k=0.5 is discussed.Comment: 21 pages, 8 figures, 3 table

http://www.medscape.com/viewarticle/819572_print

Abstract Introduction: Ultrasonography is being increasingly utilized in acute care settings with expanding applications. Pneumothorax evaluation by ultrasonography is a fast, safe, easy and inexpensive alternative to chest radiographs. In this review, we provide a comprehensive analysis of the current literature comparing ultrasonography and chest radiography for the diagnosis of pneumothorax. Methods: We searched English-language articles in MEDLINE, EMBASE and Cochrane Library dealing with both ultrasonography and chest radiography for diagnosis of pneumothorax. In eligible studies that met strict inclusion criteria, we conducted a meta-analysis to evaluate the diagnostic accuracy of pleural ultrasonography in comparison with chest radiography for the diagnosis of pneumothorax. Results: We reviewed 601 articles and selected 25 original research articles for detailed review. Only 13 articles met all of our inclusion criteria and were included in the final analysis. One study used lung sliding sign alone, 12 studies used lung sliding and comet tail signs, and 6 studies searched for lung point in addition to the other two signs. Ultrasonography had a pooled sensitivity of 78.6% (95% CI, 68.1 to 98.1) and a specificity of 98.4% (95% CI, 97.3 to 99.5). Chest radiography had a pooled sensitivity of 39.8% (95% CI, 29.4 to 50.3) and a specificity of 99.3% (95% CI, 98.4 to 100). Our meta-regression and subgroup analyses indicate that consecutive sampling of patients compared to convenience sampling provided higher sensitivity results for both ultrasonography and chest radiography. Consecutive versus nonconsecutive sampling and trauma versus nontrauma settings were significant sources of heterogeneity. In addition, subgroup analysis showed significant variations related to operator and type of probe used. Conclusions: Our study indicates that ultrasonography is more accurate than chest radiography for detection of pneumothorax. The results support the previous investigations in this field, add new valuable information obtained from subgroup analysis, and provide accurate estimates for the performance parameters of both bedside ultrasonography and chest radiography for pneumothorax evaluation

A Combined Deep Learning-Gradient Boosting Machine Framework for Fluid Intelligence Prediction

The ABCD Neurocognitive Prediction Challenge is a community driven competition asking competitors to develop algorithms to predict fluid intelligence score from T1-w MRIs. In this work, we propose a deep learning combined with gradient boosting machine framework to solve this task. We train a convolutional neural network to compress the high dimensional MRI data and learn meaningful image features by predicting the 123 continuous-valued derived data provided with each MRI. These extracted features are then used to train a gradient boosting machine that predicts the residualized fluid intelligence score. Our approach achieved mean square error (MSE) scores of 18.4374, 68.7868, and 96.1806 for the training, validation, and test set respectively.Comment: Challenge in Adolescent Brain Cognitive Development Neurocognitive Predictio

Metabotropic glutamate receptor 5 neuroimaging in schizophrenia

The metabotropic glutamate receptor 5 (mGluR5) is a promising drug target for the treatment of schizophrenia. In this study, we compared mGluR5 distribution volume ration (DVR) in subjects with schizophrenia and healthy controls. Given our previous findings, we matched samples for gender, age, and smoking status. Binding to mGluR5 was determined using positron emission tomography and [(11)C]ABP688, which binds to an allosteric site with high selectivity. DVR in the 15 individuals with schizophrenia did not differ from that of the 15 controls. In both groups, smoking was associated with marked global reductions in mGluR5 availability (on average 23.8%). In nonsmoking subjects with schizophrenia, there was a positive correlation between mGluR5 DVR in the medial orbitofrontal cortex and the use of antipsychotic drugs (r=0.9, p=0.019). Because antipsychotic drugs such as clozapine appeared to have indirect effects on mGluR5 signaling, our findings may be clinically relevant. They also provide promising leads for elucidating the high comorbidity between schizophrenia and tobacco addiction. Low mGluR5 DVR in smokers my represent a risk factor for schizophrenia. Alternatively, smoking may counteract the potential upregulation of mGluR5 by antipsychotic drugs

High-spin States in \u3csup\u3e191, 193\u3c/sup\u3eAu and \u3csup\u3e192\u3c/sup\u3ePt: Evidence for Oblate Deformation and Triaxial Shapes

High-spin states of 191, 193Au and 192Pt have been populated in the 186W(11B, xn) and 186W(11B, p4n) reactions, respectively, at a beam energy of 68 MeV and their γ decay was studied using the YRAST Ball detector array at the Wright Nuclear Structure Laboratory at Yale University. The level scheme of 193Au has been extended up to Iπ = 55/2+. New transitions were observed also in 191Au and 192Pt. Particle-plus-Triaxial-Rotor (PTR) and Total Routhian Surface (TRS) calculations were performed to determine the equilibrium deformations of the Au isotopes. The predictions for oblate deformations in these nuclei are in agreement with the experimental data. Development of nonaxial shapes is discussed within the framework of the PTR model

Nonlinear Markov Random Fields Learned via Backpropagation

Although convolutional neural networks (CNNs) currently dominate competitions on image segmentation, for neuroimaging analysis tasks, more classical generative approaches based on mixture models are still used in practice to parcellate brains. To bridge the gap between the two, in this paper we propose a marriage between a probabilistic generative model, which has been shown to be robust to variability among magnetic resonance (MR) images acquired via different imaging protocols, and a CNN. The link is in the prior distribution over the unknown tissue classes, which are classically modelled using a Markov random field. In this work we model the interactions among neighbouring pixels by a type of recurrent CNN, which can encode more complex spatial interactions. We validate our proposed model on publicly available MR data, from different centres, and show that it generalises across imaging protocols. This result demonstrates a successful and principled inclusion of a CNN in a generative model, which in turn could be adapted by any probabilistic generative approach for image segmentation.Comment: Accepted for the international conference on Information Processing in Medical Imaging (IPMI) 2019, camera ready versio

Gastrointestinal stromal tumour of the duodenum in childhood: a rare case report

<p>Abstract</p> <p>Background</p> <p>Gastrointestinal stromal tumours (GISTs) are uncommon primary mesenchymal tumours of the gastrointestinal tract mostly observed in the adults. Duodenal GISTs are relatively rare in adults and it should be regarded as exceptional in childhood. In young patients duodenal GISTs may be a source of potentially lethal haemorrhage and this adds diagnostic and therapeutic dilemmas to the concern about the long-term outcome.</p> <p>Case presentation</p> <p>A 14-year-old boy was referred to our hospital with severe anaemia due to recurrent episodes of upper gastrointestinal haemorrhage. Endoscopy, small bowel series, scintigraphy and video capsule endoscopy previously done elsewhere were negative. Shortly after the admission, the patient underwent emergency surgery for severe recurrence of the bleeding. At surgery, a 4 cm solid mass arising from the wall of the fourth portion of the duodenum was identified. The invasion and the erosion of the duodenal mucosa was confirmed by intra-operative pushed duodenoscopy. The mass was resected by a full-thickness duodenal wall excision with adequate grossly free margins. Immunohistochemical analysis of the specimen revealed to be positive for CD117 (c-KIT protein) consistent with a diagnosis of GIST. The number of mitoses was < 5/50 HPF. Mutational analysis for c-KIT/PDGFRA tyrosine kinase receptor genes resulted in a wildtype pattern. The patient had an uneventful course and he has remained disease-free during two years of follow-up.</p> <p>Conclusion</p> <p>Duodenal GISTs in children are very rare and may present with massive bleeding. Cure can be achieved by complete surgical resection, but even in the low-aggressive tumours the long-term outcome may be unpredictable.</p

Determination of composition and structure of spongy bone tissue in human head of femur by Raman spectral mapping

Biomechanical properties of bone depend on the composition and organization of collagen fibers. In this study, Raman microspectroscopy was employed to determine the content of mineral and organic constituents and orientation of collagen fibers in spongy bone in the human head of femur at the microstructural level. Changes in composition and structure of trabecula were illustrated using Raman spectral mapping. The polarized Raman spectra permit separate analysis of local variations in orientation and composition. The ratios of ν2PO43−/Amide III, ν4PO43−/Amide III and ν1CO32−/ν2PO43− are used to describe relative amounts of spongy bone components. The ν1PO43−/Amide I ratio is quite susceptible to orientation effect and brings information on collagen fibers orientation. The results presented illustrate the versatility of the Raman method in the study of bone tissue. The study permits better understanding of bone physiology and evaluation of the biomechanical properties of bone