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

Mineral maturity and crystallinity index are distinct characteristics of bone mineral

The purpose of this study was to test the hypothesis that mineral maturity and crystallinity index are two different characteristics of bone mineral. To this end, Fourier transform infrared microspectroscopy (FTIRM) was used. To test our hypothesis, synthetic apatites and human bone samples were used for the validation of the two parameters using FTIRM. Iliac crest samples from seven human controls and two with skeletal fluorosis were analyzed at the bone structural unit (BSU) level by FTIRM on sections 2–4 lm thick. Mineral maturity and crystallinity index were highly correlated in synthetic apatites but poorly correlated in normal human bone. In skeletal fluorosis, crystallinity index was increased and maturity decreased, supporting the fact of separate measurement of these two parameters. Moreover, results obtained in fluorosis suggested that mineral characteristics can be modified independently of bone remodeling. In conclusion, mineral maturity and crystallinity index are two different parameters measured separately by FTIRM and offering new perspectives to assess bone mineral traits in osteoporosis

Quantification of bound microbubbles in ultrasound molecular imaging

Molecular markers associated with diseases can be visualized and quantified noninvasively with targeted ultrasound contrast agent (t-UCA) consisting of microbubbles (MBs) that can bind to specific molecular targets. Techniques used for quantifying t-UCA assume that all unbound MBs are taken out of the blood pool few minutes after injection and only MBs bound to the molecular markers remain. However, differences in physiology, diseases, and experimental conditions can increase the longevity of unbound MBs. In such conditions, unbound MBs will falsely be quantified as bound MBs. We have developed a novel technique to distinguish and classify bound from unbound MBs. In the post-processing steps, first, tissue motion was compensated using block-matching (BM) techniques. To preserve only stationary contrast signals, a minimum intensity projection (MinIP) or 20th-percentile intensity projection (PerIP) was applied. The after-flash MinIP or PerIP was subtracted from the before-flash MinIP or PerIP. In this way, tissue artifacts in contrast images were suppressed. In the next step, bound MB candidates were detected. Finally, detected objects were tracked to classify the candidates as unbound or bound MBs based on their displacement. This technique was validated in vitro, followed by two in vivo experiments in mice. Tumors (n = 2) and salivary glands of hypercholesterolemic mice (n = 8) were imaged using a commercially available scanner. Boluses of 100 μL of a commercially available t-UCA targeted to angiogenesis markers and untargeted control UCA were injected separately. Our results show considerable reduction in misclassification of unbound MBs as bound ones. Using our method, the ratio of bound MBs in salivary gland for images with targeted UCA versus control UCA was improved by up to two times compared with unprocessed images

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

Partial Volume Segmentation of Brain MRI Scans of any Resolution and Contrast

Partial voluming (PV) is arguably the last crucial unsolved problem in Bayesian segmentation of brain MRI with probabilistic atlases. PV occurs when voxels contain multiple tissue classes, giving rise to image intensities that may not be representative of any one of the underlying classes. PV is particularly problematic for segmentation when there is a large resolution gap between the atlas and the test scan, e.g., when segmenting clinical scans with thick slices, or when using a high-resolution atlas. In this work, we present PV-SynthSeg, a convolutional neural network (CNN) that tackles this problem by directly learning a mapping between (possibly multi-modal) low resolution (LR) scans and underlying high resolution (HR) segmentations. PV-SynthSeg simulates LR images from HR label maps with a generative model of PV, and can be trained to segment scans of any desired target contrast and resolution, even for previously unseen modalities where neither images nor segmentations are available at training. PV-SynthSeg does not require any preprocessing, and runs in seconds. We demonstrate the accuracy and flexibility of the method with extensive experiments on three datasets and 2,680 scans. The code is available at https://github.com/BBillot/SynthSeg.Comment: accepted for MICCAI 202

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

Triaxial Deformation and Nuclear Shape Transition in \u3csup\u3e192\u3c/sup\u3eAu

Background: Nuclei in the A≈190 mass region show gradual shape changes from prolate through nonaxial deformed shapes and ultimately towards spherical shapes as the Pb region is approached. Exploring how this shape evolution occurs will help us understand the evolution of collectivity in this region. Purpose: The level scheme of the 192Au nucleus in A ≈ 190 region was studied in order to deduce its deformations. Methods: High-spin states of 192Au have been populated in the 186W(11B, 5n) reaction 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 (WNSL), Yale University. Results: Based on double and triple γ-ray coincidence data the level scheme of 192Au has been extended up to Iπ = 32+ at an excitation energy of ∼6 MeV. Conclusion: The results are discussed in the framework of pairing and deformation self-consistent total Routhian surface (TRS) and cranked shell model (CSM) calculations. The comparison of the experimental observations with the calculations indicates that this nucleus takes a nonaxial shape similar to other Au nuclei in this region

Mechanical model for a collagen fibril pair in extracellular matrix

In this paper, we model the mechanics of a collagen pair in the connective tissue extracellular matrix that exists in abundance throughout animals, including the human body. This connective tissue comprises repeated units of two main structures, namely collagens as well as axial, parallel and regular anionic glycosaminoglycan between collagens. The collagen fibril can be modeled by Hooke's law whereas anionic glycosaminoglycan behaves more like a rubber-band rod and as such can be better modeled by the worm-like chain model. While both computer simulations and continuum mechanics models have been investigated the behavior of this connective tissue typically, authors either assume a simple form of the molecular potential energy or entirely ignore the microscopic structure of the connective tissue. Here, we apply basic physical methodologies and simple applied mathematical modeling techniques to describe the collagen pair quantitatively. We find that the growth of fibrils is intimately related to the maximum length of the anionic glycosaminoglycan and the relative displacement of two adjacent fibrils, which in return is closely related to the effectiveness of anionic glycosaminoglycan in transmitting forces between fibrils. These reveal the importance of the anionic glycosaminoglycan in maintaining the structural shape of the connective tissue extracellular matrix and eventually the shape modulus of human tissues. We also find that some macroscopic properties, like the maximum molecular energy and the breaking fraction of the collagen, are also related to the microscopic characteristics of the anionic glycosaminoglycan

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