Nanoparticle iron-phosphate anode material for Li-ion battery

Nanoparticle crystalline iron phosphates (FePO4.2H(2)O and FePO4) were synthesized using a (CTAB) surfactant as an anode material for Li rechargeable batteries. The electrochemical properties of the nanoparticle iron phosphates were characterized with a voltage window of 2.4-0 V. A variscite orthorhombic FePO4.2H(2)O showed a large initial charge capacity of 609 mAh/g. On the other hand, a tridymite triclinic FePO4 exhibited excellent cyclability: the capacity retention up to 30 cycles was similar to80%, from 485 to 375 mAh/g. The iron phosphate anodes exhibited the highest reported capacity, while the cathode LiFePO4 has an ideal capacity of 170 mAh/g.open515

Linkless octree using multi-level perfect hashing

The standard C/C++ implementation of a spatial partitioning data structure, such as octree and quadtree, is often inefficient in terms of storage requirements particularly when the memory overhead for maintaining parent-to-child pointers is significant with respect to the amount of actual data in each tree node. In this work, we present a novel data structure that implements uniform spatial partitioning without storing explicit parent-to-child pointer links. Our linkless tree encodes the storage locations of subdivided nodes using perfect hashing while retaining important properties of uniform spatial partitioning trees, such as coarse-to-fine hierarchical representation, efficient storage usage, and efficient random accessibility. We demonstrate the performance of our linkless trees using image compression and path planning examples.postprin

Global Ultrasound Elastography Using Convolutional Neural Network

Displacement estimation is very important in ultrasound elastography and failing to estimate displacement correctly results in failure in generating strain images. As conventional ultrasound elastography techniques suffer from decorrelation noise, they are prone to fail in estimating displacement between echo signals obtained during tissue distortions. This study proposes a novel elastography technique which addresses the decorrelation in estimating displacement field. We call our method GLUENet (GLobal Ultrasound Elastography Network) which uses deep Convolutional Neural Network (CNN) to get a coarse time-delay estimation between two ultrasound images. This displacement is later used for formulating a nonlinear cost function which incorporates similarity of RF data intensity and prior information of estimated displacement. By optimizing this cost function, we calculate the finer displacement by exploiting all the information of all the samples of RF data simultaneously. The Contrast to Noise Ratio (CNR) and Signal to Noise Ratio (SNR) of the strain images from our technique is very much close to that of strain images from GLUE. While most elastography algorithms are sensitive to parameter tuning, our robust algorithm is substantially less sensitive to parameter tuning.Comment: 4 pages, 4 figures; added acknowledgment section, submission type late

Effect of Nonlinear Multi-axial Elasticity and Anisotropic Plasticity on Quasi-static Dent Properties of Automotive Steel Sheets

This study investigates the influence of the elasto-plastic properties of automotive steel sheets on the denting behavior and suggests a constitutive modeling approach for reliable dent analysis. The stress strain behaviors of three kinds of steel sheets were measured in uniaxial tension, in-plane biaxial tension and forward-reverse simple shear tests. Advanced constitutive models were employed to capture the plastic anisotropy, reverse loading characteristics such as the Bauschinger effect, and elastic modulus degradation. In particular, the biaxial elastic modulus and its degradation behavior were measured and implemented in the constitutive model. The suggested model significantly improved the prediction of dents compared to the conventional model in terms of the load-displacement curve. Sensitivity studies on the constitutive model demonstrated that mainly plastic anisotropy and elastic behavior of a material influence the panel stiffness, whereas the reverse loading behavior strongly affects the permanent dent depth. (C) 2016 Elsevier Ltd. All rights reserved.1151Ysciescopu

Necrotic tumor growth: an analytic approach

The present paper deals with a free boundary problem modeling the growth process of necrotic multi-layer tumors. We prove the existence of flat stationary solutions and determine the linearization of our model at such an equilibrium. Finally, we compute the solutions of the stationary linearized problem and comment on bifurcation.Comment: 14 pages, 3 figure

The effect of stellar and AGN feedback on the low-redshift Lyman a forest in the Sherwood simulation suite

We study the effect of different feedback prescriptions on the properties of the low redshift ($z\leq1.6$) Ly$\alpha$ forest using a selection of hydrodynamical simulations drawn from the Sherwood simulation suite. The simulations incorporate stellar feedback, AGN feedback and a simplified scheme for efficiently modelling the low column density Ly$\alpha$ forest. We confirm a discrepancy remains between Cosmic Origins Spectrograph (COS) observations of the Ly$\alpha$ forest column density distribution function (CDDF) at $z \simeq 0.1$ for high column density systems ($N_{\rm HI}>10^{14}\rm\,cm^{-2}$), as well as Ly$\alpha$ velocity widths that are too narrow compared to the COS data. Stellar or AGN feedback -- as currently implemented in our simulations -- have only a small effect on the CDDF and velocity width distribution. We conclude that resolving the discrepancy between the COS data and simulations requires an increase in the temperature of overdense gas with $\Delta=4$--$40$, either through additional He$\,\rm \scriptstyle II\$ photo-heating at $z>2$ or fine-tuned feedback that ejects overdense gas into the IGM at just the right temperature for it to still contribute significantly to the Ly$\alpha$ forest. Alternatively a larger, currently unresolved turbulent component to the line width could resolve the discrepancy

International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) - the propagation of knowledge in ultrasound for the improvement of OB/GYN care worldwide: experience of basic ultrasound training in Oman.

BACKGROUND: The aim of this study is to evaluate effectiveness of a new ISUOG (International Society of Ultrasound in Obstetrics and Gynecology) Outreach Teaching and Training Program delivered in Muscat, Oman. METHODS: Quantitative assessments to evaluate knowledge and practical skills were administered before and after an ultrasound course for sonologists attending the ISUOG Outreach Course, which took place in November, 2017, in Oman. Trainees were selected from each region of the country following a national vetting process conducted by the Oman Ministry of Health. Twenty-eight of the participants were included in the analysis. Pre- and post-training practical and theoretical scores were evaluated and compared. RESULTS: Participants achieved statistically significant improvements, on average by 47% (p < 0.001), in both theoretical knowledge and practical skills. Specifically, the mean score in the theoretical knowledge test significantly increased from 55.6% (± 14.0%) to 81.6% (± 8.2%), while in the practical test, the mean score increased from 44.6% (± 19.5%) to 65.7% (± 23.0%) (p < 0.001). Performance was improved post-course among 27/28 participants (96.4%) in the theoretical test (range: 14 to 200%) and among 24/28 (85.7%) trainees in the practical skills test (range: 5 to 217%). CONCLUSION: Application of the ISUOG Basic Training Curriculum and Outreach Teaching and Training Course improved the theoretical knowledge and practical skills of local health personnel. Long-term re-evaluation is, however, considered imperative to ascertain and ensure knowledge retention

<i>C-elegans</i> model identifies genetic modifiers of alpha-synuclein inclusion formation during aging

Inclusions in the brain containing alpha-synuclein are the pathological hallmark of Parkinson's disease, but how these inclusions are formed and how this links to disease is poorly understood. We have developed a &lt;i&gt;C-elegans&lt;/i&gt; model that makes it possible to monitor, in living animals, the formation of alpha-synuclein inclusions. In worms of old age, inclusions contain aggregated alpha-synuclein, resembling a critical pathological feature. We used genome-wide RNA interference to identify processes involved in inclusion formation, and identified 80 genes that, when knocked down, resulted in a premature increase in the number of inclusions. Quality control and vesicle-trafficking genes expressed in the ER/Golgi complex and vesicular compartments were overrepresented, indicating a specific role for these processes in alpha-synuclein inclusion formation. Suppressors include aging-associated genes, such as sir-2.1/SIRT1 and lagr-1/LASS2. Altogether, our data suggest a link between alpha-synuclein inclusion formation and cellular aging, likely through an endomembrane-related mechanism. The processes and genes identified here present a framework for further study of the disease mechanism and provide candidate susceptibility genes and drug targets for Parkinson's disease and other alpha-synuclein related disorders

Pair-breaking quantum phase transition in superconducting nanowires

A quantum phase transition (QPT) between distinct ground states of matter is a wide-spread phenomenon in nature, yet there are only a few experimentally accessible systems where the microscopic mechanism of the transition can be tested and understood. These cases are unique and form the experimentally established foundation for our understanding of quantum critical phenomena. Here we report the discovery that a magnetic-field-driven QPT in superconducting nanowires - a prototypical 1d-system - can be fully explained by the critical theory of pair-breaking transitions characterized by a correlation length exponent $\nu \approx 1$ and dynamic critical exponent $z \approx 2$. We find that in the quantum critical regime, the electrical conductivity is in agreement with a theoretically predicted scaling function and, moreover, that the theory quantitatively describes the dependence of conductivity on the critical temperature, field magnitude and orientation, nanowire cross sectional area, and microscopic parameters of the nanowire material. At the critical field, the conductivity follows a $T^{(d-2)/z}$ dependence predicted by phenomenological scaling theories and more recently obtained within a holographic framework. Our work uncovers the microscopic processes governing the transition: The pair-breaking effect of the magnetic field on interacting Cooper pairs overdamped by their coupling to electronic degrees of freedom. It also reveals the universal character of continuous quantum phase transitions.Comment: 22 pages, 5 figure