On renal insufficiency measurement and reference standards using the logarithm of a cumulative exponential and multiple other plasma and renal clearance models

For current models and methods, glomerular filtration rates below 20 ml/min in adults resulted in modelling concentration tails that were frequently unseen on linear-log plotting. The resulting sometimes unobservable tail was predicted using the negative logarithm of a cumulative exponential (LCE), from the latter of its two asymptotes; a logarithm for decreasing time and an exponential tail as time increases. Lambert's Omega is the scaled time at which the two asymptotes are equal. The LCE formula uses two plasma samples, minimum, and fit 13 24 h $^{51}$Cr-EDTA studies with an 8% standard deviation of residuals compared to 20% error for monoexponentials. The LCE model was unbiased for prediction of 43 5 h urinary $^{51}$Cr-EDTA activity cases whereas the mono- and bi-exponential, as well as, adaptively regularised gamma variate models were relatively overestimating. Reference standard corrections were explored. The LCE model detected two otherwise unidentified absent renal function cases (GFR < 0.01 ml/min) in a 41 case $^{169}$Yb-DTPA dataset suggesting its use for detecting anephric conditions. Prospective clinical testing, and metabolic scaling of renal insufficiency is advised for potential changes to patient triage, e.g., for conservative management, dialysis, and kidney or liver transplantation.Comment: 21 pages, 9 figures, under revie

Stochastic embedding DFT: theory and application to p-nitroaniline

Over this past decade, we combined the idea of stochastic resolution of identity with a variety of electronic structure methods. In our stochastic Kohn-Sham DFT method, the density is an average over multiple stochastic samples, with stochastic errors that decrease as the inverse square root of the number of sampling orbitals. Here we develop a stochastic embedding density functional theory method (se-DFT) that selectively reduces the stochastic error (specifically on the forces) for a selected sub-system(s). The motivation, similar to that of other quantum embedding methods, is that for many systems of practical interest the properties are often determined by only a small sub-system. In stochastic embedding DFT two sets of orbitals are used: a deterministic one associated with the embedded subspace, and the rest which is described by a stochastic set. The method is exact in the limit of large number of stochastic samples. We apply se-DFT to study a p-nitroaniline molecule in water, where the statistical errors in the forces on the system (the p-nitroaniline molecule) are reduced by an order of magnitude compared with non-embedding stochastic DFT

Dissociation Quotients of Malonic Acid in Aqueous Sodium Chloride Media to 100°C1

The first and second molal dissociation quotients of malonic acid were measured potentiometrically in a concentration cell fitted with hydrogen electrodes. The hydrogen ion molality of malonic acidJbimalonate solutions was measured relative to a standard aqueous HCI solution from 0 to 100°C over 25° intervals at five ionic strengths ranging from 0.1 to 5.0 molal (NaCl). The molal dissociation quotients and available literature data were treated in the all anionic form by a seven-term equation. This treatment yielded the following thermodynamic quantities for the first acid dissociation equilibrium at 25°C: log K1a = -2.852 ± 0.003. ΔH1̊a = 0.1 ±0.3 kJ-mol-1. ΔS1̊a = -54.4±1.0 J-mol-1-K-1 and ΔCp̊,1a = -185±20 J-mol-1-K-1. Measurements of the bimalonatelmalonate system were made over the same intervals of temperature and ionic strength. A similar regression of the present and previously published equilibrium quotients using a seven- term equation yielded the following values for the second acid dissociation equilibrium at 25°C: log K2a = -5.697 ± 0.001. ΔH2̊a = -5.13±0.11 kJ-mol-1, ΔS2̊a = -126.3±0.4 J-mol-1-K-1. and ΔCp̊,2a = -250+10 J-mol-1-K-1

Modeling the Temporal Nature of Human Behavior for Demographics Prediction

Mobile phone metadata is increasingly used for humanitarian purposes in developing countries as traditional data is scarce. Basic demographic information is however often absent from mobile phone datasets, limiting the operational impact of the datasets. For these reasons, there has been a growing interest in predicting demographic information from mobile phone metadata. Previous work focused on creating increasingly advanced features to be modeled with standard machine learning algorithms. We here instead model the raw mobile phone metadata directly using deep learning, exploiting the temporal nature of the patterns in the data. From high-level assumptions we design a data representation and convolutional network architecture for modeling patterns within a week. We then examine three strategies for aggregating patterns across weeks and show that our method reaches state-of-the-art accuracy on both age and gender prediction using only the temporal modality in mobile metadata. We finally validate our method on low activity users and evaluate the modeling assumptions.Comment: Accepted at ECML 2017. A previous version of this paper was titled 'Using Deep Learning to Predict Demographics from Mobile Phone Metadata' and was accepted at the ICLR 2016 worksho

Dissociation Quotients of Malonic Acid in Aqueous Sodium Chloride Media to 100°C1

The first and second molal dissociation quotients of malonic acid were measured potentiometrically in a concentration cell fitted with hydrogen electrodes. The hydrogen ion molality of malonic acidJbimalonate solutions was measured relative to a standard aqueous HCI solution from 0 to 100°C over 25° intervals at five ionic strengths ranging from 0.1 to 5.0 molal (NaCl). The molal dissociation quotients and available literature data were treated in the all anionic form by a seven-term equation. This treatment yielded the following thermodynamic quantities for the first acid dissociation equilibrium at 25°C: log K1a = -2.852 ± 0.003. ΔH1̊a = 0.1 ±0.3 kJ-mol-1. ΔS1̊a = -54.4±1.0 J-mol-1-K-1 and ΔCp̊,1a = -185±20 J-mol-1-K-1. Measurements of the bimalonatelmalonate system were made over the same intervals of temperature and ionic strength. A similar regression of the present and previously published equilibrium quotients using a seven- term equation yielded the following values for the second acid dissociation equilibrium at 25°C: log K2a = -5.697 ± 0.001. ΔH2̊a = -5.13±0.11 kJ-mol-1, ΔS2̊a = -126.3±0.4 J-mol-1-K-1. and ΔCp̊,2a = -250+10 J-mol-1-K-1

Shifting the Conversation: The Lived Experiences of Teachers within Tier 2 of Response to Intervention

The study explored the lived experiences of teachers who participated in a shared intervention with an interventionist within the Tier 2 level of Response to Intervention (RtI). A qualitative phenomenological approach was used to explore the lived experiences of the teachers. Teachers are required to participate in RtI prior to identifying a student with a learning disability, as dictated by the Individuals with Disabilities Education Act (2004). RtI is a two-pronged model. It is used as a method for identifying students with learning disabilities. Also, RtI provides a structure/process for providing early intervention for students who are struggling academically. The Learning Disabilities Theory, behaviorism, multiple intelligences, and differentiated instruction influenced the design and implementation of the RtI initiative in response to IDEA 2004. Shared Leadership Theory influenced analysis of how teachers view their collaborative responsibilities within Tier 2 of RtI. Insights gained may improve teachers’ professional practices, schools’ organizational procedures, and state and federal policies for identifying students with learning disabilities. The essence of the experience of these ten K-5 teachers within Tier 2 of RtI was that the factors that influenced their experiences created great variability with how each experienced Tier 2. While the participants had common Tier 2 experiences within communication, data collection and documentation, instruction and assessment, and intervention design, the particulars of how each of these was experienced by each participant differed

Superconductors with Topological Order

We propose a mechanism of superconductivity in which the order of the ground state does not arise from the usual Landau mechanism of spontaneous symmetry breaking but is rather of topological origin. The low-energy effective theory is formulated in terms of emerging gauge fields rather than a local order parameter and the ground state is degenerate on topologically non-trivial manifolds. The simplest example of this mechanism of superconductivty is concretely realized as global superconductivty in Josephson junction arrays.Comment: 4 pages, no figure

Multiscale simulations in simple metals: a density-functional based methodology

We present a formalism for coupling a density functional theory-based quantum simulation to a classical simulation for the treatment of simple metallic systems. The formalism is applicable to multiscale simulations in which the part of the system requiring quantum-mechanical treatment is spatially confined to a small region. Such situations often arise in physical systems where chemical interactions in a small region can affect the macroscopic mechanical properties of a metal. We describe how this coupled treatment can be accomplished efficiently, and we present a coupled simulation for a bulk aluminum system.Comment: 15 pages, 7 figure

Cadmium Malonate Complexation in Aqueous Sodium Trifluoromethanesulfonate Media to 75°C; Including Dissociation Quotients of Malonic Acid

The molal formation quotients for cadmium-malonate complexes were measured potentiometrically from 5 to 75°C, at ionic strengths of 0.1, 0.3, 0.6 and 1.0 molal in aqueous sodium trifluoromethanesulfonate (NaTf) media. In addition, the stepwise dissociation quotients for malomc acid were measured in the same medium from 5 to 100°C, at ionic strengths of 0.1, 0.3, 0.6, and 1.0 molal by the same method. The dissociation quotients for malonic acid were modeled as a function of temperature and ionic strength with empirical equations formulated such that the equilibrium constants at infinite dilution were consistent, within the error estimates, with the malonic acid dissociation constants obtained in NaCl media. The equilibrium constants calculated for the dissociation of malonic acid at 25°C and infinite dilution are log K1a = -2.86 ± 0.01 and log K2a = -5.71 ± 0.01. A single Cd-malonate species, CdCH2C2O4, was identified from the complexation study and the formation quotients for this species were also modeled as a function of temperature and ionic strength. Thermodynamic parameters obtained by differentiating the equation with respect to temperature for the formation of CdCH2C2O4 at 25°C and infinite dilution are: log K = 3.45 ± 0.09, ΔH° = 7 ± 6 kJ-mol-1, ΔS° = 91 ± 22 J-K-1-mol-1, and ΔC°p = 400 ± 300J-K-1-mol-1

Chlamydia Hijacks ARF GTPases To Coordinate Microtubule Posttranslational Modifications and Golgi Complex Positioning.

The intracellular bacterium Chlamydia trachomatis develops in a parasitic compartment called the inclusion. Posttranslationally modified microtubules encase the inclusion, controlling the positioning of Golgi complex fragments around the inclusion. The molecular mechanisms by which Chlamydia coopts the host cytoskeleton and the Golgi complex to sustain its infectious compartment are unknown. Here, using a genetically modified Chlamydia strain, we discovered that both posttranslationally modified microtubules and Golgi complex positioning around the inclusion are controlled by the chlamydial inclusion protein CT813/CTL0184/InaC and host ARF GTPases. CT813 recruits ARF1 and ARF4 to the inclusion membrane, where they induce posttranslationally modified microtubules. Similarly, both ARF isoforms are required for the repositioning of Golgi complex fragments around the inclusion. We demonstrate that CT813 directly recruits ARF GTPases on the inclusion membrane and plays a pivotal role in their activation. Together, these results reveal that Chlamydia uses CT813 to hijack ARF GTPases to couple posttranslationally modified microtubules and Golgi complex repositioning at the inclusion.IMPORTANCEChlamydia trachomatis is an important cause of morbidity and a significant economic burden in the world. However, how Chlamydia develops its intracellular compartment, the so-called inclusion, is poorly understood. Using genetically engineered Chlamydia mutants, we discovered that the effector protein CT813 recruits and activates host ADP-ribosylation factor 1 (ARF1) and ARF4 to regulate microtubules. In this context, CT813 acts as a molecular platform that induces the posttranslational modification of microtubules around the inclusion. These cages are then used to reposition the Golgi complex during infection and promote the development of the inclusion. This study provides the first evidence that ARF1 and ARF4 play critical roles in controlling posttranslationally modified microtubules around the inclusion and that Chlamydia trachomatis hijacks this novel function of ARF to reposition the Golgi complex