Tropical Combinatorics and Whittaker functions

We establish a fundamental connection between the geometric RSK correspondence and GL(N,R)-Whittaker functions, analogous to the well known relationship between the RSK correspondence and Schur functions. This gives rise to a natural family of measures associated with GL(N,R)-Whittaker functions which are the analogues in this setting of the Schur measures on integer partitions. The corresponding analogue of the Cauchy-Littlewood identity can be seen as a generalisation of an integral identity for GL(N,R)-Whittaker functions due to Bump and Stade. As an application, we obtain an explicit integral formula for the Laplace transform of the law of the partition function associated with a one-dimensional directed polymer model with log-gamma weights recently introduced by one of the authors (TS).Comment: 31 pages,6 figures, updated introductio

Behavioral modeling of low-frequency noise in switched-capacitor circuits using Python

In precision circuits validating the performance in the presence of low-frequency noise is particularly challenging especially at transistor level, as long simulations are required to observe the low frequency performance. However, running such system-level simulations is rarely practical at transistor level as these simulations can take days to weeks to complete. This work presents a high-level model in Python for generating low-frequency noise which can be used for validating the low-frequency performance of a design in a timely manner. Simulation times can be reduced from days to minutes, enabling designers to achieve a high-level simulation coverage. With Python and NumPy this can be achieved using open-source software tools at no cost

A study protocol of a randomised controlled trial to measure the effects of an augmented prescribed exercise programme (APEP) for frail older medical patients in the acute setting

Background: Older adults experience functional decline in hospital leading to increased healthcare burden and morbidity. The benefits of augmented exercise in hospital remain uncertain. The aim of this trial is to measure the short and longer-term effects of augmented exercise for older medical in-patients on their physical performance, quality of life and health care utilisation. Design and Methods: Two hundred and twenty older medical patients will be blindly randomly allocated to the intervention or sham groups. Both groups will receive usual care (including routine physiotherapy care) augmented by two daily exercise sessions. The sham group will receive stretching and relaxation exercises while the intervention group will receive tailored strengthening and balance exercises. Differences between groups will be measured at baseline, discharge, and three months. The primary outcome measure will be length of stay. The secondary outcome measures will be healthcare utilisation, activity (accelerometry), physical performance (Short Physical Performance Battery), falls history in hospital and quality of life (EQ-5D-5 L). Discussion: This simple intervention has the potential to transform the outcomes of the older patient in the acute setting

An Improved linearity ring oscillator-based current-to-digital converter

Many biosensors produce single-ended current outputs. Lab-on-chip applications demand parallel readout channels requiring low area current-to-digital converters. High HD2 has limited the current controlled ring oscillator’s (CCROs) adoption as a low area, single-ended converter. This work improves CCRO open loop linearity by 10 dB. A wide-bandwidth current buffer is also designed. A low area (0.0025 mm 2 ), low power ( 357 μW ), single-ended, and 1 MHz bandwidth converter suitable for array readout is presented with the measured performance

Enhanced local-type inflationary trispectrum from a non-vacuum initial state

We compute the primordial trispectrum for curvature perturbations produced during cosmic inflation in models with standard kinetic terms, when the initial quantum state is not necessarily the vacuum state. The presence of initial perturbations enhances the trispectrum amplitude for configuration in which one of the momenta, say $k_3$, is much smaller than the others, $k_3 \ll k_{1,2,4}$. For those squeezed configurations the trispectrum acquires the so-called local form, with a scale dependent amplitude that can get values of order $\epsilon ({k_1}/{k_3})^2$. This amplitude can be larger than the prediction of the so-called Maldacena consistency relation by a factor $10^6$, and can reach the sensitivity of forthcoming observations, even for single-field inflationary models.Comment: 11 pages, 1 figure. References added, typos corrected, minor change

Behavioral modeling of SAR ADCs in Simulink

This paper presents a toolbox for the behavioral simulation of SAR ADCs in Simulink®. The models include the most limiting circuit effects such as sampled thermal noise, capacitor mismatch, finite settling, comparator noise and offset. A user friendly interface is also included to allow study and high-level design of SAR ADCs, which is illustrated by means of a design example. It is also shown that the proposed toolbox is several orders of magnitude faster than electrical simulators, while keeping a high accuracy

A 2-MS/s, 11.22 ENOB, extended input range SAR ADC with improved DNL and offset calculation

A 12-bit successive approximation register analog-to-digital converter (ADC) with extended input range is presented. Employing an input sampling scaling technique, the presented ADC can digitize the signals with an input range of 3.2 V pp-d (±1.33 V REF ). The circuit also includes a comparator offset compensation technique that results in a residual offset of less than 0.5 LSB. The chip has been designed and implemented in a 0.13-μm CMOS process and demonstrates the state-of-the-art performance, featuring an SNDR of 69.3 dB and the SFDR of 79 dB without requiring any calibration. Total power consumption of the ADC is 0.9 mW, with a measured differential non-linearity of 1.2/-1.0 LSB and INL of 2.3/-2.2 LSB

Tracing chemical evolution over the extent of the Milky Way's Disk with APOGEE Red Clump Stars

We employ the first two years of data from the near-infrared, high-resolution SDSS-III/APOGEE spectroscopic survey to investigate the distribution of metallicity and alpha-element abundances of stars over a large part of the Milky Way disk. Using a sample of ~10,000 kinematically-unbiased red-clump stars with ~5% distance accuracy as tracers, the [alpha/Fe] vs. [Fe/H] distribution of this sample exhibits a bimodality in [alpha/Fe] at intermediate metallicities, -0.9<[Fe/H]<-0.2, but at higher metallicities ([Fe/H]=+0.2) the two sequences smoothly merge. We investigate the effects of the APOGEE selection function and volume filling fraction and find that these have little qualitative impact on the alpha-element abundance patterns. The described abundance pattern is found throughout the range 5<R<11 kpc and 0<|Z|<2 kpc across the Galaxy. The [alpha/Fe] trend of the high-alpha sequence is surprisingly constant throughout the Galaxy, with little variation from region to region (~10%). Using simple galactic chemical evolution models we derive an average star formation efficiency (SFE) in the high-alpha sequence of ~4.5E-10 1/yr, which is quite close to the nearly-constant value found in molecular-gas-dominated regions of nearby spirals. This result suggests that the early evolution of the Milky Way disk was characterized by stars that shared a similar star formation history and were formed in a well-mixed, turbulent, and molecular-dominated ISM with a gas consumption timescale (1/SFE) of ~2 Gyr. Finally, while the two alpha-element sequences in the inner Galaxy can be explained by a single chemical evolutionary track this cannot hold in the outer Galaxy, requiring instead a mix of two or more populations with distinct enrichment histories.Comment: 18 pages, 17 figures. Accepted for publication in Ap

Metabolomic profiling of a modified alcohol liquid diet model for liver injury in the mouse uncovers new markers of disease

Metabolomic evaluation of urine and liver was conducted to assess the biochemical changes that occur as a result of alcohol-induced liver injury. Male C57BL/6J mice were fed an isocaloric control-or alcohol-containing liquid diet with 35% of calories from corn oil, 18% protein and 47% carbohydrate/alcohol for up to 36 days ad libitum. Alcohol treatment was initiated at 7 g/kg/day and gradually reached a final dose of 21 g/kg/day. Urine samples were collected at 22, 30 and 36 days and in additional treatment groups, liver and serum samples were harvested at 28 days. Steatohepatitis was induced in the alcohol-fed group since a 5-fold increase in serum alanine aminotransferase activity, a 6-fold increase in liver injury score (necrosis, inflammation and steatosis) and an increase in lipid peroxidation in liver were observed. Liver and urine samples were analyzed by nuclear magnetic resonance spectroscopy and electrospray infusion/Fourier transform ion cyclotron resonance-mass spectrometry. In livers of alcohol-treated mice the following changes were noted. Hypoxia and glycolysis were activated as evidenced by elevated levels of alanine and lactate. Tyrosine, which is required for L-DOPA and dopamine as well as thyroid hormones, was elevated possibly reflecting alterations of basal metabolism by alcohol. A 4-fold increase in the prostacyclin inhibitor 7,10,13,16-docosatetraenoic acid, a molecule important for regulation of platelet formation and blood clotting, may explain why chronic drinking causes serious bleeding problems. Metabolomic analysis of the urine revealed that alcohol treatment leads to decreased excretion of taurine, a metabolite of glutathione, and an increase in lactate, n-acetylglutamine and n-acetylglycine. Changes in the latter two metabolites suggest an inhibition of the kidney enzyme aminoacylase I and may be useful as markers for alcohol consumption

Advanced solid state nano-electrochemical sensors and system for agri 4.0 applications

Global food production needs to increase in order to meet the demands of an ever growing global population. As resources are finite, the most feasible way to meet this demand is to minimize losses and improve efficiency. Regular monitoring of factors like animal health, soil and water quality for example, can ensure that the resources are being used to their maximum efficiency. Existing monitoring techniques however have limitations, such as portability, turnaround time and requirement for additional reagents. In this work, we explore the use of micro- and nano-scale electrode devices, for the development of an electrochemical sensing platform to digitalize a wide range of applications within the agri-food sector. With this platform, we demonstrate the direct electrochemical detection of pesticides, specifically clothianidin and imidacloprid, with detection limits of 0.22 ng/mL and 2.14 ng/mL respectively, and nitrates with a detection limit of 0.2 µM. In addition, interdigitated electrode structures also enable an in-situ pH control technique to mitigate pH as an interference and modify analyte response. This technique is applied to the analysis of monochloramine, a common water disinfectant. Concerning biosensing, the sensors are modified with bio-molecular probes for the detection of both bovine viral diarrhea virus species and antibodies, over a range of 1 ng/mL to 10 µg/mL. Finally, a portable analogue front end electronic reader is developed to allow portable sensing, with control and readout undertaken using a smart phone application. Finally, the sensor chip platform is integrated with these electronics to provide a fully functional end-to-end smart sensor system compatible with emerging Agri-Food digital decision support tools