Variable typing: Assigning meaning to variables in mathematical text

Information about the meaning of mathematical variables in text is useful in NLP/IR tasks such as symbol disambiguation, topic modeling and mathematical information retrieval (MIR). We introduce variable typing, the task of assigning one mathematical type (multi-word technical terms referring to mathematical concepts) to each variable in a sentence of mathematical text. As part of this work, we also introduce a new annotated data set composed of 33,524 data points extracted from scientific documents published on arXiv. Our intrinsic evaluation demonstrates that our data set is sufficient to successfully train and evaluate current classifiers from three different model architectures. The best performing model is evaluated on an extrinsic task: MIR, by producing a typed formula index. Our results show that the best performing MIR models make use of our typed index, compared to a formula index only containing raw symbols, thereby demonstrating the usefulness of variable typing

Play in the Grade One Classroom: An Exploration of Teacher Beliefs, Classroom Organization, and Obstacles to Implementation in Quebec

A mixed methods investigation into Grade One teachers’ beliefs and practices about play in the classroom was conducted in a French public school board in Quebec. Forty-three teachers completed questionnaires, while a subset of 10 classrooms were photographed, and open-ended interviews were conducted with 7 teachers. Correlation between beliefs, practices, and experience teaching showed that ‘learning through play’ was positively associated with belief in ‘educational toys and manipulation’ (rs = 0.313, p < 0.05), and greater frequency of teacher self reported play activities (r = 0.524, p < 0.01). Teachers who had more experience teaching Grade One, believed less in ‘learning through play’ (r = -0.341, p < 0.05) and reported using fewer play practices in their classes (r = 0.365, p < 0.05). Total years teaching was also negatively correlated with belief in ‘learning through play’ (r = -0.410, p < 0.01). Photographs revealed minimal variation between classrooms, with some elements of play in half of the classrooms. Interviews revealed that teachers found play to be an effective learning strategy, that they primarily used games as play activities in their classrooms, and that school personnel and personal experience supported their use of play, while lack of time, budget and materials limited the amount of play activities implemented

Development and application of rice starch based edible coating to improve the postharvest storage potential and quality of plum fruit (<i>Prunus salicina</i>)

The study investigated the possibility of enhancing the shelf life of plum fruit coated with rice starch-ι-carrageenan (RS-ι-car) composite coating blended with sucrose fatty acid esters (FAEs). Film solution (starch 3%, carrageenan 1.5% and FAEs 2%) was prepared by mixing the ingredients and properties of stand-alone films (physical, mechanical, barrier and surface morphology) were studied before applying the coating on fruit surface. Fruit were stored at 20 °C for 3 weeks and analyzed for weight loss, ethylene production, respiration rate, color change, firmness, and titratable acidity (TA) and soluble solid content (SSC). Surface morphology of stand-alone film and fruit surface (after applying on the plum fruit) was studied using scanning electron microscopy (SEM). Phytochemical analysis was performed during the storage period and total phenolic content (TPC), total antioxidant capacity (TAC), flavonoid content (FC) and free radical scavenging activity were determined. The rice starch composite coating was shown to be effective in reducing both weight loss (WL) and respiration rate and inhibiting the endogenous ethylene production when compared to the uncoated control fruit stored at room temperature (p &lt; 0.05). TPC, TAC, FC and free radical scavenging activity was unaffected in the coated fruit throughout the storage period (p &lt; 0.05). The findings reported in this study indicate that the RS-ι-car-FAEs coating prolongs the shelf life and maintains the overall quality of plum fruit during storage and could potentially be commercialized as a new edible coating for the plum fruit industry

Algebraic-matrix calculation of vibrational levels of triatomic molecules

We introduce an accurate and efficient algebraic technique for the computation of the vibrational spectra of triatomic molecules, of both linear and bent equilibrium geometry. The full three-dimensional potential energy surface (PES), which can be based on entirely {\it ab initio} data, is parameterized as a product Morse-cosine expansion, expressed in bond-angle internal coordinates, and includes explicit interactions among the local modes. We describe the stretching degrees of freedom in the framework of a Morse-type expansion on a suitable algebraic basis, which provides exact analytical expressions for the elements of a sparse Hamiltonian matrix. Likewise, we use a cosine power expansion on a spherical harmonics basis for the bending degree of freedom. The resulting matrix representation in the product space is very sparse and vibrational levels and eigenfunctions can be obtained by efficient diagonalization techniques. We apply this method to carbonyl sulfide OCS, hydrogen cyanide HCN, water H$_2$O, and nitrogen dioxide NO$_2$. When we base our calculations on high-quality PESs tuned to the experimental data, the computed spectra are in very good agreement with the observed band origins.Comment: 11 pages, 2 figures, containg additional supporting information in epaps.ps (results in tables, which are useful but not too important for the paper

Does skeletal muscle have an 'epi'-memory? The role of epigenetics in nutritional programming, metabolic disease, aging and exercise

Skeletal muscle mass, quality and adaptability are fundamental in promoting muscle performance, maintaining metabolic function and supporting longevity and healthspan. Skeletal muscle is programmable and can ‘remember’ early‐life metabolic stimuli affecting its function in adult life. In this review, the authors pose the question as to whether skeletal muscle has an ‘epi’‐memory? Following an initial encounter with an environmental stimulus, we discuss the underlying molecular and epigenetic mechanisms enabling skeletal muscle to adapt, should it re‐encounter the stimulus in later life. We also define skeletal muscle memory and outline the scientific literature contributing to this field. Furthermore, we review the evidence for early‐life nutrient stress and low birth weight in animals and human cohort studies, respectively, and discuss the underlying molecular mechanisms culminating in skeletal muscle dysfunction, metabolic disease and loss of skeletal muscle mass across the lifespan. We also summarize and discuss studies that isolate muscle stem cells from different environmental niches in vivo (physically active, diabetic, cachectic, aged) and how they reportedly remember this environment once isolated in vitro. Finally, we will outline the molecular and epigenetic mechanisms underlying skeletal muscle memory and review the epigenetic regulation of exercise‐induced skeletal muscle adaptation, highlighting exercise interventions as suitable models to investigate skeletal muscle memory in humans. We believe that understanding the ‘epi’‐memory of skeletal muscle will enable the next generation of targeted therapies to promote muscle growth and reduce muscle loss to enable healthy aging

Evaluation of the optical switching characteristics of erbium-doped fibres for the development of a fibre Bragg grating sensor interrogator

A polling topology that employs optical switching based on the properties of erbium-doped fibres (EDFs) is used to interrogate an array of FBGs. The properties of the EDF are investigated in its pumped and un-pumped states and the EDFs’ switching properties are evaluated by comparing them with a high performance electronically controlled MEM optical switch. Potential advantages of the proposed technique are discussed. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only

Design of Microwave Pulse Compressors Using Small Form-Factor Waveguide Cavities

A microwave pulse compressor (MPC) consisting of an iris, a straight waveguide section, and a T-junction can be used in order to convert a long pulse with lower power to a shorter pulse with a higher power. A significant compression gain can be achieved, provided that the system is designed precisely. The duration of the compressed pulse is proportional to the cavity length, thus imposing a constraint on the development of mobile systems. In this work, we present the circuit/transmission-line-based design methodology that we follow in order to fold the cavity (while retaining the same electrical length) by using T-junction turns. For example, we design a 1.3-GHz folded compressor and compare its performance to the corresponding one of a straight-cavity compressor. The 3-D full-wave simulations with CST Studio Suite and experimental measurements with the developed compressor confirm the accuracy of the proposed design methodology

Application of neural networks to synchro-Compton blazar emission models

Jets from supermassive black holes in the centers of active galaxies are the most powerful persistent sources of electromagnetic radiation in the Universe. To infer the physical conditions in the otherwise out-of-reach regions of extragalactic jets we usually rely on fitting of their spectral energy distribution (SED). The calculation of radiative models for the jet non-thermal emission usually relies on numerical solvers of coupled partial differential equations. In this work machine learning is used to tackle the problem of high computational complexity in order to significantly reduce the SED model evaluation time, which is needed for SED fitting with Bayesian inference methods. We compute SEDs based on the synchrotron self-Compton model for blazar emission using the radiation code ATHE${\nu}$A, and use them to train Neural Networks exploring whether these can replace the original computational expensive code. We find that a Neural Network with Gated Recurrent Unit neurons can effectively replace the ATHE${\nu}$A leptonic code for this application, while it can be efficiently coupled with MCMC and nested sampling algorithms for fitting purposes. We demonstrate this through an application to simulated data sets and with an application to observational data. We offer this tool in the community through a public repository. We present a proof-of-concept application of neural networks to blazar science. This is the first step in a list of future applications involving hadronic processes and even larger parameter spaces.Comment: 12 pages, submitted, comments are welcome, code will be soon available at https://github.com/tzavellas/blazar_m

An FPGA-based system for generalised electron devices testing

Electronic systems are becoming more and more ubiquitous as our world digitises. Simultaneously, even basic components are experiencing a wave of improvements with new transistors, memristors, voltage/current references, data converters, etc, being designed every year by hundreds of R &D groups world-wide. To date, the workhorse for testing all these designs has been a suite of lab instruments including oscilloscopes and signal generators, to mention the most popular. However, as components become more complex and pin numbers soar, the need for more parallel and versatile testing tools also becomes more pressing. In this work, we describe and benchmark an FPGA system developed that addresses this need. This general purpose testing system features a 64-channel source-meter unit, and [Formula: see text] banks of 32 digital pins for digital I/O. We demonstrate that this bench-top system can obtain [Formula: see text] current noise floor, [Formula: see text] pulse delivery at [Formula: see text] and [Formula: see text] maximum current drive/channel. We then showcase the instrument's use in performing a selection of three characteristic measurement tasks: (a) current-voltage characterisation of a diode and a transistor, (b) fully parallel read-out of a memristor crossbar array and (c) an integral non-linearity test on a DAC. This work introduces a down-scaled electronics laboratory packaged in a single instrument which provides a shift towards more affordable, reliable, compact and multi-functional instrumentation for emerging electronic technologies