Effect of calf-starter protein solubility on calf performance

Three starters containing differently processed protein supplements were fed to Holstein heifer calves, using an early weaning program. One starter contained soybean meal. The other starters contained soybean grits processed through an extrusion cooker to reduce the protein solubility to an intermediate (PDI> 50%) or low (PDI < 15 %) level. Calf performance was similar on all three starters

Noblesse Oblige

Commencement address given by James Lewis Morrill, Vice President of the University, to the Winter 1937 graduating class of The Ohio State University, University Hall Chapel, Columbus, Ohio, March 19, 1937

Generalised Interpretable Shapelets for Irregular Time Series

The shapelet transform is a form of feature extraction for time series, in which a time series is described by its similarity to each of a collection of `shapelets'. However it has previously suffered from a number of limitations, such as being limited to regularly-spaced fully-observed time series, and having to choose between efficient training and interpretability. Here, we extend the method to continuous time, and in doing so handle the general case of irregularly-sampled partially-observed multivariate time series. Furthermore, we show that a simple regularisation penalty may be used to train efficiently without sacrificing interpretability. The continuous-time formulation additionally allows for learning the length of each shapelet (previously a discrete object) in a differentiable manner. Finally, we demonstrate that the measure of similarity between time series may be generalised to a learnt pseudometric. We validate our method by demonstrating its performance and interpretability on several datasets; for example we discover (purely from data) that the digits 5 and 6 may be distinguished by the chirality of their bottom loop, and that a kind of spectral gap exists in spoken audio classification

Neural Controlled Differential Equations for Online Prediction Tasks

Neural controlled differential equations (Neural CDEs) are a continuous-time extension of recurrent neural networks (RNNs), achieving state-of-the-art (SOTA) performance at modelling functions of irregular time series. In order to interpret discrete data in continuous time, current implementations rely on non-causal interpolations of the data. This is fine when the whole time series is observed in advance, but means that Neural CDEs are not suitable for use in \textit{online prediction tasks}, where predictions need to be made in real-time: a major use case for recurrent networks. Here, we show how this limitation may be rectified. First, we identify several theoretical conditions that interpolation schemes for Neural CDEs should satisfy, such as boundedness and uniqueness. Second, we use these to motivate the introduction of new schemes that address these conditions, offering in particular measurability (for online prediction), and smoothness (for speed). Third, we empirically benchmark our online Neural CDE model on three continuous monitoring tasks from the MIMIC-IV medical database: we demonstrate improved performance on all tasks against ODE benchmarks, and on two of the three tasks against SOTA non-ODE benchmarks

Regioselective Radical Arene Amination for the Concise Synthesis of <i>ortho</i>-Phenylenediamines.

The formation of arene C-N bonds directly from C-H bonds is of great importance and there has been rapid recent development of methods for achieving this through radical mechanisms, often involving reactive N-centered radicals. A major challenge associated with these advances is that of regiocontrol, with mixtures of regioisomeric products obtained in most protocols, limiting broader utility. We have designed a system that utilizes attractive noncovalent interactions between an anionic substrate and an incoming radical cation in order to guide the latter to the arene ortho position. The anionic substrate takes the form of a sulfamate-protected aniline and telescoped cleavage of the sulfamate group after amination leads directly to ortho-phenylenediamines, key building blocks for a range of medicinally relevant diazoles. Our method can deliver both free amines and monoalkyl amines allowing access to unsymmetrical, selectively monoalkylated benzimidazoles and benzotriazoles. As well as providing concise access to valuable ortho-phenylenediamines, this work demonstrates the potential for utilizing noncovalent interactions to control positional selectivity in radical reactions