Machine Learning at Microsoft with ML .NET

Machine Learning is transitioning from an art and science into a technology available to every developer. In the near future, every application on every platform will incorporate trained models to encode data-based decisions that would be impossible for developers to author. This presents a significant engineering challenge, since currently data science and modeling are largely decoupled from standard software development processes. This separation makes incorporating machine learning capabilities inside applications unnecessarily costly and difficult, and furthermore discourage developers from embracing ML in first place. In this paper we present ML .NET, a framework developed at Microsoft over the last decade in response to the challenge of making it easy to ship machine learning models in large software applications. We present its architecture, and illuminate the application demands that shaped it. Specifically, we introduce DataView, the core data abstraction of ML .NET which allows it to capture full predictive pipelines efficiently and consistently across training and inference lifecycles. We close the paper with a surprisingly favorable performance study of ML .NET compared to more recent entrants, and a discussion of some lessons learned

Mechanical properties of ceria nanorods and nanochains; The effect of dislocations, grain-boundaries and oriented attachment

We predict that the presence of extended defects can reduce the mechanical strength of a ceria nanorod by 70%. Conversely, the pristine material can deform near its theoretical strength limit. Specifically, atomistic models of ceria nanorods have been generated with full microstructure, including: growth direction, morphology, surface roughening (steps, edges, corners), point defects, dislocations and grain-boundaries. The models were then used to calculate the mechanical strength as a function of microstructure. Our simulations reveal that the compressive yield strengths of ceria nanorods, ca. 10 nm in diameter and without extended defects, are 46 and 36 GPa for rods oriented along [211] and [110] respectively, which represents almost 10% of the bulk elastic modulus and are associated with yield strains of about 0.09. Tensile yield strengths were calculated to be about 50% lower with associated yield strains of about 0.06. For both nanorods, plastic deformation was found to proceed via slip in the {001} plane with direction ã??110ã?? - a primary slip system for crystals with the fluorite structure. Dislocation evolution for the nanorod oriented along [110] was nucleated via a cerium vacancy present at the surface. A nanorod oriented along [321] and comprising twin-grain boundaries with {111} interfacial planes was calculated to have a yield strength of about 10 GPa (compression and tension) with the grain boundary providing the vehicle for plastic deformation, which slipped in the plane of the grain boundary, with an associated ã??110ã?? slip direction. We also predict, using a combination of atomistic simulation and DFT, that rutile-structured ceria is feasible when the crystal is placed under tension. The mechanical properties of nanochains, comprising individual ceria nanoparticles with oriented attachment and generated using simulated self-assembly, were found to be similar to those of the nanorod with grain-boundary. Images of the atom positions during tension and compression are shown, together with animations, revealing the mechanisms underpinning plastic deformation. For the nanochain, our simulations help further our understanding of how a crystallising ice front can be used to 'sculpt' ceria nanoparticles into nanorods via oriented attachment. © 2011 The Royal Society of Chemistry

Prefrontal cortex output circuits guide reward seeking through divergent cue encoding

The prefrontal cortex is a critical neuroanatomical hub for controlling motivated behaviours across mammalian species. In addition to intra-cortical connectivity, prefrontal projection neurons innervate subcortical structures that contribute to reward-seeking behaviours, such as the ventral striatum and midline thalamus. While connectivity among these structures contributes to appetitive behaviours, how projection-specific prefrontal neurons encode reward-relevant information to guide reward seeking is unknown. Here we use in vivo two-photon calcium imaging to monitor the activity of dorsomedial prefrontal neurons in mice during an appetitive Pavlovian conditioning task. At the population level, these neurons display diverse activity patterns during the presentation of reward-predictive cues. However, recordings from prefrontal neurons with resolved projection targets reveal that individual corticostriatal neurons show response tuning to reward-predictive cues, such that excitatory cue responses are amplified across learning. By contrast, corticothalamic neurons gradually develop new, primarily inhibitory responses to reward-predictive cues across learning. Furthermore, bidirectional optogenetic manipulation of these neurons reveals that stimulation of corticostriatal neurons promotes conditioned reward-seeking behaviour after learning, while activity in corticothalamic neurons suppresses both the acquisition and expression of conditioned reward seeking. These data show how prefrontal circuitry can dynamically control reward-seeking behaviour through the opposing activities of projection-specific cell populations

Olfactory Receptors in Non-Chemosensory Organs: The Nervous System in Health and Disease

Olfactory receptors (ORs) and down-stream functional signaling molecules adenylyl cyclase 3 (AC3), olfactory G protein \u3b1 subunit (G\u3b1olf), OR transporters receptor transporter proteins 1 and 2 (RTP1 and RTP2), receptor expression enhancing protein 1 (REEP1), and UDP-glucuronosyltransferases (UGTs) are expressed in neurons of the human and murine central nervous system (CNS). In vitro studies have shown that these receptors react to external stimuli and therefore are equipped to be functional. However, ORs are not directly related to the detection of odors. Several molecules delivered from the blood, cerebrospinal fluid, neighboring local neurons and glial cells, distant cells through the extracellular space, and the cells' own self-regulating internal homeostasis can be postulated as possible ligands. Moreover, a single neuron outside the olfactory epithelium expresses more than one receptor, and the mechanism of transcriptional regulation may be different in olfactory epithelia and brain neurons. OR gene expression is altered in several neurodegenerative diseases including Parkinson's disease (PD), Alzheimer's disease (AD), progressive supranuclear palsy (PSP) and sporadic Creutzfeldt-Jakob disease (sCJD) subtypes MM1 and VV2 with disease-, region- and subtype-specific patterns. Altered gene expression is also observed in the prefrontal cortex in schizophrenia with a major but not total influence of chlorpromazine treatment. Preliminary parallel observations have also shown the presence of taste receptors (TASRs), mainly of the bitter taste family, in the mammalian brain, whose function is not related to taste. TASRs in brain are also abnormally regulated in neurodegenerative diseases. These seminal observations point to the need for further studies on ORs and TASRs chemoreceptors in the mammalian brain

Logansport Wastewater Treatment Plant

There is no abstract available for this thesis.Thesis (B. Arch.)College of Architecture and Plannin