Effect of Urea and Distillers Inclusion in Dry- Rolled Corn Based Diets on Heifer Performance and Carcass Characteristics

Crossbred heifers (n=96, BW = 810 ± 20) were utilized to evaluate the effects of increasing wet distillers grains plus solubles and urea inclusion in a dry rolled corn based finishing diet on performance and carcass characteristics. Heifers were individually fed using a calan gate system with a 2 × 2 factorial arrangement of treatments. Factors included distillers inclusion at either 10 or 20% of diet DM and urea inclusion at either 0.2 or 1.4% of diet DM. Th ere was no difference for final body weight, average daily gain, and feed conversion on a live or carcass adjusted basis for either urea or distillers inclusion in the diet. Dry matter intake was reduced with increased urea inclusion; however, distillers inclusion did not influence intake. Added distillers and urea in the diet had minimal impact on performance suggesting supplemental urea in a dry rolled corn based finishing diets is of minimal benefit when feeding at least 10% distillers grains

Multi-modal fusion methods for robust emotion recognition using body-worn physiological sensors in mobile environments

High-accuracy physiological emotion recognition typically requires participants to wear or attach obtrusive sensors (e.g., Electroencephalograph). To achieve precise emotion recognition using only wearable body-worn physiological sensors, my doctoral work focuses on researching and developing a robust sensor fusion system among different physiological sensors. Developing such fusion system has three problems: 1) how to pre-process signals with different temporal characteristics and noise models, 2) how to train the fusion system with limited labeled data and 3) how to fuse multiple signals with inaccurate and inexact ground truth. To overcome these challenges, I plan to explore semi-supervised, weakly supervised and unsupervised machine learning methods to obtain precise emotion recognition in mobile environments. By developing such techniques, we can measure the user engagement with larger amounts of participants and apply the emotion recognition techniques in a variety of scenarios such as mobile video watching and online education

Effect of Urea and Distillers Inclusion in Dry- Rolled Corn Based Diets on Heifer Performance and Carcass Characteristics

Crossbred heifers (n=96, BW = 810 ± 20) were utilized to evaluate the effects of increasing wet distillers grains plus solubles and urea inclusion in a dry rolled corn based finishing diet on performance and carcass characteristics. Heifers were individually fed using a calan gate system with a 2 × 2 factorial arrangement of treatments. Factors included distillers inclusion at either 10 or 20% of diet DM and urea inclusion at either 0.2 or 1.4% of diet DM. Th ere was no difference for final body weight, average daily gain, and feed conversion on a live or carcass adjusted basis for either urea or distillers inclusion in the diet. Dry matter intake was reduced with increased urea inclusion; however, distillers inclusion did not influence intake. Added distillers and urea in the diet had minimal impact on performance suggesting supplemental urea in a dry rolled corn based finishing diets is of minimal benefit when feeding at least 10% distillers grains

One-shot Empirical Privacy Estimation for Federated Learning

Privacy estimation techniques for differentially private (DP) algorithms are useful for comparing against analytical bounds, or to empirically measure privacy loss in settings where known analytical bounds are not tight. However, existing privacy auditing techniques usually make strong assumptions on the adversary (e.g., knowledge of intermediate model iterates or the training data distribution), are tailored to specific tasks and model architectures, and require retraining the model many times (typically on the order of thousands). These shortcomings make deploying such techniques at scale difficult in practice, especially in federated settings where model training can take days or weeks. In this work, we present a novel "one-shot" approach that can systematically address these challenges, allowing efficient auditing or estimation of the privacy loss of a model during the same, single training run used to fit model parameters, and without requiring any a priori knowledge about the model architecture or task. We show that our method provides provably correct estimates for privacy loss under the Gaussian mechanism, and we demonstrate its performance on a well-established FL benchmark dataset under several adversarial models

Temporal Cross-Media Retrieval with Soft-Smoothing

Multimedia information have strong temporal correlations that shape the way modalities co-occur over time. In this paper we study the dynamic nature of multimedia and social-media information, where the temporal dimension emerges as a strong source of evidence for learning the temporal correlations across visual and textual modalities. So far, cross-media retrieval models, explored the correlations between different modalities (e.g. text and image) to learn a common subspace, in which semantically similar instances lie in the same neighbourhood. Building on such knowledge, we propose a novel temporal cross-media neural architecture, that departs from standard cross-media methods, by explicitly accounting for the temporal dimension through temporal subspace learning. The model is softly-constrained with temporal and inter-modality constraints that guide the new subspace learning task by favouring temporal correlations between semantically similar and temporally close instances. Experiments on three distinct datasets show that accounting for time turns out to be important for cross-media retrieval. Namely, the proposed method outperforms a set of baselines on the task of temporal cross-media retrieval, demonstrating its effectiveness for performing temporal subspace learning.Comment: To appear in ACM MM 201

Unleashing the Power of Randomization in Auditing Differentially Private ML

We present a rigorous methodology for auditing differentially private machine learning algorithms by adding multiple carefully designed examples called canaries. We take a first principles approach based on three key components. First, we introduce Lifted Differential Privacy (LiDP) that expands the definition of differential privacy to handle randomized datasets. This gives us the freedom to design randomized canaries. Second, we audit LiDP by trying to distinguish between the model trained with $K$ canaries versus $K - 1$ canaries in the dataset, leaving one canary out. By drawing the canaries i.i.d., LiDP can leverage the symmetry in the design and reuse each privately trained model to run multiple statistical tests, one for each canary. Third, we introduce novel confidence intervals that take advantage of the multiple test statistics by adapting to the empirical higher-order correlations. Together, this new recipe demonstrates significant improvements in sample complexity, both theoretically and empirically, using synthetic and real data. Further, recent advances in designing stronger canaries can be readily incorporated into the new framework

A Basin Redox Transect at the Dawn of Animal Life

Multiple eukaryotic clades make their first appearance in the fossil record between ~810 and 715 Ma. Molecular clock studies suggest that the origin of animal multicellularity may have been part of this broader eukaryotic radiation. Animals require oxygen to fuel their metabolism, and low oxygen levels have been hypothesized to account for the temporal lag between metazoan origins and the Cambrian radiation of large, ecologically diverse animals. Here, paleoredox conditions were investigated in the Fifteenmile Group, Ogilvie Mountains, Yukon, Canada, which hosts an 811 Ma ash horizon and spans the temporal window that captures the inferred origin and early evolution of animals. Iron-based redox proxies, redox-sensitive trace elements, organic carbon percentages and pyrite sulfur isotopes were analyzed in seven stratigraphic sections along two parallel basin transects. These data suggest that for this basin, oxygenated shelf waters overlay generally anoxic deeper waters. The anoxic water column was dominantly ferruginous, but brief periods of euxinia likely occurred. These oscillations coincide with changes in total organic carbon, suggesting euxinia was primarily driven by increased organic carbon loading. Overall, these data are consistent with proposed quantitative constraints on Proterozoic atmospheric oxygen being greater than 1% of modern levels, but less than present levels. Comparing these oxygen levels against the likely oxygen requirements of the earliest animals, both theoretical considerations and the ecology of modern oxygen-deficient settings suggest that the inferred oxygen levels in the mixed layer would not have been prohibitive to the presence of sponges, eumetazoans or bilaterians. Thus the evolution of the earliest animals was probably not limited by the low absolute oxygen levels that may have characterized Neoproterozoic oceans, although these inferred levels would constrain animals to very small sizes and low metabolic rates.Earth and Planetary SciencesOrganismic and Evolutionary Biolog

Course of FEV1 after Onset of Bronchiolitis Obliterans Syndrome in Lung Transplant Recipients

Rationale: Bronchiolitis obliterans syndrome (BOS), defined by loss of lung function, develops in the majority of lung transplant recipients. However, there is a paucity of information on the subsequent course of lung function in these patients. Objectives: To characterize the course of FEV1 over time after development of BOS and to determine the predictors that influence the rate of functional decline of FEV1. Methods: FEV1% predicted (FEV1%pred) trajectories were studied in 111 lung transplant recipients with BOS by multivariate, linear, mixed-effects statistical models. Measurements and Main Results: FEV1%pred varied over time after BOS onset, with the steepest decline typically seen in the first 6 months (12% decline; p < 0.0001). Bilateral lung transplant recipients had significantly higher FEV1%pred at BOS diagnosis (71 vs. 47%; p < 0.0001) and at 24 months after BOS onset (58 vs. 41%; p = 0.0001). Female gender and pretransplant diagnosis of idiopathic pulmonary fibrosis were associated with a steeper decline in FEV1%pred in the first 6 months after BOS diagnosis (p = 0.02 and 0.04, respectively). A fall in FEV1 greater than 20% in the 6 months preceding BOS (termed “rapid onset”) was associated with shorter time to BOS onset (p = 0.01), lower FEV1%pred at BOS onset (p < 0.0001), steeper decline in the first 6 months (p = 0.03), and lower FEV1%pred at 2 years after onset (p = 0.0002). Conclusions: Rapid onset of BOS, female gender, pretransplant diagnosis of idiopathic pulmonary fibrosis, and single-lung transplantation are associated with worse pulmonary function after BOS onset.Supported in part by National Institutes of Health grants K23 HL077719 (V.N.L.) and K24 HL04212 (F.J.M.), and by a grant from the American Society of Transplantation/ Chest Foundation (V.N.L.).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91969/1/2007 AJRCCM Course of FEV1 after Onset of Bronchiolitis Obliterans Syndrome in Lung Transplant Recipients.pd