Effect of choline or betaine supplementation on broilers exposed to different temperature treatments

In this study, we looked at the effects of supplemental choline or betaine on broiler performance under different temperature conditions. In total there were eighty pens containing ten birds each for a total of 800 Cobb MX™ X Cobb 500™ (Cobb-Vantress, Incorporated, Siloam Springs, AR, USA). Each pen was randomly assigned to one of five dietary treatments in this study: Treatment 1, basal diet, Treatment 2, basal diet plus 500 methyl equivalents added choline, Treatment 3, basal diet plus 1000 methyl equivalents added choline, Treatment 4, basal diet plus 500 methyl equivalents added betaine, and Treatment 5 basal diet plus 1000 methyl equivalents added betaine. The pens were divided equally into two rooms. One room was assigned a treatment classified as thermoneutral (TN) while the second room was designated as high temperature (HT). Dietary treatments did not significantly impact performance (p\u3e0.05), but temperature treatments did have a negative effect on feed intake and feed to gain conversion during days 21 through 42 (p \u3c 0.05). The lack of effect found during this study may have been due to variance in the anticipated feed composition and the actual feed composition. The feed fed during this study contained more methionine, an amino acid known to minimize supplemental choline effects, than what was anticipated. This study showed that high temperatures have a negative impact on performance, and since our dietary treatments were high in methionine, it is still not known whether choline or betaine supplementation, above recommended amounts, to a broiler ration is beneficial or not

Osteoporotic and Neoplastic Compression Fracture Classification on Longitudinal CT

Classification of vertebral compression fractures (VCF) having osteoporotic or neoplastic origin is fundamental to the planning of treatment. We developed a fracture classification system by acquiring quantitative morphologic and bone density determinants of fracture progression through the use of automated measurements from longitudinal studies. A total of 250 CT studies were acquired for the task, each having previously identified VCFs with osteoporosis or neoplasm. Thirty-six features or each identified VCF were computed and classified using a committee of support vector machines. Ten-fold cross validation on 695 identified fractured vertebrae showed classification accuracies of 0.812, 0.665, and 0.820 for the measured, longitudinal, and combined feature sets respectively.Comment: Contributed 4-Page Paper to be presented at the 2016 IEEE International Symposium on Biomedical Imaging (ISBI), April 13-16, 2016, Prague, Czech Republi

Mktg

A new approach to learning the principles of marketing, MKTG is the Asia–Pacific edition of a proven, innovative solution to enhance the students' learning experience. Concise, yet complete, coverage supported by a suite of online learning aids equips students with the tools required to successfully undertake an introductory marketing course. Paving a new way to both teaching and learning, MKTG is designed to truly connect with today's busy tech-savy student. Students have access to online interactive quizzing, videos, podcasts, flashcards, marketing plans, games and more. An accessible, easy-to-read text along with tear out review cards complete a package which helps students to learn important concepts faster

Assembly Time Estimation: Assembly Mate Based Structural Complexity Metric Predictive Modeling

This paper presents an automated tool for estimating assembly times of products based on a three step process: connectivity graph generation from assembly mate information, structural complexity metric analysis of the graph, and application of the complexity metric vector to predictive artificial neural network models. The tool has been evaluated against different training set cases, suggesting that partially defined assembly models and training product variety are critical characteristics. Moreover, the tool is shown to be robust and insensitive to different modeling engineers. The tool has been implemented in a commercial CAD system and shown to yield results of within ±25% of predicted values. Additional extensions and experiments are recommended to improve the tool

Deep convolutional networks for automated detection of posterior-element fractures on spine CT

Injuries of the spine, and its posterior elements in particular, are a common occurrence in trauma patients, with potentially devastating consequences. Computer-aided detection (CADe) could assist in the detection and classification of spine fractures. Furthermore, CAD could help assess the stability and chronicity of fractures, as well as facilitate research into optimization of treatment paradigms. In this work, we apply deep convolutional networks (ConvNets) for the automated detection of posterior element fractures of the spine. First, the vertebra bodies of the spine with its posterior elements are segmented in spine CT using multi-atlas label fusion. Then, edge maps of the posterior elements are computed. These edge maps serve as candidate regions for predicting a set of probabilities for fractures along the image edges using ConvNets in a 2.5D fashion (three orthogonal patches in axial, coronal and sagittal planes). We explore three different methods for training the ConvNet using 2.5D patches along the edge maps of 'positive', i.e. fractured posterior-elements and 'negative', i.e. non-fractured elements. An experienced radiologist retrospectively marked the location of 55 displaced posterior-element fractures in 18 trauma patients. We randomly split the data into training and testing cases. In testing, we achieve an area-under-the-curve of 0.857. This corresponds to 71% or 81% sensitivities at 5 or 10 false-positives per patient, respectively. Analysis of our set of trauma patients demonstrates the feasibility of detecting posterior-element fractures in spine CT images using computer vision techniques such as deep convolutional networks.Comment: To be presented at SPIE Medical Imaging, 2016, San Dieg

Investigation and comparison of multi-state and two-state atom laser output-couplers

We investigate the spatial structure and temporal dynamics created in a Bose-Einstein condensate (BEC) by radio-frequency (RF) atom laser output-couplers using a one-dimensional mean-field model. We compare the behavior of a `pure' two-state atom laser to the multi-level systems demonstrated in laboratories. In particular, we investigate the peak homogeneous output flux, classical fluctuations in the beam and the onset of a bound state which shuts down the atom laser output.Comment: 9 pages, 8 figure

Public-private Partnerships for Government Financing, Controlling Risk, and Value-for--money: The UK Experience

Sponsored Report (for Acquisition Research Program)One of the key requirements to a successful Public-private Partnership (PPP) is the transfer of risk from the government to the private sector. This research examines the PPP experience in the United Kingdom (UK) Ministry of Defense to determine if they would be applicable to the US Department of Defense (DoD). PPP agreements have provided the UK increased capabilities. Also, this research provides an in-depth analysis of Private Financed Initiatives (PFI) that Serco Inc. has undertaken. Finally, this research evaluates the increases in value-for-money resulting from the PPP transfer of risk to the private sector. The research concludes that PPPs should be continued and expanded to provide increased real-time capability to the DoD while supporting private industry. Since the government has the lowest cost of borrowing, PPPs agreements may not appear to be cost effective as a means of procurement. However, the benefits from transferring risk to the private sector can more than offset the higher financing cost. PPPs reallocate risk and up-front capital requirements allowing the government to spread program cost over time. Without initial capital outlays, the government can acquire higher priority goods and services with its limited resources. In addition, PPPs provide the government with an increased infrastructure and technological capability than would otherwise not be available.Naval Postgraduate School Acquisition Research ProgramApproved for public release; distribution is unlimited

Using public-private partnerships and energy savings contracts to fund DoD mobile assets

The Department of Defense (DoD) has engaged in numerous Public-Private Partnership (PPP) ventures such as outsourcing of services and privatization of military housing. In the past, the activities considered for PPPs have been primarily administrative and support functions. This research explores the possibility of expanding the use of PPPs to enhance the DoD combat and combat-support functions. First, to better understand how PPPs function (the partnership relationships and financing arrangements), we examine Hannon Armstrong's fee for service contract solution to the lack of appropriated funds for establishing a vital fiber-optic link near the Arctic Circle. Next, we explore the history of Energy Savings Performance Contracts (ESPCs) and their potential application to re-engining the Air Force's B-52H through PPPs. Historically, this program has only been used for fixed assets, not mobile assets like engines. There is little debate over the success of ESPC contracts in reducing energy consumption, but their use in DoD mobile assets is new. Finally, we conclude that applying ESPCs to mobile assets has the potential to reduce energy consumption, save millions of dollars and increase combat efficiency.Approved for public release; distribution is unlimited