The effect of dietary nitrogen on nitrogen partitioning and milk production in grazing dairy cows : A thesis presented in partial fulfilment of the requirements for the Master of Animal Science at Massey University Palmerston North, New Zealand

Two experiments were conducted during spring (8th October to 12th November 2009) as part of a larger study, to study the effects of increasing levels of crude protein (CP) in pasture on milk production, dry matter intake (DMI) and nitrogen (N) partitioning in dairy cows. The first experiment was undertaken over 25 days (8th October to 1st November 2009), where fifteen multiparous, rumen fistulated, early lactation Holstein-Friesian cows (505 ± 10.4 kg liveweight; 4.1 body condition score ± 0.044, mean ± standard deviation) were assigned to one of three urea supplementation treatments: Control (0 g/day urea; ~20% CP), Medium (350 g/day urea; ~25% CP) and High (690 g/day urea: ~30% CP). Urea was supplemented to the pasture-based diet to increase CP content while maintaining similar concentrations of all other nutrients across treatments. All cows were offered ~20 kg dry matter (DM)/day perennial ryegrass-based pasture (CP = 20.6 ± 0.56% DM; metabolisable energy (ME) = 11.8 ± 0.06 MJ/kg DM). Cows were acclimated to their urea treatment over a 25 day experimental period. The objective of this study was to determine the effect of increased dietary CP in grazing cows on DMI and milk yield. Dry matter intake was estimated using a back calculation method from the energy requirements of the cows. The results indicate a complex interaction between DMI, milk yield and urea intake. As dietary CP increased, the milk yield increased; however, as urea’s contribution to total dietary CP concentration increased, the increase in both DMI and milk yield was less. Milk yield decreased when urea supplementation increased beyond 350 g/day, and the interaction evident in milk yield was mirrored in yields of fat, CP and lactose (P <0.001). The addition of urea had no effect on milk fat, protein and lactose percentages. The second experiment was conducted over 22 days (22nd October to 12th November 2009), involving ten multiparous, rumen fistulated, early lactation Holstein-Friesian cows (520 ± 5.6 kg liveweight; 4.15 body condition score ± 0.078, mean ± standard deviation). This experiment was undertaken to study N partitioning in pasture-fed grazing dairy cows using urea supplementation as a non-protein N (NPN) model to ensure all other nutritional characteristics of the forage remained the same. All cows were offered ~19 kg DM/day of perennial ryegrass-based pasture (CP = 18.4 ± 0.64% DM; ME = 11.4 ± 0.06 MJ/kg DM). Cows were assigned to one of two experimental groups: Control (0 g/day urea; ~18% CP), and a Urea supplemented group (350 g/day urea; ~23% CP). Cows were acclimated to the diets and metabolism stalls for 14 days, and a further 7 days were used for total collection of urine, faeces and milk. Increasing dietary CP content had no effect on DMI, milk yield, milk composition, and faecal N. Urinary urea N (UUN) and urine N yield and concentrations increased as dietary CP content increased however, urinary creatinine, ammonia (NH3), calcium and magnesium were not affected. Rumen urea and NH3 concentrations were increased as CP content increased. Milk urea N showed trends for linear responses to increasing N intake (P <0.001, R2 = 0.47). A 16.5% increase in N intake resulted in a 42.5% increase in milk urea nitrogen (MUN) concentration; however, the relationship was restricted to low MUN concentrations. Urinary N increased linearly as a result of N intake, although the relationship was restricted due to the underestimation of urinary N and the limited range of N intake values. The 28% increase in urinary N excretion resulted from a sharp 3.6% decline in N efficiency as dietary N content increased. The main conclusions of this thesis were the ability for excessive urea intake to reduce milk yield in grazing dairy cows. Further research is needed to determine if high soluble NPN concentrations in fresh pasture would affect DMI and milk yield in the same way. Increasing N intake results in linear increases in MUN, urinary N and UUN. These relationships could provide useful tools to predict urinary N excretion due to the strong relationships between these variables. Further research is needed to develop robust prediction equations for the relationships between these variables in grazing dairy cows before they could be used as regulatory tools

The preservation, storage, and handling of black-and-white photographic records

The subject of this article is the preservation of processed blackand- white photographic records in libraries. Since silver gelatin photographic films and papers have been around for about a century, and since by far the largest number of black-and-white photographic images are silver gelatin images, knowledge of the properties of these records is extensive. Factors that may affect their stability are, for the most part, well known.published or submitted for publicatio

Asymptotic data analysis on manifolds

Given an m-dimensional compact submanifold $\mathbf{M}$ of Euclidean space $\mathbf{R}^s$, the concept of mean location of a distribution, related to mean or expected vector, is generalized to more general $\mathbf{R}^s$-valued functionals including median location, which is derived from the spatial median. The asymptotic statistical inference for general functionals of distributions on such submanifolds is elaborated. Convergence properties are studied in relation to the behavior of the underlying distributions with respect to the cutlocus. An application is given in the context of independent, but not identically distributed, samples, in particular, to a multisample setup.Comment: Published at http://dx.doi.org/10.1214/009053606000000993 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Deep Learning Applied to the Asteroseismic Modeling of Stars with Coherent Oscillation Modes

We develop a novel method based on machine learning principles to achieve optimal initiation of CPU-intensive computations for forward asteroseismic modeling in a multi-D parameter space. A deep neural network is trained on a precomputed asteroseismology grid containing about 62 million coherent oscillation-mode frequencies derived from stellar evolution models. These models are representative of the core-hydrogen burning stage of intermediate-mass and high-mass stars. The evolution models constitute a 6D parameter space and their predicted low-degree pressure- and gravity-mode oscillations are scanned, using a genetic algorithm. A software pipeline is created to find the best fitting stellar parameters for a given set of observed oscillation frequencies. The proposed method finds the optimal regions in the 6D parameters space in less than a minute, hence providing the optimal starting point for further and more detailed forward asteroseismic modeling in a high-dimensional context. We test and apply the method to seven pulsating stars that were previously modeled asteroseismically by classical grid-based forward modeling based on a $\chi^2$ statistic and obtain good agreement with past results. Our deep learning methodology opens up the application of asteroseismic modeling in +6D parameter space for thousands of stars pulsating in coherent modes with long lifetimes observed by the $Kepler$ space telescope and to be discovered with the TESS and PLATO space missions, while applications so far were done star-by-star for only a handful of cases. Our method is open source and can be used by anyone freely.Comment: Accepted for publication in PASP Speciale Volume on Machine Learnin

Regular maps of high density

A regular map is a surface together with an embedded graph, having properties similar to those of the surface and graph of a platonic solid. We analyze regular maps with reflection symmetry and a graph of density strictly exceeding 1/2, and we conclude that all regular maps of this type belong to a family of maps naturally defined on the Fermat curves x^n+y^n+z^n=0, excepting the one corresponding to the tetrahedron.Comment: 13 pages, 4 figure

SSHCure: a flow-based SSH intrusion detection system

SSH attacks are a main area of concern for network managers, due to the danger associated with a successful compromise. Detecting these attacks, and possibly compromised victims, is therefore a crucial activity. Most existing network intrusion detection systems designed for this purpose rely on the inspection of individual packets and, hence, do not scale to today's high-speed networks. To overcome this issue, this paper proposes SSHCure, a flow-based intrusion detection system for SSH attacks. It employs an efficient algorithm for the real-time detection of ongoing attacks and allows identification of compromised attack targets. A prototype implementation of the algorithm, including a graphical user interface, is implemented as a plugin for the popular NfSen monitoring tool. Finally, the detection performance of the system is validated with empirical traffic data

Half-Saturation Constants in Functional Responses

Our aim is to provide an overview of half-saturation constants reported in literature and to explore their consistency with body size. In many ecological models, intake of nutrients by plants and consumption of food by animals is considered to be a hyperbolic function of the nutrient concentration and the food density, respectively. However, data on the concentration (or density) at which half of the maximum intake rate is reached are scarce, limiting the applicability of the computational models. The meta-analysis was conducted on literature published worldwide. Most studies focused on algae and invertebrates, whereas some included fish, birds and mammals. The half-saturation constants obtained were linked to body size using ordinary regression analysis. The observed trends were compared to those noted in reviews on other density parameters. Half-saturation constants for different clades range within one or two orders of magnitude. Although these constants are inherently variable, exploring allometric relationships across different taxa helps to improve consistent parameterization of ecological models.Comment: 6 pages, 4 figures, 1 tabl

Disruption of the developmental programme of Trypanosoma brucei by genetic ablation of TbZFP1, a differentiation-enriched CCCH protein

The regulation of differentiation is particularly important in microbial eukaryotes that inhabit multiple environments. The parasite Trypanosoma brucei is an extreme example of this, requiring exquisite gene regulation during transmission from mammals to the tsetse fly vector. Unusually, trypanosomes rely almost exclusively on post-transcriptional mechanisms for regulated gene expression. Hence, RNA binding proteins are potentially of great significance in controlling stage-regulated processes. We have previously identified TbZFP1 as a trypanosome molecule transiently enriched during differentiation to tsetse midgut procyclic forms. This small protein (101 amino acids) contains the unusual CCCH zinc finger, an RNA binding motif. Here, we show that genetic ablation of TbZFP1 compromises repositioning of the mitochondrial genome, a specific event in the strictly regulated differentiation programme. Despite this, other events that occur both before and after this remain intact. Significantly, this phenotype correlates with the TbZFP1 expression profile during differentiation. This is the first genetic disruption of a developmental regulator in T. brucei. It demonstrates that programmed events in parasite development can be uncoupled at the molecular level. It also further supports the importance of CCCH proteins in key aspects of trypanosome cell function

Checking-in on Network Functions

When programming network functions, changes within a packet tend to have consequences---side effects which must be accounted for by network programmers or administrators via arbitrary logic and an innate understanding of dependencies. Examples of this include updating checksums when a packet's contents has been modified or adjusting a payload length field of a IPv6 header if another header is added or updated within a packet. While static-typing captures interface specifications and how packet contents should behave, it does not enforce precise invariants around runtime dependencies like the examples above. Instead, during the design phase of network functions, programmers should be given an easier way to specify checks up front, all without having to account for and keep track of these consequences at each and every step during the development cycle. In keeping with this view, we present a unique approach for adding and generating both static checks and dynamic contracts for specifying and checking packet processing operations. We develop our technique within an existing framework called NetBricks and demonstrate how our approach simplifies and checks common dependent packet and header processing logic that other systems take for granted, all without adding much overhead during development.Comment: ANRW 2019 ~ https://irtf.org/anrw/2019/program.htm