The effects of stall surfaces and milk yield on the lying behavior of dairy cow

The importance of lying behavior to dairy cows and the feasible definition of lying has attracted many studies on the subject. Cattle show both behavioral and physiological stress responses when subjected to thwarting of their lying behavior. If cows are unable to lie down they later compensate for lost lying time when possible. Environmental factors such as housing and bedding systems have been noted to affect the time spent lying, but there is usually large variation in lying time between individuals. Internal factors such as the reproductive stage, age and health of cows affect their lying time and can cause variation. However, the effect of higher milk production on behavior has not previously been illuminated. The objective of this study was to provide data applicable for the improvement of resting conditions of cows. The preference of stall surface material, differences in normal behavior per unit time and various health measures were observed. The aim was to evaluate lying behavior and cow comfort on different stall bedding materials. In addition, the effect of milk yield on behavior was examined in a tie stall experiment. The preferences for surface materials were investigated in 5 experiments using 3 surface materials with bedding manipulations. According to the results, the cows preferred abundant straw bedding and soft rubber mats. However, they showed an aversion to sand bedding. Some individuals even refused to use stalls with sand when no organic bedding material was present. However, this study was unable to determine the reason for the avoidance, as neither the sand particle size nor thermal properties appeared critical. However, previous exposure to particular surface materials increased the preference for them. The amount of straw bedding was found to be an important factor affecting the preferences for stalls, and the lying time in stalls increased when the flooring softness was improved by applying straw or by installing elastic mats. Despite sand being the least preferred flooring material in preference tests, the health of legs improved during exposure to sand-floored stalls. Moreover cows using sand were cleaner than those that used straw stalls. Thus, sand bedding entailed some health benefits despite the contradictory results of preference tests, which more strongly reflected the perceptions of individual animals. Milk yield was observed to affect behavior by reducing the lying time, possibly due to factors other than longer duration of eating. High yielding cows seemed to intensify their lying bouts, as they were observed to lie with the neck muscles relaxed sooner after lying down than lower yielding cows. In conclusion, cows were found to prefer softer stall surface materials and organic bedding material. In addition, the lying time was reduced by a high milk yield, although the lying time seemed to be important for resting. Cows might differ in the needs for their lying environment. The management of dairy cows should eliminate any unnecessary prevention of lying, as even in tie-stalls high yielding cows seem to be affected by time constraints. Adding fresh bedding material to stalls increases the comfort of any stall flooring material.

Improved Conditions For L2-Stability Of Nonstationary Feedback-Systems

Concerning the L2-stability of feedback systems containing a linear time-varying operator, some of the stringent restrictions imposed on the multiplier as well as the linear part of the system, in the criteria presented earlier, are relaxed.

A particle filtering approach for structural system identification in vehicle–structure interaction problems

The problem of identification of parameters of a beam-moving oscillator system based on measurement of time histories of beam strains and displacements is considered. The governing equations of motion here have time varying coefficients. The parameters to be identified are however time invariant and consist of mass, stiffness and damping characteristics of the beam and oscillator subsystems. A strategy based on dynamic state estimation method, that employs particle filtering algorithms, is proposed to tackle the identification problem. The method can take into account measurement noise, guideway unevenness, spatially incomplete measurements, finite element models for supporting structure and moving vehicle, and imperfections in the formulation of the mathematical models. Numerical illustrations based on synthetic data on beam-oscillator system are presented to demonstrate the satisfactory performance of the proposed procedure.

Customer asset management in action: using customers portfolio for allocating resources across business-to-business relationships for improved shareholder value

Suvi Nenonen Customer asset management in action: using customer portfolios for allocating resources across business-to-business relationships for improved shareholder value Customers are crucial assets to all firms as customers are the ultimate source of all cash flows. Regardless this financial importance of customer relationships, for decades there has been a lack of suitable frameworks explaining how customer relationships contribute to the firm financial performance and how this contribution can be actively managed. In order to facilitate a better understanding of the customer asset, contemporary marketing has investigated the use of financial theories and asset management practices in the customer relationship context. Building on this, marketing academics have promoted the customer lifetime value concept as a solution for valuating and managing customer relationships for optimal financial outcomes. However, the empirical investigation of customer asset management lags behind the conceptual development steps taken. Additionally, the practitioners have not embraced the use of customer lifetime value in guiding managerial decisions - especially in the business-to-business context. The thesis points out that there are fundamental differences between customer relationships and investment instruments as investment targets, effectively eliminating the possibility to use financial theories in a customer relationships context or to optimize the customer base as a single investment portfolio. As an alternative, the thesis proposes the use of customer portfolio approach for allocating resources across the customer base for improved shareholder value. In the customer portfolio approach, the customer base of a firm is divided into multiple portfolios based on customer relationships’ potential to contribute to the shareholder value creation. After this, customer management concepts are tailored to each customer portfolio, designed to improve the shareholder value in their own respect. Therefore, effective customer asset management with the customer portfolio approach necessitates that firms are able to manage multiple parallel customer management concepts, or business models, simultaneously. The thesis is one of the first empirical studies on customer asset management, bringing empirical evidence from multiple business-to-business case studies on how customer portfolio models can be formed, how customer portfolios can be managed, and how customer asset management has contributed to the firm financial performance.

Customer asset management in action: using customers portfolio for allocating resources across business-to-business relationships for improved shareholder value

Suvi Nenonen Customer asset management in action: using customer portfolios for allocating resources across business-to-business relationships for improved shareholder value Customers are crucial assets to all firms as customers are the ultimate source of all cash flows. Regardless this financial importance of customer relationships, for decades there has been a lack of suitable frameworks explaining how customer relationships contribute to the firm financial performance and how this contribution can be actively managed. In order to facilitate a better understanding of the customer asset, contemporary marketing has investigated the use of financial theories and asset management practices in the customer relationship context. Building on this, marketing academics have promoted the customer lifetime value concept as a solution for valuating and managing customer relationships for optimal financial outcomes. However, the empirical investigation of customer asset management lags behind the conceptual development steps taken. Additionally, the practitioners have not embraced the use of customer lifetime value in guiding managerial decisions - especially in the business-to-business context. The thesis points out that there are fundamental differences between customer relationships and investment instruments as investment targets, effectively eliminating the possibility to use financial theories in a customer relationships context or to optimize the customer base as a single investment portfolio. As an alternative, the thesis proposes the use of customer portfolio approach for allocating resources across the customer base for improved shareholder value. In the customer portfolio approach, the customer base of a firm is divided into multiple portfolios based on customer relationships’ potential to contribute to the shareholder value creation. After this, customer management concepts are tailored to each customer portfolio, designed to improve the shareholder value in their own respect. Therefore, effective customer asset management with the customer portfolio approach necessitates that firms are able to manage multiple parallel customer management concepts, or business models, simultaneously. The thesis is one of the first empirical studies on customer asset management, bringing empirical evidence from multiple business-to-business case studies on how customer portfolio models can be formed, how customer portfolios can be managed, and how customer asset management has contributed to the firm financial performance.

COMMON-Sense net:Improved water management for resource-poor farmers via sensor networks

We describe the on-going design and implementation of a sensor network for agricultural management targeted at resource-poor farmers in India. Our focus on semi-arid regions led us to concentrate on water-related issues. Throughout 2004, we carried out a survey on the information needs of the population living in a cluster of villages in our study area. The results highlighted the potential that environment-related information has for the improvement of farming strategies in the face of highly variable conditions, in particular for risk management strategies (choice of crop varieties, sowing and harvest periods, prevention of pests and diseases, efficient use of irrigation water etc.). This leads us to advocate an original use of Information and Communication Technologies (ICT). We believe our demand-driven approach for the design of appropriate ICT tools that are targeted at the resource-poor to be relatively new. In order to go beyond a pure technocratic approach, we adopted an iterative, participatory methodology.

Glowworm-inspired robot swarm for simultaneous taxis towards multiple radiation sources

This paper presents a glowworm metaphor based distributed algorithm that enables a collection of minimalist mobile robots to split into subgroups, exhibit simultaneous taxis-behavior towards, and rendezvous at multiple radiation sources such as nuclear/hazardous chemical spills and fire-origins in a fire calamity. The algorithm is based on a glowworm swarm optimization (GSO) technique that finds multiple optima of multimodal functions. The algorithm is in the same spirit as the ant-colony optimization (ACO) algorithms, but with several significant differences. The agents in the glowworm algorithm carry a luminescence quantity called luciferin along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luciferin. The key feature that is responsible for the working of the algorithm is the use of an adaptive local-decision domain, which we use effectively to detect the multiple source locations of interest. The glowworms have a finite sensor range which defines a hard limit on the local-decision domain used to compute their movements. Extensive simulations validate the feasibility of applying the glowworm algorithm to the problem of multiple source localization. We build four wheeled robots called glowworms to conduct our experiments. We use a preliminary experiment to demonstrate the basic behavioral primitives that enable each glowworm to exhibit taxis behavior towards source locations and later demonstrate a sound localization task using a set of four glowworms.

Improved procedures for the Beckmann rearrangement: the reaction of ketoxime carbonates with boron trifluoride etherate

A variety of ketoxime ethyl carbonates-easily prepared from the oximes and ethyl chloroformate-undergo the Beckmann rearrangement upon treatment with 1 equivalent of boron trifluoride etherate, in dichloromethane solution at room temperature in excellent yields (generally 75-99%). (C) 2000 Elsevier Science Ltd. All rights reserved.

Improved procedures for the Beckmann rearrangement: the reaction of ketoxime carbonates with boron trifluoride etherate

A variety of ketoxime ethyl carbonates-easily prepared from the oximes and ethyl chloroformate-undergo the Beckmann rearrangement upon treatment with 1 equivalent of boron trifluoride etherate, in dichloromethane solution at room temperature in excellent yields (generally 75-99%). (C) 2000 Elsevier Science Ltd. All rights reserved.

The hard-particle model for a dense granular flow down an inclined plane

Perfectly hard particles are those which experience an infinite repulsive force when they overlap, and no force when they do not overlap. In the hard-particle model, the only static state is the isostatic state where the forces between particles are statically determinate. In the flowing state, the interactions between particles are instantaneous because the time of contact approaches zero in the limit of infinite particle stiffness. Here, we discuss the development of a hard particle model for a realistic granular flow down an inclined plane, and examine its utility for predicting the salient features both qualitatively and quantitatively. We first discuss Discrete Element simulations, that even very dense flows of sand or glass beads with volume fraction between 0.5 and 0.58 are in the rapid flow regime, due to the very high particle stiffness. An important length scale in the shear flow of inelastic particles is the `conduction length' delta = (d/(1 - e(2))(1/2)), where d is the particle diameter and e is the coefficient of restitution. When the macroscopic scale h (height of the flowing layer) is larger than the conduction length, the rates of shear production and inelastic dissipation are nearly equal in the bulk of the flow, while the rate of conduction of energy is O((delta/h)(2)) smaller than the rate of dissipation of energy. Energy conduction is important in boundary layers of thickness delta at the top and bottom. The flow in the boundary layer at the top and bottom is examined using asymptotic analysis. We derive an exact relationship showing that the a boundary layer solution exists only if the volume fraction in the bulk decreases as the angle of inclination is increased. In the opposite case, where the volume fraction increases as the angle of inclination is increased, there is no boundary layer solution. The boundary layer theory also provides us with a way of understanding the cessation of flow when at a given angle of inclination when the height of the layer is decreased below a value h(stop), which is a function of the angle of inclination. There is dissipation of energy due to particle collisions in the flow as well as due to particle collisions with the base, and the fraction of energy dissipation in the base increases as the thickness decreases. When the shear production in the flow cannot compensate for the additional energy drawn out of the flow due to the wall collisions, the temperature decreases to zero and the flow stops. Scaling relations can be derived for h(stop) as a function of angle of inclination.

An improved representation of vehicle incompatibility in frontal NCAP tests using a modified rigid barrier

With the objective of better understanding the significance of New Car Assessment Program (NCAP) tests conducted by the National Highway Traffic Safety Administration (NHTSA), head-on collisions between two identical cars of different sizes and between cars and a pickup truck are studied in the present paper using LS-DYNA models. Available finite element models of a compact car (Dodge Neon), midsize car (Dodge Intrepid), and pickup truck (Chevrolet C1500) are first improved and validated by comparing theanalysis-based vehicle deceleration pulses against corresponding NCAP crash test histories reported by NHTSA. In confirmation of prevalent perception, simulation-bascd results indicate that an NCAP test against a rigid barrier is a good representation of a collision between two similar cars approaching each other at a speed of 56.3 kmph (35 mph) both in terms of peak deceleration and intrusions. However, analyses carried out for collisions between two incompatible vehicles, such as an Intrepid or Neon against a C1500, point to the inability of the NCAP tests in representing the substantially higher intrusions in the front upper regions experienced by the cars, although peak decelerations in cars arc comparable to those observed in NCAP tests. In an attempt to improve the capability of a front NCAP test to better represent real-world crashes between incompatible vehicles, i.e., ones with contrasting ride height and lower body stiffness, two modified rigid barriers are studied. One of these barriers, which is of stepped geometry with a curved front face, leads to significantly improved correlation of intrusions in the upper regions of cars with respect to those yielded in the simulation of collisions between incompatible vehicles, together with the yielding of similar vehicle peak decelerations obtained in NCAP tests.

Improved prediction of plane transverse jets in supersonic crossflows

THE flowfield due to transverse injection of a round sonic jet into a supersonic flowis a configuration of interest in the design of supersonic combustors or thrust vector control of supersonic jets. The flow is also of fundamental interest because it presents separation from a smooth surface, embedded subsonic regions, curved shear layers, strong shocks, an unusual development of the injected jet into a kidney-shaped streamwise vortex pair, and a wake behind the jet. Although the geometry is simple, the flow is complex and is a good candidate for assessing the behavior of turbulence models for high-speed flow, beginning with the corresponding two-dimensional flow shown in Fig. 1. At the slot, an underexpanded sonic jet expands rapidly into the supersonic crossflow. Expansion waves reflect at the jet boundary, coalesce, and give rise to a Mach surface (Mach disk for round jets).

Improved synthesis of carbon nanotubes with junctions and of single-walled carbon nanotubes

Pyrolysis of thiophene over nickel nanoparticles dispersed on silica is shown to yield Y-junction carbon nanotubes with smaller diameters than those obtained by the pyrolysis of organometallic-thiophene mixtures. In the presence of water vapour, the pyrolysis of organometallic-hydrocarbon mixtures yields single-walled nanotubes, as well as relatively narrow-diameter carbon nanotubes with Y-junctions. Pyrolysis-of organometallic-hydrocarbon mixtures, in the absence of water vapour, only gives nanotubes with T- and Y-junctions.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.