The effects of urea and artificial saliva on rumen bacterial protein synthesis in sheep receiving a high-cereal diet

Four sheep fitted with cannulas in the rumen and duodenum and given a basal diet of 18% chopped hay, 41% rolled barley and 41% flaked maize, known to be associated with low rates of bacterial protein synthesis in the rumen, were used in a 4 × 4 Latin Square experiment to study the effects of continuous intraruminal infusions of water (2 litres day^?1; control), urea solution (7.5 g urea litre^?1, 2 litres day^?1; urea), artificial saliva (4 litres day^?1; saliva) and artificial saliva with added urea (3.75 g urea litre^?1, 4 litres day^?1; saliva+urea) on rumen ammonia-nitrogen concentration, pH, liquid clearance rates and bacterial protein synthesis. Rumen ammonia-nitrogen concentrations for control, urea, saliva and saliva + urea treatments were 81, 158, 38 and 151 mg litre^?1, respectively. Corresponding mean values for rumen pH were 6.18, 6.09, 6.37 and 6.41 units and for rumen liquid clearance rates 0.082, 0.057, 0.062 and 0.051 h^?1. The mean rate of bacterial protein synthesis in the rumen, estimated from the duodenal entry of α-?-diaminopimelic acid, for the control treatment was 163 g crude protein (CP) kg^?1 organic matter (OM) apparently digested in the stomach. Corresponding rates for the saliva and saliva + urea treatments were 169 g CP kg^?1 OM apparently digested and 215 g CP kg^?1 OM apparently digested, indicating responses in protein synthesis to the urea+saliva treatment but not to the saliva alone treatment. Infusion of urea solution increased the mean rate of protein synthesis to 204 g CP kg^?1 OM apparently digested in the stomach but the responses were variable between animals and in three of the animals were small. It is concluded that with the type of diet used an enhanced entry of saliva into the rumen is necessary to ensure that supplementary urea produces a consistent improvement in ruminal protein synthesis.     

Scalable Room Synchronizations

This paper presents a scalable solution to the group mutual exclusion problem, with applications to linearizable stacks and queues, and related problems. Our solution allows entry and exit from the mutually exclusive regions in $O(t_r + \tau)$ time, where $t_r$ is the maximum time spent in a critical region by a user, and $\tau$ is the maximum time taken by any instruction, including a fetch-and-add instruction. This bound holds regardless of the number of users. We describe how stacks and queues can be implemented using two regions, one for pushing (enqueueing) and one for popping (dequeueing). These implementations are particularly simple, are linearizable, and support access in time proportional to a fetch-and-add operation. In addition, we present experimental results comparing room synchronizations with the Keane–Moir algorithm for group mutual exclusion.     

Involving older people with dementia and their carers in designing computer based support systems: some methodological considerations

Older people with dementia are a particularly challenging user group to involve in the process of designing interactive systems that could assist them. It may also be difficult to involve family caregivers of people with dementia, as they are most likely to be older themselves and uncertain about technology. Paid care staff, whilst younger, may be unclear about the benefits of technology and lack confidence in their ability to incorporate it into their work. Over the past 7 years, the authors of this paper have worked closely with people with dementia, their families and professional care staff to develop and evaluate a multimedia computer system to support communication between people with dementia and caregivers. To achieve this, a number of user involvement issues were addressed, ranging from legal and ethical considerations of working with people with dementia to the reluctance of hard-pressed staff to add to their workload for a research project. In addition, developing and conducting evaluations and eliciting the views of people with dementia who have working memory impairment plus additional cognitive and social difficulties emerged as a central issue. A variety of approaches were explored within this project, which are described in this paper, including familiarizing the whole team with the unique difficulties posed by dementia, continuous confirmation of participants’ consent, and ways to measure enjoyment, engagement, and joint interaction using observation.     

Application of Bayesian Network Learning Methods to Waste Water Treatment Plants

Bayesian Networks have been proposed as an alternative to rule-based systems in domains with uncertainty. Applications in monitoring and control can benefit from this form of knowledge representation. Following the work of Chong and Walley, we explore the possibilities of Bayesian Networks in the Waste Water Treatment Plants (WWTP) monitoring and control domain. We show the advantages of modelling knowledge in such a domain by means of Bayesian networks, put forth new methods for knowledge acquisition, describe their applications to a real waste water treatment plant and comment on the results. We also show how a Bayesian Network learning environment was used in the process and which characteristics of data in the domain suggested new ways of representing knowledge in network form but with uncertainty representations formalisms other than probability. The results of applying a possibilistic extension of current learning methods are also shown and compared.     

The bone diagnostic instrument II: indentation distance increase

The bone diagnostic instrument (BDI) is being developed with the long-term goal of providing a way for researchers and clinicians to measure bone material properties of human bone in vivo. Such measurements could contribute to the overall assessment of bone fragility in the future. Here, we describe an improved BDI, the Osteoprobe IItrade mark. In the Osteoprobe IItrade mark, the probe assembly, which is designed to penetrate soft tissue, consists of a reference probe (a 22 gauge hypodermic needle) and a test probe (a small diameter, sharpened rod) which slides through the inside of the reference probe. The probe assembly is inserted through the skin to rest on the bone. The distance that the test probe is indented into the bone can be measured relative to the position of the reference probe. At this stage of development, the indentation distance increase (IDI) with repeated cycling to a fixed force appears to best distinguish bone that is more easily fractured from bone that is less easily fractured. Specifically, in three model systems, in which previous mechanical testing and/or tests reported here found degraded mechanical properties such as toughness and postyield strain, the BDI found increased IDI. However, it must be emphasized that, at this time, neither the IDI nor any other mechanical measurement by any technique has been shown clinically to correlate with fracture risk. Further, we do not yet understand the mechanism responsible for determining IDI beyond noting that it is a measure of the continuing damage that results from repeated loading. As such, it is more a measure of plasticity than elasticity in the bone.     

Discovery of stage-related proteins in esophageal squamous cell carcinoma using proteomic analysis

Esophageal squamous cell carcinoma (ESCC) is the major subtype of esophageal cancers in China, and characterized with high morbidity and mortality. So far, the diagnosis of ESCC is mainly dependent on the alterations in esophageal histology, but most cases of ESCC with low stage do not display visible histological abnormalities. Therefore, a deep understanding of the mechanism of ESCC progression and seeking stage-specific molecules might improve the diagnosis and therapy for ESCC. In this study, we used proteomics to analyze ESCC tissues with classification by TNM stage, and determined the proteomic features correlated with ESCC progression (from stages I to III). Proteins that exhibited significantly different expression patterns between ESCC and corresponding normal esophageal tissues were identified using MS. The identified proteins with differentiated expression mainly fell into three protein categories (i.e. cytoskeleton system-associated proteins, metabolism enzymes, and heat shock proteins). In addition, real-time PCR highlighted some molecules that were associated with tumor stages at the mRNA level, such as enolase 1, chromosome 1 ORF 10, elastase inhibitor, α B crystalline, stress-induced phosphoprotein 1, and squamous cell carcinoma antigen 1. Altogether, these data provided further information on ESCC progression and potential drug targets for ESCC clinical therapy.     

Contextual modulation via low-level vision processing

Gabor wavelets are well established as being useful for modeling neuronal response properties of the primary visual cortex. However, current Gabor models do not account for long-range contextual modulation. This paper introduces a new model which extends a state-of-the-art model of contextual modulation by incorporating long-range convolution at the scale of the visual field. The significance of this new mechanism is that it accounts for perceptual filling-in of occluded receptive fields with purely low-level vision processing.     

Programmatically defining the software footprint of sensor networks using the Android platform

Sensor networks are being used for an increasing number of applications ranging from environmental monitoring and precision agriculture to manufacturing and health care. By gathering data at unprecedented temporal and spatial granularity, sensor networks are revolutionizing these applications. Given the scale and complexity of these systems, they face a critical challenge in software Operations and Management, that is, installing, configuring, and updating thousands of software components in a heterogeneous sensor network. In this paper, we discuss automating and simplifying the process of defining the software environment on a sensor node running the Android platform. Android has significant share in the mobile phone market and runs on a broad range of devices including embedded platforms. This paper outlines the use of a new method for configuring embedded devices and sensor networks by drawing from techniques used for defining the software environment in data centers. We have also developed a software prototype to allow for a simple, reproducible, and flexible configuration of the Android software stack on a sensor node. Our exploratory research provides an insight into the use of modular configuration techniques in embedded devices and how they can be applied to the Android ecosystem. Copyright © 2013 John Wiley & Sons, Ltd.     

A molecular dynamics study of the effects of branching characteristics of LDPE on its miscibility with HDPE

The effects of branching characteristics of low-density polyethylene (LDPE) on its melt miscibility with high-density polyethylene (HDPE) were studied using molecular simulation. In particular, molecular dynamics (MD) was applied to compute Hildebrand solubility parameters (δ) of models of HDPE and LDPE with different branch contents at five temperatures that are well above their melting temperatures. Values computed for δ agreed very well with experiment. The Flory-Huggins interaction parameters (χ) for blends of HDPE and different LDPE models were then calculated using the computed δ values. The level of branch content for LDPE above which the blends are immiscible and segregate in the melt was found to be around 30 branches/1000 long chain carbons at the chosen simulation temperatures. This value is significantly lower than that of butene-based linear low-density polyethylene (LLDPE) (40 branches/1000 carbons) in the blends with HDPE computed by one of the authors (polymer 2000; 41:8741). The major difference between LDPE and LLDPE models is that each modeled LDPE molecule has three long chains while each modeled LLDPE molecule had only one long chain. The present results together with those of the LLDPE/HDPE blends suggest that the long chain branching may have significant influence on the miscibility of polyethylene blends at elevated temperatures.