Highly epidemic strains of methicillin-resistant Staphylococcus aureus (MRSA) do not differ from other MRSA or methicillin-sensitive strains in capsule formation, Protein A content or adherence to HEp-2 cells

During the 1990s, two strains of epidemic methicillin-resistant Staphylococcus aureus, designated ‘phage types EMRSA-15 and EMRSA-16, have emerged as significant hospital pathogens. They have resisted standard methods of control and spread widely amongst in the UK, often becoming endemic, while the incidence of other epidemic types of MRSA has either declined or not changed. This suggests that EMRSA-15 and EMRSA-16 possess special properties that favour their dissemination and survival. In order to investigate this hypothesis, a study was undertaken that examined methicillin-sensitive and methicillinresistant strains of Staphylococcus aureus, including EMRSA types 1, 2, 3, 15 and 16, for capsule formation, the amount of bound protein A produced, and quantitative adherence to the human continuous epithelial cell line HEp-2. Although all these properties varied amongst the strains examined, there was no relationship between any of them and methicillin resistance or epidemic type, and, incidentally, no relationship between cell-wall bound protein A content and adherence

Potential of wind-powered renewable energy membrane systems for Ghana

Areas of the world that lack fresh water often have an ample supply of wind or solar energy, making renewable energy an attractive option as a power source for desalination systems. Particularly, wind energy is attractive because of its relatively low cost, high efficiency, and recent technological advancements in this area of research. To open system applicability to a broader range of geographical areas, the feasibility of substituting solar panels with a wind turbine on an existing membrane desalination systemthat has undergone testing in the Australian outback is examined. The use of wind turbines will provide greater scope for the system's implementation in various parts of the world according to the local wind or solar resources.Acomparison of several small wind turbines coupled with wind speed data from Ghana showed that a 1 kW FuturEnergy wind turbine would give the best performance for the lowest cost and is therefore the most appropriate for coupling with the membrane system. The predicted permeate production is 1.3 m3/d at a specific energy consumption (SEC) of 1.8 kWh/m3

Placing the Fijian Honeyeaters within the meliphagid radiation: implications for origins and conservation

Understanding the evolutionary relationships of threatened species provides an important framework for making decisions about their conservation. However, unrecognised problems with the underlying phylogenetic analyses may bias the decision-making process. Recent phylogenetic studies have improved our understanding of Meliphagidae, but also indicate discordance between molecular datasets. Here, we examine the causes of this discordance using maximum likelihood tree-building and network analyses of identically sampled datasets for four genetic loci. Our results suggest that while we can be reasonably confident of relationships within species groups, discordance within and between molecular datasets tends to obscure relationships towards the base of the meliphagid tree. This ongoing uncertainty likely reflects differences in the sampling of markers and taxa between previously published analyses. To avoid the problems of conflicting data we used divergence time analyses of only the most densely sampled marker, NADH-ubiquinone oxidoreductase chain 2, to investigate the age and origins of the Fijian Meliphagidae. Our analyses suggest two temporally distinct colonisations of the Fijian archipelago. The large-bodied honeyeaters arrived ,15.6 million years ago, subsequently diversifying and spreading to Tonga and Samoa. In contrast, Myzomela appears to have arrived within the last 5.0 million years. The phylogenetic results therefore imply that conserving the evolutionary diversity of Meliphagidae in Polynesia requires that effort be spread across both the currently recognised taxa and geographical range

Prey selection by African wild dogs (Lycaon pictus) in northern Botswana

Prey selection varies among large carnivores in different ecosystems. Factors influencing prey selection include availability, sex, age, body condition, body size, the prey’s anti-predatory mechanisms such as vigilance and speed, and habitat selection.https://sawma.co.za/african-journal-of-wildlife-researcham2022Mammal Research InstituteZoology and Entomolog

Optimal (Randomized) Parallel Algorithms in the Binary-Forking Model

In this paper we develop optimal algorithms in the binary-forking model for a variety of fundamental problems, including sorting, semisorting, list ranking, tree contraction, range minima, and ordered set union, intersection and difference. In the binary-forking model, tasks can only fork into two child tasks, but can do so recursively and asynchronously. The tasks share memory, supporting reads, writes and test-and-sets. Costs are measured in terms of work (total number of instructions), and span (longest dependence chain). The binary-forking model is meant to capture both algorithm performance and algorithm-design considerations on many existing multithreaded languages, which are also asynchronous and rely on binary forks either explicitly or under the covers. In contrast to the widely studied PRAM model, it does not assume arbitrary-way forks nor synchronous operations, both of which are hard to implement in modern hardware. While optimal PRAM algorithms are known for the problems studied herein, it turns out that arbitrary-way forking and strict synchronization are powerful, if unrealistic, capabilities. Natural simulations of these PRAM algorithms in the binary-forking model (i.e., implementations in existing parallel languages) incur an $\Omega(\log n)$ overhead in span. This paper explores techniques for designing optimal algorithms when limited to binary forking and assuming asynchrony. All algorithms described in this paper are the first algorithms with optimal work and span in the binary-forking model. Most of the algorithms are simple. Many are randomized

Prompt gamma activation analysis (PGAA) and short-lived neutron activation analysis (NAA) applied to the characterization of legacy materials

Without quality historical records that provide the composition of legacy materials, the elemental and/or chemical characterization of such materials requires a manual analytical strategy that may expose the analyst to unknown toxicological hazards. In addition, much of the existing legacy inventory also incorporates radioactivity, and, although radiological composition may be determined by various nuclear-analytical methods, most importantly, gamma-spectroscopy, current methods of chemical characterization still require direct sample manipulation, thereby presenting special problems with broad implications for both the analyst and the environment. Alternately, prompt gamma activation analysis (PGAA) provides a'single-shot' in-situ, non-destructive method that provides a complete assay of all major entrained elemental constituents.1-3. Additionally, neutron activation analysis (NAA) using short-lived activation products complements PGAA and is especially useful when NAA activation surpasses the PGAA in elemental sensitivity

Organizational Adaptation to Changing Environments

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66531/2/10.1177_000276428502800507.pd

Can three-flavor oscillations solve the solar neutrino problem?

The most promising solution to the solar neutrino problem are neutrino oscillations, which usually are analyzed within the reduced 2-flavor scheme, because the solutions found therein reasonably well reproduce the recent data of Super-Kamiokande about the recoil-electron energy spectrum, zenith-angle and seasonal variations, and the event rate data of all the neutrino detectors. In this work, however, a survey of the complete parameter space of 3-flavor oscillations is performed. Basically eight new additional solutions could be identified, where the best one with \Delta m(12)^2=2.7x10^(-10) eV^2, \Delta m(13)^2=1.0x10^(-5) eV^2, \Theta(12)=23, and \Theta(13)=1.3 (denoted SVO) is slightly more probable than any 2-flavor solution. However, including the results of the atmospheric neutrino problem excludes all 3-flavour solutions apart from the SLMA-solution (\Delta m(12)^2=7.9x10^(-6) eV^2, \Delta m(13)^2=2.5x10^(-4) eV^2, \Theta(12)=1.4, and \Theta(13)=20). Besides, the ability of SNO and Borexino to discriminate the various 2- and 3-flavor solutions is investigated. Only with very good statistics in these experiments the correct solution to the solar neutrino problem can be identified unambiguously.Comment: 22 pages, 19 figures, REVTeX, submitted to Phys.Rev.D, article with better resolved figures available under http://www.mpa-garching.mpg.de/~schlattl/public.htm

Optimal designs for rational function regression

We consider optimal non-sequential designs for a large class of (linear and nonlinear) regression models involving polynomials and rational functions with heteroscedastic noise also given by a polynomial or rational weight function. The proposed method treats D-, E-, A-, and $\Phi_p$-optimal designs in a unified manner, and generates a polynomial whose zeros are the support points of the optimal approximate design, generalizing a number of previously known results of the same flavor. The method is based on a mathematical optimization model that can incorporate various criteria of optimality and can be solved efficiently by well established numerical optimization methods. In contrast to previous optimization-based methods proposed for similar design problems, it also has theoretical guarantee of its algorithmic efficiency; in fact, the running times of all numerical examples considered in the paper are negligible. The stability of the method is demonstrated in an example involving high degree polynomials. After discussing linear models, applications for finding locally optimal designs for nonlinear regression models involving rational functions are presented, then extensions to robust regression designs, and trigonometric regression are shown. As a corollary, an upper bound on the size of the support set of the minimally-supported optimal designs is also found. The method is of considerable practical importance, with the potential for instance to impact design software development. Further study of the optimality conditions of the main optimization model might also yield new theoretical insights.Comment: 25 pages. Previous version updated with more details in the theory and additional example