A middleware service for coordinated adaptation of communication services in groups of devices

Abstract—Recent research in pervasive computing has shown that context-awareness and dynamic adaptation are fundamental requirements of mobile distributed applications. However, most approaches that focus on context-aware dynamic adaptation use only the context information available at the mobile device to trigger a local adaptation. However, for distributed collaborative applications this is clearly insufficient, since a same adaptation has to be done, in synch, at all mobile devices of the group, and hence should also be based on a commonly agreed context. Therefore, for such kinds of applications one requires mechanisms and protocols to exchange the context information among the devices and to coordinate of the adaptation operations at a group of mobile device. In this paper we present a middleware service for coordinated adaptation of communication services in groups of devices. At each device this adaptation is achieved with minimal disruption for the application’s remote interactions. This middleware service is based on the notion of global context and a generic protocol for global context election and synchronization of the adaptation steps, which we called Moratus. Our middleware service was implemented using JGroups and evaluated for groups of up to 30 devices, showing acceptable latency for groups of such size. I

Black holes admitting a Freudenthal dual

The quantised charges x of four dimensional stringy black holes may be assigned to elements of an integral Freudenthal triple system whose automorphism group is the corresponding U-duality and whose U-invariant quartic norm Delta(x) determines the lowest order entropy. Here we introduce a Freudenthal duality x -> \tilde{x}, for which \tilde{\tilde{x}}=-x. Although distinct from U-duality it nevertheless leaves Delta(x) invariant. However, the requirement that \tilde{x} be integer restricts us to the subset of black holes for which Delta(x) is necessarily a perfect square. The issue of higher-order corrections remains open as some, but not all, of the discrete U-duality invariants are Freudenthal invariant. Similarly, the quantised charges A of five dimensional black holes and strings may be assigned to elements of an integral Jordan algebra, whose cubic norm N(A) determines the lowest order entropy. We introduce an analogous Jordan dual A*, with N(A) necessarily a perfect cube, for which A**=A and which leaves N(A) invariant. The two dualities are related by a 4D/5D lift.Comment: 32 pages revtex, 10 tables; minor corrections, references adde

Colorless operators in a non-associative quantum theory

The associators/antiassociators for the product of four non-associative operators are deduced. By analogy with SU(3) gauge theory the notion of colorless (white) operators is introduced. Some properties of white operators are considered. It is hypothesized that white operators do not give any contribution to corresponding associators/antiassociators. It is suggested that the observables in a non-associative quantum theory correspond to the white operators only.Comment: final version, title and text are change

Beyond a catalogue of differences: A theoretical frame and good practice guidelines for researching sex/gender in human health

Extensive medical, public health, and social science research have focused on cataloguing male–female differences in human health. Unfortunately, much of this research unscientifically and unquestionably attributes these differences to biological causes – as exemplified in the Institute of Medicine’s conclusion that “every cell has a sex.” In this manuscript we theorize the entanglement of sex and gender in human health research and articulate good practice guidelines for assessing the role of biological processes – along with social and biosocial processes – in the production of non-reproductive health differences between and among men and women. There are two basic tenets underlying this project. The first is that sex itself is not a biological mechanism and the second is that “sex” and “gender” are entangled, and analyses should proceed by assuming that measures of sex are not pristine, but include effects of gender. Building from these tenets – and using cardiovascular disease as a consistent example – we articulate a process that scientists and researchers can use to seriously and systematically assess the role of biology and social environment in the production of health among men and women. We hope that this intervention will be one further step toward understanding the complexity and nuance of health outcomes, and that this increased knowledge can be used to improve human health

Random forest classification as a tool in epidemiological modelling: Identification of farm-specific characteristics relevant for the occurrence of Fasciola hepatica on German dairy farms

Fasciola hepatica is an internal parasite of both human and veterinary relevance. In order to control fasciolosis, a multitude of attempts to predict the risk of infection such as risk maps or forecasting models have been developed. These attempts mainly focused on the influence of geo-climatic and meteorological features. Predicting bovine fasciolosis on farm level taking into account farm-specific settings yet remains challenging. In the present study, a new methodology for this purpose, a data-driven machine learning approach using a random forest classification algorithm was applied to a cross-sectional data set of farm characteristics, management regimes, and farmer aspects within two structurally different dairying regions in Germany in order to identify factors relevant for the occurrence of F. hepatica that could predict farm-level bulk tank milk positivity. The resulting models identified farm-specific key aspects in regard to the presence of F. hepatica. In study region North, farm-level production parameters (farm-level milk yield, farm-level milk fat, farm-level milk protein), leg hygiene, body condition (prevalence of overconditioned and underconditioned cows, respectively) and pasture access were identified as features relevant in regard to farm-level F. hepatica positivity. In study region South, pasture access together with farm-level lameness prevalence, farm-level prevalence of hock lesions, herd size, parity, and farm-level milk fat appeared to be important covariates. The stratification of the analysis by study region allows for the extrapolation of the results to similar settings of dairy husbandry. The local, region-specific modelling of F. hepatica presence in this work contributes to the understanding of on-farm aspects of F. hepatica appearance. The applied technique represents a novel approach in this context to model epidemiological data on fasciolosis which allows for the identification of farms at risk and together with additional findings in regard to the epidemiology of fasciolosis, can facilitate risk assessment and deepen our understanding of on-farm drivers of the occurrence of F. hepatica

Orbits and Attractors for N=2 Maxwell-Einstein Supergravity Theories in Five Dimensions

BPS and non-BPS orbits for extremal black-holes in N=2 Maxwell-Einstein supergravity theories (MESGT) in five dimensions were classified long ago by the present authors for the case of symmetric scalar manifolds. Motivated by these results and some recent work on non-supersymmetric attractors we show that attractor equations in N=2 MESGTs in d=5 do indeed possess the distinct families of solutions with finite Bekenstein-Hawking entropy. The new non-BPS solutions have non-vanishing central charge and matter charge which is invariant under the maximal compact subgroup of the stabilizer of the non-BPS orbit. Our analysis covers all symmetric space theories G/H such that G is a symmetry of the action. These theories are in one-to-one correspondence with (Euclidean) Jordan algebras of degree three. In the particular case of N=2 MESGT with scalar manifold SU*(6)/USp(6) a duality of the two solutions with regard to N=2 and N=6 supergravity is also considered.Comment: Added a footnote on notation and comments on the attactor nature of non BPS solutions in section 5. Typos corrected. Version to appear in NPB. Latex file, 24 page

A machine learning approach using partitioning around medoids clustering and random forest classification to model groups of farms in regard to production parameters and bulk tank milk antibody status of two major internal parasites in dairy cows

Fasciola hepatica and Ostertagia ostertagi are internal parasites of cattle compromising physiology, productivity, and well-being. Parasites are complex in their effect on hosts, sometimes making it difficult to identify clear directions of associations between infection and production parameters. Therefore, unsupervised approaches not assuming a structure reduce the risk of introducing bias to the analysis. They may provide insights which cannot be obtained with conventional, supervised methodology. An unsupervised, exploratory cluster analysis approach using the k–mode algorithm and partitioning around medoids detected two distinct clusters in a cross-sectional data set of milk yield, milk fat content, milk protein content as well as F. hepatica or O. ostertagi bulk tank milk antibody status from 606 dairy farms in three structurally different dairying regions in Germany. Parasite–positive farms grouped together with their respective production parameters to form separate clusters. A random forests algorithm characterised clusters with regard to external variables. Across all study regions, co–infections with F. hepatica or O. ostertagi, respectively, farming type, and pasture access appeared to be the most important factors discriminating clusters (i.e. farms). Furthermore, farm level lameness prevalence, herd size, BCS, stage of lactation, and somatic cell count were relevant criteria distinguishing clusters. This study is among the first to apply a cluster analysis approach in this context and potentially the first to implement a k–medoids algorithm and partitioning around medoids in the veterinary field. The results demonstrated that biologically relevant patterns of parasite status and milk parameters exist between farms positive for F. hepatica or O. ostertagi, respectively, and negative farms. Moreover, the machine learning approach confirmed results of previous work and shed further light on the complex setting of associations a between parasitic diseases, milk yield and milk constituents, and management practices

Associations of production characteristics with the on-farm presence of Fasciola hepatica in dairy cows vary across production levels and indicate differences between breeds

Fasciola hepatica is one of the economically most important endoparasites in cattle production. The aim of the present work was to evaluate the relevance of production level on the associations of on-farm presence of F. hepatica with farm-level milk yield, milk fat, and milk protein in Holstein cows, a specialised dairy breed, and in Simmental cows, a dual purpose breed. Furthermore, we investigated whether differential associations were present depending on breed. Data from 560 dairy farms across Germany housing 93,672 cows were analysed. The presence of F. hepatica antibodies was determined via ELISA on bulk tank milk samples. Quantile regression was applied to model the median difference in milk yield, milk fat, and milk protein depending on the interaction of breed and fluke occurrence. Whereas a reduction in milk yield (-1,206 kg, p < 0.001), milk fat (-22.9 kg, p = 0.001), and milk protein (-41.6 kg, p <0.001) was evident on F. hepatica positive German Holstein farms, only milk fat (-33.8 kg, p = 0.01) and milk protein (-22.6 kg, p = 0.03) were affected on F. hepatica positive German Simmental farms. Subsequently, production traits were modelled within each of the two breeds for low, medium, and high producing farms in the presence of F. hepatica antibodies and of confounders. On Holstein farms, the presence of F. hepatica seropositivity was associated with lower production, while on German Simmental farms such an association was less evident. This work demonstrates that production level is relevant when assessing the associations between the exposure to F. hepatica with production characteristics. Moreover, both models indicate a breed dependence. This could point towards a differential F. hepatica resilience of specialised dairy breeds in comparison with dual purpose breeds

Explicit Orbit Classification of Reducible Jordan Algebras and Freudenthal Triple Systems

We determine explicit orbit representatives of reducible Jordan algebras and of their corresponding Freudenthal triple systems. This work has direct application to the classification of extremal black hole solutions of N = 2, 4 locally supersymmetric theories of gravity coupled to an arbitrary number of Abelian vector multiplets in D = 4, 5 space-time dimensions.Comment: 18 pages. Updated to match published versio

Jordan Pairs, E6 and U-Duality in Five Dimensions

By exploiting the Jordan pair structure of U-duality Lie algebras in D = 3 and the relation to the super-Ehlers symmetry in D = 5, we elucidate the massless multiplet structure of the spectrum of a broad class of D = 5 supergravity theories. Both simple and semi-simple, Euclidean rank-3 Jordan algebras are considered. Theories sharing the same bosonic sector but with different supersymmetrizations are also analyzed.Comment: 1+41 pages, 1 Table; v2 : a Ref. and some comments adde