High-order half-integral conservative post-Newtonian coefficients in the redshift factor of black hole binaries

The post-Newtonian approximation is still the most widely used approach to obtaining explicit solutions in general relativity, especially for the relativistic two-body problem with arbitrary mass ratio. Within many of its applications, it is often required to use a regularization procedure. Though frequently misunderstood, the regularization is essential for waveform generation without reference to the internal structure of orbiting bodies. In recent years, direct comparison with the self-force approach, constructed specifically for highly relativistic particles in the extreme mass ratio limit, has enabled preliminary confirmation of the foundations of both computational methods, including their very independent regularization procedures, with high numerical precision. In this paper, we build upon earlier work to carry this comparison still further, by examining next-to-next-to-leading order contributions beyond the half integral 5.5PN conservative effect, which arise from terms to cubic and higher orders in the metric and its multipole moments, thus extending scrutiny of the post-Newtonian methods to one of the highest orders yet achieved. We do this by explicitly constructing tail-of-tail terms at 6.5PN and 7.5PN order, computing the redshift factor for compact binaries in the small mass ratio limit, and comparing directly with numerically and analytically computed terms in the self-force approach, obtained using solutions for metric perturbations in the Schwarzschild space-time, and a combination of exact series representations possibly with more typical PN expansions. While self-force results may be relativistic but with restricted mass ratio, our methods, valid primarily in the weak-field slowly-moving regime, are nevertheless in principle applicable for arbitrary mass ratios.Comment: 33 pages, no figure; minor correction

Half-integral conservative post-Newtonian approximations in the redshift factor of black hole binaries

Recent perturbative self-force computations (Shah, Friedman & Whiting, submitted to Phys. Rev. {\bf D}, arXiv:1312.1952 [gr-qc]), both numerical and analytical, have determined that half-integral post-Newtonian terms arise in the conservative dynamics of black-hole binaries moving on exactly circular orbits. We look at the possible origin of these terms within the post-Newtonian approximation, find that they essentially originate from non-linear "tail-of-tail" integrals and show that, as demonstrated in the previous paper, their first occurrence is at the 5.5PN order. The post-Newtonian method we use is based on a multipolar-post-Minkowskian treatment of the field outside a general matter source, which is re-expanded in the near zone and extended inside the source thanks to a matching argument. Applying the formula obtained for generic sources to compact binaries, we obtain the redshift factor of circular black hole binaries (without spins) at 5.5PN order in the extreme mass ratio limit. Our result fully agrees with the determination of the 5.5PN coefficient by means of perturbative self-force computations reported in the previously cited paper.Comment: 18 pages, no figures, references updated and minor corrections include

IoT in medical diagnosis: detecting excretory functional disorders for Older adults via bathroom activity change using unobtrusive IoT technology

The Internet of Things (IoT) and Artificial Intelligence (AI) are promising technologies that can help make the health system more efficient, which concurrently can be particularly useful to help maintain a high quality of life for older adults, especially in light of healthcare staff shortage. Many health issues are challenging to manage both by healthcare staff and policymakers. They have a negative impact on older adults and their families and are an economic burden to societies around the world. This situation is particularly critical for older adults, a population highly vulnerable to diseases that needs more consideration and care. It is, therefore, crucial to improve diagnostic and management as well as proposed prevention strategies to enhance the health and quality of life of older adults. In this study, we focus on detecting symptoms in early stages of diseases to prevent the deterioration of older adults' health and avoid complications. We focus on digestive and urinary system disorders [mainly the Urinary Tract Infection (UTI) and the Irritable Bowel Syndrome (IBS)] that are known to affect older adult populations and that are detrimental to their health and quality of life. Our proposed approach relies on unobtrusive IoT and change point detections algorithms to help follow older adults' health status daily. The approach monitors long-term behavior changes and detects possible changes in older adults' behavior suggesting early onsets or symptoms of IBS and UTI. We validated our approach with medical staff reports and IoT data collected in the residence of 16 different older adults during periods ranging from several months to a few years. Results are showing that our proposed approach can detect changes associated to symptoms of UTI and IBS, which were confirmed with observations and testimonies from the medical staff

Hadamard Regularization

Motivated by the problem of the dynamics of point-particles in high post-Newtonian (e.g. 3PN) approximations of general relativity, we consider a certain class of functions which are smooth except at some isolated points around which they admit a power-like singular expansion. We review the concepts of (i) Hadamard ``partie finie'' of such functions at the location of singular points, (ii) the partie finie of their divergent integral. We present and investigate different expressions, useful in applications, for the latter partie finie. To each singular function, we associate a partie-finie (Pf) pseudo-function. The multiplication of pseudo-functions is defined by the ordinary (pointwise) product. We construct a delta-pseudo-function on the class of singular functions, which reduces to the usual notion of Dirac distribution when applied on smooth functions with compact support. We introduce and analyse a new derivative operator acting on pseudo-functions, and generalizing, in this context, the Schwartz distributional derivative. This operator is uniquely defined up to an arbitrary numerical constant. Time derivatives and partial derivatives with respect to the singular points are also investigated. In the course of the paper, all the formulas needed in the application to the physical problem are derived.Comment: 50 pages, to appear in Journal of Mathematical Physic

Factors affecting feelings of justice in biodiversity conflicts : towards fairer jaguar management in Calakmul, Mexico

Funding was provided by Mitacs through a Globalink Research Award to MLL, BS and SC, a José-Sarukhan Excellence Award given by the Centro del Cambio Global y Sustentabilidad del Sureste to MLL, an Excellence Award from the Quebec Center for Biodiversity Science to MLL, and a grant from the Université de Sherbrooke to SC.Conservation focuses on environmental objectives, but neglecting social concerns can lead to feelings of injustice among some actors and thus jeopardise conservation aims. Through a case study on a biodiversity conflict around jaguar management in Southern Mexico, we explored actors' feelings of injustice and their associated determinants. We employed a framework distinguishing four dimensions of justice: recognition, ecological, distributive and procedural. By conducting and analysing 235 interviews with farmers and ranchers, we investigated what drive their feeling of injustice, namely their perceptions of the injustice itself, individual characteristics and interactions with their environment. The participants selected 10 statements representing criteria characterizing their feeling of justice toward jaguar management, which they compared using pair-wise comparisons. A pioneering statistical analysis, BTLLasso, revealed that self-interest assumptions were not upheld; feelings of injustice were only weakly influenced by experience of depredation. Feelings of injustice were influenced mainly by factors related to actors' intra-and inter-group relationships (e.g. perception of collective responsibility, perceived coherence in the group to which they identified). This nuanced understanding of how people build their perception of justice can inform fairer and more effective conservation approaches. Whilst details will be context specific, it emerged that building relationships and enabling debate over ecological responsibilities are important and conservation efforts should go beyond merely offering financial compensation. We conclude that perception of justice is a neglected but important aspect to include in integrative approaches to managing biodiversity conflicts, and that novel mixed methods can advance both conceptual and applied understanding in this area.PostprintPeer reviewe

How to make more out of community data? A conceptual framework and its implementation as models and software

Community ecology aims to understand what factors determine the assembly and dynamics of species assemblages at different spatiotemporal scales. To facilitate the integration between conceptual and statistical approaches in community ecology, we propose Hierarchical Modelling of Species Communities (HMSC) as a general, flexible framework for modern analysis of community data. While non-manipulative data allow for only correlative and not causal inference, this framework facilitates the formulation of data-driven hypotheses regarding the processes that structure communities. We model environmental filtering by variation and covariation in the responses of individual species to the characteristics of their environment, with potential contingencies on species traits and phylogenetic relationships. We capture biotic assembly rules by species-to-species association matrices, which may be estimated at multiple spatial or temporal scales. We operationalise the HMSC framework as a hierarchical Bayesian joint species distribution model, and implement it as R-and Matlab-packages which enable computationally efficient analyses of large data sets. Armed with this tool, community ecologists can make sense of many types of data, including spatially explicit data and time-series data. We illustrate the use of this framework through a series of diverse ecological examples.Peer reviewe

Diverging trends and drivers of Arctic flower production in Greenland over space and time

The Arctic is warming at an alarming rate. While changes in plant community composition and phenology have been extensively reported, the effects of climate change on reproduction remain poorly understood. We quantified multidecadal changes in flower density for nine tundra plant species at a low- and a high-Arctic site in Greenland. We found substantial changes in flower density over time, but the temporal trends and drivers of flower density differed both between species and sites. Total flower density increased over time at the low-Arctic site, whereas the high-Arctic site showed no directional change. Within and between sites, the direction and rate of change differed among species, with varying effects of summer temperature, the temperature of the previous autumn and the timing of snowmelt. Finally, all species showed a strong trade-off in flower densities between successive years, suggesting an effective cost of reproduction. Overall, our results reveal region- and taxon-specific variation in the sensitivity and responses of co-occurring species to shared climatic drivers, and a clear cost of reproductive investment among Arctic plants. The ultimate effects of further changes in climate may thus be decoupled between species and across space, with critical knock-on effects on plant species dynamics, food web structure and overall ecosystem functioning