Extrinsic local regression on manifold-valued data

We propose an extrinsic regression framework for modeling data with manifold valued responses and Euclidean predictors. Regression with manifold responses has wide applications in shape analysis, neuroscience, medical imaging and many other areas. Our approach embeds the manifold where the responses lie onto a higher dimensional Euclidean space, obtains a local regression estimate in that space, and then projects this estimate back onto the image of the manifold. Outside the regression setting both intrinsic and extrinsic approaches have been proposed for modeling i.i.d manifold-valued data. However, to our knowledge our work is the first to take an extrinsic approach to the regression problem. The proposed extrinsic regression framework is general, computationally efficient and theoretically appealing. Asymptotic distributions and convergence rates of the extrinsic regression estimates are derived and a large class of examples are considered indicating the wide applicability of our approach

Extrinsic Local Regression on Manifold-Valued Data

We propose an extrinsic regression framework for modeling data with manifold valued responses and Euclidean predictors. Regression with manifold responses has wide applications in shape analysis, neuroscience, medical imaging and many other areas. Our approach embeds the manifold where the responses lie onto a higher dimensional Euclidean space, obtains a local regression estimate in that space, and then projects this estimate back onto the image of the manifold. Outside the regression setting both intrinsic and extrinsic approaches have been proposed for modeling i.i.d manifold-valued data. However, to our knowledge our work is the first to take an extrinsic approach to the regression problem. The proposed extrinsic regression framework is general, computationally efficient and theoretically appealing. Asymptotic distributions and convergence rates of the extrinsic regression estimates are derived and a large class of examples are considered indicating the wide applicability of our approach

MLPerf Inference Benchmark

Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded. Over 100 organizations are building ML inference chips, and the systems that incorporate existing models span at least three orders of magnitude in power consumption and five orders of magnitude in performance; they range from embedded devices to data-center solutions. Fueling the hardware are a dozen or more software frameworks and libraries. The myriad combinations of ML hardware and ML software make assessing ML-system performance in an architecture-neutral, representative, and reproducible manner challenging. There is a clear need for industry-wide standard ML benchmarking and evaluation criteria. MLPerf Inference answers that call. In this paper, we present our benchmarking method for evaluating ML inference systems. Driven by more than 30 organizations as well as more than 200 ML engineers and practitioners, MLPerf prescribes a set of rules and best practices to ensure comparability across systems with wildly differing architectures. The first call for submissions garnered more than 600 reproducible inference-performance measurements from 14 organizations, representing over 30 systems that showcase a wide range of capabilities. The submissions attest to the benchmark's flexibility and adaptability.Comment: ISCA 202

Multifunctional hybrid materials based on transparent poly(methyl methacrylate) reinforced by lanthanoid hydroxo clusters

Three pentanuclear lanthanoid hydroxo clusters of composition [Ln(OH)5(abzm)10], where Ln = Eu, Tb,Ho and abzm = di(4-allyloxy)benzoylmethanide, have been prepared. The structures have beencharacterised by means of IR, Raman, elemental analyses and X-ray diffraction, showing a pyramidalsquare-based cluster core. The clusters (Tb and Ho) exhibit Curie?Weiss Law behaviour, displayingantiferromagnetic ordering at low temperatures. The emission properties of the Eu cluster demonstratethe abzm- ligand is an efficient antenna (lex = 420 nm) only for the sensitisation of Eu luminescence inthe visible range, via energy transfer to the 5D0 state of the trivalent metal. The clusters have beenreacted in the presence of methyl methacrylate and azobisisobutyronitrile to prepare reinforcedpolymers via radical polymerisation. The obtained materials exhibit swelling upon immersion intoorganic solvents up to 110% of their original size, in agreement with the presence of cluster-crosslinked polymeric chains. Also, no loss of transparency was observed in the preparation of the materials. The characteristic red emission of the Eu cluster in also retained in the polymeric material

Retroperitoneal liposarcomas: The experience of a tertiary Asian center

10.1186/1477-7819-9-12World Journal of Surgical Oncology9

Unexpected Ecological Resilience in Bornean Orangutans and Implications for Pulp and Paper Plantation Management

Ecological studies of orangutans have almost exclusively focused on populations living in primary or selectively logged rainforest. The response of orangutans to severe habitat degradation remains therefore poorly understood. Most experts assume that viable populations cannot survive outside undisturbed or slightly disturbed forests. This is a concern because nearly 75% of all orangutans live outside protected areas, where degradation of natural forests is likely to occur, or where these are replaced by planted forests. To improve our understanding of orangutan survival in highly altered forest habitats, we conducted population density surveys in two pulp and paper plantation concessions in East Kalimantan, Indonesia. These plantations consist of areas planted with fast-growing exotics intermixed with stands of highly degraded forests and scrublands. Our rapid surveys indicate unexpectedly high orangutan densities in plantation landscapes dominated by Acacia spp., although it remains unclear whether such landscapes can maintain long-term viable populations. These findings indicate the need to better understand how plantation-dominated landscapes can potentially be incorporated into orangutan conservation planning. Although we emphasize that plantations have less value for overall biodiversity conservation than natural forests, they could potentially boost the chances of orangutan survival. Our findings are based on a relatively short study and various methodological issues need to be addressed, but they suggest that orangutans may be more ecologically flexible than previously thought

Systematic Screening of Drosophila Deficiency Mutations for Embryonic Phenotypes and Orphan Receptor Ligands

This paper defines a collection of Drosophila deletion mutations (deficiencies) that can be systematically screened for embryonic phenotypes, orphan receptor ligands, and genes affecting protein localization. It reports the results of deficiency screens we have conducted that have revealed new axon guidance phenotypes in the central nervous system and neuromuscular system and permitted a quantitative assessment of the number of potential genes involved in regulating guidance of specific motor axon branches. Deficiency “kits” that cover the genome with a minimum number of lines have been established to facilitate gene mapping. These kits cannot be systematically analyzed for phenotypes, however, since embryos homozygous for many deficiencies in these kits fail to develop due to the loss of key gene products encoded within the deficiency. To create new kits that can be screened for phenotype, we have examined the development of the nervous system in embryos homozygous for more than 700 distinct deficiency mutations. A kit of ∼400 deficiency lines for which homozygotes have a recognizable nervous system and intact body walls encompasses >80% of the genome. Here we show examples of screens of this kit for orphan receptor ligands and neuronal antigen expression. It can also be used to find genes involved in expression, patterning, and subcellular localization of any protein that can be visualized by antibody staining. A subset kit of 233 deficiency lines, for which homozygotes develop relatively normally to late stage 16, covers ∼50% of the genome. We have screened it for axon guidance phenotypes, and we present examples of new phenotypes we have identified. The subset kit can be used to screen for phenotypes affecting all embryonic organs. In the future, these deficiency kits will allow Drosophila researchers to rapidly and efficiently execute genome-wide anatomical screens that require examination of individual embryos at high magnification