Clustering files of chemical structures using the Szekely-Rizzo generalization of Ward's method

Ward's method is extensively used for clustering chemical structures represented by 2D fingerprints. This paper compares Ward clusterings of 14 datasets (containing between 278 and 4332 molecules) with those obtained using the Szekely–Rizzo clustering method, a generalization of Ward's method. The clusters resulting from these two methods were evaluated by the extent to which the various classifications were able to group active molecules together, using a novel criterion of clustering effectiveness. Analysis of a total of 1400 classifications (Ward and Székely–Rizzo clustering methods, 14 different datasets, 5 different fingerprints and 10 different distance coefficients) demonstrated the general superiority of the Székely–Rizzo method. The distance coefficient first described by Soergel performed extremely well in these experiments, and this was also the case when it was used in simulated virtual screening experiments

Power law in a gauge-invariant cut-off regularisation

We study one-loop quantum corrections of a compactified Abelian 5d gauge field theory. We use a cut-off regularisation procedure which respects the symmetries of the model, i.e. gauge invariance, exhibits the expected power-like divergences and therefore allows the derivation of power-law behavior of the effective 4d gauge coupling in a coherent manner.Comment: 5 pages, 1 figure, 5 graphs, few references added, to appear in Phys.Rev. Rapid Communication

Plausibility functions and exact frequentist inference

In the frequentist program, inferential methods with exact control on error rates are a primary focus. The standard approach, however, is to rely on asymptotic approximations, which may not be suitable. This paper presents a general framework for the construction of exact frequentist procedures based on plausibility functions. It is shown that the plausibility function-based tests and confidence regions have the desired frequentist properties in finite samples---no large-sample justification needed. An extension of the proposed method is also given for problems involving nuisance parameters. Examples demonstrate that the plausibility function-based method is both exact and efficient in a wide variety of problems.Comment: 21 pages, 5 figures, 3 table

Symmetry preserving regularization with a cutoff

A Lorentz and gauge symmetry preserving regularization method is proposed in 4 dimension based on momentum cutoff. We use the conditions of gauge invariance or freedom of shift of the loop-momentum to define the evaluation of the terms carrying Lorentz indices, e.g. proportional to k_{\mu}k_{\nu}. The remaining scalar integrals are calculated with a four dimensional momentum cutoff. The finite terms (independent of the cutoff) are unambiguous and agree with the result of dimensional regularization.Comment: 12 pages, 1 figure, v2 references adde

A Review of Multi- Compartment Infectious Disease Models

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156488/2/insr12402.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156488/1/insr12402_am.pd

Sea ice dynamics influence halogen deposition to Svalbard

Sea ice is an important parameter in the climate system and its changes impact upon the polar albedo and at- mospheric and oceanic circulation. Iodine (I) and bromine (Br) have been measured in a shallow firn core drilled at the summit of the Holtedahlfonna glacier (Northwest Spitsber- gen, Svalbard). Changing I concentrations can be linked to the March–May maximum sea ice extension. Bromine en- richment, indexed to the Br / Na sea water mass ratio, appears to be influenced by changes in the seasonal sea ice area. I is emitted from marine biota and so the retreat of March–May sea ice coincides with enlargement of the open-ocean surface which enhances marine primary production and consequent I emission. The observed Br enrichment could be explained by greater Br emissions during the Br explosions that have been observed to occur mainly above first year sea ice during the early springtime. In this work we present the first compari- son between halogens in surface snow and Arctic sea ice ex- tension. Although further investigation is required to charac- terize potential depositional and post-depositional processes, these preliminary findings suggest that I and Br can be linked to variability in the spring maximum sea ice extension and seasonal sea ice surface area

Halogen-based reconstruction of Russian Arctic sea ice area from the Akademii Nauk ice core (Severnaya Zemlya)

The role of sea ice in the Earth climate system is still under debate, although it is known to influence albedo, ocean circulation, and atmosphere-ocean heat and gas exchange. Here we present a reconstruction of 1950 to 1998AD sea ice in the Laptev Sea based on the Akademii Nauk ice core (Severnaya Zemlya, Russian Arctic). The chemistry of halogens bromine (Br) and iodine (I) is strongly active and influenced by sea ice dynamics, in terms of physical, chemical and biological process. Bromine reacts on the sea ice surface in autocatalyzing "bromine explosion" events, causing an enrichment of the Br/Na ratio and hence a bromine excess (Br-exc) in snow compared to that in seawater. Iodine is suggested to be emitted from algal communities growing under sea ice. The results suggest a connection between Br-exc and spring sea ice area, as well as a connection between iodine concentration and summer sea ice area. The correlation coefficients obtained between Br-exc and spring sea ice (r = 0.44) as well as between iodine and summer sea ice (r = 0.50) for the Laptev Sea suggest that these two halogens could become good candidates for extended reconstructions of past sea ice changes in the Arctic

The Hepatokine TSK does not affect brown fat thermogenic capacity, body weight gain, and glucose homeostasis

Objectives Hepatokines are proteins secreted by the liver that impact the functions of the liver and various tissues through autocrine, paracrine, and endocrine signaling. Recently, Tsukushi (TSK) was identified as a new hepatokine that is induced by obesity and cold exposure. It was proposed that TSK controls sympathetic innervation and thermogenesis in brown adipose tissue (BAT) and that loss of TSK protects against diet-induced obesity and improves glucose homeostasis. Here we report the impact of deleting and/or overexpressing TSK on BAT thermogenic capacity, body weight regulation, and glucose homeostasis. Methods We measured the expression of thermogenic genes and markers of BAT innervation and activation in TSK-null and TSK-overexpressing mice. Body weight, body temperature, and parameters of glucose homeostasis were also assessed in the context of TSK loss and overexpression. Results The loss of TSK did not affect the thermogenic activation of BAT. We found that TSK-null mice were not protected against the development of obesity and did not show improvement in glucose tolerance. The overexpression of TSK also failed to modulate thermogenesis, body weight gain, and glucose homeostasis in mice

Comparing composite likelihood methods based on pairs for spatial Gaussian random fields

In the last years there has been a growing interest in proposing methods for estimating covariance functions for geostatistical data. Among these, maximum likelihood estimators have nice features when we deal with a Gaussian model. However maximum likelihood becomes impractical when the number of observations is very large. In this work we review some solutions and we contrast them in terms of loss of statistical efficiency and computational burden. Specifically we focus on three types of weighted composite likelihood functions based on pairs and we compare them with the method of covariance tapering. Asymptotic properties of the three estimation methods are derived. We illustrate the effectiveness of the methods through theoretical examples, simulation experiments and by analyzing a data set on yearly total precipitation anomalies at weather stations in the United States.In the last years there has been a growing interest in proposing methods for estimating covariance functions for geostatistical data. Among these, maximum likelihood estimators have nice features when we deal with a Gaussian model. However maximum likelihood becomes impractical when the number of observations is very large. In this work we review some solutions and we contrast them in terms of loss of statistical efficiency and computational burden. Specifically we focus on three types of weighted composite likelihood functions based on pairs and we compare them with the method of covariance tapering. Asymptotic properties of the three estimation methods are derived. We illustrate the effectiveness of the methods through theoretical examples, simulation experiments and by analyzing a data set on yearly total precipitation anomalies at weather stations in the United States