A statistical analysis of neural computation

This paper presents an architecture and learning algorithm for a feedforward neural network implementing a two pattern (image) classifier. By considering the input pixels to be random variables, a statistical binary hypothesis (likelihood ratio) test is implemented. A linear threshold separates p[X|H_0] and p[X|H_1], minimizing a risk function. In this manner, a single neuron is considered as a BSC with the pdf error tails probability ε. A Single layer of neurons is viewed as a parallel bank of independent BSC’s, which is equivalent to a single effective BSC representing that layer’s hypothesis testing performance. A multiple layer network is viewed as a cascade of BSC channels, and which again collapses into a single effective BSC

A statistical analysis of neural computation

This paper presents an architecture and learning algorithm for a feedforward neural network implementing a two pattern (image) classifier. By considering the input pixels to be random variables, a statistical binary hypothesis (likelihood ratio) test is implemented. A linear threshold separates p[X|H_0] and p[X|H_1], minimizing a risk function. In this manner, a single neuron is considered as a BSC with the pdf error tails probability ε. A Single layer of neurons is viewed as a parallel bank of independent BSC’s, which is equivalent to a single effective BSC representing that layer’s hypothesis testing performance. A multiple layer network is viewed as a cascade of BSC channels, and which again collapses into a single effective BSC

Author Correction: A consensus-based transparency checklist.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

A consensus-based transparency checklist

We present a consensus-based checklist to improve and document the transparency of research reports in social and behavioural research. An accompanying online application allows users to complete the form and generate a report that they can submit with their manuscript or post to a public repository

The SAMI Galaxy Survey: Cubism and covariance, putting round pegs into square holes

We present a methodology for the regularization and combination of sparse sampled and irregularly gridded observations from fibre-optic multiobject integral field spectroscopy. The approach minimizes interpolation and retains image resolution on combining subpixel dithered data. We discuss the methodology in the context of the Sydney-AAO multiobject integral field spectrograph (SAMI) Galaxy Survey underway at the Anglo-Australian Telescope. The SAMI instrument uses 13 fibre bundles to perform high-multiplex integral field spectroscopy across a 1° diameter field of view. The SAMI Galaxy Survey is targeting ~3000 galaxies drawn from the full range of galaxy environments. We demonstrate the subcritical sampling of the seeing and incomplete fill factor for the integral field bundles results in only a 10 per cent degradation in the final image resolution recovered. We also implement a new methodology for tracking covariance between elements of the resulting data cubes which retains 90 per cent of the covariance information while incurring only a modest increase in the survey data volume

2019 update of the WSES guidelines for management of Clostridioides (Clostridium) difficile infection in surgical patients

In the last three decades, Clostridium difficile infection (CDI) has increased in incidence and severity in many countries worldwide. The increase in CDI incidence has been particularly apparent among surgical patients. Therefore, prevention of CDI and optimization of management in the surgical patient are paramount. An international multidisciplinary panel of experts from the World Society of Emergency Surgery (WSES) updated its guidelines for management of CDI in surgical patients according to the most recent available literature. The update includes recent changes introduced in the management of this infection.Peer reviewe

South American Plasmodium falciparum after the Malaria Eradication Era: Clonal Population Expansion and Survival of the Fittest Hybrids

Malaria has reemerged in many regions where once it was nearly eliminated. Yet the source of these parasites, the process of repopulation, their population structure, and dynamics are ill defined. Peru was one of malaria eradication's successes, where Plasmodium falciparum was nearly eliminated for two decades. It reemerged in the 1990s. In the new era of malaria elimination, Peruvian P. falciparum is a model of malaria reinvasion. We investigated its population structure and drug resistance profiles. We hypothesized that only populations adapted to local ecological niches could expand and repopulate and originated as vestigial populations or recent introductions. We investigated the genetic structure (using microsatellites) and drug resistant genotypes of 220 parasites collected from patients immediately after peak epidemic expansion (1999–2000) from seven sites across the country. The majority of parasites could be grouped into five clonal lineages by networks and AMOVA. The distribution of clonal lineages and their drug sensitivity profiles suggested geographic structure. In 2001, artesunate combination therapy was introduced in Peru. We tested 62 parasites collected in 2006–2007 for changes in genetic structure. Clonal lineages had recombined under selection for the fittest parasites. Our findings illustrate that local adaptations in the post-eradication era have contributed to clonal lineage expansion. Within the shifting confluence of drug policy and malaria incidence, populations continue to evolve through genetic outcrossing influenced by antimalarial selection pressure. Understanding the population substructure of P. falciparum has implications for vaccine, drug, and epidemiologic studies, including monitoring malaria during and after the elimination phase

The population of merging compact binaries inferred using gravitational waves through GWTC-3

We report on the population properties of 76 compact binary mergers detected with gravitational waves below a false alarm rate of 1 per year through GWTC-3. The catalog contains three classes of binary mergers: BBH, BNS, and NSBH mergers. We infer the BNS merger rate to be between 10 $\rm{Gpc^{-3} yr^{-1}}$ and 1700 $\rm{Gpc^{-3} yr^{-1}}$ and the NSBH merger rate to be between 7.8 $\rm{Gpc^{-3}\, yr^{-1}}$ and 140 $\rm{Gpc^{-3} yr^{-1}}$ , assuming a constant rate density versus comoving volume and taking the union of 90% credible intervals for methods used in this work. Accounting for the BBH merger rate to evolve with redshift, we find the BBH merger rate to be between 17.9 $\rm{Gpc^{-3}\, yr^{-1}}$ and 44 $\rm{Gpc^{-3}\, yr^{-1}}$ at a fiducial redshift (z=0.2). We obtain a broad neutron star mass distribution extending from $1.2^{+0.1}_{-0.2} M_\odot$ to $2.0^{+0.3}_{-0.3} M_\odot$. We can confidently identify a rapid decrease in merger rate versus component mass between neutron star-like masses and black-hole-like masses, but there is no evidence that the merger rate increases again before 10 $M_\odot$. We also find the BBH mass distribution has localized over- and under-densities relative to a power law distribution. While we continue to find the mass distribution of a binary's more massive component strongly decreases as a function of primary mass, we observe no evidence of a strongly suppressed merger rate above $\sim 60 M_\odot$. The rate of BBH mergers is observed to increase with redshift at a rate proportional to $(1+z)^{\kappa}$ with $\kappa = 2.9^{+1.7}_{-1.8}$ for $z\lesssim 1$. Observed black hole spins are small, with half of spin magnitudes below $\chi_i \simeq 0.25$. We observe evidence of negative aligned spins in the population, and an increase in spin magnitude for systems with more unequal mass ratio