Stochastic Particle Flow for Nonlinear High-Dimensional Filtering Problems

A series of novel filters for probabilistic inference that propose an alternative way of performing Bayesian updates, called particle flow filters, have been attracting recent interest. These filters provide approximate solutions to nonlinear filtering problems. They do so by defining a continuum of densities between the prior probability density and the posterior, i.e. the filtering density. Building on these methods' successes, we propose a novel filter. The new filter aims to address the shortcomings of sequential Monte Carlo methods when applied to important nonlinear high-dimensional filtering problems. The novel filter uses equally weighted samples, each of which is associated with a local solution of the Fokker-Planck equation. This hybrid of Monte Carlo and local parametric approximation gives rise to a global approximation of the filtering density of interest. We show that, when compared with state-of-the-art methods, the Gaussian-mixture implementation of the new filtering technique, which we call Stochastic Particle Flow, has utility in the context of benchmark nonlinear high-dimensional filtering problems. In addition, we extend the original particle flow filters for tackling multi-target multi-sensor tracking problems to enable a comparison with the new filter

Understanding the Role of Expert Intuition in Medical Image Annotation: A Cognitive Task Analysis Approach

To improve contemporary machine learning (ML) models, research is increasingly looking at tapping in and incorporating the knowledge of domain experts. However, expert knowledge often relies on intuition, which is difficult to formalize for incorporation into ML models. Against this backdrop, we investigate the role of intuition in the context of expert medical image annotation. We apply a cognitive task analysis approach, where we observe and interview six expert medical image annotators to gain insights into pertinent decision cues and the role of intuition during annotation. Our results show that intuition plays an important role in various steps of the medical image annotation process, particularly in the appraisals of very easy or very difficult images, and in case purely cognitive appraisals remain inconclusive. Overall, we contribute to a better understanding of expert intuition in medical image annotation and provide possible interfaces to incorporate said intuition into ML models

Understanding the Role of Expert Intuition in Medical Image Annotation: A Cognitive Task Analysis Approach

​To improve contemporary machine learning (ML) models, research is increasingly looking at tapping in and incorporating the knowledge of domain experts. However, expert knowledge often relies on intuition, which is difficult to formalize for incorporation into ML models. Against this backdrop, we investigate the role of intuition in the context of expert medical image annotation. We apply a cognitive task analysis approach, where we observe and interview six expert medical image annotators to gain insights into pertinent decision cues and the role of intuition during annotation. Our results show that intuition plays an important role in various steps of the medical image annotation process, particularly in the appraisals of very easy or very difficult images, and in case purely cognitive appraisals remain inconclusive. Overall, we contribute to a better understanding of expert intuition in medical image annotation and provide possible interfaces to incorporate said intuition into ML models

Mothers Reveal More of Their Vocal Identity When Talking to Infants

Voice timbre – the unique acoustic information in a voice by which its speaker can be recognized – is particularly critical in mother-infant interaction. Correct identification of vocal timbre is necessary in order for infants to recognize their mothers as familiar both before and after birth, providing a basis for social bonding between infant and mother. The exact mechanisms underlying infant voice recognition remain ambiguous and have predominantly been studied in terms of cognitive voice recognition abilities of the infant. Here, we show – for the first time – that caregivers actively maximize their chances of being correctly recognized by presenting more details of their vocal timbre through adjustments to their voices known as infant-directed speech (IDS) or baby talk, a vocal register which is wide-spread through most of the world’s cultures. Using acoustic modelling (k-means clustering of Mel Frequency Cepstral Coefficients) of IDS in comparison with adult-directed speech (ADS), we found in two cohorts of speakers - US English and Swiss German mothers - that voice timbre clusters of in IDS are significantly larger to comparable clusters in ADS. This effect leads to a more detailed representation of timbre in IDS with subsequent benefits for recognition. Critically, an automatic speaker identification using a Gaussian-mixture model based on Mel Frequency Cepstral Coefficients showed significantly better performance in two experiments when trained with IDS as opposed to ADS. We argue that IDS has evolved as part of an adaptive set of evolutionary strategies that serve to promote indexical signalling by caregivers to their offspring which thereby promote social bonding via voice and acquiring linguistic systems

Metatranscriptomic Sequencing of a Cyanobacterial Soil-Surface Consortium with and without a Diverse Underlying Soil Microbiome.

Soil surface consortia are easily observed and sampled, allowing examination of their interactions with soil microbiomes. Here, we present metatranscriptomic sequences from Dark Green 1 (DG1), a cyanobacterium-based soil surface consortium, in the presence and absence of an underlying soil microbiome and/or urea

Tourette-like behaviors in the normal population are associated with hyperactive/impulsive ADHD-like behaviors but do not relate to deficits in conditioned inhibition or response inhibition

Attention-Deficit Hyperactivity Disorder (ADHD) and Tourette Syndrome (TS) present as distinct conditions clinically; however, comorbidity and inhibitory control deficits have been proposed for both. Whilst such deficits have been studied widely within clinical populations, findings are mixed — partly due to comorbidity and/or medication effects — and studies have rarely distinguished between subtypes of the disorders. Studies in the general population are sparse. Using a continuity approach, the present study examined (i) the relationships between inattentive and hyperactive/impulsive aspects of ADHD and TS-like behaviors in the general population, and (ii) their unique associations with automatic and executive inhibitory control, as well as (iii) yawning (a proposed behavioural model of TS). One hundred and thirty-eight participants completed self-report measures for ADHD and TS-like behaviors as well as yawning, and aconditioned inhibition task to assess automatic inhibition

Semantic Enrichment for Building Information Modeling: Procedure for Compiling Inference Rules and Operators for Complex Geometry

Semantic enrichment of building models adds meaningful domain-specific or application-specific information to a digital building model. It is applicable to solving interoperability problems and to compilation of models from point cloud data. The SeeBIM (Semantic Enrichment Engine for BIM) prototype software encapsulates domain expert knowledge in computer readable rules for inference of object types, identity and aggregation of systems. However, it is limited to axis-aligned bounding box geometry and the adequacy of its rule-sets cannot be guaranteed. This paper solves these drawbacks by (1) devising a new procedure for compiling inference rule sets that are known a priori to be adequate for complete and thorough classification of model objects, and (2) enhancing the operators to compute complex geometry and enable precise topological rule processing. The procedure for compiling adequate rule sets is illustrated using a synthetic concrete highway bridge model. A real-world highway bridge model, with 333 components of 13 different types and compiled from a laser scanned point cloud, is used to validate the approach and test the enhanced SeeBIM system. All of the elements are classified correctly, demonstrating the efficacy of the approach to semantic enrichment

Successive translocation into and out of the mitochondrial matrix

We investigated the import and sorting pathways of cytochrome b2 and cytochrome c1, which are functionally located in the intermembrane space of mitochondria. Both proteins are synthesized on cytoplasmic ribosomes as larger precursors and are processed in mitochondria in two steps upon import. The precursors are first translocated across both mitochondrial membranes via contact sites into the matrix. Processing by the matrix peptidase leads to intermediate-sized forms, which are subsequently redirected across the inner membrane. The second proteolytic processing occurs in the intermembrane space. We conclude that the hydrophobic stretches in the presequences of the intermediate-sized forms do not stop transfer across the inner membrane, but rather act as transport signals to direct export from the matrix into the intermembrane space

Functional Expression of Human Adenine Nucleotide Translocase 4 in Saccharomyces Cerevisiae

The adenine nucleotide translocase (ANT) mediates the exchange of ADP and ATP across the inner mitochondrial membrane. The human genome encodes multiple ANT isoforms that are expressed in a tissue-specific manner. Recently a novel germ cell-specific member of the ANT family, ANT4 (SLC25A31) was identified. Although it is known that targeted depletion of ANT4 in mice resulted in male infertility, the functional biochemical differences between ANT4 and other somatic ANT isoforms remain undetermined. To gain insight into ANT4, we expressed human ANT4 (hANT4) in yeast mitochondria. Unlike the somatic ANT proteins, expression of hANT4 failed to complement an AAC-deficient yeast strain for growth on media requiring mitochondrial respiration. Moreover, overexpression of hANT4 from a multi-copy plasmid interfered with optimal yeast growth. However, mutation of specific amino acids of hANT4 improved yeast mitochondrial expression and supported growth of the AAC-deficient yeast on non-fermentable carbon sources. The mutations affected amino acids predicted to interact with phospholipids, suggesting the importance of lipid interactions for function of this protein. Each mutant hANT4 and the somatic hANTs exhibited similar ADP/ATP exchange kinetics. These data define common and distinct biochemical characteristics of ANT4 in comparison to ANT1, 2 and 3 providing a basis for study of its unique adaptation to germ cells