Unsupervised Learning of Invariance Transformations

The need for large amounts of training data in modern machine learning is one of the biggest challenges of the field. Compared to the brain, current artificial algorithms are much less capable of learning invariance transformations and employing them to extrapolate knowledge from small sample sets. It has recently been proposed that the brain might encode perceptual invariances as approximate graph symmetries in the network of synaptic connections. Such symmetries may arise naturally through a biologically plausible process of unsupervised Hebbian learning. In the present paper, we illustrate this proposal on numerical examples, showing that invariance transformations can indeed be recovered from the structure of recurrent synaptic connections which form within a layer of feature detector neurons via a simple Hebbian learning rule. In order to numerically recover the invariance transformations from the resulting recurrent network, we develop a general algorithmic framework for finding approximate graph automorphisms. We discuss how this framework can be used to find approximate automorphisms in weighted graphs in general

Type I interferon regulation by USP18 is a key vulnerability in cancer

Precise regulation of Type I interferon signaling is crucial for combating infection and cancer while avoiding autoimmunity. Type I interferon signaling is negatively regulated by USP18. USP18 cleaves ISG15, an interferon-induced ubiquitin-like modification, via its canonical catalytic function, and inhibits Type I interferon receptor activity through its scaffold role. USP18 loss-of-function dramatically impacts immune regulation, pathogen susceptibility, and tumor growth. However, prior studies have reached conflicting conclusions regarding the relative importance of catalytic versus scaffold function. Here, we develop biochemical and cellular methods to systematically define the physiological role of USP18. By comparing a patient-derived mutation impairing scaffold function (I60N) to a mutation disrupting catalytic activity (C64S), we demonstrate that scaffold function is critical for cancer cell vulnerability to Type I interferon. Surprisingly, we discovered that human USP18 exhibits minimal catalytic activity, in stark contrast to mouse USP18. These findings resolve human USP18's mechanism-of-action and enable USP18-targeted therapeutics

Cyber-physical production system for energy-flexible control of production machines

Since the share of renewable energy continues to grow, the resulting fluctuations of energy supply in the electricity grid must be balanced. Electricity consumers can help achieving this by reacting to fluctuations in supply and adjusting their demand (demand response). As one of the largest electricity consumers, industry should embrace this opportunity by implementing energy flexibility measures for demand response. In an energy-flexible production, machines have multiple objectives: First they must meet the traditional production targets: high quality, low cost, and short production time. Additionally, they should react to electricity price signals or to external power change requests and adjust their electrical consumption, for example by interrupting an active process. Forecasts of future machine behavior including energy consumption and the state of machine components help to improve the effectiveness of a proposed energy-flexible controller that enables machines to achieve these objectives. In addition, the machine and the controller must communicate with each other and external sources. Therefore, we propose the implementation of a cyber-physical production system (CPPS) for energy-flexible operation of production machines. Our CPPS consists of a simulation model for forecasting, an automation data model for controlling production machines via OPC UA and of a software framework, which is based on co-simulation, to provide the environment for controlling and optimizing the production machine in an energy-flexible manner. We show that co-simulation can be used to achieve energy-flexible operation of production machines and avoid unsafe states of the system. We apply the framework to an aqueous component cleaning machine performing a batch process. The operation of the electric tank heating element and the start times of cleaning process steps are optimized. With this work we show the successful development of the CPPS and the corresponding software framework, which will be transferred to other machines and more complex controllers in the future

The DPRM Theorem in Isabelle (Short Paper)

Hilbert\u27s 10th problem asks for an algorithm to tell whether or not a given diophantine equation has a solution over the integers. The non-existence of such an algorithm was shown in 1970 by Yuri Matiyasevich. The key step is known as the DPRM theorem: every recursively enumerable set of natural numbers is Diophantine. We present the formalization of Matiyasevich\u27s proof of the DPRM theorem in Isabelle. To represent recursively enumerable sets in equations, we implement and arithmetize register machines. Using several number-theoretic lemmas, we prove that exponentiation has a diophantine representation. Further, we contribute a small library of number-theoretic implementations of binary digit-wise relations. Finally, we discuss and contribute an is_diophantine predicate. We expect the complete formalization of the DPRM theorem in the near future; at present it is complete except for a minor gap in the arithmetization proofs of register machines and extending the is_diophantine predicate by two binary digit-wise relations

Comparing Medical and Recreational Cannabis Users on Socio-Demographic, Substance and Medication Use, and Health and Disability Characteristics

Background: While recreational cannabis use is common, medical cannabis programs have proliferated across North America, including a federal program in Canada. Few comparisons of medical and recreational cannabis users (RCUs) exist; this study compared these groups on key characteristics. Methods: Data came from a community-recruited sample of formally approved medical cannabis users (MCUs; n = 53), and a sub-sample of recreational cannabis users (RCUs; n = 169) from a representative adult survey in Ontario (Canada). Samples were telephone-surveyed on identical measures, including select socio-demographic, substance and medication use, and health and disability measures. Based on initial bivariate comparisons, multivariate logistical regression with a progressive adjustment approach was performed to assess independent predictors of group status. Results: In bivariate analyses, older age, lower household income, lower alcohol use, higher cocaine, prescription opioid, depression and anxiety medication use, and lower health and disability status were significantly associated with medical cannabis use. In the multivariate analysis, final model, household income, alcohol use, and disability levels were associated with medical cannabis use. Conclusions/Scientific Significance: Compared to RCUs, medical users appear to be mainly characterized by factors negatively influencing their overall health status. Future studies should investigate the actual impact and net benefits of medical cannabis use on these health problems

Multimodal Evaluation of Long-Term Salivary Gland Alterations in Sarcoidosis

Background: Sarcoidosis is a systemic inflammatory disease characterized by non-caseating granulomas. In addition to the lungs as classical site of affection, extrapulmonary manifestations are common, for example in the cervical lymph nodes or the salivary glands. The aim of this investigation is the analysis of the long-term course of glandular symptoms and the sonographic evaluation of long-term salivary gland changes. Material and methods: All patients with a diagnosis of sarcoidosis over a period of 20 years in the departments of otorhinolaryngology, rheumatology, and pneumology were identified. In addition to clinical examinations and functional evaluation of the salivary glands, a sonographic examination of the salivary glands was carried out. The changes in the area of the salivary glands were assessed using B-mode sonography and different elastographic methods with appropriate scoring systems. Results: A total of 76 patients were included in the study (age 35.1 ± 21.6 years). Overall, 17 patients presented with salivary gland manifestation at the time of the initial diagnosis. Of these patients, 15 received steroid therapy, 6 were also treated with another drug, and 2 patients were not treated with drugs. The time span between initial diagnosis and follow-up was 88.2 months (±83.0). At the time of the initial diagnosis, 17/17 complained of swelling of the salivary glands, 9/17 of xerostomia, and 8/17 of pain in the area of the salivary glands. At the time of follow-up, 5/17 reported swelling of the salivary glands, 6/17 reported xerostomia, and 1/17 reported pain in the salivary gland area. Sonography showed sonomorphological abnormalities of the salivary glands only in individual cases, with only mild alterations on average. Conclusion: In summary, it can be observed that patients with initial symptoms in the area of the salivary glands, such as swelling or pain, also suffer more frequently from dry mouth and eyes. In all patients, however, these symptoms regressed over time. A previous diagnosis of sarcoidosis with involvement of the salivary glands only leads to permanent abnormalities in the area of the salivary glands in individual cases

Deep Convolutional Neural Networks Provide Motion Grading for High-Resolution Peripheral Quantitative Computed Tomography of the Scaphoid

In vivo high-resolution peripheral quantitative computed tomography (HR-pQCT) studies on bone characteristics are limited, partly due to the lack of standardized and objective techniques to describe motion artifacts responsible for lower-quality images. This study investigates the ability of such deep-learning techniques to assess image quality in HR-pQCT datasets of human scaphoids. In total, 1451 stacks of 482 scaphoid images from 53 patients, each with up to six follow-ups within one year, and each with one non-displaced fractured and one contralateral intact scaphoid, were independently graded by three observers using a visual grading scale for motion artifacts. A 3D-CNN was used to assess image quality. The accuracy of the 3D-CNN to assess the image quality compared to the mean results of three skilled operators was between 92% and 96%. The 3D-CNN classifier reached an ROC-AUC score of 0.94. The average assessment time for one scaphoid was 2.5 s. This study demonstrates that a deep-learning approach for rating radiological image quality provides objective assessments of motion grading for the scaphoid with a high accuracy and a short assessment time. In the future, such a 3D-CNN approach can be used as a resource-saving and cost-effective tool to classify the image quality of HR-pQCT datasets in a reliable, reproducible and objective way

Moral processing deficit in behavioral variant frontotemporal dementia is associated with facial emotion recognition and brain changes in default mode and salience network areas

Introduction: Behavioral variant frontotemporal dementia (bvFTD) is associated with abnormal emotion recognition and moral processing. Methods: We assessed emotion detection, discrimination, matching, selection, and categorization as well as judgments of nonmoral, moral impersonal, moral personal low- and high-conflict scenarios. Results: bvFTD patients gave more utilitarian responses on low-conflict personal moral dilemmas. There was a significant correlation between a facial emotion processing measure derived through principal component analysis and utilitarian responses on low-conflict personal scenarios in the bvFTD group (controlling for MMSE-score and syntactic abilities). Voxel-based morphometric multiple regression analysis in the bvFTD group revealed a significant association between the proportion of utilitarian responses on personal low-conflict dilemmas and gray matter volume in ventromedial prefrontal areas (pheight < .0001). In addition, there was a correlation between utilitarian responses on low-conflict personal scenarios in the bvFTD group and resting-state fractional Amplitude of Low Frequency Fluctuations (fALFF) in the anterior insula (pheight < .005). Conclusions: The results underscore the importance of emotions in moral cognition and suggest a common basis for deficits in both abilities, possibly related to reduced experience of emotional sensations. At the neural level abnormal moral cognition in bvFTD is related to structural integrity of the medial prefrontal cortex and functional characteristics of the anterior insula. The present findings provide a common basis for emotion recognition and moral reasoning and link them with areas in the default mode and salience network.status: publishe

Formation Dominates Resorption With Increasing Mineralized Density and Time Postfracture in Cortical but Not Trabecular Bone: A Longitudinal HRpQCT Imaging Study in the Distal Radius

ABSTRACT Clinical evaluation of fracture healing is often limited to an assessment of fracture bridging from radiographic images, without consideration for other aspects of bone quality. However, recent advances in HRpQCT offer methods to accurately monitor microstructural bone remodeling throughout the healing process. In this study, local bone formation and resorption were investigated during the first year post fracture in both the fractured (n = 22) and contralateral (n = 19) radii of 34 conservatively treated patients (24 female, 10 male) who presented with a unilateral radius fracture at the Innsbruck University Hospital, Austria. HRpQCT images and clinical metrics were acquired at six time points for each patient. The standard HRpQCT image acquisition was captured for all radii, with additional distal and proximal image acquisitions for the fractured radii. Measured radial bone densities were isolated with a voxel‐based mask and images were rigidly registered to images from the previous imaging session using a pyramid‐based approach. From the registered images, bone formation and resorption volume fractions were quantified for multiple density‐based thresholds and compared between the fractured and contralateral radius and relative to demographics, bone morphometrics, and fracture metrics using regression. Compared with the contralateral radius, both bone formation and resorption were significantly increased in the fractured radius throughout the study for nearly all evaluated thresholds. Higher density cortical bone formation continually increased throughout the duration of the study and was significantly greater than resorption during late‐stage healing in both the fractured and intact regions of the radius. With the small and diverse study population, only weak relationships between fracture remodeling and patient‐specific parameters were unveiled. However this study provides methods for the analysis of local bone remodeling during fracture healing and highlights relevant considerations for future studies, specifically that remodeling postfracture is likely to continue beyond 12‐months postfracture. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research