Towards Inferential Reproducibility of Machine Learning Research

Reliability of machine learning evaluation -- the consistency of observed evaluation scores across replicated model training runs -- is affected by several sources of nondeterminism which can be regarded as measurement noise. Current tendencies to remove noise in order to enforce reproducibility of research results neglect inherent nondeterminism at the implementation level and disregard crucial interaction effects between algorithmic noise factors and data properties. This limits the scope of conclusions that can be drawn from such experiments. Instead of removing noise, we propose to incorporate several sources of variance, including their interaction with data properties, into an analysis of significance and reliability of machine learning evaluation, with the aim to draw inferences beyond particular instances of trained models. We show how to use linear mixed effects models (LMEMs) to analyze performance evaluation scores, and to conduct statistical inference with a generalized likelihood ratio test (GLRT). This allows us to incorporate arbitrary sources of noise like meta-parameter variations into statistical significance testing, and to assess performance differences conditional on data properties. Furthermore, a variance component analysis (VCA) enables the analysis of the contribution of noise sources to overall variance and the computation of a reliability coefficient by the ratio of substantial to total variance.Comment: Published at ICLR 2023 (see https://openreview.net/pdf?id=li4GQCQWkv

The dynamic organization of fungal acetyl-CoA carboxylase

Acetyl-CoA carboxylases (ACCs) catalyse the committed step in fatty-acid biosynthesis: the ATP-dependent carboxylation of acetyl-CoA to malonyl-CoA. They are important regulatory hubs for metabolic control and relevant drug targets for the treatment of the metabolic syndrome and cancer. Eukaryotic ACCs are single-chain multienzymes characterized by a large, non-catalytic central domain (CD), whose role in ACC regulation remains poorly characterized. Here we report the crystal structure of the yeast ACC CD, revealing a unique four-domain organization. A regulatory loop, which is phosphorylated at the key functional phosphorylation site of fungal ACC, wedges into a crevice between two domains of CD. Combining the yeast CD structure with intermediate and low-resolution data of larger fragments up to intact ACCs provides a comprehensive characterization of the dynamic fungal ACC architecture. In contrast to related carboxylases, large-scale conformational changes are required for substrate turnover, and are mediated by the CD under phosphorylation control

Ensembling Neural Networks for Improved Prediction and Privacy in Early Diagnosis of Sepsis

Ensembling neural networks is a long-standing technique for improving the generalization error of neural networks by combining networks with orthogonal properties via a committee decision. We show that this technique is an ideal fit for machine learning on medical data: First, ensembles are amenable to parallel and asynchronous learning, thus enabling efficient training of patient-specific component neural networks. Second, building on the idea of minimizing generalization error by selecting uncorrelated patient-specific networks, we show that one can build an ensemble of a few selected patient-specific models that outperforms a single model trained on much larger pooled datasets. Third, the non-iterative ensemble combination step is an optimal low-dimensional entry point to apply output perturbation to guarantee the privacy of the patient-specific networks. We exemplify our framework of differentially private ensembles on the task of early prediction of sepsis, using real-life intensive care unit data labeled by clinical experts.Comment: Accepted at MLHC 202

Small-scale structure of cold dark matter

We investigate the clumping of cold dark matter (CDM) at small scales. If the CDM particle is the neutralino, we find that collisional damping during its kinetic decoupling from the radiation fluid and free streaming introduce a small-scale cut-off in the primordial power spectrum of CDM. This cut-off sets the scale for the very first CDM objects in the Universe, which we expect to have a mass of $\sim 10^{-12} M_\odot$. For non-thermal CDM candidates, such as axions, wimpzillas, or primordial black holes, the cosmological QCD transition might induce features in the primordial spectrum at similar mass scales.Comment: 3 pages, talk given at TAUP99, Pari

Travel-Associated Zika Virus Disease Acquired in the Americas Through February 2016

BACKGROUND: Zika virus has spread rapidly in the Americas and has been imported into many nonendemic countries by travelers. OBJECTIVE: To describe clinical manifestations and epidemiology of Zika virus disease in travelers exposed in the Americas. DESIGN: Descriptive, using GeoSentinel records. SETTING: 63 travel and tropical medicine clinics in 30 countries. PATIENTS: Ill returned travelers with a confirmed, probable, or clinically suspected diagnosis of Zika virus disease seen between January 2013 and 29 February 2016. MEASUREMENTS: Frequencies of demographic, trip, and clinical characteristics and complications. RESULTS: Starting in May 2015, 93 cases of Zika virus disease were reported. Common symptoms included exanthema (88%), fever (76%), and arthralgia (72%). Fifty-nine percent of patients were exposed in South America; 71% were diagnosed in Europe. Case status was established most commonly by polymerase chain reaction (PCR) testing of blood and less often by PCR testing of other body fluids or serology and plaque-reduction neutralization testing. Two patients developed Guillain–Barre syndrome, and 3 of 4 pregnancies had adverse outcomes (microcephaly, major fetal neurologic abnormalities, and intrauterine fetal death). LIMITATION: Surveillance data collected by specialized clinics may not be representative of all ill returned travelers, and denominator data are unavailable. CONCLUSION: These surveillance data help characterize the clinical manifestations and adverse outcomes of Zika virus disease among travelers infected in the Americas and show a need for global standardization of diagnostic testing. The serious fetal complications observed in this study highlight the importance of travel advisories and prevention measures for pregnant women and their partners. Travelers are sentinels for global Zika virus circulation and may facilitate further transmission

Development and validation of a sensor prototype for near-infrared imaging of the newborn brain

Imaging brain oxygenation is crucial for preventing brain lesions in preterm infants. Our aim is to build and validate a near-infrared optical tomography (NIROT) sensor for the head of neonates. This sensor, combined with an optoacoustic device, will enable quantitative monitoring of the structural and functional information of the brain. Since the head of preterm infants is small and fragile great care must be taken to produce a comfortable and compact device in which a sufficient number of light sources and detectors can be implemented. Here we demonstrate our first prototype. Heterogeneous silicone phantoms were produced to validate the prototype's data acquisition, data processing, and image reconstruction. Reconstructed optical properties agree well with the target values. The mechanical performance of the new NIROT sensor prototype confirms its suitability for the clinical application

3D printing of functional assemblies with integrated polymer-bonded magnets demonstrated with a prototype of a rotary blood pump

Conventional magnet manufacturing is a significant bottleneck in the development processes of products that use magnets, because every design adaption requires production steps with long lead times. Additive manufacturing of magnetic components delivers the opportunity to shift to agile and test-driven development in early prototyping stages, as well as new possibilities for complex designs. In an effort to simplify integration of magnetic components, the current work presents a method to directly print polymer-bonded hard magnets of arbitrary shape into thermoplastic parts by fused deposition modeling. This method was applied to an early prototype design of a rotary blood pump with magnetic bearing and magnetic drive coupling. Thermoplastics were compounded with 56 vol.% isotropic NdFeB powder to manufacture printable filament. With a powder loading of 56 vol.%, remanences of 350 mT and adequate mechanical flexibility for robust processability were achieved. This compound allowed us to print a prototype of a turbodynamic pump with integrated magnets in the impeller and housing in one piece on a low-cost, end-user 3D printer. Then, the magnetic components in the printed pump were fully magnetized in a pulsed Bitter coil. The pump impeller is driven by magnetic coupling to non-printed permanent magnets rotated by a brushless DC motor, resulting in a flow rate of 3 L/min at 1000 rpm. For the first time, an application of combined multi-material and magnet printing by fused deposition modeling was shown. The presented process significantly simplifies the prototyping of products that use magnets, such as rotary blood pumps, and opens the door for more complex and innovative designs. It will also help postpone the shift to conventional manufacturing methods to later phases of the development process

Mitgliedschaft - das magische Mittel zur Herstellung von Konformität in Organisationen

Kühl S. Mitgliedschaft - das magische Mittel zur Herstellung von Konformität in Organisationen. In: Bucher B, Hagmann T, Kuhn R, Thomann G, eds. Loyalität. Resonanz - Gestalten von Organisationen in flüchtigen Zeiten. Vol 2. 1st ed. Bern: hep verlag; 2011: 48-68

Detection of inspiratory recruitment of atelectasis by automated lung sound analysis as compared to four-dimensional computed tomography in a porcine lung injury model

Background: Cyclic recruitment and de-recruitment of atelectasis (c-R/D) is a contributor to ventilator-induced lung injury (VILI). Bedside detection of this dynamic process could improve ventilator management. This study investigated the potential of automated lung sound analysis to detect c-R/D as compared to four-dimensional computed tomography (4DCT). Methods: In ten piglets (25 ± 2 kg), acoustic measurements from 34 thoracic piezoelectric sensors (Meditron ASA, Norway) were performed, time synchronized to 4DCT scans, at positive end-expiratory pressures of 0, 5, 10, and 15 cmH2O during mechanical ventilation, before and after induction of c-R/D by surfactant washout. 4DCT was post-processed for within-breath variation in atelectatic volume (Δ atelectasis) as a measure of c-R/D. Sound waveforms were evaluated for: 1) dynamic crackle energy (dCE): filtered crackle sounds (600–700 Hz); 2) fast Fourier transform area (FFT area): spectral content above 500 Hz in frequency and above −70 dB in amplitude in proportion to the total amount of sound above −70 dB amplitude; and 3) dynamic spectral coherence (dSC): variation in acoustical homogeneity over time. Parameters were analyzed for global, nondependent, central, and dependent lung areas. Results: In healthy lungs, negligible values of Δ atelectasis, dCE, and FFT area occurred. In lavage lung injury, the novel dCE parameter showed the best correlation to Δ atelectasis in dependent lung areas (R2 = 0.88) where c-R/D took place. dCE was superior to FFT area analysis for each lung region examined. The analysis of dSC could predict the lung regions where c-R/D originated. Conclusions: c-R/D is associated with the occurrence of fine crackle sounds as demonstrated by dCE analysis. Standardized computer-assisted analysis of dCE and dSC seems to be a promising method for depicting c-R/D