A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification

Reliable application of machine learning-based decision systems in the wild is one of the major challenges currently investigated by the field. A large portion of established approaches aims to detect erroneous predictions by means of assigning confidence scores. This confidence may be obtained by either quantifying the model's predictive uncertainty, learning explicit scoring functions, or assessing whether the input is in line with the training distribution. Curiously, while these approaches all state to address the same eventual goal of detecting failures of a classifier upon real-life application, they currently constitute largely separated research fields with individual evaluation protocols, which either exclude a substantial part of relevant methods or ignore large parts of relevant failure sources. In this work, we systematically reveal current pitfalls caused by these inconsistencies and derive requirements for a holistic and realistic evaluation of failure detection. To demonstrate the relevance of this unified perspective, we present a large-scale empirical study for the first time enabling benchmarking confidence scoring functions w.r.t all relevant methods and failure sources. The revelation of a simple softmax response baseline as the overall best performing method underlines the drastic shortcomings of current evaluation in the abundance of publicized research on confidence scoring. Code and trained models are at https://github.com/IML-DKFZ/fd-shifts

Longitudinal photocurrent spectroscopy of a single GaAs/AlGaAs v-groove quantum wire

Modulation-doped GaAs v-groove quantum wires (QWRs) have been fabricated with novel electrical contacts made to two-dimensional electron-gas (2DEG) reservoirs. Here, we present longitudinal photocurrent (photoconductivity/PC) spectroscopy measurements of a single QWR. We clearly observe conductance in the ground-state one-dimensional subbands; in addition, a highly temperature-dependent response is seen from other structures within the v-groove. The latter phenomenon is attributed to the effects of structural topography and localization on carrier relaxation. The results of power-dependent PC measurements suggest that the QWR behaves as a series of weakly interacting localized states, at low temperatures

Electron surface layer at the interface of a plasma and a dielectric wall

We study the potential and the charge distribution across the interface of a plasma and a dielectric wall. For this purpose, the charge bound to the wall is modelled as a quasi-stationary electron surface layer which satisfies Poisson's equation and minimizes the grand canonical potential of the wall-thermalized excess electrons constituting the wall charge. Based on an effective model for a graded interface taking into account the image potential and the offset of the conduction band to the potential just outside the dielectric, we specifically calculate the potential and the electron distribution for magnesium oxide, silicon dioxide and sapphire surfaces in contact with a helium discharge. Depending on the electron affinity of the surface, we find two vastly different behaviors. For negative electron affinity, electrons do not penetrate into the wall and an external surface charge is formed in the image potential, while for positive electron affinity, electrons penetrate into the wall and a space charge layer develops in the interior of the dielectric. We also investigate how the electron surface layer merges with the bulk of the dielectric.Comment: 15 pages, 9 figures, accepted versio

Temperature-dependence of the phase-coherence length in InN nanowires

We report on low-temperature magnetotransport measurements on InN nanowires, grown by plasma-assisted molecular beam epitaxy. The characteristic fluctuation pattern observed in the conductance was employed to obtain information on phase-coherent transport. By analyzing the root-mean-square and the correlation field of the conductance fluctuations at various temperatures the phase-coherence length was determined.Comment: 4 pages, 4 figure

Distribution and Characteristics of Listeria spp. in Pigs and Pork Production Chains in Germany

Listeria (L.) monocytogenes is a foodborne pathogen that can cause disease, mainly in elderly, pregnant or immunocompromised persons through consumption of contaminated food, including pork products. It is widespread in the environment and can also be found in asymptomatic carrier animals, for example, in different tissues of pigs. To learn more about their nature, 16 Listeria spp. isolates found in tonsils and intestinal content of pigs and 13 isolates from the slaughterhouse environment were characterized using next-generation sequencing (NGS). A wide distribution of clonal complexes was observed in pigs, as well as in the pork production chain, suggesting multiple sources of entry. Hypervirulent clones were found in pig tonsils, showing the potential risk of pigs as source of isolates causing human disease. The presence of closely related isolates along the production chain suggests a cross-contamination in the slaughterhouse or recontamination from the same source, strengthening the importance of efficient cleaning and disinfection procedures. The phenotypical antimicrobial resistance status of L. monocytogenes isolates was examined via broth microdilution and revealed a low resistance level. Nevertheless, genotypical resistance data suggested multiple resistances in some non-pathogenic L. innocua isolates from pig samples, which might pose a risk of spreading resistances to pathogenic species

Effects by Paramagnetic and Diamagnetic Materials in a 1.5-Tesla Highfield Magnetic Resonance Imaging System (MRI)

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Dieser Artikel zeigt die Ergebnisse einer experimentellen Untersuchung des Störeinflusses von paramagnetischen und diamagnetischen Materialien auf die Bildgebung in einem geschlossenen 1,5-Tesla-Hochfeld-Magnetresonanztomographen(MRT). Mit drei verschiedenen Sequenztypen (SE, GE, EPI) wurden unterschiedlich große metallische und nichtmetallische Werkstückprofile hinsichtlich der entstehenden Artefakte untersucht. Zur Darstellung der Artefakte wurde ein mit Gd-Mn-Lösung gefüllter Kunststoffbehälter (Phantom) verwendet, zu dem die zu untersuchenden Materialien während der Versuchsdurchführung in definierten Abständen parallel verschoben wurden. Die Auswertung der Schnittbilder erfolgte in transversaler und sagittaler Untersuchungsebene und ergab, daß Aluminium- und Kunststoffprofile auch bei sehr geringem Abstand zum Phantom die kleinsten Bildstörungen verursachten. Besonders starke Artefakte wurden bei den untersuchten Stahl- und Kupferprofilen festgestellt. Bei einem Vergleich der angewendeten Sequenztypen konnte nachgewiesen werden, daß besonders die SE-Sequenz, trotz der teilweise stark variierenden Materialprofile, eine geringere Artefaktanfälligkeit und somit eine höhere Stabilität in der Bildgebung im Gegensatz zur GE- und EPI-Sequenz aufwies. Diese Untersuchungen wurden im Anschluß an eine intensive Literaturstudie (Internet, Medline, Meditec) durchgeführt. Relevante Publikationsquellen gibt es bisher nur sehr wenige.This article shows the results of an experimental investigation of the interference by paramagnetic and diamagnetic materials on imaging in a closed 1.5 Tesla high field magnetic resonance imaging System(MRI). For different types of sequences (SE, GE, EPI) the effects of metal and non-metal profiles in producing artefacts were investigated. A phantom (plastictrunk) filled with Gd-Mn-solution was used for representation of the artefacts. The materials analysed were placed parallel to the phantom at predetermined distances. The images were obtained in transverse and sagittal planes and analysed with respect to the resulting artefacts.The results show that aluminium and polymer profiles produce the weakest artefacts, even when the material is positioned close to the phantom. A comparison of the sequence types shows that the SE-sequence has a low sensitivity to artefacts, despite the great profile variation in size and shape. The SE-sequence accordingly showed a higher imaging stability scompared with the GE- and EPI-sequences. Steel and copper produced the strongest artefacts. The examination was begun after an intensive study of the literature(Internet, Medline, Meditec). So far have been few publications on this subject

The Mass Definition in Hqet and a New Determination of Vcb_{\text{cb}}

Positive powers of the mass parameter in a physical quantity calculated with the help of heavy quark effective theory originate from a Wilson coefficient in the matching of QCD and HQET Green function. We show that this mass parameter enters the calculation as a well--defined running current mass. We further argue that the recently found ill--definition of the pole mass, which is the natural expansion parameter of HQET, does not affect a phenomenological analysis which uses truncated perturbative series. We reanalyse inclusive semileptonic decays of heavy mesons and obtain the $c$ quark mass $m_c^{\overline{\text{MS}}}(m_c) = (1.35\pm 0.20)\,\text{GeV}$ where the error is almost entirely due to scale--uncertainties. We also obtain $m_b^{\overline{\text{MS}}}(m_b) = (4.6\pm 0.3)\,\text{GeV}$ and $|V_{cb}|(\tau_B/1.49\,\text{ps})^{1/2} = 0.036\pm 0.005$ where the errors come from the uncertainty in the kinetic energy of the heavy quark inside the meson, in the experimental branching ratios, in QCD input parameters, and scale--uncertainties.Comment: 21 p., 5 figs, all style files incl., TUM-T31-56/R (Sec. 2 revised, phenomenological results unchanged

cOOpD: Reformulating COPD classification on chest CT scans as anomaly detection using contrastive representations

Classification of heterogeneous diseases is challenging due to their complexity, variability of symptoms and imaging findings. Chronic Obstructive Pulmonary Disease (COPD) is a prime example, being underdiagnosed despite being the third leading cause of death. Its sparse, diffuse and heterogeneous appearance on computed tomography challenges supervised binary classification. We reformulate COPD binary classification as an anomaly detection task, proposing cOOpD: heterogeneous pathological regions are detected as Out-of-Distribution (OOD) from normal homogeneous lung regions. To this end, we learn representations of unlabeled lung regions employing a self-supervised contrastive pretext model, potentially capturing specific characteristics of diseased and healthy unlabeled regions. A generative model then learns the distribution of healthy representations and identifies abnormalities (stemming from COPD) as deviations. Patient-level scores are obtained by aggregating region OOD scores. We show that cOOpD achieves the best performance on two public datasets, with an increase of 8.2% and 7.7% in terms of AUROC compared to the previous supervised state-of-the-art. Additionally, cOOpD yields well-interpretable spatial anomaly maps and patient-level scores which we show to be of additional value in identifying individuals in the early stage of progression. Experiments in artificially designed real-world prevalence settings further support that anomaly detection is a powerful way of tackling COPD classification

Net Charge on a Noble Gas Atom Adsorbed on a Metallic Surface

Adsorbed noble gas atoms donate (on the average) a fraction of an electronic charge to the substrate metal. The effect has been experimentally observed as an adsorptive change in the electronic work function. The connection between the effective net atomic charge and the binding energy of the atom to the metal is theoretically explored.Comment: ReVvTeX 3.1 format, Two Figures, Three Table

Untersuchungen zur Ankopplung von gentechnisch modifizierten HEK293-Zellen an siliziumbasierte Transducer-Materialien

Um die elektrische Signalübertragung zwischen biologischen Systemen und Halbleitermaterialien zu untersuchen, beschäftigt sich die aktuelle Forschung in jüngster Zeit mit der direkten Ankopplung von Nervenzellen an Siliziumchips und Metallelektroden. Die Generierung elektrischer Impulse hängt dabei von Ionenkanälen in der Plasmamembran dieser Zellen ab. Mittels molekularbiologischer Verfahren fertigen wir gentechnisch modifizierte HEK 293 Zellen an. Es werden Zellinien hergestellt, die sowohl Dopamin-Rezeptoren, als auch zyklisch nukleotid-gesteuerte Ionenkanäle (CNG Kanäle) konstitutiv exprimieren. Die Dopamin-Rezeptoren erkennen spezifische Botenstoffe (Dopamin) in einer Lösung und erzeugen ein intrazelluläres biochemisches Signal. Es kommt zum Anstieg der intrazellulären Konzentration des Botenstoffes cAMP. Die CNG-Kanäle werden durch dieses zyklische Nukleotid direkt geöffnet. Mono- und divalente Kationen fließen durch den geöffneten Kanal in die Zelle. Die Zelle wird dabei elektrisch erregt und das Membranpotential ändert sich. Die Änderung des Membranpotentials soll als Meßgröße mit Hilfe eines Halbleiterchips gemessen werden. Gegenwärtig wird die bioelektronische Schnittstelle zwischen Zelle und Halbleiterstruktur im einzelnen charakterisiert. Dabei werden unterschiedliche Übertragungsmechanismen - an Hand von Mikroelektroden und kapazitiven Feldeffektstrukturen - auf der Basis von planarem, strukturiertem und porösem Silizium untersucht. Um die Haftung der Zellen auf den Siliziumchips zu verbessern, wurden die Chipoberflächen mittels verschiedener Methoden aktiviert (Sauerstoffplasmabehandlung, Poly-L-lysin, Laminin). Die Ergebnisse dieser Untersuchungen, sowie einleitende Ergebnisse, die die Signalübertragung an der Zell/Silizium-Schnittstelle betreffen, werden präsentiert und diskutiert