Geochemie und mikroskalige Elementverteilung in lateritischen Verwitterungsresiduen - Bohnerze

Bohnerze der oberjurassischen Kalkgebiete Süddeutschlands gelten aufgrund neuerer Studien als umgelagerte Residuen eines lateritischen Verwitterungsregimes während der Kreide und des Eozäns. Durch mineralogisch-chemische Analysen sowie der Erstellung von Elementbildern gelang eine näherungsweise Zuordnung von morphologisch unterscheidbaren Bohnerzformen zu den einzelnen Bereichen eines Lateritprofils. Dabei entsprechen pisoidische Bohnerze lateritischen Konkretionen aus dem Degradationsbereich am Übergang einer Eisenkruste (eigentlicher Laterit/Ferricrete) zum Bereich der Oberflächenverwitterung. Bei den nodulären Bohnerze handelt es sich zum Einen um Goethit-imprägnierte Bohnerztonaggregate und zum Anderen um Bruchstücke einer massiven Eisenkruste

Complex Independent Component Analysis of Frequency-Domain Electroencephalographic Data

Independent component analysis (ICA) has proven useful for modeling brain and electroencephalographic (EEG) data. Here, we present a new, generalized method to better capture the dynamics of brain signals than previous ICA algorithms. We regard EEG sources as eliciting spatio-temporal activity patterns, corresponding to, e.g., trajectories of activation propagating across cortex. This leads to a model of convolutive signal superposition, in contrast with the commonly used instantaneous mixing model. In the frequency-domain, convolutive mixing is equivalent to multiplicative mixing of complex signal sources within distinct spectral bands. We decompose the recorded spectral-domain signals into independent components by a complex infomax ICA algorithm. First results from a visual attention EEG experiment exhibit (1) sources of spatio-temporal dynamics in the data, (2) links to subject behavior, (3) sources with a limited spectral extent, and (4) a higher degree of independence compared to sources derived by standard ICA.Comment: 21 pages, 11 figures. Added final journal reference, fixed minor typo

A Common HLA-DPA1 Variant Is Associated with Hepatitis B Virus Infection but Fails to Distinguish Active from Inactive Caucasian Carriers

Background and Aims: Chronic infection with the hepatitis B virus (HBV) is a major health issue worldwide. Recently, single nucleotide polymorphisms (SNPs) within the human leukocyte antigen (HLA)-DP locus were identified to be associated with HBV infection in Asian populations. Most significant associations were observed for the A alleles of HLA-DPA1 rs3077 and HLA-DPB1 rs9277535, which conferred a decreased risk for HBV infection. We assessed the implications of these variants for HBV infection in Caucasians. Methods: Two HLA-DP gene variants (rs3077 and rs9277535) were analyzed for associations with persistent HBV infection and with different clinical outcomes, i.e., inactive HBsAg carrier status versus progressive chronic HBV (CHB) infection in Caucasian patients (n = 201) and HBsAg negative controls (n = 235). Results: The HLA-DPA1 rs3077 C allele was significantly associated with HBV infection (odds ratio, OR = 5.1, 95% confidence interval, CI: 1.9–13.7; p = 0.00093). However, no significant association was seen for rs3077 with progressive CHB infection versus inactive HBsAg carrier status (OR = 2.7, 95% CI: 0.6–11.1; p = 0.31). In contrast, HLA-DPB1 rs9277535 was not associated with HBV infection in Caucasians (OR = 0.8, 95% CI: 0.4–1.9; p = 1). Conclusions: A highly significant association of HLA-DPA1 rs3077 with HBV infection was observed in Caucasians. However, as a differentiation between different clinical courses of HBV infection was not possible, knowledge of the HLA-DPA1 genotype cannot be translated into personalized anti-HBV therapy approaches

Composable Long-Term Security with Rewinding

Long-term security, a variant of Universally Composable (UC) security introduced by Müller-Quade and Unruh (JoC ’10), allows to analyze the security of protocols in a setting where all hardness assumptions no longer hold after the protocol execution has finished. Such a strict notion is highly desirable when properties such as input privacy need to be guaranteed for a long time, e.g. zero-knowledge proofs for secure electronic voting. Strong impossibility results rule out so-called long-term-revealing setups, e.g. a common reference string (CRS), to achieve long-term security, with known constructions for long-term security requiring hardware assumptions, e.g. signature cards. We circumvent these impossibility results by making use of new techniques, allowing rewinding-based simulation in a way that universal composability is possible. The new techniques allow us to construct a long-term-secure composable commitment scheme in the CRS-hybrid model, which is provably impossible in the notion of Müller-Quade and Unruh. We base our construction on a statistically hiding commitment scheme in the CRS-hybrid model with CCA-like properties. To provide a CCA oracle, we cannot rely on superpolynomial extraction techniques, as statistically hiding commitments do not define a unique value. Thus, we extract the value committed to via rewinding. However, even a CCA “rewinding oracle” without additional properties may be useless, as extracting a malicious committer could require to rewind other protocols the committer participates in. If this is e.g. a reduction, this clearly is forbidden. Fortunately, we can establish the well-known and important property of k-robust extractability, which guarantees that extraction is possible without rewinding k-round protocols the malicious committer participates in. While establishing this property for statistically binding commitment schemes is already non-trivial, it is even more complicated for statistically hiding ones. We then incorporate rewinding-based commitment extraction into the UC framework via a helper in analogy to Canetti, Lin and Pass (FOCS 2010), allowing both adversary and environment to extract statistically hiding commitments. Despite the rewinding, our variant of long-term security is universally composable. Our new framework provides the first setting in which a commitment scheme that is both statistically hiding and composable can be constructed from standard polynomial-time hardness assumptions and a CRS only. Unfortunately, we can prove that our setting does not admit long-term-secure oblivious transfer (and thus general two-party computations). Still, our long-term-secure commitment scheme suffices for natural applications, such as long-term secure and composable (commit-and-prove) zero-knowledge arguments of knowledge

Simple model for 1/f noise

We present a simple stochastic mechanism which generates pulse trains exhibiting a power law distribution of the pulse intervals and a $1/f^\alpha$ power spectrum over several decades at low frequencies with $\alpha$ close to one. The essential ingredient of our model is a fluctuating threshold which performs a Brownian motion. Whenever an increasing potential $V(t)$ hits the threshold, $V(t)$ is reset to the origin and a pulse is emitted. We show that if $V(t)$ increases linearly in time, the pulse intervals can be approximated by a random walk with multiplicative noise. Our model agrees with recent experiments in neurobiology and explains the high interpulse interval variability and the occurrence of $1/f^\alpha$ noise observed in cortical neurons and earthquake data.Comment: 4 pages, 4 figure

Fluorescence optical imaging feature selection with machine learning for differential diagnosis of selected rheumatic diseases

Background and objectiveAccurate and fast diagnosis of rheumatic diseases affecting the hands is essential for further treatment decisions. Fluorescence optical imaging (FOI) visualizes inflammation-induced impaired microcirculation by increasing signal intensity, resulting in different image features. This analysis aimed to find specific image features in FOI that might be important for accurately diagnosing different rheumatic diseases.Patients and methodsFOI images of the hands of patients with different types of rheumatic diseases, such as rheumatoid arthritis (RA), osteoarthritis (OA), and connective tissue diseases (CTD), were assessed in a reading of 20 different image features in three phases of the contrast agent dynamics, yielding 60 different features for each patient. The readings were analyzed for mutual differential diagnosis of the three diseases (One-vs-One) and each disease in all data (One-vs-Rest). In the first step, statistical tools and machine-learning-based methods were applied to reveal the importance rankings of the features, that is, to find features that contribute most to the model-based classification. In the second step machine learning with a stepwise increasing number of features was applied, sequentially adding at each step the most crucial remaining feature to extract a minimized subset that yields the highest diagnostic accuracy.ResultsIn total, n = 605 FOI of both hands were analyzed (n = 235 with RA, n = 229 with OA, and n = 141 with CTD). All classification problems showed maximum accuracy with a reduced set of image features. For RA-vs.-OA, five features were needed for high accuracy. For RA-vs.-CTD ten, OA-vs.-CTD sixteen, RA-vs.-Rest five, OA-vs.-Rest eleven, and CTD-vs-Rest fifteen, features were needed, respectively. For all problems, the final importance ranking of the features with respect to the contrast agent dynamics was determined.ConclusionsWith the presented investigations, the set of features in FOI examinations relevant to the differential diagnosis of the selected rheumatic diseases could be remarkably reduced, providing helpful information for the physician

Surveillance of SARS-CoV-2 in Frankfurt am Main from October to December 2020 Reveals High Viral Diversity Including Spike Mutation N501Y in B.1.1.70 and B.1.1.7.

BACKGROUND: International travel is a major driver of the introduction and spread of SARS-CoV-2. AIM: To investigate SARS-CoV-2 genetic diversity in the region of a major transport hub in Germany, we characterized the viral sequence diversity of the SARS-CoV-2 variants circulating in Frankfurt am Main, the city with the largest airport in Germany, from the end of October to the end of December 2020. METHODS: In total, we recovered 136 SARS-CoV-2 genomes from nasopharyngeal swab samples. We isolated 104 isolates that were grown in cell culture and RNA from the recovered viruses and subjected them to full-genome sequence analysis. In addition, 32 nasopharyngeal swab samples were directly sequenced. RESULTS AND CONCLUSION: We found 28 different lineages of SARS-CoV-2 circulating during the study period, including the variant of concern B.1.1.7 (Δ69/70, N501Y). Six of the lineages had not previously been observed in Germany. We detected the spike protein (S) deletion Δ69/Δ70 in 15% of all sequences, a four base pair (bp) deletion (in 2.9% of sequences) and a single bp deletion (in 0.7% of sequences) in ORF3a, leading to ORF3a truncations. In four sequences (2.9%), an amino acid deletion at position 210 in S was identified. In a single sample (0.7%), both a 9 bp deletion in ORF1ab and a 7 bp deletion in ORF7a were identified. One sequence in lineage B.1.1.70 had an N501Y substitution while lacking the Δ69/70 in S. The high diversity of sequences observed over two months in Frankfurt am Main highlights the persisting need for continuous SARS-CoV-2 surveillance using full-genome sequencing, particularly in cities with international airport connections

Caroline - ein autonom fahrendes Fahrzeug im Stadtverkehr

We have previously shown that the physiological size of postsynaptic currents maximises energy efficiency rather than information transfer across the retinothalamic relay synapse. Here, we investigate information transmission and postsynaptic energy use at the next synapse along the visual pathway: from relay neurons in the thalamus to spiny stellate cells in layer 4 of the primary visual cortex (L4SS). Using both multicompartment Hodgkin-Huxley-type simulations and electrophysiological recordings in rodent brain slices, we find that increasing or decreasing the postsynaptic conductance of the set of thalamocortical inputs to one L4SS cell decreases the energy efficiency of information transmission from a single thalamocortical input. This result is obtained in the presence of random background input to the L4SS cell from excitatory and inhibitory corticocortical connections, which were simulated (both excitatory and inhibitory) or injected experimentally using dynamic-clamp (excitatory only). Thus, energy efficiency is not a unique property of strong relay synapses: even at the relatively weak thalamocortical synapse, each of which contributes minimally to the output firing of the L4SS cell, evolutionarily-selected postsynaptic properties appear to maximise the information transmitted per energy used