Neue Funde von Lepthyphantes geniculatus in Sachsen-Anhalt (Araneae, Linyphiidae)

Vorkommen desselten gefundenen Lepthyphantes geniculatus KULCZYNSKI, 1898 sind aus Deutschland bisher nur vom Gipskarstgebiet des Kyffhäusers (N-Thüringen) bekannt. 1964 und 1965 wurden dort auf zwei Gipshügeln in der Umgebung von Bad Frankenhausen insgesamt 4 männliche und 2 weibliche in Bodenfallen nachgewiesen (v. BROEN 1965, 1966)

Study of the Effective Torus Exhaust High Vacuum Pumping System Performance in the Inner Tritium Plant Loop of EU-DEMO

The requirement for a reduction of the tritium inventory of the European demonstration fusion reactor (EU-DEMO) has led to the active research and development of a continuously working pumping process termed “KALPUREX.” This process foresees the direct recycling of a large fraction of the unburnt hydrogen isotopologues via superpermeation in metal foil pumps during the burn phase. The remaining exhaust gas mixture is pumped by continuously operating, mercury-driven linear diffusion pumps. Diffusion pumps are kinetic high vacuum pumps whose pumping principle is based on the momentum transfer from a supersonic mercury vapor jet to the pumped gas mixture. Like many high vacuum pumps, they feature species-dependent pumping speeds. In the present work, we develop a simplified hybrid model of the high vacuum pumping train in order to estimate the effective pumping speed of the integrated system. The results of this model and its implications on the further development of the vacuum system are discussed for the burn and dwell phases of EU-DEMO

A case study for unlocking the potential of deep learning in asset-liability-management

The extensive application of deep learning in the field of quantitative risk management is still a relatively recent phenomenon. This article presents the key notions of Deep Asset-Liability-Management (“Deep ALM”) for a technological transformation in the management of assets and liabilities along a whole term structure. The approach has a profound impact on a wide range of applications such as optimal decision making for treasurers, optimal procurement of commodities or the optimization of hydroelectric power plants. As a by-product, intriguing aspects of goal-based investing or Asset-Liability-Management (ALM) in abstract terms concerning urgent challenges of our society are expected alongside. We illustrate the potential of the approach in a stylized case

Temporal dissociation of neural activity underlying synesthetic and perceptual colors

Grapheme-color synesthetes experience color when seeing achromatic symbols. We examined whether similar neural mechanisms underlie color perception and synesthetic colors using magnetoencephalography. Classification models trained on neural activity from viewing colored stimuli could distinguish synesthetic color evoked by achromatic symbols after a delay of ∼100 ms. Our results provide an objective neural signature for synesthetic experience and temporal evidence consistent with higher-level processing in synesthesia

On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics

Many finance, physics, and engineering phenomena are modeled by continuous-time dynamical systems driven by highly irregular (stochastic) inputs. A powerful tool to perform time series analysis in this context is rooted in rough path theory and leverages the so-called Signature Transform. This algorithm enjoys strong theoretical guarantees but is hard to scale to high-dimensional data. In this paper, we study a recently derived random projection variant called Randomized Signature, obtained using the Johnson-Lindenstrauss Lemma. We provide an in-depth experimental evaluation of the effectiveness of the Randomized Signature approach, in an attempt to showcase the advantages of this reservoir to the community. Specifically, we find that this method is preferable to the truncated Signature approach and alternative deep learning techniques in terms of model complexity, training time, accuracy, robustness, and data hungriness.Comment: Accepted for IEEE IJCNN 202

Hierarchy and Feedback in the Evolution of the E. coli Transcription Network

The E.coli transcription network has an essentially feedforward structure, with, however, abundant feedback at the level of self-regulations. Here, we investigate how these properties emerged during evolution. An assessment of the role of gene duplication based on protein domain architecture shows that (i) transcriptional autoregulators have mostly arisen through duplication, while (ii) the expected feedback loops stemming from their initial cross-regulation are strongly selected against. This requires a divergent coevolution of the transcription factor DNA-binding sites and their respective DNA cis-regulatory regions. Moreover, we find that the network tends to grow by expansion of the existing hierarchical layers of computation, rather than by addition of new layers. We also argue that rewiring of regulatory links due to mutation/selection of novel transcription factor/DNA binding interactions appears not to significantly affect the network global hierarchy, and that horizontally transferred genes are mainly added at the bottom, as new target nodes. These findings highlight the important evolutionary roles of both duplication and selective deletion of crosstalks between autoregulators in the emergence of the hierarchical transcription network of E.coli.Comment: to appear in PNA

Sex-dependent influence of endogenous estrogen in pulmonary hypertension

Rationale: The incidence of pulmonary arterial hypertension (PAH) is greater in women suggesting estrogens may play a role in the disease pathogenesis. Experimentally, in males exogenously administered estrogen can protect against PH; however in models that display female susceptibility estrogens may play a causative role. Objectives: To clarify the influence of endogenous estrogen and gender in PH and assess the therapeutic potential of a clinically available aromatase inhibitor. Methods: We interrogated the effect of reduced endogenous estrogen in males and females using the aromatase inhibitor, anastrozole, in two models of PH; the hypoxic mouse and Sugen 5416/hypoxic rat. We also determined the effects of gender on pulmonary expression of aromatase in these models and in lungs from PAH patients. Results: Anastrozole attenuated PH in both models studied, but only in females. To verify this effect was due to reduced estrogenic activity we confirmed that in hypoxic mice inhibition of estrogen receptor alpha also has a therapeutic effect specifically in females. Female rodent lung displays increased aromatase and decreased BMPR2 and Id1 expression compared to male. Anastrozole treatment reversed the impaired BMPR2 pathway in females. Increased aromatase expression was also detected in female human pulmonary artery smooth muscle cells compared to male. Conclusions: The unique phenotype of female pulmonary arteries facilitates the therapeutic effects of anastrozole in experimental PH confirming a role for endogenous estrogen in the disease pathogenesis in females and suggests aromatase inhibitors may have therapeutic potential

Politik-Check Pharmastandort Deutschland: Potenziale erkennen - Chancen nutzen

Zukünftig wird das wirtschaftliche Wachstum vor allem durch die kapital- und wissensintensiven Industrien getragen. Die forschungsintensive Pharmabranche gehört dabei zu den zentralen Zukunftsbranchen. Die Studie untersucht die Chancen der Pharmaindustrie in Deutschland anhand einer Standortanalyse und durch eine Befragung von Experten und Entscheidungsträgern der deutschen und internationalen Pharmaunternehmen. Es zeigt sich, dass der Pharmastandort Deutschland im internationalen Vergleich seit 1990 an Bedeutung verloren hat. Die Maßnahmen der Großen Koalition haben den Standort in der letzten Zeit verbessert, sind aber aus Sicht der Interviewpartner häufig unzureichend. Weitere Maßnahmen müssen im internationalen Kontext entwickelt werden. In der Studie werden konkrete Vorschläge zur Stärkung des Pharmastandorts Deutschland vorgelegt