Visceral vasculature in the family Cordylidae (Reptilia: Squamata)

Major circulatory patterns in lizards of the family Cordylidae are poorly known, but may serve as a source of characters for systematics. Two specimens each of the cordylines, Cordylus jordani and C. pofyzonus, and the gerrhosaurine, Zonosaurus madagascariensis were prepared by Microfil™ injection and whole body clearing and staining to serve as the basis for a comparison of cordylid visceral vasculature. The greatest amount of variation within the family is seen in the vessels of the hepatic portal system, whereas venous drainage and the arterial system (exclusive of the coeliac artery and its branches) are largely conservative within the group. Despite extensive homoplasy in lizards as a whole, cordylids (sensu lato), and especially gerrhosaurines, share a number of features of vasculature that support their sister-group relationship to the Scincidae. The proximity of the origin of the anterior and posterior mesenteric arteries stands as a putative synapomorphy of cordylines + gerrhosaurines. Features of the hepatic portal drainage may be autapomorphic for the genus Cordylus or for cordylines as a whole

Starling: A Blockchain-based System for Coordinated Obstacle Mapping in Dynamic Vehicular Environments

Current Vehicle-to-Vehicle solutions cannot ensure the authenticity of safety-critical vehicle and traffic data. Moreover, they do not allow malicious vehicles to be detected and eliminated. However, this is becoming mandatory, as more and more vehicles are on the road and communicating with each other. We propose a system called Starling, which focuses on trusted coordinated obstacle mapping using blockchain technology and a distributed database. Starling enables vehicles to share detected obstacles with other vehicles in a secure and verifiable manner, thus improving road safety. It ensures that data was not manipulated, changed, or deleted and is based on an open protocol so that vehicles can exchange data regardless of their manufacturer. In a case study, we demonstrate how a consensus is reached among vehicles and conduct a comprehensive evaluation of the Starling system using Ethereum and the InterPlanetary File System

When to Say What and How: Adapting the Elaborateness and Indirectness of Spoken Dialogue Systems

With the aim of designing a spoken dialogue system which has the ability to adapt to the user's communication idiosyncrasies, we investigate whether it is possible to carry over insights from the usage of communication styles in human-human interaction to human-computer interaction. In an extensive literature review, it is demonstrated that communication styles play an important role in human communication. Using a multi-lingual data set, we show that there is a significant correlation between the communication style of the system and the preceding communication style of the user. This is why two components that extend the standard architecture of spoken dialogue systems are presented: 1) a communication style classifier that automatically identifies the user communication style and 2) a communication style selection module that selects an appropriate system communication style. We consider the communication styles elaborateness and indirectness as it has been shown that they influence the user's satisfaction and the user's perception of a dialogue. We present a neural classification approach based on supervised learning for each task. Neural networks are trained and evaluated with features that can be automatically derived during an ongoing interaction in every spoken dialogue system. It is shown that both components yield solid results and outperform the baseline in form of a majority-class classifier

Modeling IT Availability Risks in Smart Factories

In the course of the ongoing digitalization of production, production environments have become increasingly intertwined with information and communication technology. As a consequence, physical production processes depend more and more on the availability of information networks. Threats such as attacks and errors can compromise the components of information networks. Due to the numerous interconnections, these threats can cause cascading failures and even cause entire smart factories to fail due to propagation effects. The resulting complex dependencies between physical production processes and information network components in smart factories complicate the detection and analysis of threats. Based on generalized stochastic Petri nets, the paper presents an approach that enables the modeling, simulation, and analysis of threats in information networks in the area of connected production environments. Different worst-case threat scenarios regarding their impact on the operational capability of a close-to-reality information network are investigated to demonstrate the feasibility and usability of the approach. Furthermore, expert interviews with an academic Petri net expert and two global leading companies from the automation and packaging industry complement the evaluation from a practical perspective. The results indicate that the developed artifact offers a promising approach to better analyze and understand availability risks, cascading failures, and propagation effects in information networks in connected production environments

The DLPS: A New Framework for Benchmarking Blockchains

Distributed Ledger Technologies (DLT) promise to revolutionize business ecosystems by permitting secure transactions without intermediaries. A widely recognized challenge that inhibits the uptake of DLT is scalability and performance. Hence, quantifying key metrics such as throughput and latency is crucial for designing DLT-based infrastructures, applications, and ecosystems. However, current benchmarking frameworks for blockchains do not cover the whole benchmarking process; impeding transparent comparisons of different DLT networks. In this paper, we present the Distributed Ledger Performance Scan (DLPS), an open-source framework for end-to-end performance characterizations of blockchains, addressing the need to transparently and automatically evaluate the performance of highly customizable configurations. We describe our new framework and argue that it significantly improves existing DLT benchmarking solutions. To demonstrate the capabilities of the DLPS, we also summarize the main results obtained from a series of experiments that we have conducted with it, giving a first comprehensive comparison of essential scalability properties of several commonly used enterprise blockchains

Tone Contours and Tone Clusters in Iau

Proceedings of the Eighteenth Annual Meeting of the Berkeley Linguistics Society: Special Session on The Typology of Tone Languages (1992

Suggestive Evidence for an Antidepressant Effect of Metreleptin Treatment in Patients with Lipodystrophy

Introduction: Lipodystrophy (LD) syndromes are rare heterogeneous disorders characterized by reduction or absence of subcutaneous fat, low or nondetectable leptin concentrations in blood and impaired hunger/satiety regulation. Metreleptin treatment reverses metabolic complications and improves eating behavior in LD. Because depression in anorexia nervosa (AN), which is also characterized by hypoleptinemia, improves substantially upon treatment with metreleptin, we hypothesized that metreleptin substitution may be associated with an antidepressant effect in patients with LD, too. Methods: In this ancillary study, 10 adult patients with LD were treated with metreleptin. To assess depressive symptoms, the self-rating questionnaire Beck's Depression Inventory (BDI) was filled in at preestablished time points prior (T1) and after initiation of metreleptin (T2: 1 week; T3: 4 weeks; T4: 12 weeks) dosing. The differences between time points were tested with nonparametric Friedman's analysis of variance. Sensitivity analyses were performed upon exclusion of the BDI items addressing appetite and weight changes. Results: According to their BDI scores, 4 patients had mild depression and 2 had moderate depression at baseline. Friedman's test revealed significant differences in BDI scores between the four time points. Post hoc analyses revealed that the difference between T1 and T3 was significant upon Bonferroni correction (p = 0.034, effect size r = 0.88). The sensitivity analyses upon exclusion of the appetite and weight change items again revealed a significant Friedman's test and significant Bonferroni corrected differences in the revised BDI scores between T1 versus T2 (p = 0.002, r = 0.99) and T1 versus T3 (p = 0.007, r = 0.79). Discussion/conclusion: Our study for the first time revealed suggestive evidence for an antidepressant effect of metreleptin in patients with LD. Metreleptin caused a rapid drop in depression scores within 1 week of treatment. A reduction of the depression score was also observed in 2 of the 3 LD patients whose BDI scores were in the normal range before start of the treatment. The reduction in total scores of BDI was still apparent after 3 months (T4) of dosing. This observation matches findings obtained in clinical case studies of AN patients, in whom depression scores also dropped during the first week of metreleptin treatment. It needs to be noted that by the nature of this observational study without a placebo group, nonspecific treatment expectation affecting mood cannot fully be ruled out.info:eu-repo/semantics/publishedVersio

Affine Toda field theories related to Coxeter groups of non-crystallographic type

We propose affine Toda field theories related to the non-crystallographic Coxeter groups H_2, H_3 and H_4. The classical mass spectrum, the classical three-point couplings and the one-loop corrections to the mass renormalisation are determined. The construction is carried out by means of a reduction procedure from crystallographic to non-crystallographic Coxeter groups. The embedding structure explains for various affine Toda field theories that their particles can be organised in pairs, such that their relative masses differ by the golden ratio.Comment: 28 pages LaTe