Karlsruhe University of Education

Abstract Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves 1 and in the first imaging of a black hole 2 . Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.

Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.

There has been significant interest and progress in the field of vehicular ad hoc networks over the last several years. VANETs comprise vehicle-to-vehicle and vehicle-to-infrastructure communications based on wireless local area network technologies. The distinctive set of candidate applications (e.g., collision warning and local traffic information for drivers), resources (licensed spectrum, rechargeable power source), and the environment (e.g., vehicular traffic flow patterns, privacy concerns) make the VANET a unique area of wireless communication. This article gives an overview of the field, providing motivations, challenges, and a snapshot of proposed solutions.

Modularity is a recently introduced quality measure for graph clusterings. It has immediately received considerable attention in several disciplines, particularly in the complex systems literature, although its properties are not well understood. We study the problem of finding clusterings with maximum modularity, thus providing theoretical foundations for past and present work based on this measure. More precisely, we prove the conjectured hardness of maximizing modularity both in the general case and with the restriction to cuts and give an Integer Linear Programming formulation. This is complemented by first insights into the behavior and performance of the commonly applied greedy agglomerative approach.

This review provides a comprehensive overview about the “hidden champion” of lithium-ion battery technology – graphite.

This article describes the technical challenges that have to be met when implementing the interesting new technology of spectrum pooling. This notion represents the coexistence of two mobile radio systems within the same frequency range. It enables the secondary utilization of already licensed frequency bands as aimed at by several regulatory authorities worldwide. The goal of spectrum pooling is to enhance spectral efficiency by overlaying a new mobile radio system on an existing one without requiring any changes to the actual licensed system. Several demanding tasks originate from this idea. Some of them have been solved in recent research projects. Others are subject to ongoing investigations. Here, the state of the art in spectrum pooling is presented.

Is there anything resembling a truly noncoordinating anion? Would it not be great to be able to prepare any crazy, beautiful, or simply useful cationic species that one has in mind, or has detected by mass spectroscopy? In condensed phases the target cation has to be partnered with a suitable counteranion. This is the moment when difficulties arise and many wonderful ideas end in the sink owing to coordination or decomposition of the anion. However, maybe these counteranion problems can be overcome by one of the new weakly coordinating anions (WCAs). Herein is an overview on the available candidates in the quest for the least coordinating anion and a summary of new applications, available starting materials, and general strategies to introduce a WCA into a system. Some of the unusual properties of WCA salts such as high solubility in low dielectric media, pseudo gas-phase conditions in condensed phases, and the stabilization of weakly bound and low-charged complexes are rationalized on thermodynamic grounds. Limits of the WCAs, that is, anion coordination and decomposition, are shown and a quantum chemical analysis of all types of WCAs is presented which allows the choice of a particular WCA to be based on quantitative data from a wide range of different anions.

The Semantic Web relies heavily on formal ontologies to structure data for comprehensive and transportable machine understanding. Thus, the proliferation of ontologies factors largely in the Semantic Web's success. The authors present an ontology learning framework that extends typical ontology engineering environments by using semiautomatic ontology construction tools. The framework encompasses ontology import, extraction, pruning, refinement and evaluation.

We compare different procedures for combining fixed-order tree-level matrix-element generators with parton showers. We use the case of W-production at the Tevatron and the LHC to compare different implementations of the so-called CKKW and MLM schemes using different matrix-element generators and different parton cascades. We find that although similar results are obtained in all cases, there are important differences.

An interesting class of "geometric intersection problems" calls for dealing with the pairwise intersections among a set of N objects in the plane, These problems arise in many applications such as printed circuit design, architectural data bases, and computer graphics. Shamos and Hoey have described a number of algorithms for detecting whether any two objects in a planar set intersect. In this paper we extend their work by giving algorithms that count the number of such intersections and algorithms that report all such intersections.

Cosserat's theory for granular materials under plane strain conditions of deformation is presented. The constitutive equations discussed are a generalization of the j 2 deformation theory of plasticity for frictional materials with internal constraint. Shear band formation is treated as a bifurcation problem and predictions about the state of bifurcation, the shear band orientation and the evolution of its thickness are made. The theoretical predictions are tested against experimental results from biaxial tests on sand specimens. Dans cet article on présente une théorie de Cosserat pour des matériaux pulvérulents soumis à des déformations planes. Les équations rhéologiques proposées représentent une généralization de la théorie de la deformation J 2 pour les matériaux à frottement interne avec contraintes internes. La formation de bandes de cisaillement y est traitée comme étant un probléme de bifurcation et on y fait des prédictions à propos de l'état de bifurcation, de l'orientation de la bande de cisaillement et de l'évolution de son épaisseur. Les prédictions basées sur la théorie sont comparées à des résultats expérimentaux obtenus dans des essais biaxiaux avec des échantillons de sable.

We compare a partners condition , where the same small group of subjects plays a repeated public good game, to a strangers condition , where subjects play this game in changing group formations. From the first period onward, subjects in the partners condition contribute significantly more to the public good than subjects in the strangers condition. Strangers' contributions show continual decay, while partners' contributions fluctuate on a high level prior to decreasing in the final periods. We interpret subjects' behaviour in terms of conditional cooperation which is characterized by both future‐oriented and reactive behaviour. JEL classifications: C 91; C 92; H 41

Safe handling of dynamic highway and inner city scenarios with autonomous vehicles involves the problem of generating traffic-adapted trajectories. In order to account for the practical requirements of the holistic autonomous system, we propose a semi-reactive trajectory generation method, which can be tightly integrated into the behavioral layer. The method realizes long-term objectives such as velocity keeping, merging, following, stopping, in combination with a reactive collision avoidance by means of optimal-control strategies within the Frenét-Frame of the street. The capabilities of this approach are demonstrated in the simulation of a typical high-speed highway scenario.

We further miniaturize a recently established silver-based negative-index metamaterial design. By comparing transmittance, reflectance, and phase-sensitive time-of-flight experiments with theory, we infer a real part of the refractive index of −0.6 at a 780 nm wavelength—which is visible in the laboratory.

XML and RDF are the current standards for establishing semantic interoperability on the Web, but XML addresses only document structure. RDF better facilitates interoperation because it provides a data model that can be extended to address sophisticated ontology representation techniques. We explain the role of ontologies in the architecture of the Semantic Web. We then briefly summarize key elements of XML and RDF, showing why using XML as a tool for semantic interoperability will be ineffective in the long run. We argue that a further representation and inference layer is needed on top of the Web's current layers, and to establish such a layer, we propose a general method for encoding ontology representation languages into RDF/RDF schema. We illustrate the extension method by applying it to Ontology Interchange Language, an ontology representation and inference language.

Position-based routing, as it is used by protocols like Greedy Perimeter Stateless Routing (GPSR) [5], is very well suited for highly dynamic environments such as inter-vehicle communication on highways. However, it has been discussed that radio obstacles [4], as they are found in urban areas, have a significant negative impact on the performance of position-based routing. In prior work [6] we presented a position-based approach which alleviates this problem and is able to find robust routes within city environments. It is related to the idea of position-based source routing as proposed in [1] for terminode routing. The algorithm needs global knowledge of the city topology as it is provided by a static street map. Given this information the sender determines the junctions that have to be traversed by the packet using the Dijkstra shortest path algorithm. Forwarding between junctions is then done in a position-based fashion. In this short paper we show how position-based routing can be aplied to a city scenario without assuming that nodes have access to a static street map and without using source routing.

The impact of COVID-19 on social life has been drastic and global. However, the different numbers of cases and different actions in different countries have been leading to various interesting yet unexplored effects on human behavior. In the present study, we compare the physical activity and recreational screen time of a representative sample of 1711 4- to 17-year-olds before and during the strictest time of the first COVID-19 lockdown in Germany. We found that sports activity declined whereas recreational screen time increased. However, a substantial increase in habitual physical activities leads to an overall increase in physical activity among children and adolescents in Germany. The effects differ in size but not in their direction between age groups and are stable for boys and girls. We conclude from this natural experiment that physical activity among children and adolescents is highly context-driven and mutual and does not act as a functional opposite to recreational screen time.

We provide a general approach for learning robotic motor skills from human demonstration. To represent an observed movement, a non-linear differential equation is learned such that it reproduces this movement. Based on this representation, we build a library of movements by labeling each recorded movement according to task and context (e.g., grasping, placing, and releasing). Our differential equation is formulated such that generalization can be achieved simply by adapting a start and a goal parameter in the equation to the desired position values of a movement. For object manipulation, we present how our framework extends to the control of gripper orientation and finger position. The feasibility of our approach is demonstrated in simulation as well as on the Sarcos dextrous robot arm. The robot learned a pick-and-place operation and a water-serving task and could generalize these tasks to novel situations.

The increasing usage of smart embedded devices in business blurs the line between the virtual and real worlds. This creates new opportunities to build applications that better integrate real-time state of the physical world, and hence, provides enterprise services that are highly dynamic, more diverse, and efficient. Service-Oriented Architecture (SOA) approaches traditionally used to couple functionality of heavyweight corporate IT systems, are becoming applicable to embedded real-world devices, i.e., objects of the physical world that feature embedded processing and communication. In such infrastructures, composed of large numbers of networked, resource-limited devices, the discovery of services and on-demand provisioning of missing functionality is a significant challenge. We propose a process and a suitable system architecture that enables developers and business process designers to dynamically query, select, and use running instances of real-world services (i.e., services running on physical devices) or even deploy new ones on-demand, all in the context of composite, real-world business applications.

Integrated antibiotic resistance (AR) surveillance is one of the objectives of the World Health Organization global action plan on antimicrobial resistance. Urban wastewater treatment plants (UWTPs) are among the most important receptors and sources of environmental AR. On the basis of the consistent observation of an increasing north-to-south clinical AR prevalence in Europe, this study compared the influent and final effluent of 12 UWTPs located in seven countries (Portugal, Spain, Ireland, Cyprus, Germany, Finland, and Norway). Using highly parallel quantitative polymerase chain reaction, we analyzed 229 resistance genes and 25 mobile genetic elements. This first trans-Europe surveillance showed that UWTP AR profiles mirror the AR gradient observed in clinics. Antibiotic use, environmental temperature, and UWTP size were important factors related with resistance persistence and spread in the environment. These results highlight the need to implement regular surveillance and control measures, which may need to be appropriate for the geographic regions.