Does B2C online logistics service quality impact urban logistics?

This paper reports on an in-progress research study regarding the impact of business to consumer (B2C) online logistics service quality (OLSQ) for shopper satisfaction and loyalty on urban logistics across the UK, France and Germany to also investigate country-specific differences of consumer online shopping behaviour and channel strategies. A two-stage approach is adopted consisting of firstly of qualitative research conducted with managers at the producer/retailer interface and secondly a quantitative survey stage targeting consumers as online shoppers to determine how their expectations of OLSQ and associated activities influence their satisfaction and ongoing loyalty. This study should contribute theoretically by considering a B2C setting for OLSQ, which is the final aspect of point-of-origin to point-of-consumption, as most general literature on these topics has been dominated by business to business (B2B) logistical designs, and also identify any discrepancies between consumer expectations or behaviour as it may affect urban logistics solutions. Further, this study should contribute practically by providing managers with an understanding of the components of OLSQ considered critical by consumers

Vertical distribution and composition of phytoplankton under the influence of an upper mixed layer

The vertical distribution of phytoplankton is of fundamental importance for the dynamics and structure of aquatic communities. Here, using an advection-reaction-diffusion model, we investigate the distribution and competition of phytoplankton species in a water column, in which inverse resource gradients of light and a nutrient can limit growth of the biomass. This problem poses a challenge for ecologists, as the location of a production layer is not fixed, but rather depends on many internal parameters and environmental factors. In particular, we study the influence of an upper mixed layer (UML) in this system and show that it leads to a variety of dynamic effects: (i) Our model predicts alternative density profiles with a maximum of biomass either within or below the UML, thereby the system may be bistable or the relaxation from an unstable state may require a long-lasting transition. (ii) Reduced mixing in the deep layer can induce oscillations of the biomass; we show that a UML can sustain these oscillations even if the diffusivity is less than the critical mixing for a sinking phytoplankton population. (iii) A UML can strongly modify the outcome of competition between different phytoplankton species, yielding bistability both in the spatial distribution and in the species composition. (iv) A light limited species can obtain a competitive advantage if the diffusivity in the deep layers is reduced below a critical value. This yields a subtle competitive exclusion effect, where the oscillatory states in the deep layers are displaced by steady solutions in the UML. Finally, we present a novel graphical approach for deducing the competition outcome and for the analysis of the role of a UML in aquatic systems.Comment: 20 pages, 8 figure

Normalized entropy density of the 3D 3-state Potts model

Using a multicanonical Metropolis algorithm we have performed Monte Carlo simulations of the 3D 3-state Potts model on $L^3$ lattices with L=20, 30, 40, 50. Covering a range of inverse temperatures from $\beta_{\min}=0$ to $\beta_{\max}=0.33$ we calculated the infinite volume limit of the entropy density $s(\beta)$ with its normalization obtained from $s(0)=\ln 3$. At the transition temperature the entropy and energy endpoints in the ordered and disordered phase are estimated employing a novel reweighting procedure. We also evaluate the transition temperature and the order-disorder interface tension. The latter estimate increases when capillary waves are taken into account.Comment: 5 pages, 4 figure

On Advanced Mobility Concepts for Intelligent Planetary Surface Exploration

Surface exploration by wheeled rovers on Earth's Moon (the two Lunokhods) and Mars (Nasa's Sojourner and the two MERs) have been followed since many years already very suc-cessfully, specifically concerning operations over long time. However, despite of this success, the explored surface area was very small, having in mind a total driving distance of about 8 km (Spirit) and 21 km (Opportunity) over 6 years of operation. Moreover, ESA will send its ExoMars rover in 2018 to Mars, and NASA its MSL rover probably this year. However, all these rovers are lacking sufficient on-board intelligence in order to overcome longer dis-tances, driving much faster and deciding autonomously on path planning for the best trajec-tory to follow. In order to increase the scientific output of a rover mission it seems very nec-essary to explore much larger surface areas reliably in much less time. This is the main driver for a robotics institute to combine mechatronics functionalities to develop an intelligent mo-bile wheeled rover with four or six wheels, and having specific kinematics and locomotion suspension depending on the operational terrain of the rover to operate. DLR's Robotics and Mechatronics Center has a long tradition in developing advanced components in the field of light-weight motion actuation, intelligent and soft manipulation and skilled hands and tools, perception and cognition, and in increasing the autonomy of any kind of mechatronic systems. The whole design is supported and is based upon detailed modeling, optimization, and simula-tion tasks. We have developed efficient software tools to simulate the rover driveability per-formance on various terrain characteristics such as soft sandy and hard rocky terrains as well as on inclined planes, where wheel and grouser geometry plays a dominant role. Moreover, rover optimization is performed to support the best engineering intuitions, that will optimize structural and geometric parameters, compare various kinematics suspension concepts, and make use of realistic cost functions like mass and consumed energy minimization, static sta-bility, and more. For self-localization and safe navigation through unknown terrain we make use of fast 3D stereo algorithms that were successfully used e.g. in unmanned air vehicle ap-plications and on terrestrial mobile systems. The advanced rover design approach is applica-ble for lunar as well as Martian surface exploration purposes. A first mobility concept ap-proach for a lunar vehicle will be presented

Responsible Data Governance of Neuroscience Big Data

Open access article.Current discussions of the ethical aspects of big data are shaped by concerns regarding the social consequences of both the widespread adoption of machine learning and the ways in which biases in data can be replicated and perpetuated. We instead focus here on the ethical issues arising from the use of big data in international neuroscience collaborations. Neuroscience innovation relies upon neuroinformatics, large-scale data collection and analysis enabled by novel and emergent technologies. Each step of this work involves aspects of ethics, ranging from concerns for adherence to informed consent or animal protection principles and issues of data re-use at the stage of data collection, to data protection and privacy during data processing and analysis, and issues of attribution and intellectual property at the data-sharing and publication stages. Significant dilemmas and challenges with far-reaching implications are also inherent, including reconciling the ethical imperative for openness and validation with data protection compliance and considering future innovation trajectories or the potential for misuse of research results. Furthermore, these issues are subject to local interpretations within different ethical cultures applying diverse legal systems emphasising different aspects. Neuroscience big data require a concerted approach to research across boundaries, wherein ethical aspects are integrated within a transparent, dialogical data governance process. We address this by developing the concept of “responsible data governance,” applying the principles of Responsible Research and Innovation (RRI) to the challenges presented by the governance of neuroscience big data in the Human Brain Project (HBP)

Neuronale Netze für betriebliche Anwendungen:Anwendungspotentiale und existierende Systeme

Der vorliegende Arbeitsbericht zeigt eine Auswahl neuronaler Netze für betriebliche Anwendungen. Aufbauend auf der Vorstellung einiger Systeme wird sowohl vom konkreten Anwendungsgebiet als auch von der konkreten Architektur des neuronalen Netzes abstrahiert, um so ein Übertragen der Erkenntnisse auf andere, ähnlich gelagerte Anwendungsprobleme zu ermöglichen. Anhand der abstrahierten Beschreibung ist es möglich, neue betriebliche Anwendungspotentiale neuronaler Netze aufzudecken. Dazu wird überprüft, inwieweit eine neue, potentielle Anwendung denselben Kriterien genügt. Aufgrund der Analogien erhält man neben einer „Machbarkeitsstudie“ ggf. bereits Hinweise auf die geeignete Wahl eines Netzwerktyps und der zugehörigen Netzwerkparameter für das neue Anwendungsproblem