Preemptive Scheduling of EV Charging for Providing Demand Response Services

We develop a new algorithm for scheduling the charging process of a large number of electric vehicles (EVs) over a finite horizon. We assume that EVs arrive at the charging stations with different charge levels and different flexibility windows. The arrival process is assumed to have a known distribution and that the charging process of EVs can be preemptive. We pose the scheduling problem as a dynamic program with constraints. We show that the resulting formulation leads to a monotone dynamic program with Lipschitz continuous value functions that are robust against perturbation of system parameters. We propose a simulation based fitted value iteration algorithm to determine the value function approximately, and derive the sample complexity for computing the approximately optimal solution.Comment: 21 pages, submitted to SEGA

REALMS 2 -RESILIENT EXPLORATION AND LUNAR MAPPING SYSTEM 2

The European Space Agency (ESA) and the European Space Resources Innovation Centre (ESRIC) created the Space Resources Challenge to invite researchers to propose innovative solutions for robotic space prospection with focus on autonomous Multi-Robot System (MRS). This paper proposes Resilient Exploration And Lunar Mapping System 2 (REALMS2), a MRS framework for planetary prospection and mapping. It is based on Robot Operating System version 2 (ROS 2) and uses Visual Simultaneous Localisation And Mapping (vSLAM) for map generation. The REALMS2 uses a mesh network for a robust ad-hoc network. A single graphical user interface (GUI)) controls all the rovers, providing a simple overview of the robotic mission. REALMS2 was used during the second field test of the ESA-ESRIC Challenge and allowed to map around 60% of the area, using three homogeneous rovers while handling communication delays and blackouts

REALMS: Resilient exploration and lunar mapping system.

peer reviewedSpace resource utilisation is opening a new space era. The scientific proof of the presence of water ice on the south pole of the Moon, the recent advances in oxygen extraction from lunar regolith, and its use as a material to build shelters are positioning the Moon, again, at the centre of important space programs. These worldwide programs, led by ARTEMIS, expect robotics to be the disrupting technology enabling humankind's next giant leap. However, Moon robots require a high level of autonomy to perform lunar exploration tasks more efficiently without being constantly controlled from Earth. Furthermore, having more than one robotic system will increase the resilience and robustness of the global system, improving its success rate, as well as providing additional redundancy. This paper introduces the Resilient Exploration and Lunar Mapping System, developed with a scalable architecture for semi-autonomous lunar mapping. It leverages Visual Simultaneous Localization and Mapping techniques on multiple rovers to map large lunar environments. Several resilience mechanisms are implemented, such as two-agent redundancy, delay invariant communications, a multi-master architecture different control modes. This study presents the experimental results of REALMS with two robots and its potential to be scaled to a larger number of robots, increasing the map coverage and system redundancy. The system's performance is verified and validated in a lunar analogue facility, and a larger lunar environment during the European Space Agency (ESA)-European Space Resources Innovation Centre Space Resources Challenge. The results of the different experiments show the efficiency of REALMS and the benefits of using semi-autonomous systems

Novel insights into the aetiology of granulomatosis with polyangiitis—a case–control study using the Clinical Practice Research Datalink

Objectives We aimed to provide insights into the aetiology of granulomatosis with polyangiitis (GPA), by conducting a large case–control study using a general population-based, prospectively collected database of healthcare records. Methods We compared all incident cases of GPA in the Clinical Practice Research Datalink 1990–2014, with up to 10 age-, sex- and general practice-matched controls. We identified potential risk factors, recorded numbers of cases and controls exposed to each, and calculated odds ratios (ORs) using conditional logistic regression. Our main analysis excluded data recorded during 1 year before diagnosis, to prevent early symptoms being mistaken for risk factors. Results We identified 757 people with GPA and matched 7546 controls. People with GPA were five times more likely to have a previous diagnosis of bronchiectasis (OR = 5.1, 95% CI: 2.7, 9.4; P 5 years prior to diagnosis. People with GPA were two to three times more likely than controls to have previous diagnoses of autoimmune diseases or chronic renal impairment, and these effects also remained stable >5 years prior to diagnosis. People with GPA were more likely to have a diagnosis of pulmonary fibrosis (OR = 5.7, 95% CI: 1.7, 19.5; P = 0.01) and sinus infections (OR = 2.7, 95% CI: 1.8, 4.2; P < 0.0001) recorded in the 3 years before diagnosis, but not before this. We also found former smoking, some medications and higher socio-economic status significantly, but less strongly, associated. Conclusion We found novel long-term associations between GPA and pre-existing bronchiectasis and autoimmune diseases

BrAPI-an application programming interface for plant breeding applications

Motivation: Modern genomic breeding methods rely heavily on very large amounts of phenotyping and genotyping data, presenting new challenges in effective data management and integration. Recently, the size and complexity of datasets have increased significantly, with the result that data are often stored on multiple systems. As analyses of interest increasingly require aggregation of datasets from diverse sources, data exchange between disparate systems becomes a challenge. Results: To facilitate interoperability among breeding applications, we present the public plant Breeding Application Programming Interface (BrAPI). BrAPI is a standardized web service API specification. The development of BrAPI is a collaborative, community-based initiative involving a growing global community of over a hundred participants representing several dozen institutions and companies. Development of such a standard is recognized as critical to a number of important large breeding system initiatives as a foundational technology. The focus of the first version of the API is on providing services for connecting systems and retrieving basic breeding data including germplasm, study, observation, and marker data. A number of BrAPI-enabled applications, termed BrAPPs, have been written, that take advantage of the emerging support of BrAPI by many databases

Sustainable and Equitable Increases in Fruit and Vegetable Productivity and Consumption are Needed to Achieve Global Nutrition Security

Increased intake of fruits and vegetables (F&V) is recommended for most populations across the globe. However, the current state of global and regional food systems is such that F&V availability, the production required to sustain them, and consumer food choices are all severely deficient to meet this need. Given the critical state of public health and nutrition worldwide, as well as the fragility of the ecological systems and resources on which they rely, there is a great need for research, investment, and innovation in F&V systems to nourish our global population. Here, we review the challenges that must be addressed in order to expand production and consumption of F&V sustainably and on a global scale. At the conclusion of the workshop, the gathered participants drafted the “Aspen/Keystone Declaration” (see below), which announces the formation of a new “Community of Practice,” whose area of work is described in this position paper. The need for this work is based on a series of premises discussed in detail at the workshop and summarized herein. To surmount these challenges, opportunities are presented for growth and innovation in F&V food systems. The paper is organized into five sections based on primary points of intervention in global F&V systems: (1) research and development, (2) information needs to better inform policy & investment, (3) production (farmers, farming practices, and supply), (4) consumption (availability, access, and demand), and (5) sustainable & equitable F&V food systems and supply chains

In-situ estimation of ice crystal properties at the South Pole using LED calibration data from the IceCube Neutrino Observatory

The IceCube Neutrino Observatory instruments about 1 km3 of deep, glacial ice at the geographic South Pole using 5160 photomultipliers to detect Cherenkov light emitted by charged relativistic particles. A unexpected light propagation effect observed by the experiment is an anisotropic attenuation, which is aligned with the local flow direction of the ice. Birefringent light propagation has been examined as a possible explanation for this effect. The predictions of a first-principles birefringence model developed for this purpose, in particular curved light trajectories resulting from asymmetric diffusion, provide a qualitatively good match to the main features of the data. This in turn allows us to deduce ice crystal properties. Since the wavelength of the detected light is short compared to the crystal size, these crystal properties do not only include the crystal orientation fabric, but also the average crystal size and shape, as a function of depth. By adding small empirical corrections to this first-principles model, a quantitatively accurate description of the optical properties of the IceCube glacial ice is obtained. In this paper, we present the experimental signature of ice optical anisotropy observed in IceCube LED calibration data, the theory and parametrization of the birefringence effect, the fitting procedures of these parameterizations to experimental data as well as the inferred crystal properties.</p