Simultaneous Optical Flow and Intensity Estimation from an Event Camera

Event cameras are bio-inspired vision sensors which mimic retinas to measure per-pixel intensity change rather than outputting an actual intensity image. This proposed paradigm shift away from traditional frame cameras offers significant potential advantages: namely avoiding high data rates, dynamic range limitations and motion blur. Unfortunately, however, established computer vision algorithms may not at all be applied directly to event cameras. Methods proposed so far to reconstruct images, estimate optical flow, track a camera and reconstruct a scene come with severe restrictions on the environment or on the motion of the camera, e.g. allowing only rotation. Here, we propose, to the best of our knowledge, the first algorithm to simultaneously recover the motion field and brightness image, while the camera undergoes a generic motion through any scene. Our approach employs minimisation of a cost function that contains the asynchronous event data as well as spatial and temporal regularisation within a sliding window time interval. Our implementation relies on GPU optimisation and runs in near real-time. In a series of examples, we demonstrate the successful operation of our framework, including in situations where conventional cameras suffer from dynamic range limitations and motion blur

Extreme events in time series aggregation: A case study for optimal residential energy supply systems

To account for volatile renewable energy supply, energy systems optimization problems require high temporal resolution. Many models use time-series clustering to find representative periods to reduce the amount of time-series input data and make the optimization problem computationally tractable. However, clustering methods remove peaks and other extreme events, which are important to achieve robust system designs. We present a general decision framework to include extreme events in a set of representative periods. We introduce a method to find extreme periods based on the slack variables of the optimization problem itself. Our method is evaluated and benchmarked with other extreme period inclusion methods from the literature for a design and operations optimization problem: a residential energy supply system. Our method ensures feasibility over the full input data of the residential energy supply system although the design optimization is performed on the reduced data set. We show that using extreme periods as part of representative periods improves the accuracy of the optimization results by 3% to more than 75% depending on system constraints compared to results with clustering only, and thus reduces system cost and enhances system reliability

Comment on "How green is blue hydrogen?"

This paper is written in response to the paper “How green is blue hydrogen?” by R. W. Howarth and M. Z. Jacobson. It aims at highlighting and discussing the method and assumptions of that paper, and thereby providing a more balanced perspective on blue hydrogen, which is in line with current best available practices and future plant specifications aiming at low CO2 emissions. More specifically, in this paper, we show that: (i) the simplified method that Howarth and Jacobson used to compute the energy balance of blue hydrogen plants leads to significant overestimation of CO2 emissions and natural gas (NG) consumption and (ii) the assumed methane leakage rate is at the high end of the estimated emissions from current NG production in the United States and cannot be considered representative of all-NG and blue hydrogen value chains globally. By starting from the detailed and rigorously calculated mass and energy balances of two blue hydrogen plants in the literature, we show the impact that methane leakage rate has on the equivalent CO2 emissions of blue hydrogen. On the basis of our analysis, we show that it is possible for blue hydrogen to have significantly lower equivalent CO2 emissions than the direct use of NG, provided that hydrogen production processes and CO2 capture technologies are implemented that ensure a high CO2 capture rate, preferably above 90%, and a low-emission NG supply chain

Wear and corrosion interactions on titanium in oral environment : literature review

The oral cavity is a complex environment where corrosive substances from dietary, human saliva, and oral biofilms may accumulate in retentive areas of dental implant systems and prostheses promoting corrosion at their surfaces. Additionally, during mastication, micromovements may occur between prosthetic joints causing a relative motion between contacting surfaces, leading to wear. Both processes (wear and corrosion) result in a bio-tribocorrosion system once that occurs in contact with biological tissues and fluids. This review paper is focused on the aspects related to the corrosion and wear behavior of titanium-based structures in the oral environment. Furthermore, the clinical relevance of the oral environment is focused on the harmful effect that acidic substances and biofilms, formed in human saliva, may have on titanium surfaces. In fact, a progressive degradation of titanium by wear and corrosion (tribocorrosion) mechanisms can take place affecting the performance of titanium-based implant and prostheses. Also, the formation of wear debris and metallic ions due to the tribocorrosion phenomena can become toxic for human tissues. This review gathers knowledge from areas like materials sciences, microbiology, and dentistry contributing to a better understanding of bio-tribocorrosion processes in the oral environment.(undefined

Comment on “How green is blue hydrogen?”

This paper is written in response to the paper “How green is blue hydrogen?” by R. W. Howarth and M. Z. Jacobson. It aims at highlighting and discussing the method and assumptions of that paper, and thereby providing a more balanced perspective on blue hydrogen, which is in line with current best available practices and future plant specifications aiming at low CO2 emissions. More specifically, in this paper, we show that: (i) the simplified method that Howarth and Jacobson used to compute the energy balance of blue hydrogen plants leads to significant overestimation of CO2 emissions and natural gas (NG) consumption and (ii) the assumed methane leakage rate is at the high end of the estimated emissions from current NG production in the United States and cannot be considered representative of all-NG and blue hydrogen value chains globally. By starting from the detailed and rigorously calculated mass and energy balances of two blue hydrogen plants in the literature, we show the impact that methane leakage rate has on the equivalent CO2 emissions of blue hydrogen. On the basis of our analysis, we show that it is possible for blue hydrogen to have significantly lower equivalent CO2 emissions than the direct use of NG, provided that hydrogen production processes and CO2 capture technologies are implemented that ensure a high CO2 capture rate, preferably above 90%, and a low-emission NG supply chain

Efficacy and safety of subcutaneous human HBV-immunoglobulin (Zutectra®) in liver transplantation: An open, prospective, single-arm phase III study

Capture and utilization of CO2 as alternative carbon feedstock for fuels, chemicals, and materials aims at reducing greenhouse gas emissions and fossil resource use. For capture of CO2, a large variety of CO2 sources exists. Since they emit much more CO2 than the expected demand for CO2 utilization, the environmentally most favorable CO2 sources should be selected. For this purpose, we introduce the environmental-merit-order (EMO) curve to rank CO2 sources according to their environmental impacts over the available CO2 supply. To determine the environmental impacts of CO2 capture, compression and transport, we conducted a comprehensive literature study for the energy demands of CO2 supply, and constructed a database for CO2 sources in Europe. Mapping these CO2 sources reveals that CO2 transport distances are usually small. Thus, neglecting transport in a first step, we find that environmental impacts are minimized by capturing CO2 first from chemical plants and natural gas processing, then from paper mills, power plants, and iron and steel plants. In a second step, we computed regional EMO curves considering transport and country-specific impacts for energy supply. Building upon regional EMO curves, we identify favorable locations for CO2 utilization with lowest environmental impacts of CO2 supply, so-called CO2 oases