Batchelorholmgaard5371

First, we explore models for learning latent actions from offline task demonstrations, and formalize the properties that latent actions should satisfy. Next, we combine learned latent actions with autonomous robot assistance to help the user reach and maintain their high-level goals. Finally, we learn a personalized alignment model between joystick inputs and latent actions. We evaluate our resulting approach in four user studies where non-disabled participants reach marshmallows, cook apple pie, cut tofu, and assemble dessert. We then test our approach with two disabled adults who leverage assistive devices on a daily basis.A novel structural model is developed to understand the determinants of green bond prices and the so-called 'greenium', that is, the premium that bondholders are willing to pay to invest in green securities rather than conventional ones. The presence of a greenium makes green bonds relatively cheap vehicles to fund environmentally sustainable projects and thus contributes to the shift to a green economy. Yet, evidence on the greenium is mixed and the determinants of green bond yields are not fully understood. In this model two sources of uncertainty are introduced, that is, of cash flows of the firm and of the effectiveness of the financed green projects. The adoption of two risk factors brings in some mathematical complexity but allows for a better modelling of the multi-facet nature of these financial instruments. Dizocilpine chemical structure Our model is rich enough to generate both a positive and a negative premium, as both have been detected in the empirical literature. Thus, we shed light on possible heterogeneity concerning the existence of a greenium in the green bond universe. Moreover, we show how green bonds affect the issuer's creditworthiness, depending on the correlation of the green project with the core business of the firm and study their impact on investors' portfolio allocation.This study is to explore the smart city information (SCI) processing technology based on the Internet of Things (IoT) and cloud computing, promoting the construction of smart cities in the direction of effective sharing and interconnection. In this study, a SCI system is constructed based on the information islands in the smart construction of various fields in smart cities. The smart environment monitoring, smart transportation, and smart epidemic prevention at the application layer of the SCI system are designed separately. A multi-objective optimization algorithm for cloud computing virtual machine resource allocation method (CC-VMRA method) is proposed, and the application of the IoT and cloud computing technology in the smart city information system is further analysed and simulated for the performance verification. The results show that the multi-objective optimization algorithm in the CC-VMRA method can greatly reduce the number of physical servers in the SCI system (less than 20), and the variance is not higher than 0.0024, which can enable the server cluster to achieve better load balancing effects. In addition, the packet loss rate of the Zigbee protocol used by the IoT gateway in the SCI system is far below the 0.1% indicator, and the delay is less than 10 ms. Therefore, the SCI system constructed by this study shows low latency and high utilization rate, which can provide experimental reference for the later construction of smart city.In this paper, we study the generalized entropy ergodic theorem for nonhomogeneous bifurcating Markov chains indexed by a binary tree. Firstly, by constructing a class of random variables with a parameter and the mean value of one, we establish a strong limit theorem for delayed sums of the bivariate functions of such chains using the Borel-Cantelli lemma. Secondly, we prove the strong law of large numbers for the frequencies of occurrence of states of delayed sums and the generalized entropy ergodic theorem. As corollaries, we generalize some known results.Named Data Networking (NDN) architectural features, including multicast data delivery, stateful forwarding, and in-network data caching, have shown promise for applications such as video streaming and file sharing. However, collaborative applications, requiring a multi-producer participation introduce new NDN design challenges. In this paper, we highlight these challenges in the context of the Network Time Protocol (NTP) and one of its most widely-used deployments for NTP server discovery, the NTP pool project. We discuss the design requirements for the support of NTP and NTP pool and present general directions for the design of a time synchronization protocol over NDN, coined Named Data Networking Time Protocol (NDNTP).Launched in 2008, NIH's DSLD (https//dsld.nlm.nih.gov/dsld/) currently catalogs information printed on over 125,000 (historical and current) labels of dietary supplement products sold in the U.S.. The database is maintained and updated continuously, and new versions deployed regularly. The new home page includes a prominent search bar and counter that displays the number of searchable labels in the database. The redesigned website yields near-instantaneous label retrieval, a more attractive layout of information, tailored search filters and download options, and the ability to view data in pictorial formats resulting in a much-improved user experience. The modernization of the DSLD ensures that this NIH resource has new forms of data delivery to meet the needs of App developers and data scientists, and improved performance for users. The DSLD is updated frequently to reflect the products sold in the rapidly evolving U.S. dietary supplement market.Teff, maize, and wheat are the major cereals grown in volcanic ash-rich soils of the Main Ethiopian Rift (MER) Valley. Teff is a gluten-free cereal native to Ethiopia, used for making a local flat bread called injera, and is getting popularity globally due to its nutritional value (gluten-free and high fiber content). Teff can thus be an alternative diet for the treatment of celiac disease, a lifelong intolerance to gluten. This study aims to assess the distribution of toxic and essential elements in these staple cereals using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and compare with mineral composition of wheat, and maize consumed in the Main Ethiopian Rift Valley. We found significantly higher mean concentrations (in mg/kg) of Mg (1400), Ca (1210), Na (33), Fe (159), Mn (71), Sr (5.6), and Cu (4.8) in teff compared to wheat and maize. Maize had the lowest concentrations of these essential elements. Mean concentrations (in μg/kg) of As (24.7) and Pb (70) in teff were relatively higher compared to wheat and maize, which had similar values of As (4.5) and Pb (8.9). Teff and wheat had similar Cd concentrations (in μg/kg) of 4.8 and 5.4 respectively compared to maize (1.5). Cadmium concentrations were below the Codex standard established for Cd in cereal grains (100 μg/kg). Only one teff sample exceeded the Codex standard set for Pb (200 μg/kg) in cereal grains. This study provides information on nutritional values and food safety of maize, wheat, and teff; the latter is becoming an alternative gluten-free diet for celiac patients in countries where wheat is commonly a staple food.Using firm-level data from the Refinitiv Datastream Worldscope database for more than 17,253 non-financial firms in 45 advanced and emerging economies, this paper examines how fiscal stimulus interacted with sectoral business cycle sensitivity has affected firms' sales and capital expenditures during the global financial crisis. Cross-sectional analyses indicate that reductions in structural fiscal balances are associated with higher firms' sales and capital expenditures (as percentage of their total assets) in 2009. This result is obtained notably for the manufacturing and construction industries and for different regions depending on the firm performance variable. Our findings have key implications for the design of fiscal response to shocks at industry and firm levels, including during the current COVID-19 pandemic.

The online version contains supplementary material available at 10.1057/s41294-021-00160-5.

The online version contains supplementary material available at 10.1057/s41294-021-00160-5.Ion mobility spectrometry coupled with mass spectrometry (IMS-MS) is a post-ionization separation technique that can be used for rapid multidimensional analyses of complex samples. IMS-MS offers untargeted analysis, including ion-specific conformational data derived as collisional cross section (CCS) values. Here, we combine nitrogen gas drift tube CCS (DTCCSN2) and Kendrick mass defect (KMD) analyses based on CH2 and H functional units to enable compositional analyses of petroleum substances. First, polycyclic aromatic compound standards were analyzed by IMS-MS to demonstrate how CCS assists the identification of isomeric species in homologous series. Next, we used case studies of a gasoline standard previously characterized for paraffin, isoparaffin, aromatic, naphthene, and olefinic (PIANO) compounds, and a crude oil sample to demonstrate the application of the KMD analyses and CCS filtering. Finally, we propose a workflow that enables confident molecular formula assignment to the IMS-MS-derived features in petroleum samples. Collectively, this work demonstrates how rapid untargeted IMS-MS analysis and the proposed data processing workflow can be used to provide confident compositional characterization of hydrocarbon-containing substances.Incorporating evidence-based community programs into clinical care recommendations and goals may help bridge the clinic-to-community transition for older adults. Engagement in evidence-based programs can help older adults manage chronic conditions and reduce fall risk through behavior change and self-management following a clinical episode of care. This paper describes evidence-based fall prevention and physical activity programs, provides resources to locate programs, and strategies to match older adults to the right programs.Anthropogenic noise is a pervasive environmental feature across both urban and non-urban habitats and presents a novel challenge especially for acoustically communicating species. While it is known that some species adjust acoustic signals to communicate more effectively in noisy habitats, we know very little about how the receivers of these signals might be impacted by anthropogenic noise. Here, we investigated female and male Litoria fallax frogs' ability to distinguish between high- and low-quality acoustic signals during the presence of background traffic noise and without. We performed a controlled behavioural experiment whereby frogs were presented with simultaneously broadcasted attractive and unattractive calls from opposing directions, once with background traffic noise and once without. We found that females in particular chose the unattractive call significantly more often (and males significantly less often) when noise was being broadcast. This indicates that anthropogenic noise potentially affects receiver responses to acoustic signals, even when calls are not acoustically masked, with potential consequences for maladaptive mating behaviours and population outcomes.

The online version contains supplementary material available at 10.1007/s10211-021-00378-7.

The online version contains supplementary material available at 10.1007/s10211-021-00378-7.