Telepresence and telerobotics

The capability for a single operator to simultaneously control complex remote multi degree of freedom robotic arms and associated dextrous end effectors is being developed. An optimal solution within the realm of current technology, can be achieved by recognizing that: (1) machines/computer systems are more effective than humans when the task is routine and specified, and (2) humans process complex data sets and deal with the unpredictable better than machines. These observations lead naturally to a philosophy in which the human's role becomes a higher level function associated with planning, teaching, initiating, monitoring, and intervening when the machine gets into trouble, while the machine performs the codifiable tasks with deliberate efficiency. This concept forms the basis for the integration of man and telerobotics, i.e., robotics with the operator in the control loop. The concept of integration of the human in the loop and maximizing the feed-forward and feed-back data flow is referred to as telepresence

The Asymmetric Effect of Diffusion Processes: Risk Sharing and Contagion

We provide a general characterization of diffusion processes, allowing to analyze both risk-sharing and contagion at the same time. We show that interdependencies are beneficial when the economic environment is favorable, and detrimental when the economic environment deteriorates. The risk of contagion increases the volatility of outcome and thus reduces the ability of the network to provide risk-sharing.Risk-sharing, Contagion, Networks.

Anisotropic compression in the high pressure regime of pure and Cr-doped vanadium dioxide

We present structural studies of V$_{1-x}$Cr$_x$O$_2$ (pure, 0.7% and 2.5% Cr doped) compounds at room temperature in a diamond anvil cell for pressures up to 20 GPa using synchrotron x-ray powder diffraction. All the samples studied show a persistence of the monoclinic $M_1$ symmetry between 4 and 12 GPa. Above 12 GPa, the monoclinic $M_1$ symmetry changes to isostructural $M_x$ phase (space group $P2_1/c$) with a significant anisotropy in lattice compression of the $b$-$c$ plane of the $M_{1}$ phase. This behavior can be reconciled invoking the pressure induced charge-delocalization

Anthropogenic Renourishment Feedback on Shorebirds: a Multispecies Bayesian Perspective

In this paper the realized niche of the Snowy Plover (Charadrius alexandrinus), a primarily resident Florida shorebird, is described as a function of the scenopoetic and bionomic variables at the nest-, landscape-, and regional-scale. We identified some possible geomorphological controls that influence nest-site selection and survival using data collected along the Florida Gulf coast. In particular we focused on the effects of beach replenishment interventions on the Snowy Plover (SP), and on the migratory Piping Plover	(PP)	(Charadrius	melodus )	and	Red	Knot	(RK)	(Calidris	canutus ).	Additionally, we investigated the potential differences between the SP breeding and wintering distributions using only regional-scale physiognomic variables and the recorded occur- rences. To quantify the relationship between past renourishment projects and shorebird species we used a Monte Carlo procedure to sample from the posterior distribution of the binomial probabilities that a region is not a nesting or a wintering ground conditional on the occurrence of a beach replenishment intervention in the same and the previous year. The results indicate that it was 2.3, 3.1, and 0.8 times more likely that a region was not a wintering ground following a year with a renourishment intervention for the SP, PP and RK respectively. For the SP it was 2.5. times more likely that a region was not a breeding ground after a renourishment event. Through a maximum entropy principle model we observed small differences in the habitat use of the SP during the breeding and the wintering season. However the habitats where RK was observed appeared quite different. While ecological niche models at the macro-scale are useful for determining habitat suitability ranges, the characterization of the species’ local niche is fundamentally important for adopting concrete multi-species management scenarios. Maintaining and creating optimal suitable habitats for SP characterized by sparse low vegetation in the foredunes areas, and uneven/low-slope beach surfaces, is the proposed conservation scenario to convert anthropic beach restorations and SP populations into a positive feedback without impacting other threatened shorebird species

Exploring the Potential of Generative AI for the World Wide Web

Generative Artificial Intelligence (AI) is a cutting-edge technology capable of producing text, images, and various media content leveraging generative models and user prompts. Between 2022 and 2023, generative AI surged in popularity with a plethora of applications spanning from AI-powered movies to chatbots. In this paper, we delve into the potential of generative AI within the realm of the World Wide Web, specifically focusing on image generation. Web developers already harness generative AI to help crafting text and images, while Web browsers might use it in the future to locally generate images for tasks like repairing broken webpages, conserving bandwidth, and enhancing privacy. To explore this research area, we have developed WebDiffusion, a tool that allows to simulate a Web powered by stable diffusion, a popular text-to-image model, from both a client and server perspective. WebDiffusion further supports crowdsourcing of user opinions, which we use to evaluate the quality and accuracy of 409 AI-generated images sourced from 60 webpages. Our findings suggest that generative AI is already capable of producing pertinent and high-quality Web images, even without requiring Web designers to manually input prompts, just by leveraging contextual information available within the webpages. However, we acknowledge that direct in-browser image generation remains a challenge, as only highly powerful GPUs, such as the A40 and A100, can (partially) compete with classic image downloads. Nevertheless, this approach could be valuable for a subset of the images, for example when fixing broken webpages or handling highly private content.Comment: 11 pages, 9 figure

Adaptive Probabilistic Forecasting of Electricity (Net-)Load

Electricity load forecasting is a necessary capability for power system operators and electricity market participants. The proliferation of local generation, demand response, and electrification of heat and transport are changing the fundamental drivers of electricity load and increasing the complexity of load modelling and forecasting. We address this challenge in two ways. First, our setting is adaptive; our models take into account the most recent observations available, yielding a forecasting strategy able to automatically respond to changes in the underlying process. Second, we consider probabilistic rather than point forecasting; indeed, uncertainty quantification is required to operate electricity systems efficiently and reliably. Our methodology relies on the Kalman filter, previously used successfully for adaptive point load forecasting. The probabilistic forecasts are obtained by quantile regressions on the residuals of the point forecasting model. We achieve adaptive quantile regressions using the online gradient descent; we avoid the choice of the gradient step size considering multiple learning rates and aggregation of experts. We apply the method to two data sets: the regional net-load in Great Britain and the demand of seven large cities in the United States. Adaptive procedures improve forecast performance substantially in both use cases for both point and probabilistic forecasting

The Asymmetric Effect of Diffusion Processes: Risk Sharing and Contagion

In this paper we provide a general characterization of diffusion processes, allowing us to analyze both risk-sharing and contagion effects at the same time. We illustrate the relevance of our theory with reference to the subprime mortgage crisis and more in general to the processes of securitization and interbank linkages. We show that interdependencies in real and financial assets are beneficial from a social point of view when the economic environment is favorable and detrimental when the economic environment deteriorates. In the latter case, private incentives are such that too many linkages are formed, with respect to what is socially desirable. The risk of contagion increases the volatility of the outcome and thus reduces the ability of the financial networks to provide risk-sharing. Our analysis suggests that a likely major explanation of the subprime mortgage crisis is the process of securitization itself, in addition to the absence of transparency about the characteristics of the underlying assets that the multiple layers of financial intermediation fostered, as commonly claimed. This may call for a different emphasis on the role of public intervention. While a goal to stabilize the economy in good times should be to disrupt the channels that bring contagion, that is a positive correlation in the returns, in a period of worsening economic conditions our analysis suggests regulatory intervention aimed at disconnecting the economy at crucial nodes. Moreover, we show that policy interventions should be aimed at rescuing institutions, but not their managers. Diminishing the cost of default actually increases the inefficiency due to the divergence between the social and the individual optimum