Stability analysis tool for tuning unconstrained decentralized model predicitive controllers

Some processes are naturally suitable to be controlled in a decentralized framework: centralized control solutions are often infeasible in dealing with large scale plants and they are technologically prohibitive when the processes are too fast for the available computational resources. In these cases, the resulting control problem is usually split in many smaller subproblems and the global requirements are guaranteed by means of a proper coordination. The unconstrained decentralized case is here considered and a coordination strategy is proposed for improving the global control performances. This paper present a tool for setting up and tuning a nominally stable decentralized Model Predictive Controller. Numerical examples are proposed for testing and validating the developed technique

Model predictive energy control of ventilation for underground stations

Smart building systems are opening up new markets, nevertheless the implementation of these novel technologies still lacks suitable and proven whole engineering solutions in complex buildings. This paper presents a detailed approach for the ventilation control of an underground space, as an example of application of the developed solution to a very harsh environment but also highly demanding in terms of energy consumption. The underground spaces are characterized by a particular thermal behavior, because of the continuous and huge thermal exchange they have with the outside, via the openings and the ground surrounding the majority of the building. The main objective of the developed methodology is to reduce energy consumption of ventilation control while maintaining acceptable comfort levels: succeeding in achieving this twofold goal in a real station and the generalization of the approach are the most relevant contributions of the paper. The developed solution is based on a Model-based Predictive Control algorithm used together with a proper monitoring platform. The model predictive control is based on a Bayesian environmental prediction model, which works in cooperation with a weather forecast web service, schedule-based predictions about trains and external fans and an occupancy detection system to appraise the real amount of people. The prediction model develops scenarios useful to allow the controller acting in advance in order to adapt the system to the current and future conditions of use, taking profit of the knowledge of the real ventilation demand. Finally, the proposed control architecture is applied to the Passeig de Gràcia metro station in Barcelona as a case study, validating the usefulness of the proposed approach and obtaining more than 30% of energy savings in the ventilation system, while maintaining the pre-existing comfort levels. The saving percentage values estimated by simulation are confirmed by the direct measures continuously taken on site through energy-meters

Training of YOLO Neural Network for the Detection of Fire Emergency Assets

Building assets surveys are cost and time demanding and the majority of current methods still rely on manual procedures. New technologies could be used to support this task. The exploitation of Artificial Intelligence (AI) for the automatic interpretation of data is spreading throughout various application fields. However, a challenge with AI is the very large number of training images required for robustly detect and classify each object class. This paper details the procedure and parameters used for the training of a custom YOLO neural network for the recognition of fire emergency assets. The minimum number of pictures for obtaining good recognition performances and the image augmentation process have been investigated. In the end, it was found that fire extinguishers and emergency signs are reasonably detected and their position inside the pictures accurately evaluated. The use case proposed in this paper for the use of custom YOLO is the retrieval of as-is information for existing buildings. The trained neural networks are part of a system that makes use of Augmented Reality devices for capturing pictures and for visualizing the results directly on site

Superconductivity in Ropes of Single-Walled Carbon Nanotubes

We report measurements on ropes of Single Walled Carbon Nanotubes (SWNT) in low-resistance contact to non-superconducting (normal) metallic pads, at low voltage and at temperatures down to 70 mK. In one sample, we find a two order of magnitude resistance drop below 0.55 K, which is destroyed by a magnetic field of the order of 1T, or by a d.c. current greater than 2.5 microA. These features strongly suggest the existence of superconductivity in ropes of SWNT.Comment: Accepted for publication in Phys. Rev. Let

Reduced-order modeling for energy performance contracting

Buildings subject to Energy Performance Contracts (EPCs) are usually quite complex public buildings, sometimes relatively old and usually barely documented from the technical standpoint. Gathering comprehensive and reliable technical information is a time consuming and expensive process that has to be carried out within the submission deadline. In these conditions, the standard approach to energy performance forecasting which uses detailed simulation is practically unfeasible. This paper proposes a reduced-order modeling approach that is tailored to the EPC tendering phase. The proposed methodology extends a third order building model, introducing explicit, albeit still abstract, representations of the heating/cooling system, of the weather influence and of the end-user gains. The extended parameter set reflects to a large degree the information that is readily available in practical on-site surveying, or that can be easily calculated from that information. As a consequence of the simplified physics, a knowledge driven, practical calibration procedure, which provides an effective way of reducing uncertainty, is proposed. The calibration procedure analyses the uncertainty present in the available knowledge and uses the constraints imposed by the implemented physics on the parameters’ dynamic to assess their value estimation. The modeling approach is exemplified through three case studies: the first one provides the comparison of the reduced-order model predictions with the outcomes of a detailed model of a small hospital, the second one is used to compare the reduced-order model predictions with the detailed measurements of energy consumption of a real building, and the third case study exemplifies the use in operational context with scarce information.Peer ReviewedPostprint (author's final draft

Superconductivity in Ropes of Single-Walled Carbon Nanotubes

We report measurements on ropes of Single Walled Carbon Nanotubes (SWNT) in low-resistance contact to non-superconducting (normal) metallic pads, at low voltage and at temperatures down to 70 mK. In one sample, we find a two order of magnitude resistance drop below 0.55 K, which is destroyed by a magnetic field of the order of 1T, or by a d.c. current greater than 2.5 microA. These features strongly suggest the existence of superconductivity in ropes of SWNT.Comment: Accepted for publication in Phys. Rev. Let

Cannabis oil: Effects on Cannabinoid-Induced Tetrad, blood pressure and metabolic parameters in female rats fed a sucrose-rich diet

Metabolic Syndrome (MS) is one of the most commonly used names for a clinical entity that brings together or associates different disorders that increase the risk of cardiovascular disease. Cannabis sativa has been used as an herbal medicine for tens of centuries. This study aimed to analyze the effects of cannabis oil administration on cannabinoid-induced tetrad, systolic and diastolic blood pressure, and metabolic parameters in normal female rats fed a sucrose-rich diet (SRD). Female Wistar rats were fed with the one of following diets for 21 days: Reference Diet (RD): standard commercial laboratory diet, SRD, and SRD+Cannabis oil (SRD+Ca): oral administration of 1 mg/kg body weight of cannabis oil daily. The full spectrum cannabis oil contains a total cannabinoid CBD:THC 2:1 ratio. Cannabis oil administration in the SRD significantly increased analgesia and decreased locomotion. Systolic and diastolic blood pressures decreased during the experimental protocol. In the SRD+Ca group, serum triglyceride levels decreased significantly, without changes in cholesterol and glucose levels. In addition, serum uric acid, AST, ALT and AP levels were significantly decreased. In the liver, the abnormalities of the histological sections observed in the SRD group and triglycerides and cholesterol content improved remarkably with the cannabis oil administration. Our results suggest that the administration of full-spectrum cannabis oil, could be useful as a strategy to prevent some of the alterations present in MS, including hypertension, dyslipidemia, and liver damage. Furthermore, the analgesic effect of cannabis oil could be observed in female rats fed an SRD.Centro de Investigación y Desarrollo en Criotecnología de Alimento

Withanolides and related steroids

Since the isolation of the first withanolides in the mid-1960s, over 600 new members of this group of compounds have been described, with most from genera of the plant family Solanaceae. The basic structure of withaferin A, a C28 ergostane with a modified side chain forming a δ-lactone between carbons 22 and 26, was considered for many years the basic template for the withanolides. Nowadays, a considerable number of related structures are also considered part of the withanolide class; among them are those containing γ-lactones in the side chain that have come to be at least as common as the δ-lactones. The reduced versions (γ and δ-lactols) are also known. Further structural variations include modified skeletons (including C27 compounds), aromatic rings and additional rings, which may coexist in a single plant species. Seasonal and geographical variations have also been described in the concentration levels and types of withanolides that may occur, especially in the Jaborosa and Salpichroa genera, and biogenetic relationships among those withanolides may be inferred from the structural variations detected. Withania is the parent genus of the withanolides and a special section is devoted to the new structures isolated from species in this genus. Following this, all other new structures are grouped by structural types. Many withanolides have shown a variety of interesting biological activities ranging from antitumor, cytotoxic and potential cancer chemopreventive effects, to feeding deterrence for several insects as well as selective phytotoxicity towards monocotyledoneous and dicotyledoneous species. Trypanocidal, leishmanicidal, antibacterial, and antifungal activities have also been reported. A comprehensive description of the different activities and their significance has been included in this chapter. The final section is devoted to chemotaxonomic implications of withanolide distribution within the Solanaceae. Overall, this chapter covers the advances in the chemistry and biology of withanolides over the last 16 years.Fil: Misico, Rosana Isabel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Orgánica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad de Microanálisis y Métodos Físicos Aplicados a la Química Orgánica (i); ArgentinaFil: Nicotra, V.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto Multidisciplinario de Biología Vegetal (p); Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Química Orgánica; ArgentinaFil: Oberti, Juan Carlos María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto Multidisciplinario de Biología Vegetal (p); Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Química Orgánica; ArgentinaFil: Barboza, Gloria Estela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Instituto Multidisciplinario de Biología Vegetal (p); Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Farmacia; ArgentinaFil: Gil, Roberto Ricardo. University Of Carnegie Mellon; Estados UnidosFil: Burton, Gerardo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Orgánica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad de Microanálisis y Métodos Físicos Aplicados a la Química Orgánica (i); Argentin

Clinical and organizational factors associated with mortality during the peak of first COVID-19 wave: the global UNITE-COVID study

Purpose: To accommodate the unprecedented number of critically ill patients with pneumonia caused by coronavirus disease 2019 (COVID-19) expansion of the capacity of intensive care unit (ICU) to clinical areas not previously used for critical care was necessary. We describe the global burden of COVID-19 admissions and the clinical and organizational characteristics associated with outcomes in critically ill COVID-19 patients. Methods: Multicenter, international, point prevalence study, including adult patients with SARS-CoV-2 infection confirmed by polymerase chain reaction (PCR) and a diagnosis of COVID-19 admitted to ICU between February 15th and May 15th, 2020. Results: 4994 patients from 280 ICUs in 46 countries were included. Included ICUs increased their total capacity from 4931 to 7630 beds, deploying personnel from other areas. Overall, 1986 (39.8%) patients were admitted to surge capacity beds. Invasive ventilation at admission was present in 2325 (46.5%) patients and was required during ICU stay in 85.8% of patients. 60-day mortality was 33.9% (IQR across units: 20%–50%) and ICU mortality 32.7%. Older age, invasive mechanical ventilation, and acute kidney injury (AKI) were associated with increased mortality. These associations were also confirmed specifically in mechanically ventilated patients. Admission to surge capacity beds was not associated with mortality, even after controlling for other factors. Conclusions: ICUs responded to the increase in COVID-19 patients by increasing bed availability and staff, admitting up to 40% of patients in surge capacity beds. Although mortality in this population was high, admission to a surge capacity bed was not associated with increased mortality. Older age, invasive mechanical ventilation, and AKI were identified as the strongest predictors of mortality