This paper provides a reformulation of the scenario-based two-stage unit commitment problem under uncertainty that allows finding unit-commitment plans that perform reasonably well both in ...expectation and for the worst case. The proposed reformulation is based on partitioning the sample space of the uncertain factors by clustering the scenarios that approximate their probability distributions. The degree of conservatism of the resulting unit-commitment plan (that is, how close it is to the one provided by a purely robust or stochastic unit-commitment formulation) is controlled by the number of partitions into which the said sample space is split. To efficiently solve the proposed reformulation of the unit-commitment problem under uncertainty, we develop two alternative parallelization and decomposition schemes that rely on a column-and-constraint generation procedure. Finally, we analyze the quality of the solutions provided by this reformulation for a case study based on the IEEE 14-node power system and test the effectiveness of the proposed parallelization and decomposition solution approaches on the larger IEEE 3-Area RTS-96 power system.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of COVID-19, is considered a zoonotic pathogen mainly transmitted human to human. Few reports indicate that pets ...may be exposed to the virus. The present report describes a cat suffering from severe respiratory distress and thrombocytopenia living with a family with several members affected by COVID-19. Clinical signs of the cat prompted humanitarian euthanasia and a detailed postmortem investigation to assess whether a COVID-19–like disease was causing the condition. Necropsy results showed the animal suffered from feline hypertrophic cardiomyopathy and severe pulmonary edema and thrombosis. SARS-CoV-2 RNA was only detected in nasal swab, nasal turbinates, and mesenteric lymph node, but no evidence of histopathological lesions compatible with a viral infection were detected. The cat seroconverted against SARS-CoV-2, further evidencing a productive infection in this animal. We conclude that the animal had a subclinical SARS-CoV-2 infection concomitant to an unrelated cardiomyopathy that led to euthanasia.
A high and homogenous trapped field, as well as the levitation force of YBCO parts are the key properties in regard to practical applications of high‐temperature superconductors. Both of these ...parameters are often the determining factor in the bulk's performance. In this contribution, the impact of bulk thickness on the trapped field and levitation force was studied in detail. A number of significantly thicker samples both with and without artificial holes were prepared. The samples were manufactured using top‐seeded melt growth with a diameter of 28 mm and a thickness of 18 mm. An additional source of “liquid phase” was placed underneath the YBCO bulks during the TSMG process in order to negate the leakage of “liquid phase.” Properties of these samples were compared and to most similar samples with and without artificial holes were chosen to be gradually ground down. SEM was employed in order to confirm the impact of artificial holes on the microstructure. The samples were characterized between each individual grinding step. Using this approach, the dependency of the trapped field and levitation force, as well as the addition of artificial holes, can be properly evaluated. The method described above has allowed us to determine the optimal bulk geometries for various applications depending on the desired properties. Such data are of the utmost importance in the field of applied high‐temperature superconducting bulks.
Research in posttraumatic growth (PTG) among cancer patients has been triggered primarily by the inclusion of serious illnesses among the events that can lead to posttraumatic stress disorder (PTSD); ...increasing survival rates among cancer patients; and, attempts at encouraging a positive psychology that focuses on a patient's ability to fight adversity. The difficulties encountered in clearly defining the processes associated with this subjective feeling of growth following recovery raise doubts concerning the real or illusory nature of the phenomenon and its adaptative value. This paper explains why cancer may be different than other traumas and why PTG may interact with this ecology of circumstances in different ways. Difficulty in identifying a single stressor, the internal source of the event, cancer as a future, ongoing and chronic integration threat, and greater perceived control differences between cancer and others traumas. This review brings together the latest studies of PTG in cancer, and focuses in the debate of the real or illusory nature of the PTG and his adaptative value. The ongoing threat, uncertainty and vulnerability associated with cancer are the variables that have been related most consistently with PTG and tend to confuse the relationship between PTG and emotional well-being, too.
A fuzzy database engine for mongoDB Medina, Juan Miguel; Blanco, Ignacio J.; Pons, Olga
International journal of intelligent systems,
September 2022, 2022-09-00, 20220901, Letnik:
37, Številka:
9
Journal Article
Recenzirano
Odprti dostop
Big Data are a paradigm through which valuable information is achieved through the analysis of a large amount of data. The sources of these data can be varied, from data streams that will be ...processed in real time, to the exploitation of transactional data stored in databases. For this last use, due to their scalability, the NoSQL databases, like
mongoDB, a DBMS oriented to documents, have been consolidated as a powerful tool for the storage and processing of large volumes of data. On the other hand, information sources for Big Data algorithms can contain imprecise information, and the way to obtain, aggregate and present results can have an imprecise nature as well. For this reason, it is useful to provide fuzzy extensions to these DBMSs. In the case of
MongoDB, there are few proposals and not very complete. This paper describes fzMongoDB, a fuzzy database engine that provides the
mongoDB database with the capacity to store documents with imprecise information and to retrieve them in a flexible way. It is implemented and integrated on the
mongoDB server using the resources it provides. The model and implementation of fzMongoDB also includes an indexing mechanism that accelerates the retrieval process on fuzzy queries. Also, the performance of these indexing mechanisms is evaluated.
Adsorption of uremic solutes to activated carbon provides a potential means to limit dialysate volumes required for new dialysis systems. The ability of activated carbon to take up uremic solutes ...has, however, not been adequately assessed.
Graded volumes of waste dialysate collected from clinical hemodialysis treatments were passed through activated carbon blocks. Metabolomic analysis assessed the adsorption by activated carbon of a wide range of uremic solutes. Additional experiments tested the ability of the activated carbon to increase the clearance of selected solutes at low dialysate flow rates.
Activated carbon initially adsorbed the majority, but not all, of 264 uremic solutes examined. Solute adsorption fell, however, as increasing volumes of dialysate were processed. Moreover, activated carbon added some uremic solutes to the dialysate, including methylguanidine. Activated carbon was particularly effective in adsorbing uremic solutes that bind to plasma proteins.
dialysis experiments showed that introduction of activated carbon into the dialysate stream increased the clearance of the protein-bound solutes indoxyl sulfate and p-cresol sulfate by 77%±12% (mean±SD) and 73%±12%, respectively, at a dialysate flow rate of 200 ml/min, but had a much lesser effect on the clearance of the unbound solute phenylacetylglutamine.
Activated carbon adsorbs many but not all uremic solutes. Introduction of activated carbon into the dialysate stream increased the clearance of those solutes that it does adsorb.
Abstract In this paper, we propose a machine learning approach for detecting superficial defects in metal surfaces using point cloud data. We compare the performance of two popular deep learning ...architectures, multilayer perceptron networks (MLPs) and fully convolutional networks (FCNs), with varying feature sets. Our results show that FCNs (F1=0.94) outperformed MLPs (F1=0.52) in terms of precision, recall, and F1-score. We found that transfer learning with pre-trained models can improve performance when the amount of available data is limited. Our study highlights the importance of considering the amount and quality of training data in developing machine learning models for defect detection in industrial settings with 3D images.
Spondyloarthritis is a group of immune-mediated rheumatic disorders that significantly impact patients' physical function and quality of life. Patients with spondyloarthritis experience a greater ...prevalence of cardiometabolic disorders, such as obesity, hypertension, dyslipidemia and diabetes mellitus, and these comorbidities are associated with increased spondyloarthritis disease activity and risk of cardiovascular events. This narrative review summarizes the evidence for a physiological link between inflammatory status and cardiometabolic comorbidities in spondyloarthritis, as well as the impact of interleukin (IL)-17 blockade versus other molecular mechanisms in patients with cardiometabolic conditions. The IL-23/IL-17 axis plays a pivotal role in the pathophysiology of spondyloarthritis by promoting inflammation and tissue remodeling at the affected joints and entheses. The importance of the IL-23/IL-17 signaling cascade in underlying sub-clinical inflammation in common cardiometabolic disorders suggests the existence of shared pathways between these processes and spondyloarthritis pathophysiology. Thus, a bidirectional relationship exists between the effects of biologic drugs and patients' cardiometabolic profile, which must be considered during treatment decision making. Biologic therapy may induce changes in patients' cardiometabolic status and cardiometabolic conditions may conversely impact the clinical response to biologic therapy. Available evidence regarding the impact of IL-17 blockade with secukinumab on cardiometabolic parameters suggests this drug does not interfere with traditional cardiovascular risk markers and could be associated with a decreased risk of cardiovascular events. Additionally, the efficacy and retention rates of secukinumab do not appear to be negatively affected by obesity, with some studies reporting a positive impact on clinical outcomes, contrary to that described with other approaches, such as tumor necrosis factor blockade. In this article, we also review evidence for this bidirectional association with other treatments for spondyloarthritis. Current evidence suggests that IL-17-targeted therapy with secukinumab is highly effective in spondyloarthritis patients with cardiometabolic comorbidities and may provide additional cardiometabolic benefits.
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