We characterize the evolution of a dynamical system by combining two well-known complex systems' tools, namely, symbolic ordinal analysis and networks. From the ordinal representation of a time series we construct a network in which every node weight represents the probability of an ordinal pattern (OP) to appear in the symbolic sequence and each edgeʼs weight represents the probability of transitions between two consecutive OPs. Several network-based diagnostics are then proposed to characterize the dynamics of different systems: logistic, tent, and circle maps. We show that these diagnostics are able to capture changes produced in the dynamics as a control parameter is varied. We also apply our new measures to empirical data from semiconductor lasers and show that they are able to anticipate the polarization switchings, thus providing early warning signals of abrupt transitions.

Hypoparathyroidism is usually caused by postsurgical or autoimmune damage to the parathyroid gland. We present the case of a 46-year-old Hispanic male with no significant past medical history who was admitted to the hospital with hypoxic respiratory failure due to coronavirus disease 2019 (COVID-19) infection and had a prolonged hospital course. He was incidentally found to have hyperphosphatemia and low parathyroid hormone (PTH) levels. During the second month of hospitalization, his phosphorus levels rose to 6.9 mg/dL (normal range: 2.4-4.7 mg/dl). His PTH levels were found to be at 8 pg/mL. Vitamin D levels obtained were also low (7 ng/dL), phosphorus was at 5.8 mg/dL with albumin of 2.9 g/dL, and calcium level was normal at 9.2 mg/dl. Parathyroid hormone-related peptide (PTHrP) level was low at 10. Malignancy and genetic causes were ruled out. The patient was started on 50,000 units of ergocalciferol once a week. He was also started on calcium acetate 1,334 mg three times a day for hyperphosphatemia. Phosphorus levels remained elevated, and sevelamer was added on discharge after he was weaned off oxygen and cleared by physical therapy. No explanation for persistent hyperphosphatemia and hypoparathyroidism was found. To date, there have been some reports linking severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to widespread tissue injury; however, there have been no reports so far on the effect of the parathyroid gland. Further studies are necessary to elaborate and to confirm the causative relationship between SARS-CoV-2 and hyperphosphatemia.

Background:The limited data available so far has shown a high mortality rate among COVID-19 patients admitted to the ICU. Possible risk factors for poor outcomes in this type of patients need to be analyzed so we can identify strategies to reduce mortality. Objective: Characterized the COVID-19 experience in Community hospital ICU. Methods: Single center retrospective cohort study involving all adult patients admitted to the ICU with severe COVID-19 infection. Results: 132 patients were admitted to ICU during the study period. There was a preponderance for males and the most common ethnicity was Hispanic. The overall mortality was 69%, and mortality after intubation was 76%. In the multivariable analysis older Age (OR = 15.7), Obesity (OR = 2.92) and Mechanical Ventilation (OR = 12.0) were found to be a significant independent risk factor for increased mortality. Conclusion:Our study confirms the high mortality rate in patients critically ill with COVID-19 requiring ICU care especially among older age group, mechanically ventilated and obese patients. Overall outcomes are comparable to larger tertiary care centers. Our findings highlight the need to plan for optimal resource allocation and tailoring therapies to target the disease so as to improve outcomes.

In recent years the problems related to modeling and improving business processes have been of growing interest. Indeed, companies are realizing the undeniable impact of a better understanding and management of business processes (BP) on the effectiveness, consistency, and transparency of their business operations.In this paper we propose to support this modeling effort with an approach that uses domain knowledge to improve the semantic quality of BP models. This approach relies on domain ontologies as a mean to capture domain knowledge and on meta-modeling techniques. The main contribution of this paper is threefold: 1) the meta-models describing both a domain ontology and a BP model are described, 2) the alignment between the concepts of both meta-models is defined and illustrated, 3) a set of OCL mapping rules is provided. A simple case study illustrates the process.