Introduction The clinical presentation of coronavirus disease 2019 (COVID-19) overlaps with many other common cold and influenza viruses. Identifying patients with a higher probability of infection becomes crucial in settings with limited access to testing. We developed a prediction instrument to assess the likelihood of a positive polymerase chain reaction (PCR) test, based solely on clinical variables that can be determined within the time frame of an emergency department (ED) patient encounter. Methods We derived and prospectively validated a model to predict SARS-CoV-2 PCR positivity in patients visiting the ED with symptoms consistent with the disease. Results Our model was based on 617 ED visits. In the derivation cohort, the median age was 36 years, 43% were men, and 9% had a positive result. The median time to testing from the onset of initial symptoms was four days (interquartile range [IQR]: 2–5 days, range 0–23 days), and 91% of all patients were discharged home. The final model based on a multivariable logistic regression included a history of close contact (adjusted odds ratio [AOR] 2.47, 95% confidence interval [CI], 1.29–4.7); fever (AOR 3.63, 95% CI, 1.931–6.85); anosmia or dysgeusia (AOR 9.7, 95% CI, 2.72–34.5); headache (AOR 1.95, 95% CI, 1.06–3.58), myalgia (AOR 2.6, 95% CI, 1.39–4.89); and dry cough (AOR 1.93, 95% CI, 1.02–3.64). The area under the curve (AUC) from the derivation cohort was 0.79 (95% CI, 0.73–0.85) and AUC 0.7 (95% CI, 0.61–0.75) in the validation cohort (N = 379). Conclusion We developed and validated a clinical tool to predict SARS-CoV-2 PCR positivity in patients presenting to the ED to assist with patient disposition in environments where COVID-19 tests or timely results are not readily available.

Several operating parameters for the control and protection of the units are acquired by the control and protection systems used in industrial applications. The use of these parameters in conjunction of physical models, empirical models and transfer functions (that represent digital replicas of the engine) allows for a broader scope of condition monitoring, taking into account the wing to wing process which spans from data acquisition to end user actionable insight. This paper describes 3 specific cases: 1) an algorithm based on the performance model of the overall GT used to monitor the axial compressor degradation and optimize the planned axial compressor water wash of an aero-derivative GT; 2) an analytic based on the flow function physic model used to monitor the clogging of the fuel nozzles in a heavy duty GT and to plan their maintenance; 3) an analytic based on a hybrid model used to monitor the axial thrust acting on a roller bearing of an aero-derivative GT and used to verify the status of the bearing and to plan its maintenance. Moreover, the paper provides details about the evaluation of the measurements, describes the model accuracy and explains how the results obtained are affected by these uncertainties and the methods used to mitigate these uncertainties. In addition, this paper shows a method to aggregate and weigh the monitoring of each single component and its own status into an overall health view.

The monitoring and diagnostics of Industrial systems is increasing in complexity with larger volume of data collected and with many methods and analytics able to correlate data and events. The setup and training of these methods and analytics are one of the impacting factors in the selection of the most appropriate solution to provide an efficient and effective service, that requires the selection of the most suitable data set for training of models with consequent need of time and knowledge. The study and the related experiences proposed in this paper describe a methodology for tracking features, detecting outliers and derive, in a probabilistic way, diagnostic thresholds to be applied by means of hierarchical models that simplify or remove the selection of the proper training dataset by a subject matter expert at any deployment. This method applies to Industrial systems employing a large number of similar machines connected to a remote data center, with the purpose to alert one or more operators when a feature exceeds the healthy distribution. Some relevant use cases are presented for an aeroderivative gas turbine covering also its auxiliary equipment, with deep dive on the hydraulic starting system. The results, in terms of early anomaly detection and reduced model training effort, are compared with traditional monitoring approaches like fixed threshold. Moreover, this study explains the advantages of this probabilistic approach in a business application like the fleet monitoring and diagnostic advanced services.

The use of the Internet by terrorists has greatly contributed to international terrorism. The Internet is a main strategic communication asset for terrorists who use online message boards and chat rooms to share information, coordinate attacks, spread propaganda, raise money, and recruit. The Internet gives terrorists a medium to legitimize, propagate, and intimidate citizens to their cause. Their strategies are based on careful analysis of human communications; thus, messages are adapted and carefully delivered to appeal to people who may need something to believe in. This study bridged the gap in knowledge by exploring, understanding, and explaining the perceptions of 10 American terrorist experts on how the use of the Internet by terrorists has shaped international terrorism. Findings of the study indicate that the use of the Internet by terrorists has shaped international terrorism, which resulted in major challenges for counterterrorism agencies in the United States and abroad due to the ability of terrorists to easily close, change, and create new websites or accounts. In addition, counterterrorism experts also have to deal with advanced encryption software and the anonymity of terrorist suspects. Terrorists are able to attract other like-minded individuals or sympathizers to their cause by using the Internet as the medium of communication. The research is significant in that it is directed at the U.S. intelligence community and international counterterrorism entities in order to make continuous improvements in the United States' homeland security by recognizing terrorist Internet tactics so they can quickly and effectively respond to them. This requires collaboration among counterterrorism agencies and organizations in the U.S. as well as collaboration among member states.