Robust Multivariate Correlation Techniques: A Confirmation Analysis using Covid-19 Data Set

Robust multivariate correlation techniques are proposed to determine the strength of the association between two or more variables of interest since the existing multivariate correlation techniques are susceptible to outliers when the data set contains random outliers. The performances of the proposed techniques were compared with the conventional multivariate correlation techniques. All techniques under study are applied on COVID-19 data sets for Malaysia and Nigeria to determine the level of association between study variables which are confirmed, discharged, and death cases. These techniques’ performances are evaluated based on the multivariate correlation (R), multivariate coefficient of determination (R^2), and Adjusted R^2. The proposed techniques showed R=0.99 and the conventional methods showed that R ranges from 0.44 to 0.73. The R^2 and the Adjusted R^2 for proposed methods are 0.98 and 0.97 while the conventional methods showed that R equals 0.53, 0.44, and 0.19 whereas Adjusted R^2 equals 0.52, 0.43, and 0.18, respectively. The proposed techniques strongly affirmed that for any patient to be discharged or die of the Covid-19, the patient must be confirmed Covid-19 positive, whereas the conventional method showed moderate to very weak affirmation. Based on the results, the proposed techniques are robust and show a very strong association between the variables of interest than the conventional techniques.

ASSURANCE CASE FOR SAFETY AND SECURITY IMPLEMENTATION: A SURVEY OF APPLICATIONS

This paper presents a survey of Assurance Case implementation for applications which are not directly related to the usual for Assurance Case regulatory regime. The UK is the country which first developed the theory of Assurance Case as a response to big catastrophes, and most applies Assurance Case regime for many industrial domains. USA, Australia and EU countries apply Assurance Case approach for safety and security regulation and licensing. For the last two decades Assurance Case has been used mostly for confirmation analysis of critical systems with established set of regulatory requirements. There are proven standards of use, notations and tools to support Assurance Case methodology. However, many researchers have tried to find approach to expand Assurance Case application to communicating domains. We group the following directions of Assurance Case applications as the following ones: Assurance Case for attributes assessment such as quality, dependability and, first of all, safety and security, Assurance Case based certification, improvement of argumentation, assurance based development, and Assurance Case for knowledge management. The main challenges and solutions of development and application of Assurance Case methodology, techniques and tools have been analyzed.

Isolation and Identification of Biofilm-Forming Staphylococcus Aureus in Commercial Cow Milk Products

Food poisoning caused by the contamination from Staphylococcus aureus are frequently found in foodespecially in dairy products. Pasteurization process in milk production was not enough to kill S. aureus becauseit formed biofilm that could survive in high temperature. This research aimed to study the presence of biofilmforming S. aureus in samples from packed commercial milk products in Yogyakarta City, Indonesia. Twentyisolates from dairy products were grown in Brain Heart Infusion (BHI) broth then inoculated into Braid-ParkerAgar (BPA) medium to get the candidate of S. aureus isolates. These isolate candidates were selected usingMannitol Salt Agar (MSA) and Congo Red Agar (CRA) medium. Another selection was done by carbohydratefermentation analysis and confirmed using API STAPH. Confirmation analysis showed that eight isolateswere identified as S. aureus. Another two isolates were identified as S. xylosus and S. haemolyticus. Therefore,it indicated the presence of Staphylococcus aureus as contaminant in dairy products.

Determination of cannabinoids in oral fluid and urine of “light cannabis” consumers: a pilot study

Background In those countries where cannabis use is still illegal, some manufacturers started producing and selling “light cannabis”: dried flowering tops containing the psychoactive principle Δ-9-tetrahydrocannabinol (THC) at concentrations lower than 0.2% together with variable concentration of cannabidiol (CBD). We here report a pilot study on the determination of cannabinoids in the oral fluid and urine of six individuals after smoking 1 g of “light cannabis”. Methods On site screening for oral fluid samples was performed, as a laboratory immunoassay test for urine samples. A validated gas chromatography-mass spectrometry (GC-MS) method was then applied to quantify THC and CBD, independently from results of screening tests. Results On site screening for oral fluid samples, with a THC cut-off of 25 ng/mL gave negative results for all the individuals at different times after smoking. Similarly, negative results for urine samples screening from all the individuals were obtained. Confirmation analyses showed that oral fluid THC was in the concentration range from 2.5 to 21.5 ng/mL in the first 30 min after smoking and then values slowly decreased. CBD values were usually one order of magnitude higher than those of THC. THC-COOH, the principal urinary THC metabolite, presented the maximum urinary value of 1.8 ng/mL, while urinary CBD had a value of 15.1 ng/mL. Conclusions Consumers of a single 1 g dose of “light cannabis” did not result as positive in urine screening, assessing recent consumption, so that confirmation would not be required. Conversely, they might result as positive to oral fluid testing with some on-site kits, with THC cut-off lower than 25 ng/mL, at least in the first hour after smoking and hence confirmation analysis can be then required. No conclusions can be drawn of eventual chronic users.

A Prediction Method of Historical Timber Buildings’ Vibrations Induced by Traffic Loads and Its Validation

A prediction method in the frequency domain is proposed for predicting the vibrations of historical timber building induced by traffic loads. The modal parameters of a structure are identified using a double-confirmation analysis method based on the autospectrum. Then, the vibration responses of the building are calculated using a limited number of measurement records by inputting the calculated vibration information for the foundation of the updated building model. The proposed method is used to predict the vibrations of the Buddhist sutra depositary at Yangzhou Zhunti Temple. Comparing the results shows that the vibration responses of a structure under traffic loads can be effectively predicted in the relevant frequency bands.