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Author(s):  
Linh H. Nghiem ◽  
Francis K. C. Hui ◽  
Samuel Müller ◽  
A. H. Welsh

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Zsigmond Benkő ◽  
Tamás Bábel ◽  
Zoltán Somogyvári

AbstractRecognition of anomalous events is a challenging but critical task in many scientific and industrial fields, especially when the properties of anomalies are unknown. In this paper, we introduce a new anomaly concept called “unicorn” or unique event and present a new, model-free, unsupervised detection algorithm to detect unicorns. The key component of the new algorithm is the Temporal Outlier Factor (TOF) to measure the uniqueness of events in continuous data sets from dynamic systems. The concept of unique events differs significantly from traditional outliers in many aspects: while repetitive outliers are no longer unique events, a unique event is not necessarily an outlier; it does not necessarily fall out from the distribution of normal activity. The performance of our algorithm was examined in recognizing unique events on different types of simulated data sets with anomalies and it was compared with the Local Outlier Factor (LOF) and discord discovery algorithms. TOF had superior performance compared to LOF and discord detection algorithms even in recognizing traditional outliers and it also detected unique events that those did not. The benefits of the unicorn concept and the new detection method were illustrated by example data sets from very different scientific fields. Our algorithm successfully retrieved unique events in those cases where they were already known such as the gravitational waves of a binary black hole merger on LIGO detector data and the signs of respiratory failure on ECG data series. Furthermore, unique events were found on the LIBOR data set of the last 30 years.


2022 ◽  
Author(s):  
Miron Bartosz Kursa

Abstract Kendall transformation is a conversion of an ordered feature into a vector of pairwise order relations between individual values. This way, it preserves ranking of observations and represents it in a categorical form. Such transformation allows for generalisation of methods requiring strictly categorical input, especially in the limit of small number of observations, when discretisation becomes problematic.In particular, many approaches of information theory can be directly applied to Kendall-transformed continuous data without relying on differential entropy or any additional parameters. Moreover, by filtering information to this contained in ranking, Kendall transformation leads to a better robustness at a reasonable cost of dropping sophisticated interactions which are anyhow unlikely to be correctly estimated. In bivariate analysis, Kendall transformation can be related to popular non-parametric methods, showing the soundness of the approach.The paper also demonstrates its efficiency in multivariate problems, as well as provides an example analysis of a real-world data.


2022 ◽  
Author(s):  
Angélica Maria Tortola Ribeiro ◽  
Paulo Justiniano Ribeiro ◽  
Wagner Hugo Bonat

Abstract We propose a covariance specification for modeling spatially continuous multivariate data. This model is based on a reformulation of Kronecker’s product of covariance matrices for Gaussian random fields. We illustrate the case with the Matérn function used for specifying marginal covariances. The structure holds for other choices of covariance functions with parameters varying in their usual domains, which makes the estimation process more accessible. The reduced computational time and flexible generalization for increasing number of variables, make it an attractive alternative for modelling spatially continuous data. Theoretical results for the likelihood function and the derivatives of the covariance matrix are presented. The proposed model is fitted to the literature’s soil250 dataset, and adequacy measures, forecast errors and estimation times are compared with the ones obtained based on classical models. Furthermore, the model is fitted to the classic meuse dataset to illustrate the model’s flexibility in a four-variate analysis. A simulation study is performed considering different parametric scenarios to evaluate the asymptotic properties of the maximum likelihood estimators. The satisfactory results, its simpler structure and the reduced estimation time make the proposed model a candidate approach for multivariate analysis of spatial data.


F1000Research ◽  
2022 ◽  
Vol 11 ◽  
pp. 10
Author(s):  
Eduardo De la Cruz-Cano ◽  
Cristina del C Jiménez–González ◽  
José A Díaz-Gandarilla ◽  
Carlos J López–Victorio ◽  
Adelma Escobar-Ramírez ◽  
...  

Background. Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is the etiological agent of the coronavirus disease 2019 (COVID-19) pandemic. Among the risk factors associated with the severity of this disease is the presence of several metabolic disorders. For this reason, the aim of this research was to identify the comorbidities and laboratory parameters among COVID-19 patients admitted to the intensive care unit (ICU), comparing the patients who required invasive mechanical ventilation (IMV) with those who did not require IMV, in order to determine the clinical characteristics associated with the COVID-19 severity. Methods. We carried out a cross-sectional study among 152 patients who were admitted to the ICU from April 1st to July 31st, 2021, in whom the comorbidities and laboratory parameters associated with the SARS-CoV-2 infection severity were identified. The data of these patients was grouped into two main groups: “patients who required IMV” and “patients who did not require IMV”. The nonparametric Mann–Whitney U test for continuous data and the χ2 test for categorical data were used to compare the variables between both groups. Results. Of the 152 COVID-19 patients who were admitted to the ICU, 66 required IMV and 86 did not require IMV. Regarding the comorbidities found in these patients, a higher prevalence of type 2 diabetes mellitus (T2DM), hypertension and obesity was observed among patients who required IMV vs. those who did not require IMV (p<0.05). Concerning laboratory parameters, only glucose, Interleukin 6 (IL-6), lactate dehydrogenase (LDH) and C-reactive protein (CRP) were significantly higher among patients who required IMV than in those who did not require IMV (p<0.05). Conclusion. This study performed in a Mexican population indicates that comorbidities such as: T2DM, hypertension and obesity, as well as elevated levels of glucose, IL-6, LDH and CRP are associated with the COVID-19 severity.


2022 ◽  
Vol 4 (1) ◽  
pp. 01-04
Author(s):  
Gürcan ARSLAN

Background: Severe acute respiratory tract infection, pneumonia, kidney failure, and multi-organ failure may develop in cases that result in death due to COVID-19. It is emphasized that the awareness of healthcare professionals about kidney functions should be increased in cases of COVID-19 pneumonia. Quick and effective steps can be taken in the treatment of COVID-19 pneumonia with the controlling approach of nurses to changes in kidney functions. Method: This study was carried out retrospectively to evaluate the kidney functions of patients diagnosed with COVID-19 pneumonia who were hospitalized in the pandemic hospital. Hospital and nurse observation files of 120 patients who were introduced to COVID-19 pneumonia between 1 May and 30 November 2020 were examined. Categorical data were described as continuous data as median with interquartile range (IQR) and percentages (%). Results: In total, 30 patients (25.0%) required mechanical ventilation, Overall, 39.1% (47) developed acute kidney injury during hospitalization, out of which 10.8% reached stage 1, 15.0% reached stage 2, and 13.3% reached stage 3. Dialytic support was required for seven (17.1% of all patients). COVID-19 pneumonia patients had higher levels of aspartate aminotransferase (AST) (55.02±58.04), alanine aminotransferase (ALT) (74.07±140.94), lactate dehydrogenase (LDH) (483.48±477.51), C-reactive protein (CRP) (88.02±72.17), D-dimer (1023±1548.01), procalcitonin (3.70± 6.52). In addition, a proportion of COVID-19 pneumonia patients but no non-COVID-19 pneumonia patients had abnormally increased AST (10.0-274.0), ALT (7.0-854.0), LDH (164-3547), CRP (5.10- 310.90), D-dimer (151-6212), procalcitonin (195-433). SpO2 of COVID-19 pneumonia patients had 78-97%, patients who need dialysis treatment due to pneumonia, follow-up coagulation profile (Procalcitonin, LDH, D-dimer), liver-renal function (ALT, AST, Creatine, Urea, Albumin), assessing signs of DVT and psychological support. 89 patients (74.2%) received corticosteroid, 73 patients (60.8%) received expectorant, 61 patients (50.8%) received vitamin C or B complex, 110 patients (91.7%) received anticoagulant and 73 patients (60.8%) received antibiotics. All of the COVID-19 pneumonia patients received the antiviral drug. Conclusion: As the disease progresses, differences in laboratory results and radiological findings may indicate that some complications have developed. COVID-19 pneumonia draws attention with liver function tests such as AST / ALT, LDH, infection markers in the blood, and the high rate of coagulation factors such as PCT and D-dimer during the hospital stay. The fact that these elevated values ​​may cause necrosis in the kidneys also brings about the truth. Careful monitoring of laboratory findings such as elevation of AST / ALT, LDH, PCT, and D-dimer in patients who develop pneumonia due to COVID-19 may provide early action for kidney damage.


F1000Research ◽  
2022 ◽  
Vol 11 ◽  
pp. 4
Author(s):  
Soichi Osozawa

Background: In Japan, more than 1,000 participants died shortly after receiving the coronavirus disease 2019 (COVID-19) vaccine, but the causal relation between the injection and death remains uncertain. Methods: Applying long-term personal vital care data for 28 months for an elderly patient, I investigated and evidenced adverse reactions after the first dose of the COVID-19 Pfizer vaccination. Results: The precise, detailed, and continuous data statistically clarified the long-term fevers associated with no meals or drinks. Interrupted time series analysis showed significant and fluctuating increases of body temperatures, pressures, and pulses, although solely long-term plots showed an abrupt and timely increase in these vital data after the vaccine. Conclusions: Anorexia was fatal, and newly reported in the present care records since the patient received the first dose of the COVID-19 vaccine.


2022 ◽  
pp. 10-15
Author(s):  
Tianrui Yang ◽  
Jessica Wooster

Introduction: Studies support incorporation of pharmacists and pharmacy students to improve health and financial outcomes during transition of care (TOC).  Standardisation of TOC educational training is currently lacking in pharmacy curricula.  Methods: This study employed a cross-sectional, descriptive study with a convenience sample at one college of pharmacy. Students participated in an anonymous Qualtrics survey including items on TOC service understanding and educational training. Results are reported as means and standard deviation for continuous data; frequencies and percentages for categorical data.  Results: Of 116 survey responses, 112 provided informed consent. Seventy-eight percent of respondents stated they have learned about TOC and 66% felt they understood what TOC entails. When asked to identify disease states commonly targeted for TOC, 77% responded incorrectly to this item. When asked to select TOC clinical activities, 66% incorrectly selected medication dispensing. Ninety-six percent of respondents replied that additional educational training on TOC would be beneficial.  Conclusion: There is a discrepancy in students’ perception of TOC services with their actual knowledge of TOC services based on survey responses.


2022 ◽  
Vol 16 ◽  
pp. 263235242110705
Author(s):  
Carol Chunfeng Wang ◽  
Ellen Yichun Han ◽  
Mark Jenkins ◽  
Xuepei Hong ◽  
Shuqin Pang ◽  
...  

Introduction: This study aimed to synthesise the best available evidence on the safety and efficacy of using moxibustion and/or acupuncture to manage cancer-related insomnia (CRI). Methods: The PRISMA framework guided the review. Nine databases were searched from its inception to July 2020, published in English or Chinese. Randomised clinical trials (RCTs) of moxibustion and or acupuncture for the treatment of CRI were selected for inclusion. Methodological quality was assessed using the method suggested by the Cochrane collaboration. The Cochrane Review Manager was used to conduct a meta-analysis. Results: Fourteen RCTs met the eligibility criteria. Twelve RCTs used the Pittsburgh Sleep Quality Index (PSQI) score as continuous data and a meta-analysis showed positive effects of moxibustion and or acupuncture ( n = 997, mean difference (MD) = −1.84, 95% confidence interval (CI) = −2.75 to −0.94, p < 0.01). Five RCTs using continuous data and a meta-analysis in these studies also showed significant difference between two groups ( n = 358, risk ratio (RR) = 0.45, 95% CI = 0.26–0.80, I2 = 39%). Conclusion: The meta-analyses demonstrated that moxibustion and or acupuncture showed a positive effect in managing CRI. Such modalities could be considered an add-on option in the current CRI management regimen.


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