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Currently, we are witnessing the emergence of big data in various fields including the biomedical and natural sciences. The size of chemoinformatics and bioinformatics databases is increasing every day. This gives us both challenges and opportunities. This chapter discusses the mathematical methods used in these fields both for the generation and analysis of such data. It is emphasized that proper use of robust statistical and machine learning methods in the analysis of the available big data may facilitate both hypothesis-driven and discovery-oriented research. © 2023 Elsevier Inc. All rights reserved.
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Background: Covid-19 is a viral disease that has been declared a pandemic by the World Health Organization.[ 1,2]. The most frequent complication has been reported to be sepsis[3]. Disseminated intravascular coagulation (DIC) has been observed in majority of mortalities.[4,5].While Disseminated Intravascular Coagulation is widely used to describe sepsis associated coagulopathy, ISTH has recently started using Sepsis Associated Coagulopathy in its definition. SIC is actually considered the early stage of DIC, and research has found that anticoagulant treatment is effective in patients meeting SIC criteria.[6,7]. Anticoagulant treatment has been shown to be beneficial in patients who do not exhibit clinical DIC, but meet SIC criteria. (Figure 1). Contemporary guidelines recommend anticoagulant treatment. Method(s): The patient groups, who were followed up with Covid-19 in Necmettin Erbakan University hospital, with and without anticoagulant treatment, will be analyzed retrospectively and comparative. Result(s): This study assessed the data of 2028 patients diagnosed with COVID-19 and subsequently given (Group1 (n=1008)) or not given (Group2 (n=1020)) anticoagulant treatment. The demographic characteristics displayed on the table exhibited similarities;D-dimer, SOFA and SIC scores demonstrated significant changes. (Table 1).Patients who developed DVT, arterial embolism and pulmonary embolism were included in the THROMBOSIS'' study. While group 1 had a thrombosis development rate of 5.15% (n=52), this rate was 19.21% (n=196) in group2.THROMBOSIS patients in group1 and 2 demonstrated a mortality rate of 38.46%(n=20) and 65.5% (n=128), respectively (p<0.001).THROMBOSIS patients in group1 and 2 were divided into subgroups according to SIC scores and their mortality rates were analyzed with respect to SICDIC scores;significant results were observed (SIC>5 was accepted as DIC).Patients who receive anticoagulant treatment subsequent to COVID-19 diagnosis have reduced disposition to thrombosis. According to SIC-DIC scores obtained through SOFA scores and clinical parameters, patients who reach DIC levels (SIC>5) have an increased rate of mortality. (Table 2).However, in group 2 patients who were diagnosed with COVID-19 and not given anticoagulant treatment due to no recommendation in prior guidelines, the mortality rate was high with every SIC score. Patients with a SIC score of 4 had a substantially high mortality rate;this is probably due to not receiving anticoagulants because DIC had not manifested.It was observed that compared to group 1, patients in group 2 who had not yet reached a DIC score, but had a SIC score of 4, had mortality rates reduced by 97% with anticoagulant treatment (p<0.001). According to SIC-DIC scores obtained through SOFA scores and clinical parameters, patients who reach DIC levels (SIC>5) have an increased rate of mortality (Tables 2 and 3). According to SIC-DIC scores obtained through SOFA scores and clinical parameters, patients who reach DIC Conclusion(s): Through our findings, we wanted to describe when COVID-19 patients who are hospitalized should receive anticoagulant treatment. Patients should be monitored with respect to their SIC scores, and clinicians should consider anticoagulant administration as it can potentially decrease mortality rate, regardless of DIC development.
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Purpose: This study aims to examine the impact of COVID-19-related job insecurity on two types of employees’ behaviors: family undermining and withdrawal. This study also proposes emotional exhaustion as a mediator and symmetrical internal communication as a moderator in the relationship between COVID-19-related job insecurity and employees’ behaviors. Design/methodology/approach: Using a time-lagged design, data were gathered from 193 employees working in Pakistan’s hospitality sector. Structural equation modeling in AMOS and PROCESS Macro were used to test the hypotheses. Findings: The results show that COVID-19-related job insecurity is positively related to family undermining and withdrawal behaviors, and these associations are mediated by emotional exhaustion. Furthermore, symmetrical internal communication weakens the positive influence of COVID-19-related job insecurity on emotional exhaustion. Additionally, the indirect impact of COVID-19-related job insecurity on employees’ behavioral outcomes via emotional exhaustion is stronger for employees with low symmetrical internal communication than for those with high levels of symmetrical internal communication. Practical implications: Hospitality management needs to focus on transparent and horizontal communication patterns to reduce the ensuing negative behaviors from COVID-19-related job insecurity. Originality/value: To the best of the authors’ knowledge, this is the first study to examine the impact of COVID-19-related job insecurity on two types of employees’ behaviors: family undermining and withdrawal. This study also offers new insights via mediating mechanisms and moderators associated with the relationship between COVID-19-related job insecurity and employees’ behavioral reactions. © 2022, Emerald Publishing Limited.
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This study concentrates on the analysis of a stochastic SIC epidemic system with an enhanced and general perturbation. Given the intricacy of some impulses caused by external disturbances, we integrate the quadratic Lévy noise into our model. We assort the long-run behavior of a perturbed SIC epidemic model presented in the form of a system of stochastic differential equations driven by second-order jumps. By ameliorating the hypotheses and using some new analytical techniques, we find the exact threshold value between extinction and ergodicity (persistence) of our system. The idea and analysis used in this paper generalize the work of N. T. Dieu et al. (2020), and offer an innovative approach to dealing with other random population models. Comparing our results with those of previous studies reveals that quadratic jump-diffusion has no impact on the threshold value, but it remarkably influences the dynamics of the infection and may worsen the pandemic situation. In order to illustrate this comparison and confirm our analysis, we perform numerical simulations with some real data of COVID-19 in Morocco. Furthermore, we arrive at the following results: (i) the time average of the different classes depends on the intensity of the noise (ii) the quadratic noise has a negative effect on disease duration (iii) the stationary density function of the population abruptly changes its shape at some values of the noise intensity. Mathematics Subject Classification 2020: 34A26; 34A12; 92D30; 37C10; 60H30; 60H10.
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Introduction: Early childhood caries is tooth decay seen in children under 72 months old. It is associated with multiple predisposing factors and has a negative impact on quality of life. In this study, our aim was to assess the oral health conditions and prevalence of early childhood caries (ECC) in children in the city of Erzurum, Turkey. Materials and Methods: This cross-sectional epidemiological study was conducted in Atatürk University, Faculty of Dentistry, Pediatric Dentistry Department/Erzurum-Turkey, in the 2015-2016 academic year. A total of 1,156 children (588 girls and 568 boys), with mean age of 4.9 ± 0.3 years (min 4, max 5) were included in the study. Restorative index (RI), deft, significant caries index (SiC), SiC10, treatment needs, number of lost primary teeth per 100 children, care index, and prevalence of carious primary teeth were evaluated. Data were analyzed by Chi-square test and Mann-Whitney U test (p < 0.05). Results: A total of 73.3% prevalence of ECC was observed in preschool children with a mean deft score of 3.9±4 and an increase in ECC with age. RI was 2.2%, SiC was 8.5, SiC10 was 12.3, caries treatment needs was 93.5%, care index was 2.1%, and number of lost primary teeth per 100 children was 0.9 tooth. Conclusion: High level of ECC indicates the necessity of starting an oral health education program for mothers and dental screening of children, and the demand for improving oral and dental services.
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Dental Caries , Child , Child, Preschool , Cross-Sectional Studies , Dental Caries/epidemiology , Dental Caries Susceptibility , Female , Humans , Male , Quality of Life , Turkey/epidemiologyABSTRACT
The paper presents the market overview of different compound semiconductor such as GaN, GaAs, and SiC impacted by the deployment of 5G in wireless infrastructure and in the new generation of handset applications. The Covid-19 impact and trade war issue are discussed, as well as technology and market trends and Yole’s forecast for the coming years. © 2021 CS MANTECH 2021 - 2021 International Conference on Compound Semiconductor Manufacturing Technology, Digest of Papers. All Rights Reserved.
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Despite the COVID-19 outbreak, the power Silicon Carbide (SiC) and GaN market continue their ascension. The high growth of the EV/HEV market impacted significantly the wide SiC industry, numerous carmakers continue qualifying SiC devices in main inverters, onboard chargers (OBC) and DC/DC converters. While GaN has found its killer application in consumer fast charging. This paper provides an overview of SiC and GaN device technology, including Yole Développement’s understanding of the market’s current dynamics and future evolution of wide band gap materials compared to mainstream Silicon power electronics market. © 2021 CS MANTECH 2021 - 2021 International Conference on Compound Semiconductor Manufacturing Technology, Digest of Papers. All Rights Reserved.
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Background: Severe acute respiratory syndrome from coronavirus-2 (SARS-CoV-2) has been associated with an increased risk of venous thromboembolism (VTE). Different anticoagulation protocols have been applied in several studies in the absence of clear evidence. A reliable deep venous thrombosis (DVT) indicator in critical patients with SARS-CoV-2 could guide the anticoagulation treatment; however, it has not yet been identified, and clinical applicability of the most common markers is debatable. The aim of our study was to determine the actual incidence of DVT in critically ill SARS-CoV-2 patients and to find a reliable tool to identify patients who might benefit from therapeutic-intensity anticoagulation. Methods: From March 1, 2020 to May 31, 2020, all patients admitted to the intensive care unit (ICU) for SARS-CoV-2 at Ospedale Regionale di Locarno, Locarno, Switzerland, were prospectively enrolled and screened daily with ultrasound for DVT. Following international consensus, a higher-intensity thromboprophylaxis was administered to all patients who were not at increased risk for bleeding. Sepsis-induced coagulopathy (SIC) and sequential organ failure assessment (SOFA) scores were calculated and time-to-DVT event in a COX proportional-hazard regression model was performed. A receiver operating characteristic (ROC) curve was used to determine sensitivity and specificity and the Youden's Index to establish the best threshold. Results: A total of 96 patients were enrolled. Deep venous thrombosis was detected in 37% of patients. Sepsis-induced coagulopathy and SOFA scores were both correlated to DVT. A SIC score of 1 vs. ≥2 showed a close association with DVT, with sensitivity, specificity, and positive and negative predictive values of 90.0, 48.1, and 49.1, and 89.7%, respectively. Most significantly though, a SOFA score of 1 or 2 points was shown to be the most accurate value in predicting the absence of DVT, indicating no need for therapeutic-intensity anticoagulation. Its sensitivity, specificity, and positive and negative predictive values were 87.9, 100, and 100, and 93.7%, respectively. The D-dimer test showed lower sensitivity and specificity whereas platelet count and aPTT were not found to be correlated to DVT. Conclusions: Patients with SOFA scores of 1 or 2 are at low risk of developing DVT and do not require therapeutic-intensity anticoagulation. Conversely, patients with scores ≥3 are at high risk of developing DVT.
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We report the rapid detection of SARS-CoV-2 in infected patients (mid-turbinate swabs and exhaled breath aerosol samples) in concentrations as low as 60 copies/mL of the virus in seconds by electrical transduction of the SARS-CoV-2 S1 spike protein antigen via SARS-CoV-2 S1 spike protein antibodies immobilized on bilayer quasi-freestanding epitaxial graphene without gate or signal amplification. The sensor demonstrates the spike protein antigen detection in a concentration as low as 1 ag/mL. The heterostructure of the SARS-CoV-2 antibody/graphene-based sensor is developed through a simple and low-cost fabrication technique. Furthermore, sensors integrated into a portable testing unit distinguished B.1.1.7 variant positive samples from infected patients (mid-turbinate swabs and saliva samples, 4000-8000 copies/mL) with a response time of as fast as 0.6 s. The sensor is reusable, allowing for reimmobilization of the crosslinker and antibodies on the biosensor after desorption of biomarkers by NaCl solution or heat treatment above 40 °C.
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Biosensing Techniques , COVID-19 , Graphite , Humans , SARS-CoV-2ABSTRACT
INTRODUCTION: Infection with SARS-CoV-2 in its most severe form leads to acute respiratory distress syndrome requiring mechanical ventilation under the conditions of the Intensive Care Unit (ICU). The state of hypercoagulation described in COVID-19 may deepen respiratory failure, leading to increased mortality. The aim of the presented study is to characterise the haemostatic profile based on the results of clotting system parameters and risk assessment of thromboembolic complications of patients hospitalised in the ICU. MATERIAL AND METHODS: This retrospective study covered the first 10 adult patients hospitalised in the ICU of the Hospital for Infectious Diseases in Warsaw in the second quarter of 2020. Demographic, clinical and laboratory parameters of the coagulation system and the risk of thromboembolic complications were assessed. Well known criteria of haemostatic disorders were used to classify the observed derangements. RESULTS: The most frequently observed deviations in the coagulation system were high concentrations of D-dimer and fibrinogen. In select cases the clotting time was prolonged. No severe thrombocytopenia was observed. All patients presented a high risk of thromboembolic complications as assesed by the Padua score. The observed clotting abnormalities did not meet the criteria for DIC (disseminated intravascular coagulation) and SIC (sepsis-induced coagulopathy) diagnosis. CONCLUSIONS: The main elements of coagulopathy that were observed in our cases differ from those usually seen in patients with recognised sepsis. The unique haemostatic profile of COVID-19 patients treated in the ICU has been described as CAC (COVID-19-associated coagulopathy).