Philippine natural bentonite is characterized using X-ray diffractometer (XRD), scanning electron microscope (SEM), chemical analysis, thermogravimetric-differential scanning calorimetry (TG-DSC), and Fourier transform infrared (FTIR) analysis. The cation exchange capacity (CEC) was also measured. XRD shows that the mineral is composed primarily of mordenite, hectorite, and montmorillonite. SEM shows the flaky and porous structure of the bentonite powder. Chemical analyses show that SiO2 (47.90 wt%) and Al2O3 (14.02 wt%) are the major components of the clay. TG-DSC shows that the mineral contains 15.55% moisture. IR transmittance spectrum shows the common vibration bands present in the sample which include O–H stretching of inter-porous water, symmetric and asymmetric stretching of hydroxyl functional groups, asymmetrical stretching of internal tetrahedra (O–Si–O and O–Al–O), symmetrical stretching of external linkages, and so on. The measured CEC were found to be 91.37 and 43.01 meq/100 g according to the ammonium acetate method and barium acetate method, respectively.

This article proposes a complex economic scenario generator that nests versions of well-known actuarial frameworks. The generator estimation relies on the Bayesian paradigm and accounts for both model and parameter uncertainty via Markov chain Monte Carlo methods. So, to the question is less more?, we answer maybe, but it depends on your criteria. From an in-sample fit perspective, on the one hand, a complex economic scenario generator seems better. From the conservatism, forecasting and coverage perspectives, on the other hand, the situation is less clear: having more complex models for the short rate, term structure and stock index returns is clearly beneficial. However, that is not the case for inflation and the dividend yield.

It is well known that the height profile of a critical conditioned Galton–Watson tree with finite offspring variance converges, after a suitable normalisation, to the local time of a standard Brownian excursion. In this work, we study the distance profile, defined as the profile of all distances between pairs of vertices. We show that after a proper rescaling the distance profile converges to a continuous random function that can be described as the density of distances between random points in the Brownian continuum random tree. We show that this limiting function a.s. is Hölder continuous of any order $\alpha<1$, and that it is a.e. differentiable. We note that it cannot be differentiable at 0, but leave as open questions whether it is Lipschitz, and whether it is continuously differentiable on the half-line $(0,\infty)$. The distance profile is naturally defined also for unrooted trees contrary to the height profile that is designed for rooted trees. This is used in our proof, and we prove the corresponding convergence result for the distance profile of random unrooted simply generated trees. As a minor purpose of the present work, we also formalize the notion of unrooted simply generated trees and include some simple results relating them to rooted simply generated trees, which might be of independent interest.

The double-mean-reverting model, introduced by Gatheral [(2008). Consistent modeling of SPX and VIX options. In The Fifth World Congress of the Bachelier Finance Society London, July 18], is known to be a successful three-factor model that can be calibrated to both CBOE Volatility Index (VIX) and S&P 500 Index (SPX) options. However, the calibration of this model may be slow because there is no closed-form solution formula for European options. In this paper, we use a rescaled version of the model developed by Huh et al. [(2018). A scaled version of the double-mean-reverting model for VIX derivatives. Mathematics and Financial Economics 12: 495–515] and obtain explicitly a closed-form pricing formula for European option prices. Our formulas for the first and second-order approximations do not require any complicated calculation of integral. We demonstrate that a faster calibration result of the double-mean revering model is available and yet the practical implied volatility surface of SPX options can be produced. In particular, not only the usual convex behavior of the implied volatility surface but also the unusual concave down behavior as shown in the COVID-19 market can be captured by our formula.

In this paper, we develop a novel game theoretic model of the interactions between an EDoS attacker and the defender based on a signaling game that is a dynamic game of incomplete information. We then derive the best defense strategies for the network defender to respond to the EDoS attacks. That is, we compute the perfect Bayesian Nash Equilibrium (PBE) of the proposed game model such as the pooling PBE, separating PBE and mixed strategy PBE. In the pooling equilibrium, each type of the attacker takes the same action and the attacker's type is not revealed to the defender, whereas in the separating equilibrium, each type of the attacker uses different actions and hence the attacker's type is completely revealed to the defender. On the other hand, in the mixed strategy PBE, both the attacker and the defender randomize their strategies to optimize their payoffs. Numerical illustration is also presented to show the efficacy of the proposed model.

Between December 2020 and March 2021, we measured anti-SARS-CoV-2 IgG titres among 725 Israeli hospital workers vaccinated against COVID-19. Infection post-dose 1 vaccination did not increase IgG titres, and individuals infected post-dose 1 had IgG levels comparable to never-infected individuals who received a single dose, lower than fully vaccinated, never-infected individuals. This suggests dose 2, currently not offered to those infected post-dose 1, may be required in these individuals. Larger studies should confirm whether individuals infected post-dose 1 need the second.

This study analysed the reported incidence of COVID-19 and associated epidemiological and socio-economic factors in the WHO African region. Data from COVID-19 confirmed cases and SARS-CoV-2 tests reported to the WHO by Member States between 25 February and 31 December 2020 and publicly available health and socio-economic data were analysed using univariate and multivariate binomial regression models. The overall cumulative incidence was 1846 cases per million population. Cape Verde (21 350 per million), South Africa (18 060 per million), Namibia (9840 per million), Eswatini (8151 per million) and Botswana (6044 per million) recorded the highest cumulative incidence, while Benin (260 per million), Democratic Republic of Congo (203 per million), Niger (141 cases per million), Chad (133 per million) and Burundi (62 per million) recorded the lowest. Increasing percentage of urban population (β = −0.011, P = 0.04) was associated with low cumulative incidence, while increasing number of cumulative SARS-CoV-2 tests performed per 10 000 population (β = 0.0006, P = 0.006) and the proportion of population aged 15–64 years (adjusted β = 0.174, P < 0.0001) were associated with high COVID-19 cumulative incidence. With limited testing capacities and overwhelmed health systems, these findings highlight the need for countries to increase and decentralise testing capacities and adjust testing strategies to target most at-risk populations.

Via generalized interval arithmetic, we propose a Generalized Interval Arithmetic Center and Range (GIA-CR) model for random intervals, where parameters in the model satisfy linear inequality constraints. We construct a constrained estimator of the parameter vector and develop asymptotically uniformly valid tests for linear equality constraints on the parameters in the model. We conduct a simulation study to examine the finite sample performance of our estimator and tests. Furthermore, we propose a coefficient of determination for the GIA-CR model. As a separate contribution, we establish the asymptotic distribution of the constrained estimator in Blanco-Fernández (2015, Multiple Set Arithmetic-Based Linear Regression Models for Interval-Valued Variables) in which the parameters satisfy an increasing number of random inequality constraints.

We propose a novel conditional quantile prediction method based on complete subset averaging (CSA) for quantile regressions. All models under consideration are potentially misspecified, and the dimension of regressors goes to infinity as the sample size increases. Since we average over the complete subsets, the number of models is much larger than the usual model averaging method which adopts sophisticated weighting schemes. We propose to use an equal weight but select the proper size of the complete subset based on the leave-one-out cross-validation method. Building upon the theory of Lu and Su (2015, Journal of Econometrics 188, 40–58), we investigate the large sample properties of CSA and show the asymptotic optimality in the sense of Li (1987, Annals of Statistics 15, 958–975) We check the finite sample performance via Monte Carlo simulations and empirical applications.

Radars used to observe meteor trails in the mesosphere deliver information on winds and temperature. Use of these radars is becoming a standard method for determining mesospheric dynamics and temperatures worldwide due to relatively low costs and ease of deployment. However, recent studies have revealed that temperatures may be overestimated in conditions such as high geomagnetic activity. The effect is thought to be most prevalent at high latitude, although this is not yet proven. Here, we demonstrate how temperatures might be corrected for geomagnetic effects; the demonstration is for a particular geographic location (Svalbard, 78°N, 16°E) because it is local geomagnetic disturbances that affects local temperature measurements, therefore requiring co-located instruments. We see that summer temperatures require a correction (reduction) of a few Kelvin, but winter estimates are more accurate.

UK universities re-opened in September 2020, amidst the coronavirus epidemic. During the first term, various national social distancing measures were introduced, including banning groups of >6 people and the second lockdown in November; however, outbreaks among university students occurred. We aimed to measure the University of Bristol staff and student contact patterns via an online, longitudinal survey capturing self-reported contacts on the previous day. We investigated the change in contacts associated with COVID-19 guidance periods: post-first lockdown (23/06/2020–03/07/2020), relaxed guidance period (04/07/2020–13/09/2020), ‘rule-of-six’ period (14/09/2020–04/11/2020) and the second lockdown (05/11/2020–25/11/2020). In total, 722 staff (4199 responses) and 738 students (1906 responses) were included in the study. For staff, daily contacts were higher in the relaxed guidance and ‘rule-of-six’ periods than the post-first lockdown and second lockdown. Mean student contacts dropped between the ‘rule-of-six’ and second lockdown periods. For both staff and students, the proportion meeting with groups larger than six dropped between the ‘rule-of-six’ period and the second lockdown period, although was higher for students than for staff. Our results suggest university staff and students responded to national guidance by altering their social contacts. Most contacts during the second lockdown were household contacts. The response in staff and students was similar, suggesting that students can adhere to social distancing guidance while at university. The number of contacts recorded for both staff and students were much lower than those recorded by previous surveys in the UK conducted before the COVID-19 pandemic.

Although the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is lasting for more than 1 year, the exposition risks of health-care providers are still unclear. Available evidence is conflicting. We investigated the prevalence of antibodies against SARS-CoV-2 in the staff of a large public hospital with multiple sites in the Antwerp region of Belgium. Risk factors for infection were identified by means of a questionnaire and human resource data. We performed hospital-wide serology tests in the weeks following the first epidemic wave (16 March to the end of May 2020) and combined the results with the answers from an individual questionnaire. Overall seroprevalence was 7.6%. We found higher seroprevalences in nurses [10.0%; 95% confidence interval (CI) 8.9–11.2] than in physicians 6.4% (95% CI 4.6–8.7), paramedical 6.0% (95% CI 4.3–8.0) and administrative staff (2.9%; 95% CI 1.8–4.5). Staff who indicated contact with a confirmed coronavirus disease 2019 (COVID-19) colleague had a higher seroprevalence (12.0%; 95% CI 10.7–13.4) than staff who did not (4.2%; 95% CI 3.5–5.0). The same findings were present for contacts in the private setting. Working in general COVID-19 wards, but not in emergency departments or intensive care units, was also a significant risk factor. Since our analysis points in the direction of active SARS-CoV-2 transmission within hospitals, we argue for implementing a stringent hospital-wide testing and contact-tracing policy with special attention to the health care workers employed in general COVID-19 departments. Additional studies are needed to establish the transmission dynamics.

Adenovirus pneumonia can occur in immunocompetent youths and adults. We conducted a retrospective analysis on five immunocompetent patients (aged ⩾14 years) with adenovirus pneumonia who visited our fever clinic between 1 February 2020 and 29 February 2020. The symptoms at clinical onset were fever, with cough and phlegm production either absent or appearing several days after disease onset. One patient with severe disease exhibited dyspnoea and a rapid development of respiratory failure. A subset of patients had concurrent gastrointestinal symptoms. The results of blood tests revealed normal leukocyte counts, decreased lymphocyte counts and increased C-reactive protein levels. The imaging findings resembled those of bacterial pneumonia, and pleural effusions were present in some cases. Most patients had a good prognosis with symptomatic treatment and supportive care. However, one patient with severe disease and a MuLBSTA score of >12 had a poor prognosis and ultimately died. Immunocompetent youths and adults may develop adenovirus pneumonia, and severe cases are at the risk of death. Since no effective treatments for adenovirus pneumonia are currently known, the early diagnosis and provision of symptomatic treatment and supportive care should be adopted to prevent the development and progression of severe disease.

To investigate temporal trends in coronavirus disease 2019 (COVID-19)-related outcomes and to evaluate whether the impacts of potential risk factors and disparities changed over time, we conducted a retrospective cohort study with 249 075 patients tested or treated for COVID-19 at Michigan Medicine (MM), from 10 March 2020 to 3 May 2021. Among these patients, 26 289 were diagnosed with COVID-19. According to the calendar time in which they first tested positive, the COVID-19-positive cohort were stratified into three-time segments (T1: March–June, 2020; T2: July–December, 2020; T3: January–May, 2021). Potential risk factors that we examined included demographics, residential-level socioeconomic characteristics and preexisting comorbidities. The main outcomes included COVID-19-related hospitalisation and intensive care unit (ICU) admission. The hospitalisation rate for COVID-positive patients decreased from 36.2% in T1 to 14.2% in T3, and the ICU admission rate decreased from 16.9% to 2.9% from T1 to T3. These findings confirm that COVID-19-related hospitalisation and ICU admission rates were decreasing throughout the pandemic from March 2020 to May 2021. Black patients had significantly higher (compared to White patients) hospitalisation rates (19.6% vs. 11.0%) and ICU admission rates (6.3% vs. 2.8%) in the full COVID-19-positive cohort. A time-stratified analysis showed that racial disparities in hospitalisation rates persisted over time and the estimates of the odds ratios (ORs) stayed above unity in both unadjusted [full cohort: OR = 1.98, 95% confidence interval (CI) (1.79, 2.19); T1: OR = 1.70, 95% CI (1.36, 2.12); T2: OR = 1.40, 95% CI (1.17, 1.68); T3: OR = 1.55, 95% CI (1.29, 1.86)] and adjusted analysis, accounting for differences in demographics, socioeconomic status, and preexisting comorbid conditions (full cohort: OR = 1.45, 95% CI (1.25, 1.68); T1: OR = 1.26, 95% CI (0.90, 1.76); T2: OR = 1.29, 95% CI (1.01, 1.64); T3: OR = 1.29, 95% CI (1.00, 1.67)).

Several studies have demonstrated that higher levels of vitamin D are associated with better prognosis and outcomes in infectious diseases. We aimed to compare the vitamin D levels of paediatric patients with mild/moderate coronavirus disease 2019 (COVID-19) disease and a healthy control group. We retrospectively reviewed the medical records of patients who were hospitalised at our university hospital with the diagnosis of COVID-19 during the period between 25 May 2020 and 24 December 2020. The mean age of the COVID-19 patients was 10.7 ± 5.5 years (range 1–18 years); 43 (57.3%) COVID-19 patients were male. The mean serum vitamin D level was significantly lower in the COVID-19 group than the control group (21.5 ± 10.0 vs. 28.0 ± 11.0 IU, P < 0.001). The proportion of patients with vitamin D deficiency was significantly higher in the COVID-19 group than the control group (44% vs. 17.5%, P < 0.001). Patients with low vitamin D levels were older than the patients with normal vitamin D levels (11.6 ± 4.9 vs. 6.2 ± 1.8 years, P = 0.016). There was a significant male preponderance in the normal vitamin D group compared with the low vitamin D group (91.7% vs. 50.8%, P = 0.03). C-reactive protein level was higher in the low vitamin D group, although the difference did not reach statistical significance (9.6 ± 2.2 vs. 4.5 ± 1.6 mg/l, P = 0.074). Our study provides an insight into the relationship between vitamin D deficiency and COVID-19 for future studies. Empiric intervention with vitamin D can be justified by low serum vitamin D levels.

Indian Ocean islands are endemic areas for human and animal leptospirosis. Maintenance host species for Leptospira spp. have still not been completely elucidated, and recently the role of cats (Felis catus) has been questioned. This cross-sectional study aims to determine whether cats are part of the maintenance community of different strains of Leptospira spp. in Reunion Island. The prevalence of Leptospira infection in an opportunistic sample of stray and domestic cats (n = 92) from Reunion Island has been studied using serological (microagglutination test) and molecular detection (polymerase chain reaction (PCR)). The results revealed a seroprevalence of 37.0% (34/92) (cut-off 1:40) without a significant difference in the living conditions of animals. The predominant serogroup was Icterohaemorrhagiae, but Ballum, Cynopteri and Australis were also detected. Using PCR, 28.6% (12/42) of stray cats were tested positive. Leptospiral DNA was detected in renal tissue, urine and blood of respectively 14.3% (6/42), 10.3% (4/39) and 11.9% (5/42) of stray cats, but 0% (0/3), 0% (0/50) and 0% (0/36) of domestic cats (P = non-applicable, P = 0,038, P = 0,058 respectively). Partial rrs gene (16S rRNA) sequencing identified Leptospira interrogans in all PCR-positive samples. Our study confirms that renal carriage and urinary shedding are possible, positioning cats, and especially stray cats as potential actors within the maintenance community of L. interrogans in Reunion Island.

Allogenic hematopoietic stem cell transplant (HSCT) recipients are susceptible to any kind of infectious agents including Clostridium difficile. We studied 86 allogenic-HSCT patients who faced diarrhoea while receiving antibiotics. DNA from stool samples were explored for the presence of C. difficile toxin genes (tcdA; tcdB) by multiplex real-time PCR. Results showed nine toxigenic C. difficile amongst which seven were positive for both toxins and two were positive for tcdB. Six of toxigenic C. difficile organisms harbouring both toxin genes were also isolated by toxigenic culture. Clostridium difficile infection was controlled successfully with oral Metronidazole and Vancomycin in the confirmed infected patients.

In October 2019, public health surveillance systems in Scotland identified an increase in the number of reported infections of Shiga toxin-producing Escherichia coli (STEC) O26:H11 involving bloody diarrhoea. Ultimately, across the United Kingdom (UK) 32 cases of STEC O26:H11 stx1a were identified, with the median age of 27 years and 64% were male; six cases were hospitalised. Among food exposures there was an association with consuming pre-packed sandwiches purchased at outlets belonging to a national food chain franchise (food outlet A) [odds ratio (OR) = 183.89, P < 0.001]. The common ingredient identified as a component of the majority of the sandwiches sold at food outlet A was a mixed salad of Apollo and Iceberg lettuce and spinach leaves. Microbiological testing of food and environmental samples were negative for STEC O26:H11, although STEC O36:H19 was isolated from a mixed salad sample taken from premises owned by food outlet A. Contamination of fresh produce is often due to a transient event and detection of the aetiological agent in food that has a short-shelf life is challenging. Robust, statistically significant epidemiological analysis should be sufficient evidence to direct timely and targeted on-farm investigations. A shift in focus from testing the microbiological quality of the produce to investigating the processes and practices through the supply chain and sampling the farm environment is recommended.