Identifying outbreaks in sewer networks: An adaptive sampling scheme under network's uncertainty.

Motivated by the implementation of a SARS-Cov-2 sewer surveillance system in Chile during the COVID-19 pandemic, we propose a set of mathematical and algorithmic tools that aim to identify the location of an outbreak under uncertainty in the network structure. Given an upper bound on the number of samples we can take on any given day, our framework allows us to detect an unknown infected node by adaptively sampling different network nodes on different days. Crucially, despite the uncertainty of the network, the method allows univocal detection of the infected node, albeit at an extra cost in time. This framework relies on a specific and well-chosen strategy that defines new nodes to test sequentially, with a heuristic that balances the granularity of the information obtained from the samples. We extensively tested our model in real and synthetic networks, showing that the uncertainty of the underlying graph only incurs a limited increase in the number of iterations, indicating that the methodology is applicable in practice.

Structure and properties of Quercus robur acorn starch extracted by pulsed electric field technology.

Pulsed electric field (PEF) technology was used to extract starch from Q. robur flours using low-intensity electric fields (0 and 0.1 kV/cm) and study the impact of PEF on the structure and properties of acorn starch concerning commercial starch. PEF technology is an advantageous method for starch extraction than the aqueous steeping from an industrial perspective since reduces extraction time and allows for continuous processing of larger suspension volumes. PEF technology preserved the amylose and amylopectin contents, hydrogen bonds, and diffraction patterns, as well as the starch native properties. Hence, PEF could be used to obtain native starches, but future studies should verify its economic viability. Acorn starches have lower damaged starch content, gelatinization temperatures, enthalpies, improved pseudoplastic behavior, reduced in-vitro digestibility, and lower resistance to deformation compared to commercial corn starch. The higher solubility and swelling power of acorn starches up to 80 °C make them a suitable food additive in fermented yogurt and milk products and thus help to value acorn and acorn starches. Hence, acorns can be used to obtain native starches, a food ingredient with a wide range of food and non-food usage, using PEF.

Mixtures of t $$ t $$ factor analysers with censored responses and external covariates: An application to educational data from Peru.

Analysing data from educational tests allows governments to make decisions for improving the quality of life of individuals in a society. One of the key responsibilities of statisticians is to develop models that provide decision-makers with pertinent information about the latent process that educational tests seek to represent. Mixtures of t $$ t $$ factor analysers (MtFA) have emerged as a powerful device for model-based clustering and classification of high-dimensional data containing one or several groups of observations with fatter tails or anomalous outliers. This paper considers an extension of MtFA for robust clustering of censored data, referred to as the MtFAC model, by incorporating external covariates. The enhanced flexibility of including covariates in MtFAC enables cluster-specific multivariate regression analysis of dependent variables with censored responses arising from upper and/or lower detection limits of experimental equipment. An alternating expectation conditional maximization (AECM) algorithm is developed for maximum likelihood estimation of the proposed model. Two simulation experiments are conducted to examine the effectiveness of the techniques presented. Furthermore, the proposed methodology is applied to Peruvian data from the 2007 Early Grade Reading Assessment, and the results obtained from the analysis provide new insights regarding the reading skills of Peruvian students.

Heterogeneous photosensitization for water reuse in cellars: evaluation of silica, spongin, and chitosan as carrier material.

Photosensitization, a powerful oxidation reaction, offers significant potential for wastewater treatment in the context of industrial process water reuse. This environmentally friendly process can be crucial in reducing water consumption and industrial pollution. The ultimate goal is to complete process water reuse, creating a closed-loop system that preserves the inherent value of water resources. The photosensitized oxidation reaction hinges on three essential components: the photosensitizer, visible light, and oxygen. In this study, we assess the performance of three distinct materials-silica, chitosan, and spongin-as carrier materials for incorporating the phthalocyanine photosensitizer (ZnPcS4) in the heterogenous photosensitization process. Among the three materials under study, chitosan emerged as the standout performer in reactor hydrodynamic performance. In the photooxidation process, the photosensitizer ZnPcS4 exhibited notable efficacy, resulting in a significant reduction of approximately 20 to 30% in the remaining COD concentration of the cellar wastewater. Chitosan demonstrated exceptional hydrodynamic characteristics and displayed a favorable response to pH adjustments within the range of 8 to 10, outperforming the other two carrier materials. To further enhance the efficiency of continuous operation, exploring methods for mitigating photosensitizer bleaching within the reaction medium and investigating the impact of different pH values on the process optimization would be prudent.

A Bayesian approach for mixed effects state-space models under skewness and heavy tails.

Human immunodeficiency virus (HIV) dynamics have been the focus of epidemiological and biostatistical research during the past decades to understand the progression of acquired immunodeficiency syndrome (AIDS) in the population. Although there are several approaches for modeling HIV dynamics, one of the most popular is based on Gaussian mixed-effects models because of its simplicity from the implementation and interpretation viewpoints. However, in some situations, Gaussian mixed-effects models cannot (a) capture serial correlation existing in longitudinal data, (b) deal with missing observations properly, and (c) accommodate skewness and heavy tails frequently presented in patients' profiles. For those cases, mixed-effects state-space models (MESSM) become a powerful tool for modeling correlated observations, including HIV dynamics, because of their flexibility in modeling the unobserved states and the observations in a simple way. Consequently, our proposal considers an MESSM where the observations' error distribution is a skew-t. This new approach is more flexible and can accommodate data sets exhibiting skewness and heavy tails. Under the Bayesian paradigm, an efficient Markov chain Monte Carlo algorithm is implemented. To evaluate the properties of the proposed models, we carried out some exciting simulation studies, including missing data in the generated data sets. Finally, we illustrate our approach with an application in the AIDS Clinical Trial Group Study 315 (ACTG-315) clinical trial data set.

Modification of Acorn Starch Structure and Properties by High Hydrostatic Pressure.

Despite being rich in starch, over half of acorn production is undervalued. High hydrostatic pressure was used to modify the properties of Q. pyrenaica (0.1 and 460 MPa for 20 min) and Q. robur (0.1 and 333 MPa for 17.4 min) acorn starches to obtain high-valued ingredients. Pressure significantly altered the span distribution and heterogeneity of the acorn starch granules depending on the species, but their morphology was unaffected. Pressurization increased the amylose/amylopectin ratio and damaged starch contents, but the effect was more prominent in Q. pyrenaica than in Q. robur. However, the polymorphism, relative crystallinity, gelatinization temperatures, and enthalpies were preserved. The pressure effect on the starch properties depended on the property and species. The solubility, swelling power, and acorn gels' resistance towards deformation for both species decreased after pressurization. For Q. pyrenaica starch, the in vitro digestibility increased, but the pseudoplastic behavior decreased after pressurization. No differences were seen for Q. robur. Regarding the commercial starch, acorn starches had lower gelatinization temperatures and enthalpies, lower in vitro digestibility, lower resistance towards deformation, superior pseudoplastic behavior, and overall higher solubility and swelling power until 80 °C. This encourages the usage of acorn starches as a new food ingredient.

Effective moisture diffusivity prediction in two Portuguese fruit cultivars (Bravo de Esmolfe apple and Madeira banana) using drying kinetics data.

Air convective dehydration was performed at various temperatures (35 °C, 40 °C, 45 °C and 50 °C) using two types of fruits cultivars produced in different regions of Portugal: the Bravo de Esmolfe apple, from the Beiras province, and the Cavendish banana, from Madeira Island. The data collected were used to predict the effective moisture diffusion, which is a crucial input parameter in drying modeling and design. As expected, the values obtained in both falling drying rate periods detected for apples increased with an increase in drying temperature. The effective moisture diffusion in apples varied from 1.968 × 10-10 m2 s-1 at 35 °C to 4.013 × 10-10 m2 s-1 at 50 °C, for the first falling drying rate period, and from 0.9567 × 10-10 m2 s-1 at 35 °C to 3.328 × 10-10 m2 s-1 at 50 °C, for the second period. The dependence of effective moisture diffusion on temperature for bananas is similar, ranging from 1.572 × 10-10 to 2.627 × 10-10 m2 s-1 as the drying temperature changed from 35 to 50 °C.

Electrocoagulation treatment of furniture industry wastewater.

Electrocoagulation was investigated as a method for treating wastewater containing polyvinyl acetate (PVAc) from the furniture industry. The study evaluated the evolution of iron concentration and passivation during the treatment process. Laboratory-scale experiments were conducted to evaluate the effects of inter-electrode distance (d), current density, and mode on treatment performance. Three values of d (0.3, 0.6, and 0.9 cm) were studied and found to have no significant effect on performance. However, lower d values resulted in reduced energy consumption due to a decrease in applied voltage. Three values of current density (132, 158, and 197 A m-2) were studied under two current modes, Direct Current (DC) and Alternating Pulsed Current (APC). The best treatment performance for DC occurred under 158 A m-2 (the treated wastewater was characterized by pH = 4.59 ± 0.02, conductivity = 996 ± 21 µS cm-1, COD = 1940 ± 55 mgO2 L-1, TSS = 105 ± 14 mg L-1, and Fe = 50.39 ± 1.87 mgFe L-1). For APC, the best performance was achieved under 197 A m-2 (the treated wastewater was characterized by pH = 6.33 ± 0.06, conductivity = 988 ± 17 µS cm-1, COD = 1942 ± 312 mgO2 L-1, TSS = 199 ± 55 mg L-1, and Fe = 44.68 ± 4.60 mgFe L-1). Despite the promising results, treatment performance was insufficient to meet the legal requirements for water discharge. APC was found to be a more economically viable approach, as it reduced anode wear, electrode passivation, and energy consumption. The quantity of iron released increased with d, and the effect of current density on iron concentration was found to be non-linear. However, applying APC reduced the iron content for all tested current densities. The tests showed that EC was effective in removing chemical oxygen demand (COD) and total suspended solids (TSS), achieving removal efficiencies above 92% and 99%, respectively. However, the studied treatment procedures were insufficient to meet the EU legal requirements for water discharge. Therefore, the obtained wastewater should undergo a post-treatment process.

Unveiling the phytochemical nature of acorns: the relevance of dehusking.

Acorns are an abundant but despised fruit in Portugal. To explore this resource, the effect of different dehusking methods (thermal dehusking and dehusking by drying) on the phenolic contents and antioxidant activity of different acorn species from Peneda-Gerês National Park was studied. Regarding the free phenolics, the phenolic contents and antioxidant activity values of Q. pyrenaica decreased after thermal dehusking and dehusking by drying. Similar results were observed for the thermally dehusked Q. robur acorns, despite the increase in gallic acid. However, the phenolic contents and antioxidant activity values increased when Q. robur acorns were dehusked by drying, despite the decrease in ellagic acid and ORAC antioxidant values. The phenolic content of Q. ilex acorns increased after both dehusking methods due to the increase of ellagic acid, which led to the increase of the ABTS, DPPH, and FRAP antioxidant activity, but the ORAC antioxidant activity decreased. In the bound fraction, the phenolic, flavonoid, and gallic acid contents increased for all species when dehusked by both methods, thus increasing the antioxidant activity values. The thermal dehusking had a very dependent effect on ellagic acid content between species, while the dehusking by drying increased the ellagic acid contents for acorn species.

Drying kinetics of two fruits Portuguese cultivars (Bravo de Esmolfe apple and Madeira banana): An experimental study.

Air convective dehydration was carried out at a laboratory scale using two fruits of cultivars produced in different regions of Portugal: Bravo de Esmolfe apple, from Beiras province, and Cavendish banana, from Madeira Island. Fresh fruits were dried in a tray drier with a hot airstream at different temperatures (35, 40, 45, and 50 °C) and velocity of 1.6 m s-1. Drying rate curves were obtained using a simple mathematical approach applied to the moisture content curves adjusting linear and polynomial functions. Different drying rate stages were noticed in the experiments made with apples (one constant drying rate period followed by two falling drying rate periods), while in the case of the banana the constant drying rate period was not perceived, being dried entirely during a unique falling drying rate period. As expected, the constant drying rate value obtained at the beginning of the experiments with apples is higher when these were conducted at higher temperatures, changing from 8.103 to 14.474 g m-2 s-1 when the airstream temperature increases from 35 to 50 °C. The correspondent critical moisture contents in the Bravo de Esmolfe apples, at the instant the constant drying rate period stops and the drying rate starts to fall, slightly decreases from 4.800 to 4.134 kgwater/kgdry solid. This study explored for the first time the drying behavior of these two important fruits that have been increasingly used in the food industry in Portugal, giving important information for the industrialization of its production.

Extending multivariate Student's- t $$ t $$ semiparametric mixed models for longitudinal data with censored responses and heavy tails.

This article extends the semiparametric mixed model for longitudinal censored data with Gaussian errors by considering the Student's t $$ t $$ -distribution. This model allows us to consider a flexible, functional dependence of an outcome variable over the covariates using nonparametric regression. Moreover, the proposed model takes into account the correlation between observations by using random effects. Penalized likelihood equations are applied to derive the maximum likelihood estimates that appear to be robust against outlying observations with respect to the Mahalanobis distance. We estimate nonparametric functions using smoothing splines under an EM-type algorithm framework. Finally, the proposed approach's performance is evaluated through extensive simulation studies and an application to two datasets from acquired immunodeficiency syndrome clinical trials.

Bayesian analysis of survival data with missing censoring indicators.

In some large clinical studies, it may be impractical to perform the physical examination to every subject at his/her last monitoring time in order to diagnose the occurrence of the event of interest. This gives rise to survival data with missing censoring indicators where the probability of missing may depend on time of last monitoring and some covariates. We present a fully Bayesian semi-parametric method for such survival data to estimate regression parameters of the proportional hazards model of Cox. Theoretical investigation and simulation studies show that our method performs better than competing methods. We apply the proposed method to analyze the survival data with missing censoring indicators from the Orofacial Pain: Prospective Evaluation and Risk Assessment study.

Bayesian semiparametric modeling for HIV longitudinal data with censoring and skewness.

In biomedical studies, the analysis of longitudinal data based on Gaussian assumptions is common practice. Nevertheless, more often than not, the observed responses are naturally skewed, rendering the use of symmetric mixed effects models inadequate. In addition, it is also common in clinical assays that the patient's responses are subject to some upper and/or lower quantification limit, depending on the diagnostic assays used for their detection. Furthermore, responses may also often present a nonlinear relation with some covariates, such as time. To address the aforementioned three issues, we consider a Bayesian semiparametric longitudinal censored model based on a combination of splines, wavelets, and the skew-normal distribution. Specifically, we focus on the use of splines to approximate the general mean, wavelets for modeling the individual subject trajectories, and on the skew-normal distribution for modeling the random effects. The newly developed method is illustrated through simulated data and real data concerning AIDS/HIV viral loads.

Flexible longitudinal linear mixed models for multiple censored responses data.

In biomedical studies and clinical trials, repeated measures are often subject to some upper and/or lower limits of detection. Hence, the responses are either left or right censored. A complication arises when more than one series of responses is repeatedly collected on each subject at irregular intervals over a period of time and the data exhibit tails heavier than the normal distribution. The multivariate censored linear mixed effect (MLMEC) model is a frequently used tool for a joint analysis of more than one series of longitudinal data. In this context, we develop a robust generalization of the MLMEC based on the scale mixtures of normal distributions. To take into account the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is considered. For this complex longitudinal structure, we propose an exact estimation procedure to obtain the maximum-likelihood estimates of the fixed effects and variance components using a stochastic approximation of the EM algorithm. This approach allows us to estimate the parameters of interest easily and quickly as well as to obtain the standard errors of the fixed effects, the predictions of unobservable values of the responses, and the log-likelihood function as a byproduct. The proposed method is applied to analyze a set of AIDS data and is examined via a simulation study.

Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies.

Polyhydroxyalkanoates (PHAs) produced from mixed microbial cultures (MMC), regarded as potential substitutes of petrochemical plastics, can be found as intracellular granules in various microorganisms under limited nutrient conditions and excess of carbon source. PHA is traditionally quantified by laborious and time-consuming chromatography analysis, and a simpler and faster method to assess PHA contents from MMC, such as quantitative image analysis (QIA), is of great interest. The main purpose of the present work was to upgrade a previously developed QIA methodology (as reported by Mesquita et al. (Anal Chim Acta 770:36-44, 2013a, Anal Chim Acta 865:8-15, 2015)) for MMC intracellular PHA contents quantification, increase the studied intracellular PHA concentration range, and extend to different sequencing batch reactor (SBR) operation strategies. Therefore, the operation of a new aerobic dynamic feeding (ADF) SBR allowed further extending the studied operating conditions, dataset, and range of the MMC intracellular PHA contents from the previously reported anaerobic/aerobic cycle SBR. Nile Blue A (NBA) staining was employed for epifluorescence microscope visualization and image acquisition, further fed to a custom developed QIA. Data from each of the feast and famine cycles of both SBR were individually processed using chemometrics analysis, obtaining the correspondent partial least squares (PLS) models. The PHA concentrations determined from PLS models were further plotted against the results obtained in the standard chromatographic method. For both SBR, the predicted ability was higher at the end of the feast stage than for the famine stage. Indeed, an independent feast and famine QIA data treatment was found to be fundamental to obtain the best prediction abilities. Furthermore, a promising overall correlation (R 2 of 0.83) could be found combining the overall QIA data regarding the PHA prediction up to a concentration of 1785.1 mg L-1 (37.3 wt%). Thus, the results confirm that the presented QIA methodology can be seen as promising for estimating higher intracellular PHA concentrations for a larger reactors operation systems and further extending the prediction range of previous studies.

Censored linear regression models for irregularly observed longitudinal data using the multivariate- t distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

Influence assessment in censored mixed-effects models using the multivariate Student's-t distribution.

In biomedical studies on HIV RNA dynamics, viral loads generate repeated measures that are often subjected to upper and lower detection limits, and hence these responses are either left- or right-censored. Linear and non-linear mixed-effects censored (LMEC/NLMEC) models are routinely used to analyse these longitudinal data, with normality assumptions for the random effects and residual errors. However, the derived inference may not be robust when these underlying normality assumptions are questionable, especially the presence of outliers and thick-tails. Motivated by this, Matos et al. (2013b) recently proposed an exact EM-type algorithm for LMEC/NLMEC models using a multivariate Student's-t distribution, with closed-form expressions at the E-step. In this paper, we develop influence diagnostics for LMEC/NLMEC models using the multivariate Student's-t density, based on the conditional expectation of the complete data log-likelihood. This partially eliminates the complexity associated with the approach of Cook (1977, 1986) for censored mixed-effects models. The new methodology is illustrated via an application to a longitudinal HIV dataset. In addition, a simulation study explores the accuracy of the proposed measures in detecting possible influential observations for heavy-tailed censored data under different perturbation and censoring schemes.

Cyclic voltammetry: a tool to quantify 2,4,6-trichloroanisole in aqueous samples from cork planks boiling industrial process.

Chloroanisoles, namely 2,4,6-trichloroanisole, are pointed out as the primary responsible of the development of musty off-flavours in bottled wine, due to their migration from cork stoppers, which results in huge economical losses for wine industry. A prevention step is the detection of these compounds in cork planks before stoppers are produced. Mass spectrometry gas chromatography is the reference method used although it is far beyond economical possibilities of the majority of cork stoppers producers. In this work, a portable cyclic voltammetry approach was used to detect 2,4,6-trichloroanisole extracted from natural cork planks to the aqueous phase during the cork boiling industrial treatment process. Analyses were carried out under ambient conditions, in less than 15 min with a low use of solvent and without any sample pre-treatment. The proposed technique had detection (0.31±0.01 ng/L) and quantification (0.95±0.05 ng/L) limits lower than the human threshold detection level. For blank solutions, without 2,4,6-trichloroanisole addition, a concentration in the order of the quantification limit was estimated (1.0±0.2 ng/L), which confirms the satisfactory performance of the proposed methodology. For aqueous samples from the industrial cork planks boiling procedure, intra-day repeatabilities were lower than 3%, respectively. Also, 2,4,6-trichloroanisole contents in the aqueous samples determined by this novel approach were in good agreement with those obtained by GC-MS (correlation coefficient equal to 0.98), confirming the satisfactory accuracy of the proposed methodology. So, since this novel approach is a fast, low-cost, portable and user-friendly method, it can be an alternative and helpful tool for in-situ industrial applications, allowing accurate detection of releasable 2,4,6-trichloroanisole in an earlier phase of cork stoppers production, which may allow implementing more effective cork treatments to reduce or avoid future 2,4,6-trichloroanisole contaminations of wine.

Identification of the 1PL model with guessing parameter: parametric and semi-parametric results.

In this paper, we study the identification of a particular case of the 3PL model, namely when the discrimination parameters are all constant and equal to 1. We term this model, 1PL-G model. The identification analysis is performed under three different specifications. The first specification considers the abilities as unknown parameters. It is proved that the item parameters and the abilities are identified if a difficulty parameter and a guessing parameter are fixed at zero. The second specification assumes that the abilities are mutually independent and identically distributed according to a distribution known up to the scale parameter. It is shown that the item parameters and the scale parameter are identified if a guessing parameter is fixed at zero. The third specification corresponds to a semi-parametric 1PL-G model, where the distribution G generating the abilities is a parameter of interest. It is not only shown that, after fixing a difficulty parameter and a guessing parameter at zero, the item parameters are identified, but also that under those restrictions the distribution G is not identified. It is finally shown that, after introducing two identification restrictions, either on the distribution G or on the item parameters, the distribution G and the item parameters are identified provided an infinite quantity of items is available.

Skew-normal/independent linear mixed models for censored responses with applications to HIV viral loads.

Often in biomedical studies, the routine use of linear mixed-effects models (based on Gaussian assumptions) can be questionable when the longitudinal responses are skewed in nature. Skew-normal/elliptical models are widely used in those situations. Often, those skewed responses might also be subjected to some upper and lower quantification limits (QLs; viz., longitudinal viral-load measures in HIV studies), beyond which they are not measurable. In this paper, we develop a Bayesian analysis of censored linear mixed models replacing the Gaussian assumptions with skew-normal/independent (SNI) distributions. The SNI is an attractive class of asymmetric heavy-tailed distributions that includes the skew-normal, skew-t, skew-slash, and skew-contaminated normal distributions as special cases. The proposed model provides flexibility in capturing the effects of skewness and heavy tail for responses that are either left- or right-censored. For our analysis, we adopt a Bayesian framework and develop a Markov chain Monte Carlo algorithm to carry out the posterior analyses. The marginal likelihood is tractable, and utilized to compute not only some Bayesian model selection measures but also case-deletion influence diagnostics based on the Kullback-Leibler divergence. The newly developed procedures are illustrated with a simulation study as well as an HIV case study involving analysis of longitudinal viral loads.