A linear programming based heuristic framework for min-max regret combinatorial optimization problems with interval costs

This work deals with a class of problems under interval data uncertainty, namely interval robust-hard problems, composed of interval data min-max regret generalizations of classical NP-hard combinatorial problems modeled as 0-1 integer linear programming problems. These problems are more challenging than other interval data min-max regret problems, as solely computing the cost of any feasible solution requires solving an instance of an NP-hard problem. The state-of-the-art exact algorithms in the literature are based on the generation of a possibly exponential number of cuts. As each cut separation involves the resolution of an NP-hard classical optimization problem, the size of the instances that can be solved efficiently is relatively small. To smooth this issue, we present a modeling technique for interval robust-hard problems in the context of a heuristic framework. The heuristic obtains feasible solutions by exploring dual information of a linearly relaxed model associated with the classical optimization problem counterpart. Computational experiments for interval data min-max regret versions of the restricted shortest path problem and the set covering problem show that our heuristic is able to find optimal or near-optimal solutions and also improves the primal bounds obtained by a state-of-the-art exact algorithm and a 2-approximation procedure for interval data min-max regret problems

Multi year aerosol characterization in the tropical Andes and in adjacent Amazonia using AERONET measurements

This work focuses on the analysis of columnar aerosol properties in the complex geophysical tropical region of South America within 10-20 South and 50-70 West. The region is quite varied and encompasses a significant part of Amazonia (lowlands) as well as high mountains in the Andes (highlands,~4000 m a.s.l.). Several AERONET stations were included to study the aerosol optical characteristics of the lowlands (Rio Branco, Ji Parana and Cuiaba in Brazil and Santa Cruz in Bolivia) and the highlands (La Paz, Bolivia) during the 2000-2014 period. Biomass-burning is by far the most important source of aerosol in the lowlands, particularly during the dry season (August-October). Multi-annual variability was investigated and showed very strong burning activity in 2005, 2006, 2007 and 2010. This resulted in smoke characterized by correspondingly strong, above-average AODs (aerosol optical depths) and homogeneous single scattering albedo (SSA) across all the stations (~0.93). For other years, however, SSA differences arise between the northern stations (Rio Branco and Ji Parana) with SSAs of ~0.95 and the southern stations (Cuiaba and Santa Cruz) with lower SSAs of ~0.85.Such differences are explained by the different types of vegetation burned in the two different regions. In the highlands, however, the transport of biomass burning smoke is found to be sporadic in nature. This sporadicity results in highly variable indicators of aerosol load and type (Angstrom exponent and fine mode fraction) with moderately significant increases in both. Regional dust and local pollution are the background aerosol in this highland region, whose elevation places it close to the free troposphere. Transported smoke particles were generally found to be more optical absorbing than in the lowlands: the hypothesis to explain this is the significantly higher amount of water vapor in Amazonia relative to the high mountain areas. The air-mass transport to La Paz was investigated using the HYSPLIT air-concentration five-days back trajectories. Two different patterns were clearly differentiated: westerly winds from the Pacific that clean the atmosphere and easterly winds favoring the transport of particles from Amazonia.Marie Skłodowska-Curie Individual Fellowships (IF) ACE_GFAT (grant agreement No 659398).European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 654109, ACTRIS-2

Acetylcholinesterase Choline-Based Ionic Liquid Inhibitors: In Vitro and in Silico Molecular Docking Studies

COMPETE Programme: SAICTPAC/0019/2015 IF/00780/2015 Project no. 022161Monocationic and dicationic cholinium ionic liquids (ILs) were synthesized and evaluated as acetylcholinesterase (AChE) inhibitors with in vitro and in silico models, and their cytotoxicity was assessed using human cell lines from skin (CRL-1502) and colon cancer (CaCo-2). The ILs with a longer alkyl chain were stronger AChE inhibitors, the dicationic ILs (DILs) being more active than the monocationic ILs. The best result was obtained for [N1,1,12,2(OH)]2Br2 at a concentration of 0.18 μM by reducing half enzyme activity without affecting the viability of tested cell lines. A saturation-transfer difference NMR (STD-NMR) binding study was carried out, demonstrating that [N1,1,12,2(OH)]2Br2 binds to AChE. STD-NMR competition binding experiments, using galanthamine as a reference ligand, clearly highlight that the IL displaces galanthamine in the AChE binding site pinpointing [N1,1,12,2(OH)]2Br2 inside the deep gorge of AChE. In order to obtain a three-dimensional (3D) view of the molecular recognition process, in silico molecular docking studies on the active site of AChE were carried out. The proposed 3D model of the AChE/DIL complex is in agreement with the STD-derived epitope mapping, which explains the competition with galanthamine and unveils key interactions in both peripheral and catalytic sites of AChE. These interactions seem essential to govern the recognition of DILs by the AChE enzyme. Our study provides a structural and functional platform that can be used for the rational design of choline-based ILs as potent AChE inhibitors.publishersversionpublishe

Influence of migration on the thought process of individuals at ultra-high risk for psychosis

OBJECTIVE To assess the influence of migration on the psychopathological presentation of individuals at ultra-high risk for psychosis (UHR) in São Paulo, Brazil. METHODS This study is part of the Subclinical Symptoms and Prodromal Psychosis (SSAPP) project, a cohort study in São Paulo, Brazil, designed to follow individuals at UHR. After screening with the Prodromal Questionnaire (PQ) and a clinical interview, the Global Assessment of Functioning (GAF) was administered, a neuropsychological assessment was performed, sociodemographic and migration data were obtained. We then analyzed UHR individuals who had migration data to see if migration had any effect on their cognition and psychopathology. Chi-square tests were used for categorical variables, and Student's t test or analysis of variance (ANOVA) were used for nonparametric and parametric distributions, respectively. RESULTS The sample was composed of 42 at-risk subjects, of whom 5 had a migration history in the past two generations. Those with migration history showed significantly more formal thought disturbances (p = 0.012) and sleeping problems (p = 0.033) compared to those without. CONCLUSIONS Our data reinforce migration as a risk factor for psychosis in developing countries as well, and highlights the importance of studying the specific effect of this factor in UHR psychopathology

Towards a precise test for malaria diagnosis in the Brazilian Amazon: comparison among field microscopy, a rapid diagnostic test, nested PCR, and a computational expert system based on artificial neural networks

<p>Abstract</p> <p>Background</p> <p>Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria.</p> <p>Methods</p> <p>The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared.</p> <p>Results</p> <p>Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the <it>Plasmodium </it>species in 12 cases of mixed infections (<it>Plasmodium vivax </it>+ <it>Plasmodium falciparum</it>). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses).</p> <p>Conclusions</p> <p>An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.</p

Social Networks Shape the Transmission Dynamics of Hepatitis C Virus

Hepatitis C virus (HCV) infects 170 million people worldwide, and is a major public health problem in Brazil, where over 1% of the population may be infected and where multiple viral genotypes co-circulate. Chronically infected individuals are both the source of transmission to others and are at risk for HCV-related diseases, such as liver cancer and cirrhosis. Before the adoption of anti-HCV control measures in blood banks, this virus was mainly transmitted via blood transfusion. Today, needle sharing among injecting drug users is the most common form of HCV transmission. Of particular importance is that HCV prevalence is growing in non-risk groups. Since there is no vaccine against HCV, it is important to determine the factors that control viral transmission in order to develop more efficient control measures. However, despite the health costs associated with HCV, the factors that determine the spread of virus at the epidemiological scale are often poorly understood. Here, we sequenced partial NS5b gene sequences sampled from blood samples collected from 591 patients in São Paulo state, Brazil. We show that different viral genotypes entered São Paulo at different times, grew at different rates, and are associated with different age groups and risk behaviors. In particular, subtype 1b is older and grew more slowly than subtypes 1a and 3a, and is associated with multiple age classes. In contrast, subtypes 1a and 3b are associated with younger people infected more recently, possibly with higher rates of sexual transmission. The transmission dynamics of HCV in São Paulo therefore vary by subtype and are determined by a combination of age, risk exposure and underlying social network. We conclude that social factors may play a key role in determining the rate and pattern of HCV spread, and should influence future intervention policies

Prevention and management of intra-operative pain during caesarean section under neuraxial anaesthesia: a technical and interpersonal approach

A woman who experiences pain during caesarean section under neuraxial anaesthesia is at risk of adverse psychological sequelae. Litigation arising from pain during caesarean section under neuraxial anaesthesia has replaced accidental awareness under general anaesthesia as the most common successful medicolegal claim against obstetric anaesthetists. Generic guidelines on caesarean section exist, but they do not provide specific recommendations for this area of anaesthetic practice. This guidance aims to offer pragmatic advice to support anaesthetists in caring for women during caesarean section. It emphasises the importance of non‐technical skills, offers advice on best practice and aims to encourage standardisation. The guidance results from a collaborative effort by anaesthetists, psychologists and patients and has been developed to support clinicians and promote standardisation of practice in this area

Motivation for Brazilian Older Adult Women to Join a Community Physical Activity Program Before COVID-19 Pandemic

Background: Intrinsic and extrinsic motivational factors can affect the levels of adherence of physical activity (PA) during the aging process. Objectives: Investigate the intrinsic and extrinsic aspects and motivation that led older women to enroll in and adhere to a community PA program before the COVID-19 pandemic. Methods: Data were collected via transversal survey before the COVID-19 pandemic. The sample consisted of 21 women, participants of a PA workshop, aged between 60 to 86 years [< 1-year (n = 8) and ≥ 1-year (n = 13) groups]. Motivation was assessed by the Motivation Inventory for Regular Physical Activity Practice (IMPRAF-54), using the 60th percentile to categorize high and low motivation, and two open questions. For qualitative assessment, content analysis was used and the answers were framed into subcategories regarding the motivation factors for adherence and permanence. Results: That adherence to the program was motivated by sociability purposes [total score: 36.0 (6.0), median (interquartile range)] and pleasure [34.0; (6.0)], while the main motivation for permanence was health [40.0 (11.0)]. Differences were noticed between the groups for sociability [38.0 (3.0) P = 0.030] and competitiveness [9.50 (12.0); P = 0.037] highest medians for the < 1 year group. Furthermore, the factors that least motivated older women were competitiveness and aesthetics. Conclusions: Health and sociability were the main motivators for the practice of physical activity among older adult women. Motivation played a fundamental role in the permanence of older adult women in the physical activity program

deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression

In this paper we describe the implementation of semi-structured deep distributional regression, a flexible framework to learn conditional distributions based on the combination of additive regression models and deep networks. Our implementation encompasses (1) a modular neural network building system based on the deep learning library TensorFlow for the fusion of various statistical and deep learning approaches, (2) an orthogonalization cell to allow for an interpretable combination of different subnetworks, as well as (3) pre-processing steps necessary to set up such models. The software package allows to define models in a user-friendly manner via a formula interface that is inspired by classical statistical model frameworks such as mgcv. The package's modular design and functionality provides a unique resource for both scalable estimation of complex statistical models and the combination of approaches from deep learning and statistics. This allows for state-of-the-art predictive performance while simultaneously retaining the indispensable interpretability of classical statistical models