Adaptive mutations in bacteria: high rate and small effects

Evolution by natural selection is driven by the continuous generation of adaptive mutations. We measured the genomic mutation rate that generates beneficial mutations and their effects on fitness in Escherichia coli under conditions in which the effect of competition between lineages carrying different beneficial mutations is minimized. We found a rate on the order of 10–5 per genome per generation, which is 1000 times as high as previous estimates, and a mean selective advantage of 1%. Such a high rate of adaptive evolution has implications for the evolution of antibiotic resistance and pathogenicity.

Nutritional status and overhydration: can bioimpedance spectroscopy be useful in haemodialysis patients?

Background: Protein-energy wasting (PEW), associated with inflammation and overhydration, is common in haemodialysis (HD) patients and is associated with high morbidity and mortality. Objective: Assess the relationship between nutritional status, markers of inflammation and body composition through bioimpedance spectroscopy (BIS) in HD patients. Methods: This observational, cross-sectional, single centre study, carried out in an HD centre in Forte da Casa (Portugal), involved 75 patients on an HD programme. In all participating patients, the following laboratory tests were conducted: haemoglobin, albumin, C-reactive protein (CRP) and 25-hydroxyvitamin D3 [25(OH)D3]. The body mass index of all patients was calculated and a modified version of subjective global assessment (SGA) was produced for patients on dialysis. Intracellular water (ICW) and extracellular water (ECW) were measured by BIS (Body Composition Monitor®, Fresenius Medical Care®) after the HD session. In statistical analysis, Spearman’s correlation was used for the univariate analysis and linear regression for the multivariate analysis (SPSS 14.0). A P value of <.05 was considered statistically significant. Results: PEW, inversely assessed through the ICW/body weight (BW) ratio, was positively related to age (P<.001), presence of diabetes (P=.004), BMI (P=.01) and CRP (P=.008) and negatively related to albumin (p=.006) and 25(OH)D3 (P=.007). Overhydration, assessed directly through the ECW/BW ratio, was positively related with CRP (P=.009) and SGA (P=.03), and negatively with 25(OH)D3 (P=.006) and BMI (P=.01). In multivariate analysis, PEW was associated with older age (P<.001), the presence of diabetes (P=.003), lower 25(OH)D3 (P=.008), higher CRP (P=.001) and lower albumin levels (P=.004). Over-hydration was associated with higher CRP (P=.001) and lower levels of 25(OH)D3 (P=.003). Conclusions: Taking these results into account, the ICW/BW and ECW/BW ratios, assessed with BIS, have proven to be good markers of the nutritional and inflammatory status of HD patients. BIS may be a useful tool for regularly assessing the nutritional and hydration status in these patients and may allow nutritional advice to be improved and adjusted.

An adaptive educational system for higher education

The main objective of an Adaptive System is to adequate its relation with the user (content presentation, navigation, interface, etc.) according to a predefined but updatable model of the user that reflects his objectives, preferences, knowledge and competences [Brusilovsky, 2001], [De Bra, 2004]. For Educational Adaptive Systems, the emphasis is placed on the student knowledge in the domain application and learning style, to allow him to reach the learning objectives proposed for his training [Chepegin, 2004]. In Educational AHS, the User Model (UM), or Student Model, has increased relevance: when the student reaches the objectives of the course, the system must be able to readapt, for example, to his knowledge [Brusilovsky, 2001]. Learning Styles are understood as something that intent to define models of how given person learns. Generally it is understood that each person has a Learning Style different and preferred with the objective of achieving better results. Some case studies have proposed that teachers should assess the learning styles of their students and adapt their classroom and methods to best fit each student's learning style [Kolb, 2005], [Martins, 2008]. The learning process must take into consideration the individual cognitive and emotional parts of the student. In summary each Student is unique so the Student personal progress must be monitored and teaching shoul not be not generalized and repetitive [Jonassen, 1991], [Martins, 2008]. The aim of this paper is to present an Educational Adaptive Hypermedia Tool based on Progressive Assessment.

User modeling In adaptive hypermedia educational systems

This document is a survey in the research area of User Modeling (UM) for the specific field of Adaptive Learning. The aims of this document are: To define what it is a User Model; To present existing and well known User Models; To analyze the existent standards related with UM; To compare existing systems. In the scientific area of User Modeling (UM), numerous research and developed systems already seem to promise good results, but some experimentation and implementation are still necessary to conclude about the utility of the UM. That is, the experimentation and implementation of these systems are still very scarce to determine the utility of some of the referred applications. At present, the Student Modeling research goes in the direction to make possible reuse a student model in different systems. The standards are more and more relevant for this effect, allowing systems communicate and to share data, components and structures, at syntax and semantic level, even if most of them still only allow syntax integration.

HIV infection and related risk behaviors in a community of recyclable waste collectors of Santos, Brazil

OBJECTIVE: To estimate the seroprevalence of HIV, hepatitis B and C and syphilis and to describe risk behaviors associated to their transmission among recyclable waste collectors. METHODS: A seroepidemiological survey was carried out in the city of Santos, Southeastern Brazil, in 2005. A total of 315 individuals were enrolled in the survey, of which 253 subjects underwent serological testing HIV, hepatitis B and C and syphilis. Statistical analysis consisted of univariate and bivariate analyses (cross-tabulation and odds ratio) and multivariate analysis (by logistic regression), relating HIV infection with established risk behaviors and seropositivity. RESULTS: Overall seroprevalences were: HIV, 8.9%; hepatitis B, 34.4%; hepatitis C, 12.4%; and syphilis, 18.4%. Subjects were characterized by a predominance of males with low educational and economic levels, subjected to parenteral and sexual exposures to HIV and other sexually transmitted infections. Multivariate analysis results indicated that risk factors for both sexually and parenterally related exposure were significantly associated with HIV in this community. CONCLUSIONS: Seroprevalences found in the study were approximately 10 to 12 times higher than the national average. These communities are socially marginalized and generally not recognized by national programs as potentially endangered populations.

Missed opportunities for congenital syphilis and HIV perinatal transmission prevention

OBJECTIVE: To estimate the prevalence of missed opportunities for congenital syphilis and HIV prevention in pregnant women who had access to prenatal care and to assess factors associated to non-testing of these infections. METHODS: Cross-sectional study comprising a randomly selected sample of 2,145 puerperal women who were admitted in maternity hospitals for delivery or curettage and had attended at least one prenatal care visit, in Brazil between 1999 and 2000. No syphilis and/or anti-HIV testing during pregnancy was a marker for missed prevention opportunity. Women who were not tested for either or both were compared to those who had at least one syphilis and one anti-HIV testing performed during pregnancy (reference category). The prevalence of missed prevention opportunity was estimated for each category with 95% confidence intervals. Factors independently associated with missed prevention opportunity were assessed through multinomial logistic regression. RESULTS: The prevalence of missed prevention opportunity for syphilis or anti-HIV was 41.2% and 56.0%, respectively. The multivariate analysis showed that race/skin color (non-white), schooling (<8 years), marital status (single), income (<3 monthly minimum wages), having sex during pregnancy, history of syphilis prior to the current pregnancy, number of prenatal care visits (<6), and last prenatal visit before the third trimester of gestation were associated with an increased risk of missed prevention opportunity. A negative association with missed prevention opportunity was found between marital status (single), prenatal care site (hospital) and first prenatal visit in the third trimester of gestation. CONCLUSIONS: High rates of non-tested women indicate failures in preventive and control actions for HIV infection and congenital syphilis. Pregnant women have been discontinuing prenatal care at an early stage and are failing to undergo prenatal screening for HIV and syphilis.

Interactions between physical and psychosocial demands of work associated to low back pain

OBJECTIVE: To examine the interaction between physical and psychosocial demands of work associated to low back pain. METHODS: Cross-sectional study carried out in a stratified proportional random sample of 577 plastic industry workers in the metropolitan area of the city of Salvador, Northeast Brazil in 2002. An anonymous standard questionnaire was administered in the workplace by trained interviewers. Physical demands at work were self-rated on a 6-point numeric scale, with anchors at each end of the scale. Factor analysis was carried out on 11 physical demand variables to identify underlying factors. Psychosocial work demands were measured by demand, control and social support questions. Multivariate analysis was performed using the likelihood ratio test. RESULTS: The factor analysis identified two physical work demand factors: material handling (factor 1) and repetitiveness (factor 2). The multiple logistic regression analysis showed that factor 1 was positively associated with low back pain (OR=2.35, 95% CI 1.50;3.66). No interaction was found between physical and psychosocial work demands but both were independently associated to low back pain. CONCLUSIONS: The study found independent effects of physical and psychosocial work demands on low back pain prevalence and emphasizes the importance of physical demands especially of material handling involving trunk bending forward and trunk rotation regardless of age, gender, and body fitness.

Does the intake of LC-PUFAS during pregnancy affect the body composition of term neonates? Preliminary results

Background: The effect of the intake of polynsaturated long chain fatty acids (LCPUFAs) during pregnancy on fetal body composition has been assessed by studies using mostly neonatal anthropometry. Their results have been inconsistent, probably because neonatal anthropometry has several validity limitations. Air displacement plethismography (ADP) is a recently validated non-invasive method for assessing body composition in neonates. Objective: To determine the effect of the intake of LCPUFAs during pregnancy on the body composition of term neonates, measured by ADP. Methods: Cross-sectional study of a convenience sample of healthy full-term neonates and their mothers. The diet during pregnancy was assessed using a validated semi-quantitative food frequency questionnaire; Food Processor Plus® was used to convert food intake into nutritional values. Body composition was estimated by anthropometry and measured by ADP using Pea Pod™ Life Measurements Inc (fat mass - FM, fat-free mass and %FM) within the first 72h after birth. Univariate and multivariate analysis (linear regression model) were performed. Results: 54 mother-neonate pairs were included. Multivariate analysis adjusted to the maternal body mass index shows positive association between LCPUFAs intake and neonatal mid-arm circumference (= 0,610, p = 0,019) and negative association between n-6:n-3 ratio intake and neonatal %FM (= -2,744, p=0,066). Conclusion: To the best of our knowledge, this is the first study on this subject using ADP and showing a negative association between LCPUFAs n-6:n-3 ratio intake in pregnancy and neonatal %FM. This preliminary finding requires confirmation increasing the study power with a greater sample and performing interventional studies.

Adaptive learning in agents behaviour: a framework for electricity markets simulation

Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.

ECG denoising based on adaptive signal processing technique

An Electrocardiogram (ECG) monitoring system deals with several challenges related with noise sources. The main goal of this text was the study of Adaptive Signal Processing Algorithms for ECG noise reduction when applied to real signals. This document presents an adaptive ltering technique based on Least Mean Square (LMS) algorithm to remove the artefacts caused by electromyography (EMG) and power line noise into ECG signal. For this experiments it was used real noise signals, mainly to observe the di erence between real noise and simulated noise sources. It was obtained very good results due to the ability of noise removing that can be reached with this technique. A recolha de sinais electrocardiogr a cos (ECG) sofre de diversos problemas relacionados com ru dos. O objectivo deste trabalho foi o estudo de algoritmos adaptativos para processamento digital de sinal, para redu c~ao de ru do em sinais ECG reais. Este texto apresenta uma t ecnica de redu c~ao de ru do baseada no algoritmo Least Mean Square (LMS) para remo c~ao de ru dos causados quer pela actividade muscular (EMG) quer por ru dos causados pela rede de energia el ectrica. Para as experiencias foram utilizados ru dos reais, principalmente para aferir a diferen ca de performance do algoritmo entre os sinais reais e os simulados. Foram conseguidos bons resultados, essencialmente devido as excelentes caracter sticas que esta t ecnica tem para remover ru dos.

Risk factors for cesarean section by category of health service

OBJECTIVE: To analyze the rate of cesarean section and differences in risk factors by category of health service, either public or private. METHODS: A cross-sectional study was carried out including all pregnant women in labor admitted to hospitals in the city of Rio Grande, Southern Brazil, between January 1 and December 31, 2007. A pre-coded and pre-tested questionnaire was used to collect on social, demographic, obstetric and newborn care information. Two regression models were constructed: one for public users and the other one for private ones. Poisson regression was used in each model in the multivariate analysis. Prevalence rates and 95% confidence intervals were calculated for each adjusted factor. RESULTS: The rate of cesarean section was 43% and 86% among public and private users. Sociodemographic factors and twin births have a more significant impact among public users as well as number of pregnancies (25% vs. 13% reduction in public and private users, respectively) and previous cesarean section (86% vs. 24% increase in public and private users, respectively). Prenatal care visits and hospital admissions affected the outcome only in women users of public services. CONCLUSIONS: Cesarean section rates were high in both groups studied, but it was twice as high among women cared in the private sector. Associated factors differ in magnitude by category of service used.

Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes

Amulti-residue methodology based on a solid phase extraction followed by gas chromatography–tandem mass spectrometry was developed for trace analysis of 32 compounds in water matrices, including estrogens and several pesticides from different chemical families, some of them with endocrine disrupting properties. Matrix standard calibration solutions were prepared by adding known amounts of the analytes to a residue-free sample to compensate matrix-induced chromatographic response enhancement observed for certain pesticides. Validation was done mainly according to the International Conference on Harmonisation recommendations, as well as some European and American validation guidelines with specifications for pesticides analysis and/or GC–MS methodology. As the assumption of homoscedasticity was not met for analytical data, weighted least squares linear regression procedure was applied as a simple and effective way to counteract the greater influence of the greater concentrations on the fitted regression line, improving accuracy at the lower end of the calibration curve. The method was considered validated for 31 compounds after consistent evaluation of the key analytical parameters: specificity, linearity, limit of detection and quantification, range, precision, accuracy, extraction efficiency, stability and robustness.

Parallel real-time support for distributed adaptive embedded applications

Real-time embedded applications require to process large amounts of data within small time windows. Parallelize and distribute workloads adaptively is suitable solution for computational demanding applications. The purpose of the Parallel Real-Time Framework for distributed adaptive embedded systems is to guarantee local and distributed processing of real-time applications. This work identifies some promising research directions for parallel/distributed real-time embedded applications.

Service offloading in adaptive real-time systems

Smartphones and other internet enabled devices are now common on our everyday life, thus unsurprisingly a current trend is to adapt desktop PC applications to execute on them. However, since most of these applications have quality of service (QoS) requirements, their execution on resource-constrained mobile devices presents several challenges. One solution to support more stringent applications is to offload some of the applications’ services to surrogate devices nearby. Therefore, in this paper, we propose an adaptable offloading mechanism which takes into account the QoS requirements of the application being executed (particularly its real-time requirements), whilst allowing offloading services to several surrogate nodes. We also present how the proposed computing model can be implemented in an Android environment

Hybrid adaptive control of a dragonfly model

Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive (HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive (DA) method in terms of faster and improved tracking and parameter convergence.