Entropy Analysis of Industrial Accident Data Series

Complex industrial plants exhibit multiple interactions among smaller parts and with human operators. Failure in one part can propagate across subsystem boundaries causing a serious disaster. This paper analyzes the industrial accident data series in the perspective of dynamical systems. First, we process real world data and show that the statistics of the number of fatalities reveal features that are well described by power law (PL) distributions. For early years, the data reveal double PL behavior, while, for more recent time periods, a single PL fits better into the experimental data. Second, we analyze the entropy of the data series statistics over time. Third, we use the Kullback–Leibler divergence to compare the empirical data and multidimensional scaling (MDS) techniques for data analysis and visualization. Entropy-based analysis is adopted to assess complexity, having the advantage of yielding a single parameter to express relationships between the data. The classical and the generalized (fractional) entropy and Kullback–Leibler divergence are used. The generalized measures allow a clear identification of patterns embedded in the data.

Rat hepatocyte invasion by Listeria monocytogenes and analysis of TNF-alpha role in apoptosis

Listeria monocytogenes, etiological agent of severe human foodborne infection, uses sophisticated mechanisms of entry into host cytoplasm and manipulation of the cellular cytoskeleton, resulting in cell death. The host cells and bacteria interaction may result in cytokine production as Tumor Necrosis Factor (TNF) alpha. Hepatocytes have potential to produce pro-inflammatory cytokines as TNF-alpha when invaded by bacteria. In the present work we showed the behavior of hepatocytes invaded by L. monocytogenes by microscopic analysis, determination of TNF-alpha production by bioassay and analysis of the apoptosis through TUNEL technique. The presence of bacterium, in ratios that ranged from 5 to 50,000 bacteria per cell, induced the rupture of cellular monolayers. We observed the presence of internalized bacteria in the first hour of incubation by electronic microscopy. The levels of TNF-alpha increased from first hour of incubation to sixth hour, ranging from 0 to 3749 pg/mL. After seven and eight hours of incubation non-significant TNF-alpha levels decrease occurred, indicating possible saturation of cellular receptors. Thus, the quantity of TNF-alpha produced by hepatocytes was dependent of the incubation time, as well as of the proportion between bacteria and cells. The apoptosis rate increased in direct form with the incubation time (1 h to 8 + 24 h), ranging from 0 to 43%, as well as with the bacteria : cells ratio. These results show the ability of hepatocyte invasion by non-hemolytic L. monocytogenes, and the main consequences of this phenomenon were the release of TNF-alpha by hepatocytes and the induction of apoptosis. We speculate that hepatocytes use apoptosis induced by TNF-alpha for release bacteria to extracellular medium. This phenomenon may facilitate the bacteria destruction by the immune system.

Introducing numerical analysis tools in engineering: a Scilab user case in electronics course

Software tools in education became popular since the widespread of personal computers. Engineering courses lead the way in this development and these tools became almost a standard. Engineering graduates are familiar with numerical analysis tools but also with simulators (e.g. electronic circuits), computer assisted design tools and others, depending on the degree. One of the main problems with these tools is when and how to start use them so that they can be beneficial to students and not mere substitutes for potentially difficult calculations or design. In this paper a software tool to be used by first year students in electronics/electricity courses is presented. The growing acknowledgement and acceptance of open source software lead to the choice of an open source software tool – Scilab, which is a numerical analysis tool – to develop a toolbox. The toolbox was developed to be used as standalone or integrated in an e-learning platform. The e-learning platform used was Moodle. The first approach was to assess the mathematical skills necessary to solve all the problems related to electronics and electricity courses. Analysing the existing circuit simulators software tools, it is clear that even though they are very helpful by showing the end result they are not so effective in the process of the students studying and self learning since they show results but not intermediate steps which are crucial in problems that involve derivatives or integrals. Also, they are not very effective in obtaining graphical results that could be used to elaborate reports and for an overall better comprehension of the results. The developed tool was based on the numerical analysis software Scilab and is a toolbox that gives their users the opportunity to obtain the end results of a circuit analysis but also the expressions obtained when derivative and integrals calculations, plot signals, obtain vector diagrams, etc. The toolbox runs entirely in the Moodle web platform and provides the same results as the standalone application. The students can use the toolbox through the web platform (in computers where they don't have installation privileges) or in their personal computers by installing both the Scilab software and the toolbox. This approach was designed for first year students from all engineering degrees that have electronics/electricity courses in their curricula.

Optimization of random amplified polymorphic DNA techniques for use in genetic studies of Cuban triatominae

Random amplified polymorphic DNA (RAPD) technique is a simple and reliable method to detect DNA polymorphism. Several factors can affect the amplification profiles, thereby causing false bands and non-reproducibility of assay. In this study, we analyzed the effect of changing the concentration of primer, magnesium chloride, template DNA and Taq DNA polymerase with the objective of determining their optimum concentration for the standardization of RAPD technique for genetic studies of Cuban Triatominae. Reproducible amplification patterns were obtained using 5 pmoL of primer, 2.5 mM of MgCl2, 25 ng of template DNA and 2 U of Taq DNA polymerase in 25 µL of the reaction. A panel of five random primers was used to evaluate the genetic variability of T. flavida. Three of these (OPA-1, OPA-2 and OPA-4) generated reproducible and distinguishable fingerprinting patterns of Triatominae. Numerical analysis of 52 RAPD amplified bands generated for all five primers was carried out with unweighted pair group method analysis (UPGMA). Jaccard's Similarity Coefficient data were used to construct a dendrogram. Two groups could be distinguished by RAPD data and these groups coincided with geographic origin, i.e. the populations captured in areas from east and west of Guanahacabibes, Pinar del Río. T. flavida present low interpopulation variability that could result in greater susceptibility to pesticides in control programs. The RAPD protocol and the selected primers are useful for molecular characterization of Cuban Triatominae.

Thermostability of heterophile antibodies from human sera infected with Schistosoma mansoni and geo-helminths: an immuno-metric statistical analysis

Antibody in human sera that induces lysis of sheep erythrocytes in hemolytic assay was investigated. The present study showed that the presence in serum of the thermostable cytolytic anti-sheep red blood cells antibodies is dependent on the Schistosoma mansoni infection, and this is more frequent in adults than in children. The thermostable characteristic of hemolysins in normal sera was not dependent on the presence of Ascaris lumbricoides, Trichuris trichiura or hookworm geo-helminths. Further, thermostable complement-activating heterophile antibodies were noticed in children in association with massive number of S. mansoni eggs. The results were obtained by using the z- and the chi-square tests. The z-test allows us to formulate a one-sided alternative, i.e., a tendency of one of the attributes. On the other hand, the chi-square test analyzes the independence between attributes by using a contingency table. Besides the obtained results being interesting in the field of schistosomiasis mansoni, they can provide a new insight into the use of statistics in medical science.

Comprehensive treatments for social cognitive deficits in schizophrenia: A critical review and effect-size analysis of controlled studies

Recent advances in psychosocial treatments for schizophrenia have targeted social cognitive deficits. A critical literature review and effect-size (ES) analysis was conducted to investigate the efficacy of comprehensive programs of social cognitive training in schizophrenia. Results revealed 16 controlled studies consisting of seven models of comprehensive treatment with only three of these treatment models investigated in more than one study. The effects of social cognitive training were reported in 11/15 studies that included facial affect recognition skills (ES=.84) and 10/13 studies that included theory-of-mind (ES=.70) as outcomes. Less than half (4/9) of studies that measured attributional style as an outcome reported effects of treatment, but effect sizes across studies were significant (ESs=.30-.52). The effect sizes for symptoms were modest, but, with the exception of positive symptoms, significant (ESs=.32-.40). The majority of trials were randomized (13/16), selected active control conditions (11/16) and included at least 30 participants (12/16). Concerns for this area of research include the absence of blinded outcome raters in more than 50% of trials and low rates of utilization of procedures for maintaining treatment fidelity. These findings provide preliminary support for the broader use of comprehensive social cognitive training procedures as a psychosocial intervention for schizophrenia.

Re-Use Assessment of Thermoset Composite Wastes as Aggregate and Filler Replacement for Concrete-Polymer Composite Materials: A case study regarding GFRP pultrusion wastes

Glass fibre-reinforced plastics (GFRP), nowadays commonly used in the construction, transportation and automobile sectors, have been considered inherently difficult to recycle due to both the cross-linked nature of thermoset resins, which cannot be remoulded, and the complex composition of the composite itself, which includes glass fibres, polymer matrix and different types of inorganic fillers. Hence, to date, most of the thermoset based GFRP waste is being incinerated or landfilled leading to negative environmental impacts and additional costs to producers and suppliers. With an increasing awareness of environmental matters and the subsequent desire to save resources, recycling would convert an expensive waste disposal into a profitable reusable material. In this study, the effect of the incorporation of mechanically recycled GFRP pultrusion wastes on flexural and compressive behaviour of polyester polymer mortars (PM) was assessed. For this purpose, different contents of GFRP recyclates (0%, 4%, 8% and 12%, w/w), with distinct size grades (coarse fibrous mixture and fine powdered mixture), were incorporated into polyester PM as sand aggregates and filler replacements. The effect of the incorporation of a silane coupling agent was also assessed. Experimental results revealed that GFRP waste filled polymer mortars show improved mechanical behaviour over unmodified polyester based mortars, thus indicating the feasibility of GFRP waste reuse as raw material in concrete-polymer composites.

Clinical and epidemiological analysis of patients with HIV/AIDS admitted to a reference hospital in the northeast region of Brazil

The AIDS epidemic has become a worldwide phenomenon of enormous magnitude and extension, deeply transforming medical practices and public health initiatives. This retrospective survey aimed to analyze clinical and epidemiological characteristics of patients with HIV/AIDS admitted to the Institute of Tropical Diseases Natan Portella, Teresina, Piauí, Brazil, from January, 2001 through December, 2004. Of the 828 patients, 43% were from other states and 71.3% were men. Average patient age was 35.4 ± 11.5 years-old and 85.5% were illiterate or had primary education. The main form of exposure to HIV was heterosexual behavior (54.1%), while injectable drug use was confirmed by only 2.7% of registered cases. The most frequent infectious complications were candidiasis (42.4%) and pneumocystosis (22.2%). Sixty-eight cases (8.2%) of visceral leishmaniasis were registered. Using multivariate analysis, individuals aged over 40 years-old, patients with active tuberculosis, Pneumocystis carinii pneumonia and central nervous system cryptococcosis showed increased risk of death. In this study, young male adults with low educational levels predominated and the most frequent opportunistic infections were candidiasis and pneumocystosis.

Analysis of Natural and Artificial Phenomena Using Signal Processing and Fractional Calculus

In this paper we study several natural and man-made complex phenomena in the perspective of dynamical systems. For each class of phenomena, the system outputs are time-series records obtained in identical conditions. The time-series are viewed as manifestations of the system behavior and are processed for analyzing the system dynamics. First, we use the Fourier transform to process the data and we approximate the amplitude spectra by means of power law functions. We interpret the power law parameters as a phenomenological signature of the system dynamics. Second, we adopt the techniques of non-hierarchical clustering and multidimensional scaling to visualize hidden relationships between the complex phenomena. Third, we propose a vector field based analogy to interpret the patterns unveiled by the PL parameters.

Longitudinal analysis of tumor marker CEA of breast cancer patients from Braga's hospital

Allied to an epidemiological study of population of the Senology Unit of Braga’s Hospital that have been diagnosed with malignant breast cancer, we describe the progression in time of repeated measurements of tumor marker Carcinoembryonic antigen (CEA). Our main purpose is to describe the progression of this tumor marker as a function of possible risk factors and, hence, to understand how these risk factors influences that progression. The response variable, values of CEA, was analyzed making use of longitudinal models, testing for different correlation structures. The same covariates used in a previous survival analysis were considered in the longitudinal model. The reference time used was time from diagnose until death from breast cancer. For diagnostic of the models fitted we have used empirical and theoretical variograms. To evaluate the fixed term of the longitudinal model we have tested for a changing point on the effect of time on the tumor marker progression. A longitudinal model was also fitted only to the subset of patients that died from breast cancer, using the reference time as time from date of death until blood test.

Analysis of correlation between cerebrospinal fluid and plasma HIV-1 RNA levels in patients with neurological opportunistic diseases

The question of whether HIV-1 RNA in cerebrospinal fluid (CSF) is derived from viral replication in the central nervous system or simply reflects the transit of infected lymphocytes from the blood compartment has long been a matter of debate. Some studies found no correlation between CSF and plasma viral load, whereas others did. The lack of a correlation between the two compartments suggests that the presence of HIV-1 RNA is not simply due to the passive passage of the virus from blood to CSF but rather due to intrathecal replication. To evaluate the correlation between plasma and CSF HIV-1 RNA levels and to identify situations in which there is no correlation between the two compartments, seventy patients were prospectively studied. The association between CSF and plasma viral load was evaluated in the total population and in subgroups of patients with similar characteristics. A correlation between the CSF and plasma compartments was observed for patients undergoing highly active antiretroviral therapy (HAART), those with a CD4 T lymphocyte count lower than 200 cells/mm³, and those with increased CSF protein content. On the other hand, no correlation was observed for patients without adequate virological control, who had a CD4 count higher than 200 cells/mm³ and who did not use HAART. The correlation between the two compartments observed in some patients suggests that CSF HIV-1 RNA levels may reflect plasma levels in these subjects. In contrast, the lack of a correlation between the two compartments in patients who were not on HAART and who had normal CSF proteins and a poor virological control possibly indicates compartmentalization of the virus in CSF and, consequently, plasma-independent intrathecal viral replication.

Mortality after Discharge from Intensive Care: the Impact of Organ System Failure and Nursing Workload Use at Discharge

OBJECTIVES: Mortality after ICU discharge accounts for approx. 20-30% of deaths. We examined whether post-ICU discharge mortality is associated with the presence and severity of organ dysfunction/failure just before ICU discharge. PATIENTS AND METHODS: The study used the database of the EURICUS-II study, with a total of 4,621 patients, including 2,958 discharged alive to the general wards (post-ICU mortality 8.6%). Over a 4-month period we collected clinical and demographic characteristics, including the Simplified Acute Physiology Score (SAPS II), Nine Equivalents of Nursing Manpower Use Score, and Sequential Organ Failure Assessment (SOFA) score. RESULTS: Those who died in the hospital after ICU discharge had a higher SAPS II score, were more frequently nonoperative, admitted from the ward, and had stayed longer in the ICU. Their degree of organ dysfunction/failure was higher (admission, maximum, and delta SOFA scores). They required more nursing workload resources while in the ICU. Both the amount of organ dysfunction/failure (especially cardiovascular, neurological, renal, and respiratory) and the amount of nursing workload that they required on the day before discharge were higher. The presence of residual CNS and renal dysfunction/failure were especially prognostic factors at ICU discharge. Multivariate analysis showed only predischarge organ dysfunction/failure to be important; thus the increased use of nursing workload resources before discharge probably reflects only the underlying organ dysfunction/failure. CONCLUSIONS: It is better to delay the discharge of a patient with organ dysfunction/failure from the ICU, unless adequate monitoring and therapeutic resources are available in the ward.

Spatial distribution of dengue in the city of Cruzeiro, São Paulo State, Brazil: use of geoprocessing tools

The aim of this article is to identify patterns in spatial distribution of cases of dengue fever that occurred in the municipality of Cruzeiro, State of São Paulo, in 2006. This is an ecological and exploratory study using the tools of spatial analysis in the preparation of thematic maps with data from Sinan-Net. An analysis was made by area, taking as unit the IBGE census, the analysis included four months in 2006 which show the occurrence of the disease in the city. The thematic maps were constructed by TerraView 3.3.1 software, the same software provided the values of the indicators of Global Moran (I M) every month and the Kernel estimation. In the year 2006, 691 cases of dengue were georeferenced (with a rate of 864.2 cases/100,000 inhabitants); the indicators of Moran and p-values obtained were I M = 0.080 (March) p = 0.11; I M = 0.285 (April) p = 0.01; I M = 0.201 (May) p = 0.01 and I M = 0.002 (June) p = 0.57. The first cases were identified in the Northeast and Central areas of Cruzeiro and the recent cases, in the North, Northeast and Central. It was possible to identify census tracts where the epidemic began and how it occurred temporally and spatially in the city.

The development and implementation of math projects in a HEI: expectations, objectives, experiences and analysis

An overwhelming problem in Math Curriculums in Higher Education Institutions (HEI), we are daily facing in the last decade, is the substantial differences in Math background of our students. When you try to transmit, engage and teach subjects/contents that your “audience” is unable to respond to and/or even understand what we are trying to convey, it is somehow frustrating. In this sense, the Math projects and other didactic strategies, developed through Learning Management System Moodle, which include an array of activities that combine higher order thinking skills with math subjects and technology, for students of HE, appear as remedial but important, proactive and innovative measures in order to face and try to overcome these considerable problems. In this paper we will present some of these strategies, developed in some organic units of the Polytechnic Institute of Porto (IPP). But, how “fruitful” are the endless number of hours teachers spent in developing and implementing these platforms? Do students react to them as we would expect? Do they embrace this opportunity to overcome their difficulties? How do they use/interact individually with LMS platforms? Can this environment that provides the teacher with many interesting tools to improve the teaching – learning process, encourages students to reinforce their abilities and knowledge? In what way do they use each available material – videos, interactive tasks, texts, among others? What is the best way to assess student’s performance in these online learning environments? Learning Analytics tools provides us a huge amount of data, but how can we extract “good” and helpful information from them? These and many other questions still remain unanswered but we look forward to get some help in, at least, “get some drafts” for them because we feel that this “learning analysis”, that tackles the path from the objectives to the actual results, is perhaps the only way we have to move forward in the “best” learning and teaching direction.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.