Biconditional Generative Adversarial Networks for Multiview Learning with Missing Views

In this paper, we present a conditional GAN with two generators and a common discriminator for multiview learning problems where observations have two views, but one of them may be missing for some of the training samples. This is for example the case for multilingual collections where documents are not available in all languages. Some studies tackled this problem by assuming the existence of view generation functions to approximately complete the missing views; for example Machine Translation to translate documents into the missing languages. These functions generally require an external resource to be set and their quality has a direct impact on the performance of the learned multiview classifier over the completed training set. Our proposed approach addresses this problem by jointly learning the missing views and the multiview classifier using a tripartite game with two generators and a discriminator. Each of the generators is associated to one of the views and tries to fool the discriminator by generating the other missing view conditionally on the corresponding observed view. The discriminator then tries to identify if for an observation, one of its views is completed by one of the generators or if both views are completed along with its class. Our results on a subset of Reuters RCV1/RCV2 collections show that the discriminator achieves significant classification performance; and that the generators learn the missing views with high quality without the need of any consequent external resource.Comment: 15 pages, 3 figur

Crystalline phases involved in the hydration of calcium silicate-based cements: Semi-quantitative Rietveld X-ray diffraction analysis

Chemical comparisons of powder and hydrated forms of calcium silicate cements (CSCs) and calculation of alterations in tricalcium silicate (Ca3SiO5) calcium hydroxide (Ca(OH)2) are essential for understanding their hydration processes. This study aimed to evaluate and compare these changes in ProRoot MTA, Biodentine and CEM cement. Powder and hydrated forms of tooth coloured ProRoot MTA, Biodentine and CEM cement were subjected to X-ray diffraction (XRD) analysis with Rietveld refinement to semi-quantitatively identify and quantify the main phases involved in their hydration process. Data were reported descriptively. Reduction in Ca3SiO5 and formation of Ca(OH)2 were seen after the hydration of ProRoot MTA and Biodentine; however, in the case of CEM cement, no reduction of Ca3SiO5 and no formation of Ca(OH)2 were detected. The highest percentages of amorphous phases were seen in Biodentine samples. Ettringite was detected in the hydrated forms of ProRoot MTA and CEM cement but not in Biodentine

Quality of life in the Iranian Blind War Survivors in 2007: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Quality of Life measurements are necessary tools for effectively evaluating health services. In the population of patients afflicted with war-related blindness in Iran, such measurements have yet to be documented and utilized. "The design and implementation of this study involved the determination of a baseline score for QOL in a population of Iranian blinded in the Iraq-Iran war in order to facilitate the design of interventions intended to improve the population's QOL."</p> <p>Methods</p> <p>This was a cross-sectional study of a representative population of 250 war victims blind in both eyes at a 14-day recreational conference.</p> <p>Results</p> <p>Participants had a mean age of 43.20(SD8.34) and their composition was 96.5% male and 3.5% female with a mean SF-36 QOL score of 59.20(SD22.80). An increasing level of education among the participants correlated with a higher QOL score (p = 0.006). The QOL also has a significant correlation to number of injuries (p < 0.0001). High systolic and diastolic blood pressure, hearing loss, and tinnitus had negative individual correlations to QOL (p = 0.016, 0.016, 0.005, p < 0.0001). The male sexual disorders of erectile dysfunction and premature ejaculation both had significant correlations to QOL (p = 0.026, p < 0.0001). Hypercholesterolemia showed significant correlation to QOL (p = 0.021).</p> <p>Conclusions</p> <p>As blind war survivors' age, they will present with a greater set of burdens despite their relatively better QOL in the physical component scale when compared with lower limb amputees. Risk factors of cardiovascular attack such as high blood pressure and hypercholesterolemia were present and need future interventions.</p> <p>Key words</p> <p>Quality of life, blindness, SF36, health</p

Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics

In [1], we have explored the theoretical aspects of feature selection and evolutionary algorithms. In this chapter, we focus on optimization algorithms for enhancing data analytic process, i.e., we propose to explore applications of nature-inspired algorithms in data science. Feature selection optimization is a hybrid approach leveraging feature selection techniques and evolutionary algorithms process to optimize the selected features. Prior works solve this problem iteratively to converge to an optimal feature subset. Feature selection optimization is a non-specific domain approach. Data scientists mainly attempt to find an advanced way to analyze data n with high computational efficiency and low time complexity, leading to efficient data analytics. Thus, by increasing generated/measured/sensed data from various sources, analysis, manipulation and illustration of data grow exponentially. Due to the large scale data sets, Curse of dimensionality (CoD) is one of the NP-hard problems in data science. Hence, several efforts have been focused on leveraging evolutionary algorithms (EAs) to address the complex issues in large scale data analytics problems. Dimension reduction, together with EAs, lends itself to solve CoD and solve complex problems, in terms of time complexity, efficiently. In this chapter, we first provide a brief overview of previous studies that focused on solving CoD using feature extraction optimization process. We then discuss practical examples of research studies are successfully tackled some application domains, such as image processing, sentiment analysis, network traffics / anomalies analysis, credit score analysis and other benchmark functions/data sets analysis

Global, regional, and national incidence, prevalence, and mortality of HIV, 1980–2017, and forecasts to 2030, for 195 countries and territories: a systematic analysis for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017

Background Understanding the patterns of HIV/AIDS epidemics is crucial to tracking and monitoring the progress of prevention and control efforts in countries. We provide a comprehensive assessment of the levels and trends of HIV/AIDS incidence, prevalence, mortality, and coverage of antiretroviral therapy (ART) for 1980–2017 and forecast these estimates to 2030 for 195 countries and territories. Methods We determined a modelling strategy for each country on the basis of the availability and quality of data. For countries and territories with data from population-based seroprevalence surveys or antenatal care clinics, we estimated prevalence and incidence using an open-source version of the Estimation and Projection Package—a natural history model originally developed by the UNAIDS Reference Group on Estimates, Modelling, and Projections. For countries with cause-specific vital registration data, we corrected data for garbage coding (ie, deaths coded to an intermediate, immediate, or poorly defined cause) and HIV misclassification. We developed a process of cohort incidence bias adjustment to use information on survival and deaths recorded in vital registration to back-calculate HIV incidence. For countries without any representative data on HIV, we produced incidence estimates by pulling information from observed bias in the geographical region. We used a re-coded version of the Spectrum model (a cohort component model that uses rates of disease progression and HIV mortality on and off ART) to produce age-sex-specific incidence, prevalence, and mortality, and treatment coverage results for all countries, and forecast these measures to 2030 using Spectrum with inputs that were extended on the basis of past trends in treatment scale-up and new infections. Findings Global HIV mortality peaked in 2006 with 1·95 million deaths (95% uncertainty interval 1·87–2·04) and has since decreased to 0·95 million deaths (0·91–1·01) in 2017. New cases of HIV globally peaked in 1999 (3·16 million, 2·79–3·67) and since then have gradually decreased to 1·94 million (1·63–2·29) in 2017. These trends, along with ART scale-up, have globally resulted in increased prevalence, with 36·8 million (34·8–39·2) people living with HIV in 2017. Prevalence of HIV was highest in southern sub-Saharan Africa in 2017, and countries in the region had ART coverage ranging from 65·7% in Lesotho to 85·7% in eSwatini. Our forecasts showed that 54 countries will meet the UNAIDS target of 81% ART coverage by 2020 and 12 countries are on track to meet 90% ART coverage by 2030. Forecasted results estimate that few countries will meet the UNAIDS 2020 and 2030 mortality and incidence targets. Interpretation Despite progress in reducing HIV-related mortality over the past decade, slow decreases in incidence, combined with the current context of stagnated funding for related interventions, mean that many countries are not on track to reach the 2020 and 2030 global targets for reduction in incidence and mortality. With a growing population of people living with HIV, it will continue to be a major threat to public health for years to come. The pace of progress needs to be hastened by continuing to expand access to ART and increasing investments in proven HIV prevention initiatives that can be scaled up to have population-level impact

Approaches in biotechnological applications of natural polymers

Natural polymers, such as gums and mucilage, are biocompatible, cheap, easily available and non-toxic materials of native origin. These polymers are increasingly preferred over synthetic materials for industrial applications due to their intrinsic properties, as well as they are considered alternative sources of raw materials since they present characteristics of sustainability, biodegradability and biosafety. As definition, gums and mucilages are polysaccharides or complex carbohydrates consisting of one or more monosaccharides or their derivatives linked in bewildering variety of linkages and structures. Natural gums are considered polysaccharides naturally occurring in varieties of plant seeds and exudates, tree or shrub exudates, seaweed extracts, fungi, bacteria, and animal sources. Water-soluble gums, also known as hydrocolloids, are considered exudates and are pathological products; therefore, they do not form a part of cell wall. On the other hand, mucilages are part of cell and physiological products. It is important to highlight that gums represent the largest amounts of polymer materials derived from plants. Gums have enormously large and broad applications in both food and non-food industries, being commonly used as thickening, binding, emulsifying, suspending, stabilizing agents and matrices for drug release in pharmaceutical and cosmetic industries. In the food industry, their gelling properties and the ability to mold edible films and coatings are extensively studied. The use of gums depends on the intrinsic properties that they provide, often at costs below those of synthetic polymers. For upgrading the value of gums, they are being processed into various forms, including the most recent nanomaterials, for various biotechnological applications. Thus, the main natural polymers including galactomannans, cellulose, chitin, agar, carrageenan, alginate, cashew gum, pectin and starch, in addition to the current researches about them are reviewed in this article.. }To the Conselho Nacional de Desenvolvimento Cientfíico e Tecnológico (CNPq) for fellowships (LCBBC and MGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nvíel Superior (CAPES) (PBSA). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and COMPETE 2020 (POCI-01-0145-FEDER-006684) (JAT)

Share of afghanistan populace in hepatitis B and hepatitis C infection's pool: is it worthwhile?

There is a notable dearth of data about Hepatitis B Virus (HBV) and Hepatitis C Virus(HCV) prevalence in Afghanistan. Awareness program and research capacity in the field of hepatitis are very limited in Afghanistan. Number of vulnerabilities and patterns of risk behaviors signal the need to take action now

Hepatitis C virus genotype frequency in Isfahan province of Iran: a descriptive cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Hepatitis C is an infectious disease affecting the liver, caused by the hepatitis C virus (HCV). The hepatitis C virus is a small, enveloped, single-stranded, positive sense RNA virus with a large genetic heterogeneity. Isolates have been classified into at least eleven major genotypes, based on a nucleotide sequence divergence of 30-35%. Genotypes 1, 2 and 3 circulate around the world, while other genotypes are mainly restricted to determined geographical areas. Genotype determination of HCV is clinically valuable as it provides important information which can be used to determine the type and duration of therapy and to predict the outcome of the disease.</p> <p>Results</p> <p>Plasma samples were collected from ninety seven HCV RNA positive patients admitted to two large medical laboratory centers in Isfahan province (Iran) from the years 2007 to 2009. Samples from patients were subjected to HCV genotype determination using a PCR based genotyping kit. The frequency of HCV genotypes was determined as follows: genotype 3a (61.2%), genotype 1a (29.5%), genotype 1b (5.1%), genotype 2 (2%) and mixed genotypes of 1a+3a (2%).</p> <p>Conclusion</p> <p>Genotype 3a is the most frequent followed by the genotype 1a, genotype 1b and genotype 2 in Isfahan province, Iran.</p

On the role of corticosterone in behavioral disorders, microbiota composition alteration and neuroimmune response in adult male mice subjected to maternal separation stress

Experiencing psychosocial adversities in early life such as maternal separation (MS) increases the risk of psychiatric disorders. Immune-inflammatory responses have imperative roles in the pathophysiology of psychiatric disorders. MS relatively changes the composition of intestinal microbiota leading to an overactivation of the hypothalamic-pituitary-adrenal (HPA) axis, and subsequently increases the corticosterone level. In this study, we aimed to evaluate the role of corticosterone in behavioral changes and microbiota modifications in a mouse model of MS afflicted neuroinflammatory response in the hippocampus. For this purpose, 180 min of MS stress was applied to mice at postnatal day (PND) 2-14 followed by behavioral tests including forced swimming test (FST), splash test, open field test (OFT) and elevated plus maze (EPM) at PND 50-52. For evaluating the role of corticosterone, mice were subjected to adrenalectomy. Using real-time RT-PCR, the expression of inflammatory genes was determined in the hippocampus and colon tissues. We found that MS provoked depressive- and anxiety-like behaviors in adult male mice. In addition, MS was able to active a neuroimmune response in the hippocampus, motivate inflammation and histopathologic changes in the colon tissue and modify the composition of gut microbiota as well. Interestingly, our findings showed that adrenalectomy (decline in the corticosterone level), could modulate the above-mentioned negative effects of MS. In conclusion, our results demonstrated that overactivation of HPA axis and the subsequent increased level of corticosterone could act, possibly, as the deleterious effects of MS on behavior, microbiota composition changes and activation of neuroimmune respons