Using deep learning for ordinal classification of mobile marketing user conversion

In this paper, we explore Deep Multilayer Perceptrons (MLP) to perform an ordinal classification of mobile marketing conversion rate (CVR), allowing to measure the value of product sales when an user clicks an ad. As a case study, we consider big data provided by a global mobile marketing company. Several experiments were held, considering a rolling window validation, different datasets, learning methods and performance measures. Overall, competitive results were achieved by an online deep learning model, which is capable of producing real-time predictions.This article is a result of the project NORTE-01-0247-FEDER-017497, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). This work was also supported by Funda¸c˜ao para a Ciˆencia e Tecnologia (FCT) within the Project Scope: UID/CEC/00319/201

Backprojection for Training Feedforward Neural Networks in the Input and Feature Spaces

After the tremendous development of neural networks trained by backpropagation, it is a good time to develop other algorithms for training neural networks to gain more insights into networks. In this paper, we propose a new algorithm for training feedforward neural networks which is fairly faster than backpropagation. This method is based on projection and reconstruction where, at every layer, the projected data and reconstructed labels are forced to be similar and the weights are tuned accordingly layer by layer. The proposed algorithm can be used for both input and feature spaces, named as backprojection and kernel backprojection, respectively. This algorithm gives an insight to networks with a projection-based perspective. The experiments on synthetic datasets show the effectiveness of the proposed method.Comment: Accepted (to appear) in International Conference on Image Analysis and Recognition (ICIAR) 2020, Springe

Analysis of parallel process in HVAC systems using deep autoencoders

P. 15-26Heating, Ventilation, and Air Conditioning (HVAC) systems are generally built in a modular manner, comprising several identical subsystems in order to achieve their nominal capacity. These parallel subsystems and elements should have the same behavior and, therefore, differences between them can reveal failures and inefficiency in the system. The complexity in HVAC systems comes from the number of variables involved in these processes. For that reason, dimensionality reduction techniques can be a useful approach to reduce the complexity of the HVAC data and study their operation. However, for most of these techniques, it is not possible to project new data without retraining the projection and, as a result, it is not possible to easily compare several projections. In this paper, a method based on deep autoencoders is used to create a reference model with a HVAC system and new data is projected using this model to be able to compare them. The proposed approach is applied to real data from a chiller with 3 identical compressors at the Hospital of LeónS

Hepatitis E in southern Vietnam: Seroepidemiology in humans and molecular epidemiology in pigs.

Viral pathogens account for a significant proportion of the burden of emerging infectious diseases in humans. The Wellcome Trust-Vietnamese Initiative on Zoonotic Infections (WT-VIZIONS) is aiming to understand the circulation of viral zoonotic pathogens in animals that pose a potential risk to human health. Evidence suggests that human exposure and infections with hepatitis E virus (HEV) genotypes (GT) 3 and 4 results from zoonotic transmission. Hypothesising that HEV GT3 and GT4 are circulating in the Vietnamese pig population and can be transmitted to humans, we aimed to estimate the seroprevalence of HEV exposure in a population of farmers and the general population. We additionally performed sequence analysis of HEV in pig populations in the same region to address knowledge gaps regarding HEV circulation and to evaluate if pigs were a potential source of HEV exposure. We found a high prevalence of HEV GT3 viral RNA in pigs (19.1% in faecal samples and 8.2% in rectal swabs) and a high HEV seroprevalence in pig farmers (16.0%) and a hospital-attending population (31.7%) in southern Vietnam. The hospital population was recruited as a general-population proxy even though this particular population subgroup may introduce bias. The detection of HEV RNA in pigs indicates that HEV may be a zoonotic disease risk in this location, although a larger sample size is required to infer an association between HEV positivity in pigs and seroprevalence in humans

Fundamental issues in systems biology.

types: Journal Article; Research Support, Non-U.S. Gov'tIn the context of scientists' reflections on genomics, we examine some fundamental issues in the emerging postgenomic discipline of systems biology. Systems biology is best understood as consisting of two streams. One, which we shall call 'pragmatic systems biology', emphasises large-scale molecular interactions; the other, which we shall refer to as 'systems-theoretic biology', emphasises system principles. Both are committed to mathematical modelling, and both lack a clear account of what biological systems are. We discuss the underlying issues in identifying systems and how causality operates at different levels of organisation. We suggest that resolving such basic problems is a key task for successful systems biology, and that philosophers could contribute to its realisation. We conclude with an argument for more sociologically informed collaboration between scientists and philosophers.Funding received from the Economic and Social Research Council (ESRC), UK, and Overseas Conference Funding from the British Academy

Teaching digital fiction: integrating experimental writing and current technologies

Today’s creative writers are immersed in a multiplicative, multimodal—digital—universe. It requires “multiliteracies”, all in a constantly and rapidly evolving technological environment, which are not yet fundamentally integrated into the basic literacy skills entrenched in school learning. How can creative writing instructors in higher education best prepare their students for the real-world contexts of their creative practice? One approach is to integrate the creative writing workshop with a focus on digital and interactive design. This paper outlines a module incorporating multiple literacies into a creative writing course, Playable Fiction, noting the affordances, limitations, and benefits of teaching workshops for writing digital fiction (“born-digital” fiction, composed for and read on digital devices). The researcher took an ethnographical approach to the question, designing a module to encourage creative writing students to experiment with digital fiction, and observing the effects on the students’ attitudes and their coursework. Included is a discussion of the benefits to students of developing multiliteracies and considerations for teaching, including issues of technical know-how and the lack of infrastructural support

Self-help interventions for depressive disorders and depressive symptoms: a systematic review

<p>Abstract</p> <p>Background</p> <p>Research suggests that depressive disorders exist on a continuum, with subthreshold symptoms causing considerable population burden and increasing individual risk of developing major depressive disorder. An alternative strategy to professional treatment of subthreshold depression is population promotion of effective self-help interventions that can be easily applied by an individual without professional guidance. The evidence for self-help interventions for depressive symptoms is reviewed in the present work, with the aim of identifying promising interventions that could inform future health promotion campaigns or stimulate further research.</p> <p>Methods</p> <p>A literature search for randomised controlled trials investigating self-help interventions for depressive disorders or depressive symptoms was performed using PubMed, PsycINFO and the Cochrane Database of Systematic Reviews. Reference lists and citations of included studies were also checked. Studies were grouped into those involving participants with depressive disorders or a high level of depressive symptoms, or non-clinically depressed participants not selected for depression. A number of exclusion criteria were applied, including trials with small sample sizes and where the intervention was adjunctive to antidepressants or psychotherapy.</p> <p>Results</p> <p>The majority of interventions searched had no relevant evidence to review. Of the 38 interventions reviewed, the ones with the best evidence of efficacy in depressive disorders were S-adenosylmethionine, St John's wort, bibliotherapy, computerised interventions, distraction, relaxation training, exercise, pleasant activities, sleep deprivation, and light therapy. A number of other interventions showed promise but had received less research attention. Research in non-clinical samples indicated immediate beneficial effects on depressed mood for distraction, exercise, humour, music, negative air ionisation, and singing; while potential for helpful longer-term effects was found for autogenic training, light therapy, omega 3 fatty acids, pets, and prayer. Many of the trials were poor quality and may not generalise to self-help without professional guidance.</p> <p>Conclusion</p> <p>A number of self-help interventions have promising evidence for reducing subthreshold depressive symptoms. Other forms of evidence such as expert consensus may be more appropriate for interventions that are not feasible to evaluate in randomised controlled trials. There needs to be evaluation of whether promotion to the public of effective self-help strategies for subthreshold depressive symptoms could delay or prevent onset of depressive illness, reduce functional impairment, and prevent progression to other undesirable outcomes such as harmful use of substances.</p

Association of maternal prenatal copper concentration with gestational duration and preterm birth: a multicountry meta-analysis

Background Copper (Cu), an essential trace mineral regulating multiple actions of inflammation and oxidative stress, has been implicated in risk for preterm birth (PTB). Objectives This study aimed to determine the association of maternal Cu concentration during pregnancy with PTB risk and gestational duration in a large multicohort study including diverse populations. Methods Maternal plasma or serum samples of 10,449 singleton live births were obtained from 18 geographically diverse study cohorts. Maternal Cu concentrations were determined using inductively coupled plasma mass spectrometry. The associations of maternal Cu with PTB and gestational duration were analyzed using logistic and linear regressions for each cohort. The estimates were then combined using meta-analysis. Associations between maternal Cu and acute-phase reactants (APRs) and infection status were analyzed in 1239 samples from the Malawi cohort. Results The maternal prenatal Cu concentration in our study samples followed normal distribution with mean of 1.92 μg/mL and standard deviation of 0.43 μg/mL, and Cu concentrations increased with gestational age up to 20 wk. The random-effect meta-analysis across 18 cohorts revealed that 1 μg/mL increase in maternal Cu concentration was associated with higher risk of PTB with odds ratio of 1.30 (95% confidence interval [CI]: 1.08, 1.57) and shorter gestational duration of 1.64 d (95% CI: 0.56, 2.73). In the Malawi cohort, higher maternal Cu concentration, concentrations of multiple APRs, and infections (malaria and HIV) were correlated and associated with greater risk of PTB and shorter gestational duration. Conclusions Our study supports robust negative association between maternal Cu and gestational duration and positive association with risk for PTB. Cu concentration was strongly correlated with APRs and infection status suggesting its potential role in inflammation, a pathway implicated in the mechanisms of PTB. Therefore, maternal Cu could be used as potential marker of integrated inflammatory pathways during pregnancy and risk for PTB