Effective Use of Word Order for Text Categorization with Convolutional Neural Networks

Convolutional neural network (CNN) is a neural network that can make use of the internal structure of data such as the 2D structure of image data. This paper studies CNN on text categorization to exploit the 1D structure (namely, word order) of text data for accurate prediction. Instead of using low-dimensional word vectors as input as is often done, we directly apply CNN to high-dimensional text data, which leads to directly learning embedding of small text regions for use in classification. In addition to a straightforward adaptation of CNN from image to text, a simple but new variation which employs bag-of-word conversion in the convolution layer is proposed. An extension to combine multiple convolution layers is also explored for higher accuracy. The experiments demonstrate the effectiveness of our approach in comparison with state-of-the-art methods

Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training

As deep neural networks are highly expressive, it is important to find solutions with small generalization gap (the difference between the performance on the training data and unseen data). Focusing on the stochastic nature of training, we first present a theoretical analysis in which the bound of generalization gap depends on what we call inconsistency and instability of model outputs, which can be estimated on unlabeled data. Our empirical study based on this analysis shows that instability and inconsistency are strongly predictive of generalization gap in various settings. In particular, our finding indicates that inconsistency is a more reliable indicator of generalization gap than the sharpness of the loss landscape. Furthermore, we show that algorithmic reduction of inconsistency leads to superior performance. The results also provide a theoretical basis for existing methods such as co-distillation and ensemble

Emergence of Increased Resistance and Extensively Drug-Resistant Tuberculosis Despite Treatment Adherence, South Africa

Improved infection control, rapid diagnostic tools, enhanced screening strategies, and pharmacokinetic studies are needed

The impact of antibiotics on growth in children in low and middle income countries: systematic review and meta-analysis of randomised controlled trials

Objectives To determine whether antibiotic treatment leads to improvements in growth in prepubertal children in low and middle income countries, to determine the magnitude of improvements in growth, and to identify moderators of this treatment effect.Design Systematic review and meta-analysis.Data sources Medline, Embase, Scopus, the Cochrane central register of controlled trials, and Web of Science.Study selection Randomised controlled trials conducted in low or middle income countries in which an orally administered antibacterial agent was allocated by randomisation or minimisation and growth was measured as an outcome. Participants aged 1 month to 12 years were included. Control was placebo or non-antimicrobial intervention.Results Data were pooled from 10 randomised controlled trials representing 4316 children, across a variety of antibiotics, indications for treatment, treatment regimens, and countries. in random effects models, antibiotic use increased height by 0.04 cm/month (95% confidence interval 0.00 to 0.07) and weight by 23.8 g/month (95% confidence interval 4.3 to 43.3). After adjusting for age, effects on height were larger in younger populations and effects on weight were larger in African studies compared with other regions.Conclusion Antibiotics have a growth promoting effect in prepubertal children in low and middle income countries. This effect was more pronounced for ponderal than for linear growth. the antibiotic growth promoting effect may be mediated by treatment of clinical or subclinical infections or possibly by modulation of the intestinal microbiota. Better definition of the mechanisms underlying this effect will be important to inform optimal and safe approaches to achieving healthy growth in vulnerable populations.Vanier Canada Graduate ScholarshipMcGill Univ, Dept Epidemiol Biostat & Occupat Hlth, Montreal, PQ, CanadaZvitambo Inst Maternal Child Hlth Res, Harare, ZimbabweQueen Mary Univ London, Blizard Inst, Ctr Paediat, London, EnglandMRC, Clin Trials Unit, London, EnglandJohns Hopkins Bloomberg Sch Publ Hlth, Dept Int Hlth, Baltimore, MD USACornell Univ, Div Nutr Sci, Program Int Nutr, Ithaca, NY 14853 USAWashington Univ, Sch Med, Dept Pediat, St Louis, MO 63110 USAUniv Malawi, Blantyre, MalawiUniv Cambridge, Dept Archaeol & Anthropol, Div Biol Anthropol, Cambridge CB2 1TN, EnglandUniversidade Federal de São Paulo, Escola Paulista Med, São Paulo, BrazilUniv British Columbia, Sch Populat & Publ Hlth, Vancouver, BC V6T 1Z3, CanadaUniversidade Federal de São Paulo, Escola Paulista Med, São Paulo, BrazilWeb of Scienc

Highly specific unnatural base pair systems as a third base pair for PCR amplification

Toward the expansion of the genetic alphabet of DNA, we present highly efficient unnatural base pair systems as an artificial third base pair for PCR. Hydrophobic unnatural base pair systems between 7-(2-thienyl)imidazo[4,5-b]pyridine (Ds) and 2-nitro-4-propynylpyrrole (Px) were fine-tuned for efficient PCR, by assessing the amplification efficiency and fidelity using different polymerases and template sequence contexts and modified Px bases. Then, we found that some modifications of the Px base reduced the misincorporation rate of the unnatural base substrates opposite the natural bases in templates without reducing the Ds–Px pairing selectivity. Under optimized conditions using Deep Vent DNA polymerase, the misincorporation rate was extremely low (0.005%/bp/replication), which is close to that of the natural base mispairings by the polymerase. DNA fragments with different sequence contexts were amplified ∼1010-fold by 40 cycles of PCR, and the selectivity of the Ds–Px pairing was >99.9%/replication, except for 99.77%/replication for unfavorable purine-Ds-purine motifs. Furthermore, >97% of the Ds–Px pair in DNA survived in the 1028-fold amplified products after 100-cycle PCR (10 cycles repeated 10 times). This highly specific Ds–Px pair system provides a framework for new biotechnology