LARF: Instrumental Variable Estimation of Causal Effects through Local Average Response Functions

LARF is an R package that provides instrumental variable estimation of treatment effects when both the endogenous treatment and its instrument (i.e., the treatment inducement) are binary. The method (Abadie 2003) involves two steps. First, pseudo-weights are constructed from the probability of receiving the treatment inducement. By default LARF estimates the probability by a probit regression. It also provides semiparametric power series estimation of the probability and allows users to employ other external methods to estimate the probability. Second, the pseudo-weights are used to estimate the local average response function conditional on treatment and covariates. LARF provides both least squares and maximum likelihood estimates of the conditional treatment effects

Query Generation based on Generative Adversarial Networks

Many problems in database systems, such as cardinality estimation, database testing and optimizer tuning, require a large query load as data. However, it is often difficult to obtain a large number of real queries from users due to user privacy restrictions or low frequency of database access. Query generation is one of the approaches to solve this problem. Existing query generation methods, such as random generation and template-based generation, do not consider the relationship between the generated queries and existing queries, or even generate semantically incorrect queries. In this paper, we propose a query generation framework based on generative adversarial networks (GAN) to generate query load that is similar to the given query load. In our framework, we use a syntax parser to transform the query into a parse tree and traverse the tree to obtain the sequence of production rules corresponding to the query. The generator of GAN takes a fixed distribution prior as input and outputs the query sequence, and the discriminator takes the real query and the fake query generated by the generator as input and outputs a gradient to guide the generator learning. In addition, we add context-free grammar and semantic rules to the generation process, which ensures that the generated queries are syntactically and semantically correct. We conduct experiments to evaluate our approach on real-world dataset, which show that our approach can generate new query loads with a similar distribution to a given query load, and that the generated queries are syntactically correct with no semantic errors. The generated query loads are used in downstream task, and the results show a significant improvement in the models trained with the expanded query loads using our approach

Establishment of a large animal model for research on transbronchial arterial intervention for lung cancer

PURPOSEWe aimed to evaluate whether bronchial artery can supply a percutaneously inoculated canine transmissible venereal tumor (CTVT) in a lung tumor model.METHODSFresh CTVT tissue blocks were percutaneously inoculated into unilateral or bilateral lungs of six immunosuppressed dogs at the mid zone of the middle or lower lobe. Tumor growth was monitored by computed tomography (CT). Ten weeks after inoculation, pulmonary arterial digital subtraction angiography (DSA), bronchial arterial DSA, transpulmonary arterial contrast-enhanced multislice CT, transbronchial arterial contrast-enhanced multislice CT (BA-MSCT), and transpulmonary arterial lipiodol multislice CT were performed.RESULTSTumor growth was seen in all 10 inoculated sites, with a maximum diameter of 2.734±0.138 cm at 10th week. Bronchial arterial blood supply was evident in 9 nodules on DSA, and was equivocal in one which was later demonstrated on BA-MSCT. No obvious pulmonary arterial blood supply was observed in any of the nodules. Lipiodol deposition was displayed in two of the small distant metastases, which indicated that pulmonary artery was involved in the supply of the metastases.CONCLUSIONOur results demonstrated bronchial arterial blood supply in this new lung cancer model. This model may be used in further research on transbronchial arterial intervention for lung cancer

A compact core-jet structure in the changing-look Seyfert NGC 2617

The nearby face-on spiral galaxy NGC 2617 underwent an unambiguous 'inside-out' multi-wavelength outburst in Spring 2013, and a dramatic Seyfert type change probably between 2010 and 2012, with the emergence of broad optical emission lines. To search for the jet activity associated with this variable accretion activity, we carried out multi-resolution and multi-wavelength radio observations. Using the very long baseline interferometric (VLBI) observations with the European VLBI Network (EVN) at 1.7 and 5.0 GHz, we find that NGC 2617 shows a partially synchrotron self-absorbed compact radio core with a significant core shift, and an optically thin steep-spectrum jet extending towards the north up to about two parsecs in projection. We also observed NGC 2617 with the electronic Multi-Element Remotely Linked Interferometer Network (e-MERLIN) at 1.5 and 5.5 GHz, and revisited the archival data of the Very Large Array (VLA) and the Very Long Baseline Array (VLBA). The radio core had a stable flux density of about 1.4 mJy at 5.0 GHz between 2013 June and 2014 January, in agreement with the expectation of a supermassive black hole in the low accretion rate state. The northern jet component is unlikely to be associated with the 'inside-out' outburst of 2013. Moreover, we report that most optically selected changing-look AGN at z<0.83 are sub-mJy radio sources in the existing VLA surveys at 1.4 GHz, and it is unlikely that they are more active than normal AGN at radio frequencies.Comment: 10 pages, 7 figures, accepted for publication in MNRA