Generalizing Trimming Bounds for Endogenously Missing Outcome Data Using Random Forests

In many experimental or quasi-experimental studies, outcomes of interest are only observed for subjects who select (or are selected) to engage in the activity generating the outcome. Outcome data is thus endogenously missing for units who do not engage, in which case random or conditionally random treatment assignment prior to such choices is insufficient to point identify treatment effects. Non-parametric partial identification bounds are a way to address endogenous missingness without having to make disputable parametric assumptions. Basic bounding approaches often yield bounds that are very wide and therefore minimally informative. We present methods for narrowing non-parametric bounds on treatment effects by adjusting for potentially large numbers of covariates, working with generalized random forests. Our approach allows for agnosticism about the data-generating process and honest inference. We use a simulation study and two replication exercises to demonstrate the benefits of our approach

Task-specific Objectives of Pre-trained Language Models for Dialogue Adaptation

Pre-trained Language Models (PrLMs) have been widely used as backbones in lots of Natural Language Processing (NLP) tasks. The common process of utilizing PrLMs is first pre-training on large-scale general corpora with task-independent LM training objectives, then fine-tuning on task datasets with task-specific training objectives. Pre-training in a task-independent way enables the models to learn language representations, which is universal to some extent, but fails to capture crucial task-specific features in the meantime. This will lead to an incompatibility between pre-training and fine-tuning. To address this issue, we introduce task-specific pre-training on in-domain task-related corpora with task-specific objectives. This procedure is placed between the original two stages to enhance the model understanding capacity of specific tasks. In this work, we focus on Dialogue-related Natural Language Processing (DrNLP) tasks and design a Dialogue-Adaptive Pre-training Objective (DAPO) based on some important qualities for assessing dialogues which are usually ignored by general LM pre-training objectives. PrLMs with DAPO on a large in-domain dialogue corpus are then fine-tuned for downstream DrNLP tasks. Experimental results show that models with DAPO surpass those with general LM pre-training objectives and other strong baselines on downstream DrNLP tasks

Exploring the experience of novelty when viewing creative adverts: An ERP study.

The electrophysiological correlates of experiencing novelty in creative advertising were studied in 28 healthy subjects using event-related potentials. Participants viewed images that were difficult to interpret until a description was presented providing either a creative description (CD) featuring an unexpected description of the image based on the original advertisement, or a normal description (ND), which was a literal description of the image (and served as a baseline condition). Participants evaluated the level of creativity of the description. The results showed that the N2 amplitude was higher for CDs than for NDs across middle and right scalp regions between 240 and 270 ms, most likely reflecting conflict detection. Moreover, CDs demonstrated greater N400 than NDs in a time window between 380 and 500 ms, it is argued that this reflects semantic integration. The present study investigates the electrophysiological correlates of experiencing novelty in advertising with ecologically valid stimuli. This substantially extends the findings of earlier laboratory studies with more artificial stimuli.N/

A Lactate Fermentation Mutant of Toxoplasma Stimulates Protective Immunity Against Acute and Chronic Toxoplasmosis

Toxoplasma gondii is an important zoonotic pathogen infecting one-third of the world’s population and numerous animals, causing significant healthcare burden and socioeconomic problems. Vaccination is an efficient way to reduce global sero-prevalence, however, ideal vaccines are not yet available. We recently discovered that the Toxoplasma mutant lacking both lactate dehydrogenases LDH1 and LDH2 (Δldh) grew well in vitro but was unable to propagate in mice, making it a good live vaccine candidate. Here, we tested the protection efficacy of ME49 Δldh using a mouse model. Vaccinated mice were efficiently protected from the lethal challenge of a variety of wild-type strains, including type 1 strain RH, type 2 strain ME49, type 3 strain VEG, and a field isolate of Chinese 1. The protection efficacies of a single vaccination were nearly 100% for most cases and it worked well against the challenges of both tachyzoites and tissue cysts. Re-challenging parasites were unable to propagate in vaccinated mice, nor did they make tissue cysts. High levels of Toxoplasma-specific IgG were produced 30 days after immunization and stayed high during the whole tests (at least 125 days). However, passive immunization of naïve mice with sera from vaccinated mice did reduce parasite propagation, but the overall protection against parasite infections was rather limited. On the other hand, Δldh immunization evoked elevated levels of Th1 cytokines like INF-γ and IL-12, at early time points. In addition, splenocytes extracted from immunized mice were able to induce quick and robust INF-γ and other pro-inflammatory cytokine production upon T. gondii antigen stimulation. Together these results suggest that cellular immune responses are the main contributors to the protective immunity elicited by Δldh vaccination, and humoral immunity also contributes partially. We also generated uracil auxotrophic mutants in ME49 and compared their immune protection efficiencies to the Δldh mutants. The results showed that these two types of mutants have similar properties as live vaccine candidates. Taken together, these results suggest that mutants lacking LDH were severely attenuated in virulence but were able to induce strong anti-toxoplasma immune responses, therefore are good candidates for live vaccines

Robust median reversion strategy for on-line portfolio selection

Ministry of Education, Singapore under its Academic Research Funding Tier

Analysis of the Generating and Influencing Factors of Vertical Cracking in Abutments during Construction

In order to analyze the causes of cracking in abutments subject to concrete shrinkage and temperature variation during the construction process and to determine factors affecting the mechanical properties of the abutment, nonlinear calculations capturing abutment behavior are conducted with Midas/FEA software. Using these calculations, the cracking mechanism is identified, and the influence of the evaluated factors is analyzed. It is concluded that the deformation between the pile cap and abutment backwall as constrained by a pile foundation when subjected to concrete shrinkage and temperature changes is the basic cause of abutment cracks during construction; these cracks form over the piles and develop upward. For a given reinforcement ratio, the distribution of horizontal crack-control steel using small, closely spaced bars is more beneficial. When pile-bearing capacity meets the standard, the width of the generated cracks tends to decrease with the decrease in the diameter of the piles. The existence of a postcast strip in the abutment backwall also contributes to the decrease in the depth of the crack. Finally, the impact of age difference between the pile cap concrete and abutment backwall concrete on cracking is inconsequential

Grand Canonical Adaptive Resolution Simulation for Molecules with Electrons: A Theoretical Framework based on Physical Consistency

A theoretical scheme for the treatment of an open molecular system with electrons and nuclei is proposed. The idea is based on the Grand Canonical description of a quantum region embedded in a classical reservoir of molecules. Electronic properties of the quantum region are calculated at constant electronic chemical potential equal to that of the corresponding (large) bulk system treated at full quantum level. Instead, the exchange of molecules between the quantum region and the classical environment occurs at the chemical potential of the macroscopic thermodynamic conditions. T he Grand Canonical Adaptive Resolution Scheme is proposed for the treatment of the classical environment; such an approach can treat the exchange of molecules according to first principles of statistical mechanics and thermodynamic. The overall scheme is build on the basis of physical consistency, with the corresponding definition of numerical criteria of control of the approximations implied by the coupling. Given the wide range of expertise required, this work has the intention of providing guiding principles for the construction of a well founded computational protocol for actual multiscale simulations from the electronic to the mesoscopic scale.Comment: Computer Physics Communications (2017), in pres