Toward Interactive Dictation

Voice dictation is an increasingly important text input modality. Existing systems that allow both dictation and editing-by-voice restrict their command language to flat templates invoked by trigger words. In this work, we study the feasibility of allowing users to interrupt their dictation with spoken editing commands in open-ended natural language. We introduce a new task and dataset, TERTiUS, to experiment with such systems. To support this flexibility in real-time, a system must incrementally segment and classify spans of speech as either dictation or command, and interpret the spans that are commands. We experiment with using large pre-trained language models to predict the edited text, or alternatively, to predict a small text-editing program. Experiments show a natural trade-off between model accuracy and latency: a smaller model achieves 30% end-state accuracy with 1.3 seconds of latency, while a larger model achieves 55% end-state accuracy with 7 seconds of latency.Comment: 17 pages, 5 tables, 4 figures; AC

Hybridization of Local Exciton and Charge-Transfer States Reduces Non-Radiative Voltage Losses in Organic Solar Cells

A number of recent studies have shown that the non-radiative voltage losses in organic solar cells can be suppressed in systems with low energetic offsets between donor and acceptor molecular states, but the physical reasons underpinning this remain unclear. Here, we present a systematic study of 18 different donor:acceptor blends to determine the effect that energetic offset has on both radiative and non-radiative recombination of the charge transfer (CT) state. We find that for certain blends, low offsets result in hybridization between charge-transfer and lowest donor or acceptor exciton states, which leads to a strong suppression in the non-radiative voltage loss to values as low as 0.23V associated with an increase in the luminescence of the CT state. Further, we extend a two-state CT-state recombination model to include the interaction between CT and first excited states, which allows us to explain the low non-radiative voltage losses as an increase in the effective CT to ground state oscillator strength due to the intensity borrowing mechanism. We show that low non‐radiative voltage losses can be achieved in material combinations with a strong electronic coupling between CT and first excited states, and where the lower band gap material has a high oscillator strength for transitions from the excited state to the ground state. Finally, from our model we propose that achieving very low non-radiative voltage losses may come at a cost of higher overall recombination rates, which may help to explain the generally lower FF and EQE of highly hybridized systems

An alkylated indacenodithieno[3,2-b]thiophene-based nonfullerene acceptor with high crystallinity exhibiting single junction solar cell efficiencies greater than 13% with low voltage losses

A new synthetic route, to prepare an alkylated indacenodithieno[3,2-b]thiophene-based nonfullerene acceptor (C8-ITIC), is reported. Compared to the reported ITIC with phenylalkyl side chains, the new acceptor C8-ITIC exhibits a reduction in the optical band gap, higher absorptivity, and an increased propensity to crystallize. Accordingly, blends with the donor polymer PBDB-T exhibit a power conversion efficiency (PCE) up to 12.4%. Further improvements in efficiency are found upon backbone fluorination of the donor polymer to afford the novel material PFBDB-T. The resulting blend with C8-ITIC shows an impressive PCE up to 13.2% as a result of the higher open-circuit voltage. Electroluminescence studies demonstrate that backbone fluorination reduces the energy loss of the blends, with PFBDB-T/C8-ITIC-based cells exhibiting a small energy loss of 0.6 eV combined with a high JSCof 19.6 mA cm-2

Accreting Protoplanets in the LkCa 15 Transition Disk

Exoplanet detections have revolutionized astronomy, offering new insights into solar system architecture and planet demographics. While nearly 1900 exoplanets have now been discovered and confirmed, none are still in the process of formation. Transition discs, protoplanetary disks with inner clearings best explained by the influence of accreting planets, are natural laboratories for the study of planet formation. Some transition discs show evidence for the presence of young planets in the form of disc asymmetries or infrared sources detected within their clearings, as in the case of LkCa 15. Attempts to observe directly signatures of accretion onto protoplanets have hitherto proven unsuccessful. Here we report adaptive optics observations of LkCa 15 that probe within the disc clearing. With accurate source positions over multiple epochs spanning 2009 - 2015, we infer the presence of multiple companions on Keplerian orbits. We directly detect H{\alpha} emission from the innermost companion, LkCa 15 b, evincing hot (~10,000 K) gas falling deep into the potential well of an accreting protoplanet.Comment: 35 pages, 3 figures, 1 table, 9 extended data item

Socioeconomic differentials in the immediate mortality effects of the national Irish smoking ban

This article has been made available through the Brunel Open Access Publishing Fund.Background: Consistent evidence has demonstrated that smoking ban policies save lives, but impacts on health inequalities are uncertain as few studies have assessed post-ban effects by socioeconomic status (SES) and findings have been inconsistent. The aim of this study was to assess the effects of the national Irish smoking ban on ischemic heart disease (IHD), stroke, and chronic obstructive pulmonary disease (COPD) mortality by discrete and composite SES indicators to determine impacts on inequalities. Methods: Census data were used to assign frequencies of structural and material SES indicators to 34 local authorities across Ireland with a 2000–2010 study period. Discrete indicators were jointly analysed through principal component analysis to generate a composite index, with sensitivity analyses conducted by varying the included indicators. Poisson regression with interrupted time-series analysis was conducted to examine monthly age and gender-standardised mortality rates in the Irish population, ages ≥35 years, stratified by tertiles of SES indicators. All models were adjusted for time trend, season, influenza, and smoking prevalence. Results: Post-ban mortality reductions by structural SES indicators were concentrated in the most deprived tertile for all causes of death, while reductions by material SES indicators were more equitable across SES tertiles. The composite indices mirrored the results of the discrete indicators, demonstrating that post-ban mortality decreases were either greater or similar in the most deprived when compared to the least deprived for all causes of death. Conclusions: Overall findings indicated that the national Irish smoking ban reduced inequalities in smoking-related mortality. Due to the higher rates of smoking-related mortality in the most deprived group, even equitable reductions across SES tertiles resulted in decreases in inequalities. The choice of SES indicator was influential in the measurement of effects, underscoring that a differentiated analytical approach aided in understanding the complexities in which structural and material factors influence mortality

Dynamic input demand functions and resource adjustment for US agriculture: state evidence

The paper presents an econometric model of dynamic agricultural input demand functions that include research based technical change and autoregressive disturbances and fits the model to annual data for a set of state aggregates pooled over 1950–1982. The methodological approach is one of developing a theoretical foundation for a dynamic input demand system and accepting state aggreage behavior as approximated by nonlinear adjustment costs and long-term profit maximization. Although other studies have largely ignored autocorrelation in dynamic input demand systems, the results show shorter adjustment lags with autocorrelation than without. Dynamic input demand own-price elasticities for the six input groups are inelastic, and the demand functions possess significant cross-price and research effects

Gene Function Classification Using Bayesian Models with Hierarchy-Based Priors

We investigate the application of hierarchical classification schemes to the annotation of gene function based on several characteristics of protein sequences including phylogenic descriptors, sequence based attributes, and predicted secondary structure. We discuss three Bayesian models and compare their performance in terms of predictive accuracy. These models are the ordinary multinomial logit (MNL) model, a hierarchical model based on a set of nested MNL models, and a MNL model with a prior that introduces correlations between the parameters for classes that are nearby in the hierarchy. We also provide a new scheme for combining different sources of information. We use these models to predict the functional class of Open Reading Frames (ORFs) from the E. coli genome. The results from all three models show substantial improvement over previous methods, which were based on the C5 algorithm. The MNL model using a prior based on the hierarchy outperforms both the non-hierarchical MNL model and the nested MNL model. In contrast to previous attempts at combining these sources of information, our approach results in a higher accuracy rate when compared to models that use each data source alone. Together, these results show that gene function can be predicted with higher accuracy than previously achieved, using Bayesian models that incorporate suitable prior information