Unsupervised Controllable Text Formalization

We propose a novel framework for controllable natural language transformation. Realizing that the requirement of parallel corpus is practically unsustainable for controllable generation tasks, an unsupervised training scheme is introduced. The crux of the framework is a deep neural encoder-decoder that is reinforced with text-transformation knowledge through auxiliary modules (called scorers). The scorers, based on off-the-shelf language processing tools, decide the learning scheme of the encoder-decoder based on its actions. We apply this framework for the text-transformation task of formalizing an input text by improving its readability grade; the degree of required formalization can be controlled by the user at run-time. Experiments on public datasets demonstrate the efficacy of our model towards: (a) transforming a given text to a more formal style, and (b) introducing appropriate amount of formalness in the output text pertaining to the input control. Our code and datasets are released for academic use.Comment: AAA

On the derivation of the renewal equation from an age-dependent branching process: an epidemic modelling perspective

Renewal processes are a popular approach used in modelling infectious disease outbreaks. In a renewal process, previous infections give rise to future infections. However, while this formulation seems sensible, its application to infectious disease can be difficult to justify from first principles. It has been shown from the seminal work of Bellman and Harris that the renewal equation arises as the expectation of an age-dependent branching process. In this paper we provide a detailed derivation of the original Bellman Harris process. We introduce generalisations, that allow for time-varying reproduction numbers and the accounting of exogenous events, such as importations. We show how inference on the renewal equation is easy to accomplish within a Bayesian hierarchical framework. Using off the shelf MCMC packages, we fit to South Korea COVID-19 case data to estimate reproduction numbers and importations. Our derivation provides the mathematical fundamentals and assumptions underpinning the use of the renewal equation for modelling outbreaks

Deciphering the Catalytic Machinery in 30S Ribosome Assembly GTPase YqeH

YqeH, a circularly permuted GTPase (cpGTPase), which is conserved across bacteria and eukaryotes including humans is important for the maturation of small (30S) ribosomal subunit in Bacillus subtilis. Recently, we have shown that it binds 30S in a GTP/GDP dependent fashion. However, the catalytic machinery employed to hydrolyze GTP is not recognized for any of the cpGTPases, including YqeH. This is because they possess a hydrophobic substitution in place of a catalytic glutamine (present in Ras-like GTPases). Such GTPases were categorized as HAS-GTPases and were proposed to follow a catalytic mechanism, different from the Ras-like proteins.MnmE, another HAS-GTPase, but not circularly permuted, utilizes a potassium ion and water mediated interactions to drive GTP hydrolysis. Though the G-domain of MnmE and YqeH share only approximately 25% sequence identity, the conservation of characteristic sequence motifs between them prompted us to probe GTP hydrolysis machinery in YqeH, by employing homology modeling in conjunction with biochemical experiments. Here, we show that YqeH too, uses a potassium ion to drive GTP hydrolysis and stabilize the transition state. However, unlike MnmE, it does not dimerize in the transition state, suggesting alternative ways to stabilize switches I and II. Furthermore, we identify a potential catalytic residue in Asp-57, whose recognition, in the absence of structural information, was non-trivial due to the circular permutation in YqeH. Interestingly, when compared with MnmE, helix alpha2 that presents Asp-57 is relocated towards the N-terminus in YqeH. An analysis of the YqeH homology model, suggests that despite such relocation, Asp-57 may facilitate water mediated catalysis, similarly as the catalytic Glu-282 of MnmE. Indeed, an abolished catalysis by D57I mutant supports this inference.An uncommon means to achieve GTP hydrolysis utilizing a K(+) ion has so far been demonstrated only for MnmE. Here, we show that YqeH also utilizes a similar mechanism. While the catalytic machinery is similar in both, mechanistic differences may arise based on the way they are deployed. It appears that K(+) driven mechanism emerges as an alternative theme to stabilize the transition state and hydrolyze GTP in a subset of GTPases, such as the HAS-GTPases

Tigers of Sundarbans in India: Is the Population a Separate Conservation Unit?

The Sundarbans tiger inhabits a unique mangrove habitat and are morphologically distinct from the recognized tiger subspecies in terms of skull morphometrics and body size. Thus, there is an urgent need to assess their ecological and genetic distinctiveness and determine if Sundarbans tigers should be defined and managed as separate conservation unit. We utilized nine microsatellites and 3 kb from four mitochondrial DNA (mtDNA) genes to estimate genetic variability, population structure, demographic parameters and visualize historic and contemporary connectivity among tiger populations from Sundarbans and mainland India. We also evaluated the traits that determine exchangeability or adaptive differences among tiger populations. Data from both markers suggest that Sundarbans tiger is not a separate tiger subspecies and should be regarded as Bengal tiger (P. t. tigris) subspecies. Maximum likelihood phylogenetic analyses of the mtDNA data revealed reciprocal monophyly. Genetic differentiation was found stronger for mtDNA than nuclear DNA. Microsatellite markers indicated low genetic variation in Sundarbans tigers (He= 0.58) as compared to other mainland populations, such as northern and Peninsular (Hebetween 0.67- 0.70). Molecular data supports migration between mainland and Sundarbans populations until very recent times. We attribute this reduction in gene flow to accelerated fragmentation and habitat alteration in the landscape over the past few centuries. Demographic analyses suggest that Sundarbans tigers have diverged recently from peninsular tiger population within last 2000 years. Sundarbans tigers are the most divergent group of Bengal tigers, and ecologically non-exchangeable with other tiger populations, and thus should be managed as a separate "evolutionarily significant unit" (ESU) following the adaptive evolutionary conservation (AEC) concept.Wildlife Institute of India, Dehra Dun (India)

State-level tracking of COVID-19 in the United States

As of 1st June 2020, the US Centers for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available deathdata within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on therate of transmission of SARS-CoV-2. We estimate thatRtwas only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals

Report 13: Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries

Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread outside of China, Europe is now experiencing large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions including case isolation, the closure of schools and universities, banning of mass gatherings and/or public events, and most recently, widescale social distancing including local and national lockdowns. In this report, we use a semi-mechanistic Bayesian hierarchical model to attempt to infer the impact of these interventions across 11 European countries. Our methods assume that changes in the reproductive number – a measure of transmission - are an immediate response to these interventions being implemented rather than broader gradual changes in behaviour. Our model estimates these changes by calculating backwards from the deaths observed over time to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. One of the key assumptions of the model is that each intervention has the same effect on the reproduction number across countries and over time. This allows us to leverage a greater amount of data across Europe to estimate these effects. It also means that our results are driven strongly by the data from countries with more advanced epidemics, and earlier interventions, such as Italy and Spain. We find that the slowing growth in daily reported deaths in Italy is consistent with a significant impact of interventions implemented several weeks earlier. In Italy, we estimate that the effective reproduction number, Rt, dropped to close to 1 around the time of lockdown (11th March), although with a high level of uncertainty. Overall, we estimate that countries have managed to reduce their reproduction number. Our estimates have wide credible intervals and contain 1 for countries that have implemented all interventions considered in our analysis. This means that the reproduction number may be above or below this value. With current interventions remaining in place to at least the end of March, we estimate that interventions across all 11 countries will have averted 59,000 deaths up to 31 March [95% credible interval 21,000-120,000]. Many more deaths will be averted through ensuring that interventions remain in place until transmission drops to low levels. We estimate that, across all 11 countries between 7 and 43 million individuals have been infected with SARS-CoV-2 up to 28th March, representing between 1.88% and 11.43% of the population. The proportion of the population infected to date – the attack rate - is estimated to be highest in Spain followed by Italy and lowest in Germany and Norway, reflecting the relative stages of the epidemics. Given the lag of 2-3 weeks between when transmission changes occur and when their impact can be observed in trends in mortality, for most of the countries considered here it remains too early to be certain that recent interventions have been effective. If interventions in countries at earlier stages of their epidemic, such as Germany or the UK, are more or less effective than they were in the countries with advanced epidemics, on which our estimates are largely based, or if interventions have improved or worsened over time, then our estimates of the reproduction number and deaths averted would change accordingly. It is therefore critical that the current interventions remain in place and trends in cases and deaths are closely monitored in the coming days and weeks to provide reassurance that transmission of SARS-Cov-2 is slowing