Miracle-dz/UniFAR-FTUs huggingface dataset:
( revised ) Title : Genomic characterisation of an international Pseudomonas aeruginosa reference panel indicates that the two major groups draw upon distinct mobile gene pools

Pseudomonas aeruginosa is an important opportunistic pathogen, especially in the context of infections of cystic fibrosis (CF). In order to facilitate coordinated study of this pathogen, an international reference panel of P. aeruginosa isolates was assembled. Here we report the genome sequencing and analysis of 33 of these isolates and 7 reference genomes to further characterise this panel. Core genome single nucleotide variant phylogeny demonstrated that the panel strains are widely distributed amongst the P. aeruginosa population. Common loss of function mutations reported as adaptive during CF (such as in mucA and mexA) were identified amongst isolates from chronic respiratory infections. From the 40 strains analysed, 37 unique resistomes were predicted, based on the Resistance Gene Identifier method using the Comprehensive Antibiotic Resistance Database. Notably, hierarchical clustering and phylogenetic reconstructions based on the presence/absence of genomic islands (GIs), prophages and other Regions of Genome Plasticity (RGPs) supported the subdivision of P. aeruginosa into two main groups. This is the largest, most diverse analysis of GIs and associated RGPs to date, and the results suggest that, at least at the largest clade grouping level (Group 1 vs Group 2), each group may be drawing upon distinct mobile gene pools.
Global estimations of the inventory and mitigation potential of methane emissions from rice cultivation conducted using the 2006 IPCC guidelines

While there have been many estimates of global CH 4 emissions from rice fields, none of them have been obtained using the IPCC guidelines. In this study, we used the Tier 1 method described in the 2006 IPCC guidelines to estimate the global CH 4 emissions from rice fields. To accomplish this, we used countryspecific statistical data regarding rice harvest areas and expert estimates of relevant agricultural activities. The estimated global emission for 2000 was 25.4 Tg/yr, which is at the lower end of earlier estimates and close to the total emission summarized by individual national communications. Monte Carlo simulation revealed a 95% uncertainty range of 14.8 to 41.5 Tg/yr. We estimated that, if all of the continuously flooded rice fields were drained at least once during the growing season, the CH 4 emissions would be reduced by 4.1 Tg/yr. Furthermore, we estimated that applying rice straw off-season wherever and whenever possible would result in a further reduction in emissions of 4.1 Tg/yr globally. Finally, if both of these mitigation options were adopted, the global CH 4 emission from rice paddies could be reduced by 7.6 Tg/yr.
The effect of maternal and child health and family planning services on mortality: is prevention enough?

OBJECTIVE--To examine the impact on mortality of a child survival strategy, mostly based on preventive interventions. DESIGN--Cross sectional comparison of cause specific mortality in two communities differing in the type, coverage, and quality of maternal and child health and family planning services. In the intervention area the services were mainly preventive, community based, and home delivered. SUBJECTS--Neonates, infants, children, and mothers in two contiguous areas of rural Bangladesh. INTERVENTIONS--In the intervention area community health workers provided advice on contraception and on feeding and weaning babies; distributed oral rehydration solution, vitamin A tablets for children under 5, and ferrous fumarate and folic acid during pregnancy; immunised children; trained birth attendants in safe delivery and when to refer; treated minor ailments; and referred seriously ill people and malnourished children to a central clinic. MAIN OUTCOME MEASURES--Overall and age and cause specific death rates, obtained by a multiple step "verbal autopsy" process. RESULTS--During the two years covered by the study overall mortality was 17% lower among neonates, 9% lower among infants aged 1-5 months, 30% lower among children aged 6-35 months, and 19% lower among women living in the study area than in those living in the control area. These differences were mainly due to fewer deaths from neonatal tetanus, measles, persistent diarrhoea with severe malnutrition among children, and fewer abortions among women. CONCLUSIONS--The programme was effective in preventing some deaths. In addition to preventive components such as tetanus and measles immunisation, health and nutrition education, and family planning, curative services are needed to reduce mortality further.
SIMULATION OF VAPOR-LIQUID EQUILIBRIUM IN MIXED SOLVENT ELECTROLYTE SOLUTIONS

We review Gibbs ensemble Monte Carlo sjmulations of vapor-liquid equilibrium in pure water, water/NaCl, water/methanol and water/methanol/Na~l mixtures. The intermolecular potentials used were taken directly from the published literature. The Ewald sum method with tinfoil boundary conditions was used to take into account long range forces. INTRODUCTION Recently, we performed a series of Gibbs ensemble Monte Carlo (GEMC) simulations (Panagiotopoulos 1987a, 1987b, 1991) of vapor-liquid equilibrium in pure water (de Pablo et al., 1991; Strauch and Cummings, 1992a) and in a prototypical water/alcohol/salt system, water/methanol/NaCl (Strauch and Cummings, 1992b) which are reviewd in this paper. These simulations are part of a broader project to develop a fund~ent~y based model for mixed solvent electrolytes (mixtures composed of two non-electrolyte species an an electrolyte) based on statistical mechanics that would be applicable over a wide range of electrolyte concentrations and which consequently requires accurate ion-ion, ion-solvent and solvent-solvent interactions. For pure water, we found that the phase envelope of pure water was predicted reasonably well by the standard SPC model (Berendsen et al., 1981). 037~381~~$06,~ Q1993 Elsevier Science Publishers B.V. AD righta reserved
0 51 10 46 v 1 1 3 N ov 2 00 5 Quantum Stratonovich Stochastic Calculus and the Quantum Wong-Zakai Theorem

We introduce the Stratonovich version of quantum stochastic calculus including integrals with respect to emission (creation), absorption (annihilation) and scattering (conservation) processes. The calculus allows us to consider the limit of regular open dynamical systems as a quantum Wong-Zakai approximation theorem. We introduce distinct definitions of Itô Dyson and Stratonovich Dyson time-ordered exponentials and give the multi-dimensional quantum noise conversion formulae between them. The convergence issues in the approximation theorem are illustrated using diagrammatic conventions.
Cognitive Mechanisms underlying Visual Perspective Taking in typical and ASC children

This is the peer reviewed version of the following article: Pearson, A. , Marsh, L. , Ropar, D. and Hamilton, A. (2016), Cognitive Mechanisms underlying visual perspective taking in typical and ASC children. Autism Res, 9: 121–130, which has been published in final form at doi: 10.1002/aur.1501. This article may be used for noncommercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
SEASONAL RADON VARIATIONS IN UTAH TESTING RESULTS: SHORT TERM TEST RESULTS WITHIN 10% OF THE EPA THRESHOLD (4.0 PCI/L) SHOULD BE REPEATED IN A DIFFERENT SEASON

Investigators in the Utah Indoor Radon Program conducted a study to observe the potential variations in seasonal radon measurement tests. Data from Utah’s Newborn Test Kit database was utilized. Initial contact letters and email reminders were sent to participating home owners, who were mailed activated charcoal detectors on 28 January 2008. The data suggests that homes where radon test results fall within 10% the U.S. Environmental Protection Agency (EPA) action level of 148 Bq m -3 (4.0 pCi/L) should be
Effects of lidar pulse density and sample size on a model-assisted approach to estimate forest inventory variables

Using lidar in an area-based model-assisted approach to forest inventory has the potential to increase estimation precision for some forest inventory variables. This study documents the bias and precision of a model-assisted (regression estimation) approach to forest inventory with lidar-derived auxiliary variables relative to lidar pulse density and the number of sample plots. For managed forests on the Lewis portion of the Lewis-McChord Joint Base (35025 ha, 23290 forested) in western Washington state, we evaluated a regression estimator for combinations of pulse density (.05–3 pulses/m2) and sample size (15–105 plots) to estimate five forest yield variables: basal area, volume, biomass, number of stems, and Lorey's height. The results indicate that there is almost no loss in precision in using as few as . 05 pulses/m2 relative to 3 pulses/m2. We demonstrate that estimation precision declined quickly for reduced sample sizes (as expected from sampling theory); but of more importance we demonstrate that sample size has a dramatic effect on the validity of inferences. Our investigations indicate that for our test dataset that central limit theorem based confidence intervals were too small on average for sample sizes smaller than 55. The results from this study can aid in identifying design components for forest inventory with lidar which satisfy users’ objectives.
Inversion of Upper Ocean Temperature Time Series for Entrainment, Advection, and Diffusivity

Abstract An inversion technique for estimating the terms of the oceanic near-surface heat transport is extended to include the vertical heat flux at the bottom of the surface mixed layer. The mixed-layer heat balance equation uses a conventional parameterization of the vertical heat flux via entrainment into the mixed layer of interior fluid during the mixed layer deepening. A heat conservation equation defined here for the sea temperature anomalies, deviations from the annual cycle, is driven by stochastic atmospheric forcing, thereby becoming essentially a stochastic partial differential equation. This equation is reduced to the regression estimator aimed on inversion of the sea temperature time series for the unknowns: vertical entrainment velocity, horizontal velocity and diffusivity, feedback factor, and atmospheric forcing parameter. The inversion scheme also involves the velocity divergence norm. The regression estimator is applied to the time series of vertical profiles of temperature anomalies co.
Eastern Tropical Pacific hurricane variability and landfalls on Mexican coasts

We investigated composites of sea surface temperature (SST), wind shear (WS) at 850−200 hPa, and zonal winds at 925 hPa during July−September of the hurricane season to determine interannual and decadal differences between weak (categories 1 to 3, HUR1−3) and intense (categories 4 to 5, HUR4−5) hurricanes in the main development region (MDR) of the Eastern Tropical Pacific (EPAC) during 1970−2010. SST in the MDR showed a statistically significant increase of 0.57°C over the whole period, but the frequency of HUR4−5 did not show a significant trend, while the frequency of HUR1−5 significantly decreased (−0.95% yr−1). This trend is linked to active and in active hurricane periods which are negatively associated with the Atlantic Multidecadal Oscillation and positively with the Pacific Decadal Oscillation (PDO). The frequency of HUR4−5 also shows a significant positive relationship with PDO and El Niño−Southern Oscillation events. This is likely due to a larger extension of the Western Hemisphere Warm Pool in the EPAC and lower WS values in the MDR during El Niño than during La Niña. Although the mean SST anomalies and WS conditions in the EPAC appear to be more favorable for cyclogenesis and intensification during El Niño, the frequency, duration, and accumulated cyclone energy of HUR4−5 are similar during El Niño and Neutral years, as are the average landfalls of category 1 to 5 hurricanes (HUR1−5). It is hypothesized that a larger size of the North Atlantic warm pool and a weaker Caribbean Low-Level Jet during Neutral years add an extra dynamical mechanism that favors cyclogenesis in the EPAC, which may not be present (or is weaker) during El Niño.
Evaluation of Secondary Dental Health Care at the Dental Specialties Center , Pelotas , Rio Grande do Sul , Brazil , 2012-2013

Objective: to evaluate the structure, care process and results of the endodontics, periodontics and surgery services at the Pelotas/RS Dental Specialties Centre (DSC). Methods: this was a cross-sectional study; an evaluation was made of the number of dental professionals and teams at the DSC, forms of referral and appointment making and no-show management; demand for services and referral to the appointment control centre between July 2012 and June 2013 were characterized. Results: 940 service users received care and 1,502 procedures were performed; 76.0% of procedures were concluded; average waiting time was 2 months; 13% of service users referred did not complete treatment and 849 were on the waiting list. Conclusion: DSC did not meet Ministry of Health required productivity parameters and needs to increase production; the appointment control centre needs protocols to guide care prioritization; moreover, the municipality needs additional DSCs.
Long-Tailed Learning as Multi-Objective Optimization

Real-world data is extremely imbalanced and presents a long-tailed distribution, resulting in models biased towards classes with sufficient samples and performing poorly on rare classes. Recent methods propose to rebalance classes but they undertake the seesaw dilemma (what is increasing performance on tail classes may decrease that of head classes, and vice versa). In this paper, we argue that the seesaw dilemma is derived from the gradient imbalance of different classes, in which gradients of inappropriate classes are set to important for updating, thus prone to overcompensation or undercompensation on tail classes. To achieve ideal compensation, we formulate long-tailed recognition as a multi-objective optimization problem, which fairly respects the contributions of head and tail classes simultaneously. For efficiency, we propose a Gradient-Balancing Grouping (GBG) strategy to gather the classes with similar gradient directions, thus approximately making every update under a Pareto descent direction. Our GBG method drives classes with similar gradient directions to form a more representative gradient and provides ideal compensation to the tail classes. Moreover, we conduct extensive experiments on commonly used benchmarks in long-tailed learning and demonstrate the superiority of our method over existing SOTA methods. Our code is released at https://github.com/WickyLee1998/GBG_v1.
Spatial Joint Species N-Mixture Models for Multi-Source Observational Data with Application to Wild Deer Population Abundance

Accurate predictions of the populations and spatial distributions of wild animal species is critical from a species management and conservation perspective. Culling is a measure taken for various reasons, including when overpopulation of a species is observed or suspected. Thus accurate estimates of population numbers are essential for specifying, monitoring, and evaluating the impact of such programmes. Population data for wild animals is generally collated from various sources and at differing spatial resolutions. Citizen science projects typically provide point referenced data, whereas site surveys, hunter reports, and official government data may be aggregated and released at a small area or regional level. Jointly modelling these data resources involves overcoming challenges of spatial misalignment. In this article, we develop an N mixture modelling methodology for joint modelling of species populations in the presence of spatially misaligned data, motivated by the three main species of wild deer in the Republic of Ireland; fallow, red and sika. Previous studies of deer populations investigated the distribution and abundance on a species by species basis, failing to account for possible correlation between individual species and the impact of ecological covariates on their distributions.
Quantifying Hierarchical Selection

At what level does selective pressure effectively act? When considering the reproductive dynamics of interacting and mutating agents, it has long been debated whether selection is better understood by focusing on the individual or if hierarchical selection emerges as a consequence of joint adaptation. Despite longstanding efforts in theoretical ecology there is still no consensus on this fundamental issue, most likely due to the difficulty in obtaining adequate data spanning sufficient number of generations and the lack of adequate tools to quantify the effect of hierarchical selection. Here we capitalise on recent advances in information-theoretic data analysis to advance this state of affairs by investigating the emergence of high-order structures -- such as groups of species -- in the collective dynamics of the Tangled Nature model of evolutionary ecology. Our results show that evolutionary dynamics can lead to clusters of species that act as a selective group, that acquire information-theoretic agency. Overall, our findings provide quantitative evidence supporting the relevance of high-order structures in evolutionary ecology, which can emerge even from relatively simple processes of adaptation and selection.
Decision-Making for Autonomous Vehicles with Interaction-Aware Behavioral Prediction and Social-Attention Neural Network

Autonomous vehicles need to accomplish their tasks while interacting with human drivers in traffic. It is thus crucial to equip autonomous vehicles with artificial reasoning to better comprehend the intentions of the surrounding traffic, thereby facilitating the accomplishments of the tasks. In this work, we propose a behavioral model that encodes drivers' interacting intentions into latent social-psychological parameters. Leveraging a Bayesian filter, we develop a receding-horizon optimization-based controller for autonomous vehicle decision-making which accounts for the uncertainties in the interacting drivers' intentions. For online deployment, we design a neural network architecture based on the attention mechanism which imitates the behavioral model with online estimated parameter priors. We also propose a decision tree search algorithm to solve the decision-making problem online. The proposed behavioral model is then evaluated in terms of its capabilities for real-world trajectory prediction. We further conduct extensive evaluations of the proposed decision-making module, in forced highway merging scenarios, using both simulated environments and real-world traffic datasets. The results demonstrate that our algorithms can complete the forced merging tasks in various traffic conditions while ensuring driving safety.
Assessment of hydrological and seasonal controls over the nitrate flushing from a forested watershed using a data mining technique

Papers published in Hydrology and Earth System Sciences Discussions are under open-access review for the journal Hydrology and Earth System Sciences Abstract Introduction Conclusions References Tables Figures Back Close Full Screen / Esc Printer-friendly Version Interactive Discussion EGU Abstract A data mining, regression tree algorithm M5 was used to review the understanding of mutual hydrological and seasonal settings which control the streamwater nitrate flushing during hydrological events within a forested watershed in the southwestern part of Slovenia, characterized by distinctive flushing, almost torrential hydrological regime. 5 The basis for the research presented an extensive dataset of continuous, high frequency measurements of seasonal meteorological conditions, watershed hydrological responses and streamwater nitrate concentrations. The dataset contained 16 recorded hydrographs occurring in different seasonal and hydrological conditions. Based on pre-defined regression tree pruning criteria, a comprehensible regression tree model was 10 obtained in the sense of the domain knowledge, which was able to adequately describe most of the streamwater nitrate concentration variations (RMSE=1.02 mg/l-N; r=0.91). The attributes which were found to be the most descriptive in the sense of streamwater nitrate concentrations were the antecedent precipitation index (API) and air temperatures in the preceding periods. The model was most successful in describ-15 ing streamwater concentrations in the range 1–4 mg/l-N, covering large proportion of the dataset. The model performance was poorer during the periods of high streamwa-ter nitrate concentration oscillations (up to 7 mg/l-N during the summer hydrographs and 14 mg/l-N during the extreme November hydrograph) related to highly variable hydrological conditions, which would require a less robust regression tree model.
The ex-factor: Characteristics of online and offline post-relationship contact and tracking among Canadian emerging adults

The breakup of an intimate relationship is a highly distressing event among emerging adults (Cutler, Glaeser, Norberg, 2001) and can often be accompanied by difficulty adjusting to the loss and “letting go” (Mearns, 1991). Research on stalking and cyberstalking behaviours address criminal activities that incite fear in a target (e.g., Spitzberg & Cupach, 2007). Little is known about more general post-relationship contact and tracking (PRCT), that is, efforts to maintain or re-establish contact with an ex-partner or to track their whereabouts, new partnerships or activities. To understand both the use and experience of PRCT, we examined reports from 271 Canadian emerging adults (aged 18–25) regarding their most recent breakup within the prior year. Results indicated that online and offline forms of post-relationship contact and tracking were common, characterizing 87.8% of all recent breakups, and were typically used in conjunction. In fact, online forms rarely occurred in isolation. Attempts to keep in contact were most commonly reported by users and targets of behaviours, whereas extreme and threatening behaviours that might comprise stalking or cyberstalking were rare. No gender differences were found in the use of PRCT behaviours, although women reported experiencing more offline forms.
Field growth and rubber yield of Hevea brasiliensis (Muëll.-Arg.) from budded versus in vitro micropropagated plants from clone IRCA 18

A hevea microcutting procedure has been defined for the propagation of selected clones, involving an initial rejuvenation phase. Experimental production based on clone IRCA 18 was carried out in 1992 and culminated in the setting up of a field trial in 1993 to compare the agronomic performance of in vitro plantlets with that of conventional budding. The results were analysed from the acclimatization phase, where problems in the resumption of apex growth have resulted in very high mortality. After growing for eight years in the field, the in vitro plantlets had a significant 6% advantage in terms of trunk circumference 1 m from the ground. A relation was sought between initial in vitro plantlet development at the time of planting, and their subsequent growth in the field. One of the challenges of micropropagation was to overcome the handicap of cuttings, with the inadequate anchoring ability of neoformed root systems. In the trial described here, none of the trees was lost through uprooting; moreover, we showed in a parallel study that in vitro plantlets obtained by micropropagation had a similar root development process to that of plants obtained from seed, notably with a vigorous taproot structure. In the two first tapping years, the in vitro plantlets produced 20% higher yields (in kg of dry rubber per tree). These results will be commented on in relation to the initial hypotheses put forward regarding the merits of in vitro plantlets for rubber cultivation, and to application prospects.