Miracle-dz/UniFAR-FTUs huggingface dataset:
New Crocodyliforms from Southwestern Europe and Definition of a Diverse Clade of European Late Cretaceous Basal Eusuchians

The late Campanian-early Maastrichtian site of Lo Hueco (Cuenca, Spain) has provided a set of well-preserved crocodyliform skull and lower jaw remains, which are described here and assigned to a new basal eusuchian taxon, Lohuecosuchus megadontos gen. et sp. nov. The reevaluation of a complete skull from the synchronous site of Fox-Amphoux (Department of Var, France) allows us to define a second species of this new genus. Phylogenetic analysis places Lohuecosuchus in a clade exclusively composed by European Late Cretaceous taxa. This new clade, defined here as Allodaposuchidae, is recognized as the sister group of Hylaeochampsidae, also comprised of European Cretaceous forms. Allodaposuchidae and Hylaeochampsidae are grouped in a clade identified as the sister group of Crocodylia, the only crocodyliform lineage that reaches our days. Allodaposuchidae shows a vicariant distribution pattern in the European Late Cretaceous archipelago, with several Ibero-Armorican forms more closely related to each other than with to Romanian Allodaposuchus precedens.
Compatibility between Legumes and Rhizobia for the Establishment of a Successful Nitrogen-Fixing Symbiosis

The root nodule symbiosis established between legumes and rhizobia is an exquisite biological interaction responsible for fixing a significant amount of nitrogen in terrestrial ecosystems. The success of this interaction depends on the recognition of the right partner by the plant within the richest microbial ecosystems on Earth, the soil. Recent metagenomic studies of the soil biome have revealed its complexity, which includes microorganisms that affect plant fitness and growth in a beneficial, harmful, or neutral manner. In this complex scenario, understanding the molecular mechanisms by which legumes recognize and discriminate rhizobia from pathogens, but also between distinct rhizobia species and strains that differ in their symbiotic performance, is a considerable challenge. In this work, we will review how plants are able to recognize and select symbiotic partners from a vast diversity of surrounding bacteria. We will also analyze recent advances that contribute to understand changes in plant gene expression associated with the outcome of the symbiotic interaction. These aspects of nitrogen-fixing symbiosis should contribute to translate the knowledge generated in basic laboratory research into biotechnological advances to improve the efficiency of the nitrogen-fixing symbiosis in agronomic systems.
Modular active curiosity-driven discovery of tool use

This article studies algorithms used by a learner to explore high-dimensional structured sensorimotor spaces such as in tool use discovery. In particular, we consider goal babbling architectures that were designed to explore and learn solutions to fields of sensorimotor problems, i.e. to acquire inverse models mapping a space of parameterized sensorimotor problems/effects to a corresponding space of parameterized motor primitives. However, so far these architectures have not been used in high-dimensional spaces of effects. Here, we show the limits of existing goal babbling architectures for efficient exploration in such spaces, and introduce a novel exploration architecture called Model Babbling (MB). MB exploits efficiently a modular representation of the space of parameterized problems/effects. We also study an active version of Model Babbling (the MACOB architecture). These architectures are compared in a simulated experimental setup with an arm that can discover and learn how to move objects using two tools with different properties, embedding structured high-dimensional continuous motor and sensory spaces.
Modeling of combustion in engines fed by hydrogen

Computer aided design of new effective and clean hydrogen engines needs mathematical tools for supercomputer modeling of hydrogen – oxygen components mixing and combustion in rocket or aviation engines. The paper presents the results of developing verification and validation of mathematical model making it possible to simulate unsteady processes of ignition and combustion in RAM or pulse detonation engines. One of peculiarities of hydrogen-oxygen rocket engine is the following. On injecting liquid components fuel (hydrogen) having must lower critical temperature comes pre-evaporated and pre-heated in combustion chamber, while oxygen could be liquid then evaporating inside the chamber. Thus contrary to most types of engines hydrogen engine has an inverse mixture entering combustion chamber, in which fuel is gaseous and oxidant is liquid. Onset of detonation being very dangerous for classical RAM engines could, however, serve the basis for creating new generation of engines pulse detonating engines (PDE). For this issue the problems of detonation onset and deflagration to detonation transition should be simulated quite accurately, because these processes strongly depend on inlet conditions, mixture composition and geometrical characteristics of combustion chamber. Key-Words: Combustion, ignition delay, non-equilibrium, diffusion, turbulence, mathematical
Causes and Effects of Corruption: What Has Past Decade's Empirical Research Taught Us? A Survey

Corruption has fierce impacts on economic and societal development and is subject to a vast range of institutional, jurisdictional, societal, and economic conditions. It is this paper's aim to provide a reassessment and a comprehensive stateâ€ ofâ€ theâ€ art survey of existing literature on corruption and its causes and effects. A particularly strong focus is put on presenting and discussing insights resulting from empirical research and contrasting recent with older findings.
Multiphase computational fluid dynamics–conjugate heat transfer for spray cooling in the non-boiling regime:

A numerical study is described to predict, in the non-boiling regime, the heat transfer from a circular flat surface cooled by a full-cone spray of water at atmospheric pressure. Simulations based on coupled Computational Fluid Dynamics and Conjugate Heat Transfer are used to predict the detailed features of the fluid flow and heat transfer for three different spray conditions involving three mass fluxes between 3.5 and 9.43 kg/m2s corresponding to spray Reynolds numbers between 82 and 220, based on a 20 mm diameter target surface. A two-phase Lagrange-Eulerian modelling approach is adopted to resolve the spray-film flow dynamics. Simultaneous evaporation and condensation within the fluid film is modelled by solving the mass conservation equation at the film-continuum interface. Predicted heat transfer coefficients on the cooled surface are compared with published experimental data showing good agreement. The spray mass flux is confirmed to be the dominant factor for heat transfer in spray cooling, where single-phase convection within the thin fluid film on the flat surface is identified as the primary heat transfer mechanism. This enhancement of heat transfer, via single-phase convection, is identified to be the result of the discrete random nature of the droplets disrupting the surface thin film.
Modeling the Dispersal of Eastern Oyster (Crassostrea virginica) larvae in Delaware Bay

The interactions of circulation and growth processes in determining the horizontal distribution of easternoyster( Crassostreavirginica )larvaeintheDelawareBayestuarywereinvestigatedwithacou-pled circulation-individual-based larvae model that used environmental conditions from the spawning seasons (mid-June to mid-September) of 1984, 1985, 1986, 2000, and 2001. Particles, representing oyster larvae, were released at ﬁve-day intervals from areas in Delaware Bay that correspond to natural oyster reefs. The simulated larval development time was used to estimate potential larval success, determined by the percent of larvae that successfully reached settlement size ( 330 μ m ) within the planktonic larval duration of 30 days. Success rates for simulated larvae released in the upper estuary were less than half of those released in the lower estuary because of the reduction in growth rate from exposure to low salinity. Simulated larval success rates were further reduced during periods of increased river discharge, which produced low salinity conditions. The simulated transport patterns showed a down-estuary drift of oyster larvae during the spawning season, which is consistent with the observed reduction in settlement and recruitment rates in the upper estuary. The simulated transport pathways patterns showed that larvae originating in the middle and lower regions of the estuary had low rates of dispersion and high rates of self-settlement. Larvae released in the upper reaches of the estuary had limited contributions to the Delaware Bay oyster population, in part because of the lower overall simulated larval success in the low salinity regions. The simulated transport patterns suggested that the upper bay exports rather than receives larvae, which has implications for the establishment of genetic traits.
Estimation of state occupancy probabilities in multistate models with dependent intermittent observation, with application to HIV viral rebounds

In follow‐up studies on chronic disease cohorts, individuals are often observed at irregular visit times that may be related to their previous disease history and other factors. This can produce bias in standard methods of estimation. Working in the context of multistate models, we consider a method of nonparametric estimation for state occupancy probabilities that adjusts for dependent follow‐up through the use of inverse‐intensity‐of‐visit weighted estimating functions and smoothing. The methodology is applied to the estimation of viral rebound probabilities in the Canadian Observational Cohort on HIV‐positive persons. Copyright © 2016 John Wiley & Sons, Ltd.
Demystifying MMD GANs

We investigate the training and performance of generative adversarial networks using the Maximum Mean Discrepancy (MMD) as critic, termed MMD GANs. As our main theoretical contribution, we clarify the situation with bias in GAN loss functions raised by recent work: we show that gradient estimators used in the optimization process for both MMD GANs and Wasserstein GANs are unbiased, but learning a discriminator based on samples leads to biased gradients for the generator parameters. We also discuss the issue of kernel choice for the MMD critic, and characterize the kernel corresponding to the energy distance used for the Cramer GAN critic. Being an integral probability metric, the MMD benefits from training strategies recently developed for Wasserstein GANs. In experiments, the MMD GAN is able to employ a smaller critic network than the Wasserstein GAN, resulting in a simpler and faster-training algorithm with matching performance. We also propose an improved measure of GAN convergence, the Kernel Inception Distance, and show how to use it to dynamically adapt learning rates during GAN training.
A Proposal for a New Method of Evaluation of the Newborn Infant

In this article, Apgar described her innovative method for assessing the viability of newborn infants by assigning "scores" of 0, 1, or 2 to the infant's respiration, pulse, color, muscle tone, and response to stimuli one minute after birth. This procedure was later known as "Apgar scoring" and is now routinely used in hospitals worldwide.
Comparative Analysis Of Tensile Bond Strength Of Three Different Pit And Fissure Sealants Using Invasive And Non-Invasive Techniques â€“ An Invitro Study

This present study was conducted to evaluate and compare the tensile bond strength of three different pit and fissure sealants â€“ 2 light cured resin sealants. Teethmate F1 and 3M Concise and one conventional glass ionomer, GC Fuji III sealant by using invasive and non-invasive techniques in premolars in vitro. Sixty premolars were taken for the study and were divided into 6 groups with ten teeth in each group. In group 1 and 2 teeth filled with Teethmate F1 light cured resin sealant using invasive and non-invasive technique respectively. In group 3 and 4 teeth filled with 3M Concise light cured resin sealant using invasive and non-invasive technique respectively. Groups 5 and 6, teeth filled with chemically cured glass ionomer sealant Fuji III using invasive and non-invasive technique respectively. The results showed the Teethmate F1 light cured resin sealant had a higher bond strength than 3M Concise light cured resin sealant and glass ionomer Fuji III sealant. The difference was statistically very significant (P<0.01). Results also showed that the invasive groups 1, 3 and 5 showed a higher tensile bond strength compared to the non-invasive groups 2, 4 and 6 for all the 3 sealants. This difference was statistically very significant (P,0.01).
Fabric Dependence in Dynamic Poroelasticity

In this paper the governing equations for wave motion in the linear theory of anisotropic poroelastic materials are developed and extended to include the dependence of the constitutive relations upon fabric - a quantitative stereological measure of the degree of structural anisotropy in the pore architecture of a porous medium. This fabric-dependent anisotropic poroelastic approach is a theoretical framework to describe the microarchitectural-dependent relationship between measurable wave properties and the elastic constants of trabecular bone, and thus represents an alternative for bone quality assessment beyond BMD alone. Current diagnosis of bone loss and osteoporosis is based on the measurement of the Bone Mineral Density (BMD) or the apparent mass density. Unfortunately, in most clinical ultrasound densitometers: 1) measurements are often performed in a single anatomical direction, 2) only the first wave arriving to the ultrasound probe is characterized, and 3) the analysis of bone status is based on empirical relationships between measurable quantities such as Speed of Sound (SOS) and Broadband Ultrasound Attenuation (BUA) and the density of the porous medium. However, the existence of a second wave in cancellous bone has been reported, which is an unequivocal signature of poroelastic media, as predicted by Biot’s poroelastic wave propagation theory.
Not all smokers appear to seek nicotine for the same reasons: implications for preclinical research in nicotine dependence

Tobacco use leads to 6 million deaths every year due to severe long‐lasting diseases. The main component of tobacco, nicotine, is recognized as one of the most addictive drugs, making smoking cessation difficult, even when 70 percent of smokers wish to do so. Clinical and preclinical studies have demonstrated consistently that nicotine seeking is a complex behavior involving various psychopharmacological mechanisms. Evidence supports that the population of smokers is heterogeneous, particularly as regards the breadth of motives that determine the urge to smoke. Here, we review converging psychological, genetic and neurobiological data from clinical and preclinical studies supporting that the mechanisms controlling nicotine seeking may vary from individual to individual. It appears timely that basic neuroscience integrates this heterogeneity to refine our understanding of the neurobiology of nicotine seeking, as tremendous progress has been made in modeling the various psychopharmacological mechanisms driving nicotine seeking in rodents. For a better understanding of the mechanisms that drive nicotine seeking, we emphasize the need for individual‐based research strategies in which nicotine seeking, and eventually treatment efficacy, are determined while taking into account individual variations in the mechanisms of nicotine seeking.
University of Birmingham Effectiveness of upper limb functional electrical stimulation after stroke for the improvement of activities of daily living and motor function: a systematic review and meta-analysis

Background: Stroke can lead to significant impairment of upper limb function which affects performance of activities of daily living (ADL). Functional electrical stimulation (FES) involves electrical stimulation of motor neurons such that muscle groups contract and create or augment a moment about a joint. Whilst lower limb FES was established in post-stroke rehabilitation, there is a lack of clarity on the effectiveness of upper limb FES. This systematic review aims to evaluate the effectiveness of post-stroke upper limb FES on ADL and motor outcomes. Methods: Systematic review of randomised controlled trials from MEDLINE, PsychINFO, EMBASE, CENTRAL, ISRCTN, ICTRP and ClinicalTrials.gov. Citation checking of included studies and systematic reviews. Eligibility criteria: participants > 18 years with haemorrhagic/ischaemic stroke, intervention group received upper limb FES plus standard care, control group received standard care. Outcomes were ADL (primary), functional motor ability (secondary) and other motor outcomes (tertiary). Quality assessment using GRADE (Grading of Recommendations Assessment, Development and Evaluation) criteria. Results: Twenty studies were included. No significant benefit of FES was found for objective ADL measures reported in six studies (standardised mean difference (SMD) 0.64; 95% Confidence Interval (CI) [ − 0.02, 1.30]; total participants in FES group ( n ) = 67); combination of all ADL measures was not possible. Analysis of three studies where FES was initiated on average within 2 months post-stroke showed a significant benefit of FES on ADL (SMD 1.24; CI [0.46, 2.03]; n = 32). In three studies where FES was initiated more than 1 year after stroke, no significant ADL improvements were seen (SMD − 0.10; CI [ − 0.59, 0.38], n = 35). Quality assessment using GRADE found very low quality evidence in all analyses due to heterogeneity, low
Zoledronic acid is an effective radiosensitizer in the treatment of osteosarcoma

To overcome radioresistance in the treatment of osteosarcoma, a primary malignant tumor of the bone, radiotherapy is generally combined with radiosensitizers. The purpose of this study was to investigate a third-generation bisphosphonate, zoledronic acid (ZOL), as a radiosensitizer for osteosarcoma. We found that exposure of KHOS/NP osteosarcoma cells to 20 μM ZOL decreased the γ-radiation dose needed to kill 90% of cells. This radiosensitizing effect of ZOL was mediated through decreased mitochondrial membrane potential, increased levels of reactive oxygen species, increased DNA damage (as assessed by counting γ-H2AX foci), decreased abundance of proteins involved in DNA repair pathways (ATR, Rad52, and DNA-PKcs), and decreased phosphorylation of PI3K-Akt and MAPK pathway proteins (Raf1, MEK1/2, ERK1/2, and Akt), as compared to γ-irradiation alone. Cells treated with ZOL plus γ-irradiation showed impaired cell migration and invasion and reduced expression of epithelial-mesenchymal transition markers (vimentin, MMP9, and Slug). In Balb/c nude mice, the mean size of orthotopic osteosarcoma tumors 2 weeks post-inoculation was 195 mm3 following γ-irradiation (8 Gy), while it was 150 mm3 after γ-irradiation plus ZOL treatment (0.1 mg/kg twice weekly for 2 weeks). These results provide a rationale for combining ZOL with radiotherapy to treat osteosarcoma.
The Impact of Clay Loading on the Relative Intercalation of Poly(Vinyl Alcohol)-Clay Composites

Polymer clay nanocomposites (PCN) materials are industrially applied because of their unique properties. However many of their physical and chemical properties have not been determined. The formed structures of polymer/clay nanocomposite depend on the nature of interactions between polymer chains and clay platelets. According to the possible modes of interactions between polymer matrix and clay sheets, these nanocomposites can be classified into: intercalated, flocculated and exfoliated nanocomposites. In this work, the morphology of the nanocomposite was studied using X-ray diffraction (XRD) and nanoscaning electron microscopy (NSEM). XRD and NSEM measurements confirmed the intercalation between poly(vinyl alcohol) chains and cloisite® 20A sheets. Because of the intercalation between the clay platelets and the PVA chains, as the clay concentration increases as the band intensities in FT-IR spectra increase. On the other hand, the XRD did not provide clear shift of any of the clay peaks for PVA/cloisite® 10A nanocomposites and confirm the non-intercalation between PVA matrix and cloisite® 10A platelets. The relative intercalation (RI) of PVA/Cloisite® 20A nanocomposites declined with increase in the clay loadings. In contrast, for PVA/Cloisite® 10A, RI values slightly increased with increasing the clay loading.
Active Learning with Logged Data

We consider active learning with logged data, where labeled examples are drawn conditioned on a predetermined logging policy, and the goal is to learn a classifier on the entire population, not just conditioned on the logging policy. Prior work addresses this problem either when only logged data is available, or purely in a controlled random experimentation setting where the logged data is ignored. In this work, we combine both approaches to provide an algorithm that uses logged data to bootstrap and inform experimentation, thus achieving the best of both worlds. Our work is inspired by a connection between controlled random experimentation and active learning, and modifies existing disagreement-based active learning algorithms to exploit logged data.
Thermal Analysis in Gas Insulated Transmission Lines Using an Improved Finite-Element Model

In this paper, an improved finite element (FE) model is proposed to investigate the temperature distribution in gas insulated transmission lines (GILs). The solution of joule losses in eddy current field analysis is indirectly coupled into fluid and thermal fields. As is different from the traditional methods, the surrounding air of the GIL is involved in the model to avoid constant convective heat transfer coefficient, thus multiple species transport technique is employed to deal with the problem of two fluid types in a single model. In addition, the temperature dependent electrical and thermal properties of the materials are considered. The steady-state and transient thermal analysis of the GIL are performed separately with the improved model. The corresponding temperature distributions are compared with experimental results reported in the literature. DOI: http://dx.doi. org/10.11591/telkomnika.v11i1. 1247 Full Text: PDF
Improved deep reinforcement learning for robotics through distribution-based experience retention

Recent years have seen a growing interest in the use of deep neural networks as function approximators in reinforcement learning. In this paper, an experience replay method is proposed that ensures that the distribution of the experiences used for training is between that of the policy and a uniform distribution. Through experiments on a magnetic manipulation task it is shown that the method reduces the need for sustained exhaustive exploration during learning. This makes it attractive in scenarios where sustained exploration is in-feasible or undesirable, such as for physical systems like robots and for life long learning. The method is also shown to improve the generalization performance of the trained policy, which can make it attractive for transfer learning. Finally, for small experience databases the method performs favorably when compared to the recently proposed alternative of using the temporal difference error to determine the experience sample distribution, which makes it an attractive option for robots with limited memory capacity.