Miracle-dz/UniFAR-FTUs huggingface dataset:
Scanning electron microscopy and in vitro cultivation of endophytic bacteria from potato tubers afflicted with zebra chip disease

Abstract Zebra chip disease (ZCD) of potato (Solanum tuberosum L.) has caused significant economic losses to the potato industry in the USA. ‘Candidatus Liberibacter solanacearum’ Liefting et al. has been associated with ZCD. This non-culturable bacterium dwells within the phloem of plants where other endophytic bacteria may also live. Knowledge concerning phloem colonization by ‘Ca. L. solanacearum’ and other endophytic bacteria may provide a better understanding about disease biology and could facilitate the development of novel disease management strategies. In this study, endophytic bacteria in potato tubers afflicted with ZCD were evaluated by scanning electron microscopy (SEM), in vitro cultivation, and PCR analyses. Bacillus, coccus, and filamentous bacterial cells were observed by SEM in phloem tissue of ZCD-diseased tubers, but were absent in healthy potato tubers. Fifty-one bacterial isolates were obtained in vitro from ZCD-affected tubers and 34 isolates were from non-ZCD tubers. Comparison of 16S rDNA sequences identified bacteria belonging to 16 genera. Seven (Brachybacterium, Enterobacter, Microbacterium, Paenibacillus, Staphylococcus, Stenotrophomonas and Variovorax) were only isolated from ZCD-affected potato tubers, whereas four (Bosea, Nocardia, Sphingomonas and Sphingopyxis) were only isolated from non-ZCD potato tubers. However, a more sensitive PCR analysis diminished the specific association of the bacteria to either ZCD or non-ZCD tubers, suggesting that infection by ‘Ca. L. solanacearum’ influenced the titres of other endophytic bacteria in potato tubers.
COMPETITION VERSUS HOST PLANT PHENOTYPE IN SPECIES COMPOSITION: WILLOW SAWFLIES'

The influence of host plant phenotype and interspecific competition on the abundance of four willow sawfly species was tested on potted cuttings of the arroyo willow, Salix lasiolepis, in northern Arizona. Interspecific competition by a stem-galling sawfly, Euura lasiolepis, was demon- strated on a leaf gallery, Pontania sp. , a leaf folder, Phyllocolpa sp. , and a petiole gallery, Euura sp. The competitive influence of the stem galler on these species is likely to be absent at low stem gall densities. Density of the stem galler is spatially patchy, so competition should be variable among willow clones in the field. The three other sawfly species form galls that are distal to stem galls and/or do not affect the shoot in a way detrimental to the stem gallery, therefore this competition appears to be asymmetrical, an "amensalism. " All sawfly species exhibited significant differences in gall densities among potted, replicate willow clones under uniform environmental conditions. This suggests underlying genetic variation among clones in susceptibility to sawfly oviposition. Each sawfly species seemed to respond to variation among clone phenotypes idiosyncratically. Under experimental conditions, host plant phenotype accounted for 1.5 to 3.2 times as much variation in the density of subordinate species as did interspecific competition; under field conditions host plant phenotype is likely to play a more important role than competition in the community patterns of herbivorous insects.
Jet Properties of Compact Steep-spectrum Sources and an Eddington-ratio-driven Unification Scheme of Jet Radiation in Active Galactic Nuclei

Compact steep-spectrum sources (CSSs) likely represent a population of young radio-loud active galactic nuclei (AGNs) and have been identified as γ-ray-emitting sources. We present a comprehensive analysis of their γ-ray emission observed with Fermi/LAT and establish their broadband spectral energy distributions (SEDs). We derive their jet properties using SED fits with a two-zone leptonic model for radiation from the compact core and the large-scale extended region, and explore the possible signature of a unification picture of jet radiation among subclasses of AGNs. We show that the observed γ-rays of CSSs with significant variability are contributed by the radiation of their compact cores via the inverse-Compton process of the torus photons. The derived power-law distribution index of the radiating electrons is p1 ∼ 1.5–1.8, magnetic field strength is B ∼ 0.15–0.6 G, and Doppler-boosting factor is δ ∼ 2.8–8.9. Assuming that the jet is composed of e± pairs, the compact cores of CSSs are magnetized and have a high radiation efficiency, similar to that of flat-spectrum radio quasars. The γ-ray-emitting CSSs on average have higher Eddington ratio and black hole mass than those non-GeV-detected CSSs, and they follow the correlation between the jet power in units of Eddington luminosity ( ) and Eddington ratio (REdd) with other subclasses of AGNs, , indicating that REdd would be a key physical driver for the unification scheme of AGN jet radiation.
GoChat: Goal-oriented Chatbots with Hierarchical Reinforcement Learning

A chatbot that converses like a human should be goal-oriented (i.e., be purposeful in conversation), which is beyond language generation. However, existing goal-oriented dialogue systems often heavily rely on cumbersome hand-crafted rules or costly labelled datasets, which limits the applicability. In this paper, we propose Goal-oriented Chatbots (GoChat), a framework for end-to-end training the chatbot to maximize the long-term return from offline multi-turn dialogue datasets. Our framework utilizes hierarchical reinforcement learning (HRL), where the high-level policy determines some sub-goals to guide the conversation towards the final goal, and the low-level policy fulfills the sub-goals by generating the corresponding utterance for response. In our experiments conducted on a real-world dialogue dataset for anti-fraud in financial, our approach outperforms previous methods on both the quality of response generation as well as the success rate of accomplishing the goal.
Using truss networks to estimate the biomass of Oreochromis niloticus, and to investigate shape characteristics.

Truss and length measurements were made on 463 tilapia Oreochromis niloticus of known mass. These measurements were then used to build mathematical models to estimate tilapia biomass. Two different approaches were used to build the models. The first was to take some simple mathematical models, and to optimize them using least squares regression. The second approach was to build models using artificial neural network software. Models were built for two different but overlapping size ranges and both approaches were successful in creating models that estimated the total biomass to within ±1%. The truss measurements were also used to assess the principal shape components of different sized tilapia.
Predicting COVID-19 Pneumonia Severity on Chest X-ray With Deep Learning

Introduction The need to streamline patient management for coronavirus disease-19 (COVID-19) has become more pressing than ever. Chest X-rays (CXRs) provide a non-invasive (potentially bedside) tool to monitor the progression of the disease. In this study, we present a severity score prediction model for COVID-19 pneumonia for frontal chest X-ray images. Such a tool can gauge the severity of COVID-19 lung infections (and pneumonia in general) that can be used for escalation or de-escalation of care as well as monitoring treatment efficacy, especially in the ICU. Methods Images from a public COVID-19 database were scored retrospectively by three blinded experts in terms of the extent of lung involvement as well as the degree of opacity. A neural network model that was pre-trained on large (non-COVID-19) chest X-ray datasets is used to construct features for COVID-19 images which are predictive for our task. Results This study finds that training a regression model on a subset of the outputs from this pre-trained chest X-ray model predicts our geographic extent score (range 0-8) with 1.14 mean absolute error (MAE) and our lung opacity score (range 0-6) with 0.78 MAE. Conclusions These results indicate that our model’s ability to gauge the severity of COVID-19 lung infections could be used for escalation or de-escalation of care as well as monitoring treatment efficacy, especially in the ICU. To enable follow up work, we make our code, labels, and data available online.
Robin fractional problems with symmetric variable growth

In this paper we study the fractional p(., .)-Laplacian and we introduce the corresponding nonlocal conormal derivative for this operator. We prove basic properties of the corresponding function space and we establish a nonlocal version of the divergence theorem for such operators. In the second part of this paper, we prove the existence of weak solutions of corresponding p(., .)-Robin boundary problems with sign-changing potentials by applying variational tools.
Historical Evidence and Human Adaptations

Phylogenetic information is often necessary to distinguish between evolutionary scenarios. Recently, some prominent proponents of evolutionary psychology have acknowledged this, and have claimed that such evidence has in fact been brought to bear on adaptive hypotheses involving complex human psychological traits. Were this possible, it would be a valuable source of evidence regarding hypothesized adaptive traits in humans. However, the structure of the Hominidae family makes this difficult or impossible. For many traits of interest, the closest extant relatives to the human species are too phenotypically different from humans for such methods to provide meaningful data. While phylogenetic information can be useful for testing adaptive hypotheses in humans, these generally involve traits that are (a) not widely shared in the species or (b) fairly widely shared in the Hominidae family, and hence likely of a lower order of complexity than the sorts of traits evolutionary psychology has so far been interested in.
Excess noise: why exceptional points do not increase sensor precision

We show that exceptional-point (EP) sensors are fundamentally limited by excess noise owing to eigenmode nonorthogonality, to the extent that the enhancement in precision (the magnitude of the scale-factor enhancement divided by the square-root of the linewidth-enhancement factor $|S|/{{K}^{1/2}}$) is never greater than unity. Indeed, in the vicinity of an EP a hole of reduced precision opens up in parameter space, where the precision drops rapidly to zero within regions of deadband or unbroken PT-symmetry. Outside of these zero-sensitivity regions the precision is nonzero, approaching its maximum value of $|S|/{{K}^{1/2}}=1$ at the EP. EPs, therefore, represent discontinuous transitions between these two regimes. We find that this behavior is universal, with the hole appearing regardless of the type of EP. Therefore, EPs should generally be avoided for sensors that utilize laser cavities. Moreover, we illustrate that a laser containing a medium at the critical anomalous dispersion is simply operating at an EP. Therefore, this limitation also applies to laser sensors based on fast light.
Brownian loops and the central charge of a Liouville random surface

We explore the geometric meaning of the so-called zeta-regularized determinant of the Laplace-Beltrami operator on a compact surface, with or without boundary. We relate the $(-c/2)$-th power of the determinant of the Laplacian to the appropriately regularized partition function of a Brownian loop soup of intensity $c$ on the surface. This means that, in a certain sense, decorating a random surface by a Brownian loop soup of intensity $c$ corresponds to weighting the law of the surface by the $(-c/2)$-th power of the determinant of the Laplacian. Next, we introduce a method of regularizing a Liouville quantum gravity (LQG) surface (with some matter central charge parameter $\mathbf{c}$) to produce a smooth surface. And we show that weighting the law of this random surface by the $( -\mathbf{c}'/ 2)$-th power of the Laplacian determinant has precisely the effect of changing the matter central charge from $\mathbf{c}$ to $\mathbf{c} + \mathbf{c}'$. Taken together with the earlier results, this provides a way of interpreting an LQG surface of matter central charge $\mathbf{c}$ as a pure LQG surface decorated by a Brownian loop soup of intensity $\mathbf{c}$. Building on this idea, we present several open problems about random planar maps and their continuum analogs. Although the original construction of LQG is well-defined only for $\mathbf{c}\leq 1$, some of the constructions and questions also make sense when $\mathbf{c}>1$.
The Galactic radial abundance gradients of C, N, O, Ne, S, Cl, and Ar from deep spectra of H ii regions

We present a reassessment of the radial abundance gradients of C, N, O, Ne, S, Cl and Ar in the Milky Way using deep spectra of 33 H II regions gathered from the literature, covering Galactocentric distances from 6 to 17 kpc. The distances of the objects have been revised using Gaia parallaxes. We recalculate the physical conditions and ionic abundances in an homogeneous way using updated atomic data. All the objects have direct determination of the electron temperature, permitting to derive their precise ionic abundances. We analyze and compare different ICF schemes for each element in order to obtain the most confident total abundances. Due to the revised distances, our results do not support previous claims about a possible flattening of the O/H gradient in the inner Galactic disk. We find that the Galactic N/O gradient is rather flat, in contrast to what has been found in other spiral galaxies. The slope of the gradients of some elements is sensitive to the ICF scheme used, especially in the case of Ne. The dispersion around the fit for the gradients of C, N, O, S, Cl and Ar is of the order of the typical uncertainties in the determination of the abundances, implying the absence of significant inhomogeneities in the chemical composition of the ionized gas phase of the ISM. We find flat gradients of log(S/O) and log(Cl/O) and very shallow or flat ones for log(Ne/O) and log(Ar/O), consistent with a lockstep evolution of Ne, S, Cl and Ar with respect to O.
FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data

Federated Learning (FL) is popular for communication-efficient learning from distributed data. To utilize data at different clients without moving them to the cloud, algorithms such as the Federated Averaging (FedAvg) have adopted a computation then aggregation model, in which multiple local updates are performed using local data before aggregation. These algorithms fail to work when faced with practical challenges, e.g., the local data being non-identically independently distributed. In this paper, we first characterize the behavior of the FedAvg algorithm, and show that without strong and unrealistic assumptions on the problem structure, it can behave erratically. Aiming at designing FL algorithms that are provably fast and require as few assumptions as possible, we propose a new algorithm design strategy from the primal-dual optimization perspective. Our strategy yields algorithms that can deal with non-convex objective functions, achieves the best possible optimization and communication complexity (in a well-defined sense), and accommodates full-batch and mini-batch local computation models. Importantly, the proposed algorithms are communication efficient, in that the communication effort can be reduced when the level of heterogeneity among the local data also reduces. In the extreme case where the local data becomes homogeneous, only $\mathcal {O}(1)$ communication is required among the agents. To the best of our knowledge, this is the first algorithmic framework for FL that achieves all the above properties.
Population and Spectral Synthesis: It Doesn’t Work without Binaries

In this chapter we discuss the population and spectral synthesis of stellar populations. We describe the method required to achieve such synthesis and discuss examples where inclusion of interacting binaries are vital to reproducing the properties of observed stellar systems. These examples include the Hertzsprung-Russell diagram, massive star number counts, core-collapse supernovae and the ionising radiation from stellar populations that power both nearby HII regions and the epoch of reionization. We finally offer some speculations on the future paths of research in spectral synthesis.
Connecting the time evolution of the turbulence interface to coherent structures

The surface area of turbulent/non-turbulent interfaces (TNTIs) is continuously produced and destroyed via stretching and curvature/propagation effects. Here, the mechanisms responsible for TNTI area growth and destruction are investigated in a turbulent flow with and without stable stratification through the time evolution equation of the TNTI area. We show that both terms have broad distributions and may locally contribute to either production or destruction. On average, however, the area growth is driven by stretching, which is approximately balanced by destruction by the curvature/propagation term. To investigate the contribution of different length scales to these processes, we apply spatial filtering to the data. In doing so, we find that the averages of the stretching and the curvature/propagation terms balance out across spatial scales of TNTI wrinkles and this scale-by-scale balance is consistent with an observed scale invariance of the nearby coherent vortices. Through a conditional analysis, we demonstrate that the TNTI area production (destruction) is localized at the front (lee) edge of the vortical structures in the interface proximity. Finally, we show that while basic mechanisms remain the same, increasing stratification reduces the rates at which TNTI surface area is produced as well as destroyed. We provide evidence that this reduction is largely connected to a change in the multiscale geometry of the interface, which tends to flatten in the wall-normal direction at all active length scales of the TNTI.
TNF-α AND IL-1α INDUCE APOPTOSIS IN SUBCONFLUENT RAT MESANGIAL CELLS. EVIDENCE FOR THE INVOLVEMENT OF HYDROGEN PEROXIDE AND LIPID PEROXIDATION AS SECOND MESSENGERS

Abstract Apoptosis of mesangial cells (MC) plays a role in glomerulonephritis (GN). In this study we investigated cytokine-induced apoptosis of cultured rat MC by morphological and biochemical features. TNF-α and IL-1α induced apoptosis in rat MC in a time- and concentration-dependent fashion. RT-PCR experiments revealed that MC express the TNF-receptor 1 (p60) gene constitutively. TNF-α as well as IL-1α stimulated the production of reactive oxygen species (ROS) and induced lipid peroxidation. Coincubation with catalase inhibited TNF-α and IL-1α induced apoptosis as well as lipid peroxidation. TNF-α, but not IL-1α increased the expression of c-jun. These results provide evidence that TNF-α and IL-1α induce apoptosis in rat MC with hydrogen peroxide and lipid peroxidation as second messengers. Increased c-jun expression may be a downstream intracellular signal of TNF-α-, but not IL-1α-induced apoptosis.
Regularized asymptotic descents: finding the global minima for a class of multiple minima problems

We propose and analyze regularized asymptotic descent (RAD) methods to find the global minimizer for a class of nonconvex, nonsmooth, or even discontinuous multiple minima functions that are extended from strongly convex functions with Lipschitz-continuous gradients. First, we establish an asymptotic representation for the solution of regularized minimization, then we construct the method based on this representation. The method can find the global minimizer without being trapped in saddle points, local minima, or discontinuities. The main theoretical result shows that the method enjoys the global linear convergence for such a class of functions. Furthermore, the method is derivative-free and its per-iteration cost, i.e., the number of function evaluations, is also bounded, so it has a complexity bound $\mathcal{O}(\log\frac{1}{\epsilon})$ for finding a point such that the gap between this point and the global minimizer is less than $\epsilon>0$. Numerical experiments in up to $500$ dimensions demonstrate the benefits of the method.
Quantifying density-ionization correlations with the 21-cm power spectrum

The Epoch of Reionization (EoR)---when neutral hydrogen in the intergalactic medium was systematically ionized---is a period in our Universe's history that is currently poorly understood. However, a key prediction of most models is a correlation between the density and ionization field during the EoR. This has consequences for the 21cm power spectrum. Here, we propose a parametrization for the density-ionization correlation and study the dependence of the 21cm power spectrum on this parameterization. We use this formalism to forecast the ability of current and future observations to constrain these correlations. We find that upper limits on the dimensionless power spectrum at redshifts $7.5 < z < 8.5$ using $k$ bins between $0.1\,\textrm{Mpc}^{-1} < k < 0.75\,\textrm{Mpc}^{-1}$ with error bars at the level of $\sim\! \! 20\,\textrm{mK}^2$ about our fiducial model would rule out uncorrelated reionization at $99\%$ credibility. Beyond upper limits, we find that at its full sensitivity, the Hydrogen Epoch of Reionization Array (HERA) will be able to place strong constraints on the sign and magnitude of density-ionization correlations.
A Proof Assistant Based Formalisation of Core Erlang

Our research is part of a wider project that aims to investigate and reason about the correctness of scheme-based source code transformations of Erlang programs. In order to formally reason about the definition of a programming language and the software built using it, we need a mathematically rigorous description of that language. In this paper, we present our proof-assistant-based formalisation of a subset of Erlang, intended to serve as a base for proving refactorings correct. After discussing how we reused concepts from related work, we show the syntax and semantics of our formal description, including the abstractions involved (e.g. closures). We also present essential properties of the formalisation (e.g. determinism) along with their machine-checked proofs. Finally, we prove the correctness of some simple refactoring strategies.
Using regional exposure criteria and upstream reference data to characterize spatial and temporal exposures to chemical contaminants

Analyses of biomarkers in fish were used to evaluate exposures among locations and across time. Two types of references were used for comparison, an upstream reference sample remote from known point sources and regional exposure criteria derived from a baseline of fish from reference sites throughout Ohio, USA. Liver, bile, and blood were sampled from white suckers (Catostomus commersoni) and common carp (Cyprinus carpio) collected during 1993 and 1996 in the Ottawa River near Lima, Ohio. Levels of exposure were measured for petroleum by naphthalene‐type metabolites, combustion by‐products by benzo[a]pyrene‐type metabolites, coplanar organic compounds by ethoxyresorufin‐O‐deethylase (EROD) activity, and urea by blood urea nitrogen (BUN) levels. The four biomarkers analyzed proved effective in determining differences between reference and polluted sampling sites, between geographically close (<0.5 km) sites, and between sampling years at sites common in both years. Calculated exposure criteria levels of the polycyclic aromatic hydrocarbon bile metabolites were found to be a conservative approximation of levels from a designated reference site and could thereby permit comparison of biomarker levels of fish from the Ottawa River to a regional reference level. Polycyclic aromatic hydrocarbon bile metabolite and EROD activity levels were more reflective of spatial patterns of contamination than BUN, although all biomarkers indicated differences overtime. Biomarkers from white suckers seemed to be more responsive in detecting changes in contaminant levels than the same biomarkers from common carp. Lower levels in 1996 of all biomarkers at many sites suggested lower exposures than in 1993 and could be indicative of some improvement over the period.