Miracle-dz/UniFAR-FTUs huggingface dataset:
Production of fumonisin B analogues and related compounds by Fusarium globosum, a newly described species from corn

Fusarium globosum Rheeder, Marasas et Nelson is a recently described species originally isolated from corn kernels harvested in the Transkei region of South Africa. On the basis of morphological criteria, F. globosum is closely related to other common fungal contaminants of corn, viz. F. moniliforme, F. proliferatum, and F. subglutinans, and accordingly it has been classified in the section Liseola. Species within the section Liseola have been reported to produce either the fumonisin B or moniliformin (MON) mycotoxins and, in some cases both. Seventeen isolates of F. globosum, cultured on corn, were screened for the production of fumonisins B1 (FB1), B2 (FB2), B3 (FB3), and MON. All isolates produced FB1 (range 5−325 μg/g), while 15 of 17 also produced FB2 (range 1−4 μg/g). For 14 of 17 isolates, the levels of FB3 produced (range 4−24 μg/g) exceeded those of the corresponding FB2 concentrations. None of the isolates produced detectable levels of MON (<1 μg/g). In addition, several isolates of F. globosum .
A white dwarf bound to the transiting planetary system WASP-98

WASP-98 is a planetary system containing a hot Jupiter transiting a late-G dwarf. A fainter star 12 arcsec distant has previously been identified as a white dwarf, with a distance and proper motion consistent with a physical association with the planetary system. We present spectroscopy of the white dwarf, with the aim of determining its mass, radius and temperature and hence the age of the system. However, the spectra show the featureless continuum and lack of spectral lines characteristic of the DC class of white dwarfs. We therefore fitted theoretical white dwarf spectra to the ugriz apparent magnitudes and Gaia DR2 parallax of this object in order to determine its physical properties and the age of the system. We find that the system is old, with a lower limit of 3.6 Gyr, but theoretical uncertainties preclude a precise determination of its age. Its kinematics are consistent with membership of the thick disc, but do not allow us to rule out the thin-disc alternative. The old age and low metallicity of the system suggest it is subject to an age-metallicity relation, but analysis of the most metal-rich and metal-poor transiting planetary systems yields only insubstantial evidence of this. We conclude that the study of bound white dwarfs can yield independent ages to planetary systems, but such analysis may be better-suited to DA and DB rather than DC white dwarfs.
On the Fraction of X-Ray-weak Quasars from the Sloan Digital Sky Survey

We investigate systematically the X-ray emission from type 1 quasars using a sample of 1825 Sloan Digital Sky Survey non-broad absorption line (non-BAL) quasars with Chandra archival observations. A significant correlation is found between the X-ray-to-optical power-law slope parameter (αOX) and the 2500 Å monochromatic luminosity (L2500Å), and the X-ray weakness of a quasar is assessed via the deviation of its αOX value from that expected from this relation. We demonstrate the existence of a population of non-BAL X-ray-weak quasars, and the fractions of quasars that are X-ray weak by factors of ≥6 and ≥10 are 5.8% ± 0.7% and 2.7% ± 0.5%, respectively. We classify X-ray-weak quasars (X-ray weak by factors of ≥6) into three categories based on their optical spectral features: weak emission-line quasars (WLQs; C iv rest-frame equivalent width < 16 Å), red quasars (Δ(g − i) > 0.2), and unclassified X-ray-weak quasars. The X-ray-weak fraction of within the WLQ population is significantly higher than that within non-WLQs, confirming previous findings that WLQs represent one population of X-ray-weak quasars. The X-ray-weak fraction of within the red quasar population is also considerably higher than that within the normal quasar population. The unclassified X-ray-weak quasars do not have unusual optical spectral features, and their X-ray weakness may be mainly related to quasar X-ray variability.
Improper Gaussian Signaling for the $K$-User MIMO Interference Channels With Hardware Impairments

This paper investigates the performance of improper Gaussian signaling (IGS) for the <inline-formula><tex-math notation="LaTeX">$K$</tex-math></inline-formula>-user multiple-input, multiple-output (MIMO) interference channel (IC) with hardware impairments (HWI). HWI may arise due to imperfections in the devices like I/Q imbalance, phase noise, etc. With I/Q imbalance, the received signal is a widely linear transformation of the transmitted signal and noise. Thus, the effective noise at the receivers becomes improper, which means that its real and imaginary parts are correlated and/or have unequal powers. IGS can improve system performance with improper noise and/or improper interference. In this paper, we study the benefits of IGS for this scenario in terms of two performance metrics: achievable rate and energy efficiency (EE). We consider the rate region, the sum-rate, the EE region and the global EE optimization problems to fully evaluate the IGS performance. To solve these non-convex problems, we employ an optimization framework based on majorization-minimization algorithms, which allow us to obtain a stationary point of any optimization problem in which either the objective function and/or constraints are linear functions of rates. Our numerical results show that IGS can significantly improve the performance of the <inline-formula><tex-math notation="LaTeX">$K$</tex-math></inline-formula>-user MIMO IC with HWI and I/Q imbalance, where its benefits increase with the number of users, <inline-formula><tex-math notation="LaTeX">$K$</tex-math></inline-formula>, and the imbalance level, and decrease with the number of antennas.
The minimum degree of minimal Ramsey graphs for cliques

We prove that sr(Kk)=O(k5r5/2)$s_r(K_k) = O(k^5 r^{5/2})$ , where sr(Kk)$s_r(K_k)$ is the Ramsey parameter introduced by Burr, Erdős and Lovász in 1976, which is defined as the smallest minimum degree of a graph G$G$ such that any r$r$ ‐colouring of the edges of G$G$ contains a monochromatic Kk$K_k$ , whereas no proper subgraph of G$G$ has this property. The construction used in our proof relies on a group theoretic model of generalised quadrangles introduced by Kantor in 1980.
From Mott Insulators to Quantum Metals.

High critical temperature cuprate superconducting materials are composed of copper oxide layers and interlayer charge reservoirs. When not doped, these cuprates are antiferromagnetic insulators. We propose to design new materials by combining alternating layers of parents of hole-doped and electron-doped of these cuprates and modifications thereof. Our goal is to find undoped cuprates that can be either an antiferromagnetic insulator or a quantum metal. The term quantum metal means a metal characterized by long range antiferromagnetic order or only strong antiferromagnetic correlations, i.e., it is thus a stable ground state against any other perturbations. The new metallic states sought here could be precursors to new superconducting states in the absence or presence of doping. Using the density functional theory, we report on two compounds {La}{Pr}CuO4 and {La}{V}CuO4 that illustrate the different physics described above. The curly brackets mean that the preparation of these compounds shall be done by depositing a layer containing Pr, then one CuO2 layer, then finally the La layer in {La}{Pr}CuO4 for example. The configuration formed by the positions of the charge reservoir atoms with respect to the CuO2 layer is an important factor in the new procedure we propose here. This paper reports on the X-ray diffraction, electronic, optical, and magnetic properties of these hypothetical materials. We found that {La}{Pr}CuO4 is a Mott insulator, but {La}{V}CuO4 is an undoped correlated quantum metal with long-range order. Our calculations were performed using the linearized plane wave method (FP-LAPW) implemented within the Wien2k software.
Whole-Brain Models to Explore Altered States of Consciousness from the Bottom Up

The scope of human consciousness includes states departing from what most of us experience as ordinary wakefulness. These altered states of consciousness constitute a prime opportunity to study how global changes in brain activity relate to different varieties of subjective experience. We consider the problem of explaining how global signatures of altered consciousness arise from the interplay between large-scale connectivity and local dynamical rules that can be traced to known properties of neural tissue. For this purpose, we advocate a research program aimed at bridging the gap between bottom-up generative models of whole-brain activity and the top-down signatures proposed by theories of consciousness. Throughout this paper, we define altered states of consciousness, discuss relevant signatures of consciousness observed in brain activity, and introduce whole-brain models to explore the biophysics of altered consciousness from the bottom-up. We discuss the potential of our proposal in view of the current state of the art, give specific examples of how this research agenda might play out, and emphasize how a systematic investigation of altered states of consciousness via bottom-up modeling may help us better understand the biophysical, informational, and dynamical underpinnings of consciousness.
Computing Large-Scale Matrix and Tensor Decomposition With Structured Factors: A Unified Nonconvex Optimization Perspective

During the past 20 years, low-rank tensor and matrix decomposition models (LRDMs) have become indispensable tools for signal processing, machine learning, and data science. LRDMs represent high-dimensional, multiaspect, and multimodal data using low-dimensional latent factors in a succinct and parsimonious way. LRDMs can serve a variety of purposes, e.g., data embedding (dimensionality reduction), denoising, latent variable analysis, model parameter estimation, and big data compression; see [1]-[5] for surveys of applications.
Effective magnetic field induced by inhomogeneous Fermi velocity in strained honeycomb structures

In addition to the known pseudomagnetic field, nonuniform strains independently induce a position-dependent Fermi velocity (PDFV) in graphene. Here we demonstrate that, due to the presence of a PDFV, the Dirac fermions on a nonuniform (strained) honeycomb lattice may experiment a sort of magnetic effect, which is linearly proportional to the momentum of the quasiparticle. As a consequence, the quasiparticles have a sublinear dispersion relation. Moreover, we analyze the general consequence of a PDFV on the Klein tunneling of electrons through pseudomagnetic barriers. In particular, we report an anomalous (Klein) tunneling for an electron passing across velocity barriers with magnetic features. Our findings about the effects induced by a PDFV on Dirac fermions in a [two-dimensional (2D)] strained honeycomb lattice could be extended to (3D) Dirac and Weyl semimetals and/or its analogous artificial systems.
Recommending Influenceable Targets based on Influence Propagation through Activity Behaviors in Online Social Media

Online Social Media (OSM) is a platform through which the users present themselves to the connected world by means of messaging, posting, reacting, tagging, and sharing on different contents with also other social activities. Nowadays, it has a vast impact on various aspects of the industry, business and society along with on users life. In an OSN platform, reaching the target users is one of the primary focus for most of the businesses and other organizations. Identification and recommendation of influenceable targets help to capture the appropriate audience efficiently and effectively. In this paper, an effective model has been discussed in egocentric OSN by incorporating an efficient influence measured Recommendation System in order to generate a list of top most influenceable target users among all connected network members for any specific social network user. Firstly the list of interacted network members has been updated based on all activities. On which the interacted network members with most similar activities have been recommended based on the specific influence category with sentiment type. After that, the top most influenceable network members in the basis of the required amount among those updated list of interacted network members have been identified with proper ranking by analyzing the similarity and frequency of their activity contents with respect to the activity contents of the main user. Through these two continuous stages, an effective list of top influenceable targets of the main user has been distinguished from the egocentric view of any social network.
Deep Reinforcement Learning for Tactile Robotics: Learning to Type on a Braille Keyboard

Artificial touch would seem well-suited for Reinforcement Learning (RL), since both paradigms rely on interaction with an environment. Here we propose a new environment and set of tasks to encourage development of tactile reinforcement learning: learning to type on a braille keyboard. Four tasks are proposed, progressing in difficulty from arrow to alphabet keys and from discrete to continuous actions. A simulated counterpart is also constructed by sampling tactile data from the physical environment. Using state-of-the-art deep RL algorithms, we show that all of these tasks can be successfully learnt in simulation, and 3 out of 4 tasks can be learned on the real robot. A lack of sample efficiency currently makes the continuous alphabet task impractical on the robot. To the best of our knowledge, this work presents the first demonstration of successfully training deep RL agents in the real world using observations that exclusively consist of tactile images. To aid future research utilising this environment, the code for this project has been released along with designs of the braille keycaps for 3D printing and a guide for recreating the experiments.
Modeling Data Reuse in Deep Neural Networks by Taking Data-Types into Cognizance

In recent years, researchers have focused on reducing the model size and number of computations (measured as “multiply-accumulate” or MAC operations) of DNNs. The energy consumption of a DNN depends on both the number of MAC operations and the energy efficiency of each MAC operation. The former can be estimated at design time; however, the latter depends on the intricate data reuse patterns and underlying hardware architecture. Hence, estimating it at design time is challenging. This article shows that the conventional approach to estimate the data reuse, viz. arithmetic intensity, does not always correctly estimate the degree of data reuse in DNNs since it gives equal importance to all the data types. We propose a novel model, termed “data type aware weighted arithmetic intensity” (<inline-formula><tex-math notation="LaTeX">$DI$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>D</mml:mi><mml:mi>I</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="jha-ieq1-3015531.gif"/></alternatives></inline-formula>), which accounts for the unequal importance of different data types in DNNs. We evaluate our model on 25 state-of-the-art DNNs on two GPUs. We show that our model accurately models data-reuse for all possible data reuse patterns for different types of convolution and different types of layers. We show that our model is a better indicator of the energy efficiency of DNNs. We also show its generality using the central limit theorem.
Analysis of Mitochondrial 4977-bp Deletion and D-Loop Variation in Iranian Non-Alcoholic Fatty Liver Disease Patients

Background: Accumulating evidence indicates that mitochondrial dysfunction is considered an effective factor in the formation or development of non-alcoholic fatty liver disease (NAFLD) although the underlying mechanisms of the changes are still unclear. Objectives: The aim of the study was to determine the 4977-bp deletion levels and variations in the displacement (D) loop region of mitochondrial DNA (mtDNA) in NAFLD patients. Methods: In this case-control study, 43 NAFLD patients and 156 controls were enrolled. The blood DNA of 43 patients with NAFLD and 156 healthy individuals was investigated to determine the 4977-bp deletion and sequence changes in the D-loop region using methods such as polymerase chain reaction (PCR), multiplex PCR, and DNA sequencing. Results: The results indicated that no 4977-bp deletion was found in any of the samples. 94 variations were found in the D-loop region including two deletions, four insertions, and 88 single nucleotide polymorphisms (SNP), 16 of which were just found in patients. There was a significant difference between the NAFLD patients and controls in six variants (P < 0.05). Two novel insertions (16171 ins T and 16221 ins C) were observed in patients. Finally, the results revealed no statistically significant difference (P > 0.05) in C variations in D310 mitochondrial DNA between the two groups. Conclusions: According to the findings, we believe that the disease damages the mitochondrial DNA and leads to the formation of these mutations. Our results also showed that D-loop alterations are frequent in NAFLD and may play a significant role in the progression of NAFLD.
Evolution of upper layer temperature in the Bay of Biscay during the last 40 years

The temperature evolution over the past 40 years in the Bay of Biscay (North-East Atlantic) is investigated from an in situ data analysis, completed with a satellite SST (Sea Surface Temperature) analysis over the last 20 years. The in situ dataset is an interannual version of the BoByClim climatology, covering the Bay of Biscay area with a 10-km horizontal resolution and a 5-m vertical step. The satellite dataset is the European COastral Sea Operational Observing and Forcast System Program (ECOOP) daily analysis, covering the IBIROOS (Iberian-Biscay-Irish Sea) area with a 4-km resolution. The study area (43 ◦ N-50 ◦ N/12 ◦ W-1 ◦ W) extends over the intersection of the domains covered by these two analyses. In the 0-200 m layer of this domain, a heat budget has been computed from an ocean circulation model over the period 1965-2004. Heat is essentially imported from the west by the North Atlantic Drift, then exported southward and northward, or transferred downward into deeper layers. The annual average of air-sea flux is weak, with a zero isoline crossing the domain from the northwest to the southeast. Ocean and atmosphere, forming a coupled system, have comparable contributions and may both result in a heat sink or source. At the interannual scale, variability is mainly controlled by the air-sea flux, with a secondary contribution from oceanic transport. A strong warming of ∼0.2 ◦ C/decade for the period 1965-2004 is apparent from the surface down to the 200-m depth. The decadal evolution is consistent with several analyses over the North Atlantic. Meanwhile, warming is approximately twice faster than in the whole basin. This trend is not steady, as a cooling period occurred until the early 1970's, and the temperature increase has been significantly stronger during the last 20 years (∼0.3 ◦ C/decade between 0 and 100 m, from 1986 to 2005). The trend and the interannual variability are maximal over the northern part of the shelf. The typical duration of interannual anomalies is two years and their penetration depth is ∼100 m, although they occasionally exceed 200 m. The interseasonal anomalies are also stronger within the mixed layer (root-mean-square, RMS = 0.6 ◦ C at the surface) than below (RMS = 0.3 ◦ C at 100 m). Their geographic distribution is radically different between the surface and the deep levels. A seasonal dependence of the warming rate is evident in the upper layer, as the temperature trend is stronger in summer than in winter (by a factor of 2 at the surface). Some of the potential implications for the ecosystem are discussed, particularly in terms of species distribution and dynamics of species exploited by fisheries.
Experimental and numerical studies on kV scattered x-ray imaging for real-time image guidance in radiation therapy

Motion management is a critical component of image guided radiotherapy for lung cancer. We previously proposed a scheme using kV scattered x-ray photons for marker-less real-time image guidance in lung cancer radiotherapy. This study reports our recent progress using the photon counting detection technique to demonstrate potential feasibility of this method and using Monte Carlo (MC) simulations and ray-tracing calculations to characterize the performance. In our scheme, a thin slice of x-ray beam was directed to the target and we measured the outgoing scattered photons using a photon counting detector with a parallel-hole collimator to establish the correspondence between detector pixels and scatter positions. Image corrections of geometry, beam attenuation and scattering angle were performed to convert the raw image to the actual image of Compton attenuation coefficient. We set up a MC simulation system using an in-house developed GPU-based MC package modeling the image formation process. We also performed ray-tracing calculations to investigate the impacts of imaging system geometry on resulting image resolution. The experiment demonstrated feasibility of using a photon counting detector to measure scattered x-ray photons and generate the proposed scattered x-ray image. After correction, x-ray scattering image intensity and Compton scattering attenuation coefficient were linearly related, with R 2 greater than 0.9. Contrast to noise ratios of different objects were improved and the values in experimental results and MC simulation results agreed with each other. Ray-tracing calculations revealed the dependence of image resolution on imaging geometry. The image resolution increases with reduced source to object distance and increased collimator height. The study demonstrated potential feasibility of using scattered x-ray imaging as a real-time image guidance method in radiation therapy.
An extremal problem on rainbow spanning trees in graphs

A spanning tree of an edge-colored graph is rainbow provided that each of its edges receives a distinct color. In this paper we consider the natural extremal problem of maximizing and minimizing the number of rainbow spanning trees in a graph $G$. Such a question clearly needs restrictions on the colorings to be meaningful. For edge-colorings using $n-1$ colors and without rainbow cycles, known in the literature as JL-colorings, there turns out to be a particularly nice way of counting the rainbow spanning trees and we solve this problem completely for JL-colored complete graphs $K_n$ and complete bipartite graphs $K_{n,m}$. In both cases, we find tight upper and lower bounds; the lower bound for $K_n$, in particular, proves to have an unexpectedly chaotic and interesting behavior. We further investigate this question for JL-colorings of general graphs and prove several results including characterizing graphs which have JL-colorings achieving the lowest possible number of rainbow spanning trees. We establish other results for general $n-1$ colorings, including providing an analogue of Kirchoff's matrix tree theorem which yields a way of counting rainbow spanning trees in a general graph $G$.
Notes on the Behavior of MC Dropout

Among the various options to estimate uncertainty in deep neural networks, Monte-Carlo dropout is widely popular for its simplicity and effectiveness. However the quality of the uncertainty estimated through this method varies and choices in architecture design and in training procedures have to be carefully considered and tested to obtain satisfactory results. In this paper we present a study offering a different point of view on the behavior of Monte-Carlo dropout, which enables us to observe a few interesting properties of the technique to keep in mind when considering its use for uncertainty estimation.