Miracle-dz/UniFAR-FTUs huggingface dataset:
Polysaccharide utilization loci and nutritional specialization in a dominant group of butyrate-producing human colonic Firmicutes

Firmicutes and Bacteroidetes are the predominant bacterial phyla colonizing the healthy human large intestine. Whilst both ferment dietary fibre, genes responsible for this important activity have been analysed only in the Bacteroidetes, with very little known about the Firmicutes. This work investigates the carbohydrate-active enzymes (CAZymes) in a group of Firmicutes, Roseburia spp. and Eubacterium rectale, which play an important role in producing butyrate from dietary carbohydrates and in health maintenance. Genome sequences of 11 strains representing E. rectale and four Roseburia spp. were analysed for carbohydrate-active genes. Following assembly into a pan-genome, core, variable and unique genes were identified. The 1840 CAZyme genes identified in the pan-genome were assigned to 538 orthologous groups, of which only 26 were present in all strains, indicating considerable inter-strain variability. This analysis was used to categorize the 11 strains into four carbohydrate utilization ecotypes (CUEs), which were shown to correspond to utilization of different carbohydrates for growth. Many glycoside hydrolase genes were found linked to genes encoding oligosaccharide transporters and regulatory elements in the genomes of Roseburia spp. and E. rectale, forming distinct polysaccharide utilization loci (PULs). Whilst PULs are also a common feature in Bacteroidetes, key differences were noted in these Firmicutes, including the absence of close homologues of Bacteroides polysaccharide utilization genes, hence we refer to Gram-positive PULs (gpPULs). Most CAZyme genes in the Roseburia/E. rectale group are organized into gpPULs. Variation in gpPULs can explain the high degree of nutritional specialization at the species level within this group.
State of the Art Report on Real-time Rendering with Hardware Tessellation

For a long time, GPUs have primarily been optimized to render more and more triangles with increasingly flexible shading. However, scene data itself has typically been generated on the CPU and then uploaded to GPU memory. Therefore, widely used techniques that generate geometry at render time on demand for the rendering of smooth and displaced surfaces were not applicable to interactive applications. As a result of recent advances in graphics hardware, in particular the GPU tessellation unit’s ability to overcome this limitation, complex geometry can now be generated within the GPU’s rendering pipeline on the fly. GPU hardware tessellation enables the generation of smooth parametric surfaces or application of displacement mapping in real-time applications. However, many well-established approaches in offline rendering are not directly transferable, due to the limited tessellation patterns or the parallel execution model of the tessellation stage. In this state of the art report, we provide an overview of recent work and challenges in this topic by summarizing, discussing and comparing methods for the rendering of smooth and highly detailed surfaces in real-time.
The volatility of gold

The volatility of equity returns generally exhibits an asymmetric reaction to positive and negative shocks. Economic explanations for this phenomenon are leverage and volatility feedback effects. This paper studies the volatility of gold and demonstrates that there is an inverted asymmetric reaction of gold to positive and negative shocks, i.e. positive shocks increase the volatility by more than negative shocks. The paper argues that this effect is a result of the safe haven property of gold. Macroeconomic and financial uncertainty is transmitted from the equity market to the gold market causing the special asymmetric reaction. The empirical results hold for gold bullion and gold coins denominated in different currencies, different time periods and for different distributional assumptions. Finally, we show that the inverted volatility effect of gold can lower the aggregate risk of a portfolio for specific correlation levels. JEL classification: C32, G10, G11, G15, L70
Rewarding and Psychomotor Stimulant Effects of Endomorphin-1: Anteroposterior Differences within the Ventral Tegmental Area and Lack of Effect in Nucleus Accumbens

Endomorphin-1 (EM-1) is a recently isolated endogenous peptide having potent analgesic activity and high affinity and selectivity for the μ-opioid receptor. The present study was designed to investigate the rewarding and psychomotor stimulant effects of EM-1 in specific brain regions. We found that rats would learn without priming or response shaping to lever-press for microinjections of EM-1 into the ventral tegmental area (VTA); responding was most vigorous for high-dose injections into the posterior VTA. Rats did not learn to lever-press for microinjections of EM-1 into the nucleus accumbens (NAS) or regions just dorsal to the VTA. Lever-pressing for EM-1 in the VTA was extinguished when vehicle was substituted for the peptide and was reinstated when EM-1 reinforcement was re-established. Conditioned place preference was established by EM-1 injections into the posterior but not the anterior VTA or the NAS. Injection of EM-1 (0.1–1.0 nmol) into the posterior VTA induced robust increases in locomotor activity, whereas injections into the anterior VTA had very weak locomotor-stimulating effects. When injected into the NAS, EM-1 (0.1–10.0 nmol) did not affect locomotor activity. The present findings implicate the posterior VTA as a highly specific and sensitive site for opioid reward and suggest a role for EM-1-containing projections to the posterior VTA in the rewarding effects of other reinforcers.
A Bayesian Multiplicative Markov Random Field Model for Determining Activated Areas in Functional Magnetic Resonance Imaging Studies

A Bayesian spatial model for detecting brain activation in functional neuroimaging (here focusing on functional magnetic resonance imaging [fMRI]) is developed that inherently trades the local functional response level with its spatial extent. The model makes no assumptions about the shape or form of activated areas, except that they are elevated above non-active areas and form contiguous regions as characterized by Markov random field prior distributions. The robustness of the model is tested under a variety of simulated conditions and the model is subsequently applied to real data from an auditory experiment. An observed secondary low-level response that occurs globally and is synchronized with the experimental stimulus necessitates an extension to the model in the form of an additional additive Markov random field. Functional magnetic resonance imaging has been playing a major role in neuroscience for more than a decade. A whole range of statistical methods have been developed and adapted in order to analyze the highly multivariate datasets that are obtained from fMRI experiments. Initially, these approaches were adapted from existing ones for detecting activated areas in Positron Emission Tomography experiments. However, subsequent methods have been developed that are tailored specifically for fMRI. Most of these methods tend to focus on performing a separate analysis (e.g. linear model or parametric curve fitting) at each voxel (3D pixel) in order to determine the existence or not of a localized brain response to an experimental stimulus. The subsequent spatial stage of these analysis methods tend to focus on determining a level at which to threshold a 3D map of, for example estimated magnitudes, such that the large number of multiple comparisons is accounted for. A spatial map showing above-threshold voxels is then usually displayed as a map of activation. Instead of level thresholding the map of statistics, we develop a Bayesian product Markov random field model that places a priori expected constraints on the smoothness of activation patterns. The presence of local activation is then dependent not only on the level of a statistic at a particular voxel, but also on both the level of the statistics at nearby voxels and the classification as either “active” or “inactive” of those same voxels. The main benefit of this approach is that the Bayesian spatial prior distributions provide a framework for detecting active regions much as a neurologist might; based on posterior evidence over a wide range of spatial scales, simultaneously considering the level of the voxel magnitudes along with the size of the elevated area.
An EPG Study of the Probing Behavior of Adult Bemisia tabaci Biotype Q (Hemiptera: Aleyrodidae) Following Exposure to Cyantraniliprole

ABSTRACT Cyantraniliprole is a novel insecticide for control of multiple chewing and sucking insect pest species including the sweetpotato whitefly Bemisia tabaci (Gennadius), which is one of the most important polyphagous pests in tropical, subtropical, and Mediterranean regions. This study aims to evaluate the effects of cyantraniliprole on the probing behavior of B. tabaci on tomato. Electrical penetration graph data indicated that on plants treated with cyantraniliprole (foliar application), adult whiteflies of the genetic variant Q2 were not able to reach the phloem and consequently did not perform the activities represented by E1 and E2 waveforms, i.e., phloem salivation (during which inoculation of geminiviruses occurs) and phloem sap ingestion (during which geminiviruses are acquired by the whiteflies), respectively. The complete failure of B. tabaci biotype Q adults to feed from the phloem of tomato plants treated with cyantraniliprole could be explained by rapid cessation of ingestion because of the mode of action of this insecticide. Overall, these findings indicated that cyantraniliprole might represent a useful new tool for producers to protect tomato plants from damage by B. tabaci.
Combined non-invasive functional and anatomical diagnostic work-up in clinical practice: the magnetic resonance and computed tomography in suspected coronary artery disease (MARCC) study.

AIMS The combined use of cardiac computed tomography (CT) coronary angiography (CTCA) and myocardial perfusion imaging allows the non-invasive evaluation of coronary morphology and function. Cardiovascular magnetic resonance (CMR) imaging has several advantages: it can simultaneously assess myocardial perfusion, ventricular and valvular function, cardiomyopathy, and aortic disease and does not involve any additional ionizing radiation. We investigated the combined use of cardiac CT and CMR for the diagnostic evaluation of patients with suspected coronary artery disease (CAD) in clinical practice. METHODS AND RESULTS A total of 192 patients with low or intermediate pre-test probability of CAD underwent CTCA and CMR. All patients with obstructive CAD on CTCA and/or myocardial ischaemia on CMR were referred for invasive coronary angiography (ICA). Fractional flow reserve was measured in case of intermediate lesions (30-70% diameter stenosis) on ICA. Additional cardiac and extra-cardiac findings by CTCA and CMR were registered. The combination of CTCA and CMR significantly improved specificity and overall accuracy (94 and 91%) for the detection of significant CAD compared with their use as a single technique (CTCA 39 and 57%, P < 0.0001; CMR 82 and 83%, P = 0.016). No events were recorded during follow-up (18 ± 6 months) in 104 patients who did not undergo ICA. Furthermore, the combined strategy provided an alternative diagnosis in 19 patients. CONCLUSION The combined use of CTCA and CMR significantly improved specificity and overall diagnostic accuracy for the detection of significant CAD and allowed the detection of alternative (extra-)cardiac disease in patients without significant CAD.
A long-term numerical solution for the insolation quantities of the Earth

We present here a new solution for the astronomical computation of the insolation quantities on Earth spanning from -250 Myr to 250 Myr. This solution has been improved with respect to La93 (Laskar et al. [CITE]) by using a direct integration of the gravitational equations for the orbital motion, and by improving the dissipative contributions, in particular in the evolution of the Earth–Moon System. The orbital solution has been used for the calibration of the Neogene period (Lourens et al. [CITE]), and is expected to be used for age calibrations of paleoclimatic data over 40 to 50 Myr, eventually over the full Palaeogene period (65 Myr) with caution. Beyond this time span, the chaotic evolution of the orbits prevents a precise determination of the Earth's motion. However, the most regular components of the orbital solution could still be used over a much longer time span, which is why we provide here the solution over 250 Myr. Over this time interval, the most striking feature of the obliquity solution, apart from a secular global increase due to tidal dissipation, is a strong decrease of about 0.38 degree in the next few millions of years, due to the crossing of the resonance (Laskar et al. [CITE]). For the calibration of the Mesozoic time scale (about 65 to 250 Myr), we propose to use the term of largest amplitude in the eccentricity, related to , with a fixed frequency of /yr, corresponding to a period of 405 000 yr. The uncertainty of this time scale over 100 Myr should be about , and over the full Mesozoic era.
The Relationship Between Nightmare Frequency and Hypnotic Susceptibility: Valid Correlation or Context-Mediated Artifact?

The possibility that a positive correlation between nightmare frequency and hypnotic susceptibility reported by Belicki and Belicki (1986) was an artifact of administering a sleep questionnaire in the context of a hypnosis experiment was tested in the present study. Measures of vividness and absorption were also administered. Forty subjects, twenty of whom were told that the measures were related to hypnotic responding, completed the questionnaires immediately prior to hypnosis. Twenty other subjects, who completed the questionnaires in contexts unrelated to hypnosis, were later hypnotized. The hypothesis that context of administration of the questionnaires influenced the relationship between the measures and hypnotic susceptibility was not supported. Replication using a larger sample was recommended.
PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum]

Over the last three decades, a large number of evolutionary algorithms have been developed for solving multi-objective optimization problems. However, there lacks an upto-date and comprehensive software platform for researchers to properly benchmark existing algorithms and for practitioners to apply selected algorithms to solve their real-world problems. The demand of such a common tool becomes even more urgent, when the source code of many proposed algorithms has not been made publicly available. To address these issues, we have developed a MATLAB platform for evolutionary multi-objective optimization in this paper, called PlatEMO, which includes more than 50 multiobjective evolutionary algorithms and more than 100 multi-objective test problems, along with several widely used performance indicators. With a user-friendly graphical user interface, PlatEMO enables users to easily compare several evolutionary algorithms at one time and collect statistical results in Excel or LaTeX files. More importantly, PlatEMO is completely open source, such that users are able to develop new algorithms on the basis of it. This paper introduces the main features of PlatEMO and illustrates how to use it for performing comparative experiments, embedding new algorithms, creating new test problems, and developing performance indicators. Source code of PlatEMO is now available at: http://bimk.ahu. edu.cn/index.php? s=/Index/Software/index.html.
Restricted Eigenvalue Properties for Correlated Gaussian Designs

Methods based on l1-relaxation, such as basis pursuit and the Lasso, are very popular for sparse regression in high dimensions. The conditions for success of these methods are now well-understood: (1) exact recovery in the noiseless setting is possible if and only if the design matrix X satisfies the restricted nullspace property, and (2) the squared l2-error of a Lasso estimate decays at the minimax optimal rate k log p / n, where k is the sparsity of the p-dimensional regression problem with additive Gaussian noise, whenever the design satisfies a restricted eigenvalue condition. The key issue is thus to determine when the design matrix X satisfies these desirable properties. Thus far, there have been numerous results showing that the restricted isometry property, which implies both the restricted nullspace and eigenvalue conditions, is satisfied when all entries of X are independent and identically distributed (i.i.d.), or the rows are unitary. This paper proves directly that the restricted nullspace and eigenvalue conditions hold with high probability for quite general classes of Gaussian matrices for which the predictors may be highly dependent, and hence restricted isometry conditions can be violated with high probability. In this way, our results extend the attractive theoretical guarantees on l1-relaxations to a much broader class of problems than the case of completely independent or unitary designs.
Edge-Directed Single-Image Super-Resolution Via Adaptive Gradient Magnitude Self-Interpolation

Super-resolution from a single image plays an important role in many computer vision systems. However, it is still a challenging task, especially in preserving local edge structures. To construct high-resolution images while preserving the sharp edges, an effective edge-directed super-resolution method is presented in this paper. An adaptive self-interpolation algorithm is first proposed to estimate a sharp high-resolution gradient field directly from the input low-resolution image. The obtained high-resolution gradient is then regarded as a gradient constraint or an edge-preserving constraint to reconstruct the high-resolution image. Extensive results have shown both qualitatively and quantitatively that the proposed method can produce convincing super-resolution images containing complex and sharp features, as compared with the other state-of-the-art super-resolution algorithms.
Opinion Extraction & Classification of Reviews from Web Documents

Automatic extraction of opinions on products from Web has been receiving interest increasingly. Such extracted knowledge helps to find out what other people think about the particular product or service. With the growing availability of resources like online review sites and personal blogs, new opportunities and challenges arise as people can, and do, actively use information technologies to seek out and understand the opinions of others. The sudden growth in the area of opinion mining, which deals with the computational techniques for opinion extraction and understanding created an utmost need to understand and view the web in a different prospect. In this paper, we demonstrate an opinion-mining framework that extracts the opinions and views of the consumers/customers, and analyze them to provide concrete market flow along with proven statistical data. The software uses classification, clustering and lingual knowledge-based opinion mining for providing these features.
The bacterial chromosome segregation protein Spo0J spreads along DNA from parS nucleation sites

Regulation of chromosome inheritance is essential to ensure proper transmission of genetic information. To accomplish accurate genome segregation, cells organize their chromosomes and actively separate them prior to cytokinesis. In Bacillus subtilis the Spo0J protein is required for accurate chromosome segregation and it regulates the developmental switch from vegetative growth to sporulation. Spo0J is a DNA‐binding protein that recognizes at least eight identified parS sites located near the origin of replication. As judged by fluorescence microscopy, Spo0J forms discrete foci associated with the oriC region of the chromosome throughout the cell cycle. In an attempt to determine the mechanisms utilized by Spo0J to facilitate productive chromosome segregation, we have investigated the DNA binding activity of Spo0J. In vivo we find Spo0J associates with several kilobases of DNA flanking its specific binding sites (parS) through a parS‐dependent nucleation event that promotes lateral spreading of Spo0J along the chromosome. Using purified components we find that Spo0J has the ability to coat non‐specific DNA substrates. These ‘Spo0J domains’ provide large structures near oriC that could potentially demark, organize or localize the origin region of the chromosome.
An intrusion detection system for smart grid neighborhood area network

Smart grid is expected to improve the efficiency, reliability and economics of current energy systems. Using two-way flow of electricity and information, smart grid builds an automated, highly distributed energy delivery network. In this paper, we present the requirements for intrusion detection systems (IDSs) in neighborhood area network (NAN) as a component of smart grid. We propose an IDS that is implemented in a distributed fashion with respect to NAN's communication and computation needs. An analytical approach is employed for detecting Wormhole attacks. We validate our NAN IDS scheme using OPNET Modeler [1]. The analytical part of the solution is developed in Maple [2] and integrated with OPNET.
Gravitational lensing by Einstein-Born-Infeld black holes

In this paper, charged black holes in general relativity coupled to Born-Infeld electrodynamics are studied as gravitational lenses. The positions and magnifications of the relativistic images are obtained using the strong deflection limit, and the results are compared with those corresponding to a Reissner-Nordstroem black hole with the same mass and charge. As numerical examples, the model is applied to the supermassive Galactic center black hole and to a small size black hole situated in the Galactic halo.