Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of excess dietary L-valine on laying hen performance, egg quality, serum free amino acids, immune function and antioxidant enzyme activity

Abstract The aim of this study was to evaluate the tolerance of laying hens for an excessive L-valine (L-val) supply on laying performance, egg quality, serum free amino acids, immune function and antioxidant enzyme activities of laying hens. A total of 720 HyLine Brown hens were allocated to 5 dietary treatment groups, each of which included 6 replicates of 24 hens, from 40 to 47 weeks of age. Graded amounts of L-val were added to the basal diet to achieve concentrations of 0 (control), 1, 2, 3 and 4 g/kg, respectively, in the experimental diets. Supplementing the diet with L-val did not affect egg production, egg mass, egg weight, feed conversion ratio (FCR) or egg quality. The average daily feed intake response to supplemental L-val was quadratic and was maximised at 2.0 g L-val/kg diet. No differences were observed for total protein, total amino acids, blood urea nitrogen (BUN), uric acid, lactate dehydrogenase (LDH), alkaline phosphatase (AKP), Ca and P concentrations among the treatments. Serum albumin concentration increased significantly in response to supplemental L-val and was also maximised at 2.0 g/kg. In addition, serum glucose increased quadratically to peak at 2.0 g L-val/kg diet. Serum free valine increased as L-val concentration increased to 2.0 g/kg diet and then decreased linearly. Supplementation of L-val did not affect the serum concentrations of total antioxidative capability (T-AOC), superoxide dismutase (SOD) and malondialdehyde (MDA). L-val supplementation did not affect the concentrations of immunoglobulins IgG, IgA, IgM and complements (C3 and C4). Serum concentration of triiodothyronine (T3) increased significantly at 2.0 g L-val/kg diet. It is concluded that high concentrations of L-val are tolerated and can be successfully supplemented into diets without detrimental effects on laying performance or immune function of laying hens.
Effect of Chemically Synthesized Aluminum Foil on Solid State Polypyrrole Capacitor

The purpose of this study is to explore the effect on capacitance features of the solid state high performance polypyrrole capacitor with the chemically synthesized aluminum foil. Atomic force microscope (AFM) was used to analyze the surface structure of the chemically synthesized aluminum foil for the experiment and distribution of polypyrrole on the surface of the foil was observed and analyzed through scanning electron microscope (SEM) and energy dispersive x-ray spectrometer (EDS). Finally, evaluation of electric performance was conducted so as to establish the parameters for the surface structure of the chemically synthesized foil with the best series capacitance features.
Operational risk assessment of wind turbines

This paper presents a framework for operational risk assessment of wind turbines (WTs). In the framework, a model for operational risk assessment of WT converters is established while considering the converter topological structures and the risk assessment of power modules, including insulated gate bipolar translator (IGBTs), diodes, and DC link capacitors. The WT anomaly detection is based on supervisory control and data acquisition (SCADA) data of wind farms. With the WT anomaly detection, a WT short-term outage estimation model is developed involving both probability of operation of WT protection relays and statistical results of WT outages. The short-term outage probability of WT converters and other important components including the gearboxes, the generators, the main bearings, and the pitch systems are integrated to evaluate the operational risk of real 1.5 MW WTs.
Polypropylene–nanosilica-filled composites: Effects of epoxy-resin-grafted nanosilica on the structural, thermal, and dynamic mechanical properties

This article reports a comparative study of polypropylene (PP) nanocomposites synthesized with nanosilica (NS) and diglycidyl ether of bisphenol A, an epoxy-resin-grafted nanosilica (ENS), as nanofillers. These nanocomposites were prepared with the melt-mixing method at a constant loading level of 2.5 wt %; this loading level was much lower than that used for fillers in conventional composites. The effects of pure NS and ENS on the thermal, structural, mechanical, and dynamic mechanical properties of PP were analyzed with wide-angle X-ray diffraction, transmission electron microscopy, thermogravimetric analysis, differential scanning calorimetry, dynamic mechanical analysis, and scanning electron microscopy. The transmission electron microscopy studies showed a better dispersion of ENS in the PP matrix, that is, in the polypropylene-epoxy-resin-grafted nanosilica (PP–ENS) nanocomposite, in comparison with NS in the PP matrix, that is, in the polypropylene–nanosilica (PP–NS) nanocomposite. Also, the thermogravimetric analysis results showed a higher thermal stability for PP–ENS than PP–NS. Furthermore, the dynamic mechanical analysis studies showed an increase in the elastic modulus and glass-transition temperature for PP–ENS with respect to PP–NS. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 2117–2124, 2006
High DNA melting temperature predicts transcription start site location in human and mouse

The accurate computational prediction of transcription start sites (TSS) in vertebrate genomes is a difficult problem. The physicochemical properties of DNA can be computed in various ways and a many combinations of DNA features have been tested in the past for use as predictors of transcription. We looked in detail at melting temperature, which measures the temperature, at which two strands of DNA separate, considering the cooperative nature of this process. We find that peaks in melting temperature correspond closely to experimentally determined transcription start sites in human and mouse chromosomes. Using melting temperature alone, and with simple thresholding, we can predict TSS with accuracy that is competitive with the most accurate state-of-the-art TSS prediction methods. Accuracy is measured using both experimentally and manually determined TSS. The method works especially well with CpG island containing promoters, but also works when CpG islands are absent. This result is clear evidence of the important role of the physical properties of DNA in the process of transcription. It also points to the importance for TSS prediction methods to include melting temperature as prior information.
RnaViz 2: an improved representation of RNA secondary structure

SUMMARY RnaViz has been developed to easily create nice, publication quality drawings of RNA secondary structure. RnaViz 2 supports CT, DCSE, and RNAML input formats and improves on many aspects of the first version, notably portability and structure annotation. RnaViz is written using a hybrid programming approach combining pieces written in C and in the scripting language Tcl/Tk, making the program very portable and extensible. AVAILABILITY Source code, binaries for Linux and MS Windows, and additional documentation are available athttp://rrna.uia. ac.be/rnaviz/
Stereoscopic 3D copy & paste

With the increase in popularity of stereoscopic 3D imagery for film, TV, and interactive entertainment, an urgent need for editing tools to support stereo content creation has become apparent. In this paper we present an end-to-end system for object copy & paste in a stereoscopic setting to address this need. There is no straightforward extension of 2D copy & paste to support the addition of the third dimension as we show in this paper. For stereoscopic copy & paste we need to handle depth, and our core objective is to obtain a convincing 3D viewing experience. As one of the main contributions of our system, we introduce a stereo billboard method for stereoscopic rendering of the copied selection. Our approach preserves the stereo volume and is robust to the inevitable inaccuracies of the depth maps computed from a stereo pair of images. Our system also includes an interactive stereoscopic segmentation tool to achieve high quality object selection. Hence, we focus on intuitive and minimal user interaction, and our editing operations perform within interactive rates to provide immediate feedback.
Avian Influenza

Minor Updates: February 2016 Importance Avian influenza viruses are highly contagious, extremely variable viruses that are widespread in birds. Wild birds in aquatic habitats are thought to be their natural reservoir hosts, but domesticated poultry and other birds can also be infected. Most viruses cause only mild disease in poultry, and are called low pathogenic avian influenza (LPAI) viruses. Highly pathogenic avian influenza (HPAI) viruses can develop from certain LPAI viruses, usually while they are circulating in poultry flocks. HPAI viruses can kill up to 90-100% of the flock, and cause epidemics that may spread rapidly, devastate the poultry industry and result in severe trade restrictions. In poultry, the presence of LPAI viruses capable of evolving into HPAI viruses can also affect international trade. Avian influenza viruses can occasionally affect mammals, including humans, usually after close contact with infected poultry. While infections in people are often limited to conjunctivitis or mild respiratory disease, some viruses can cause severe illness. In particular, Asian lineage H5N1 HPAI viruses have caused rare but lifethreatening infections, now totaling nearly 850 laboratory-confirmed cases since 1997, and H7N9 LPAI viruses have caused more than 600 serious human illnesses in China since 2013. Avian influenza viruses can also infect other species of mammals, sometimes causing severe or fatal disease. In rare cases, avian influenza viruses can become adapted to circulate in a mammalian species. During the last century, such viruses have caused or contributed to at least three pandemics in humans, contributed to the diversity of swine influenza viruses in pigs, and also produced one of the two canine influenza viruses now circulating among dogs.
Crowdsourcing as a methodology to obtain large and varied robotic data sets

For autonomous robots to operate successfully in unknown environments, their computer vision algorithms need to generalize over many different environments. However, due to practical considerations robotic vision experiments are typically limited to a single robot and a few (laboratory) environments. We propose crowdsourcing as a methodology for gathering large and varied robotic data sets. We evaluate the methodology by performing the first crowdsourcing experiment involving actual robots. In particular, we have made a space-game called `Astro Drone' for a toy quad rotor, the Parrot AR drone. Nine months after the game's release, there are 14,628 downloads and 840 contributions, consisting of visual features and drone state estimates. Data mining shows the methodology's potential, providing insights such as the relation between the number of visual features and obstacle distances.
Preparation of Bonelike Apatite Composite Sponge

A novel sponge, coated with bonelike hydroxycarbonate apatite (HCA) on it s skeleton surface, was derived via a particle-leaching technique combined with a b omimetic processing. In the present work, a compact consisting of calcium carbonate / poly(lacti c acid) composite (CCPC) and sucrose formed by hot-pressing, was soaked in the simulated body fluid at 37 °C. Within initial 1 h, the sucrose was completely dissolved out, resulting in the formation of large-sized pores in the compact, and subsequently, after 3 d of soaking, bonelike HCA formed on the skeleton consisting of CCPC. The formed sponge has numerous, large pores of 450 to 580 μm in diamet er, which are connected with channels having a diameter in the range of 70 to 120 μm, as well a high porosity of 89 %.
Novel MRI detection of the ischemic penumbra: direct assessment of metabolic integrity

We describe a novel magnetic resonance imaging technique to directly assess the metabolic integrity of penumbral tissue following stroke. For ischemically stressed tissue to be salvageable, it has to be capable of recovering aerobic metabolism (in place of anaerobic metabolism) on reperfusion. We probed ischemic brain tissue by altering the rate of oxygen delivery using a challenge of 100% oxygen ventilation. Any change from anaerobic to aerobic metabolism should alter the rate of lactate production and hence, levels of tissue lactate. Stroke was induced by permanent middle cerebral artery occlusion in rats. In Series 1 (n = 6), changes in tissue lactate during and following 100% oxygen challenge were monitored using 1H magnetic resonance spectroscopy (MRS). Diffusion weighted imaging (DWI) and perfusion weighted imaging (PWI) were used to locate MRS voxels within the ischemic core, the homotopic contralateral striatum and within PWI/DWI mismatch (i.e. presumed penumbra). After 20 min of oxygen, lactate signal change was −16.1 ± 8.8% (mean ± SD) in PWI/DWI mismatch, +2.8 ± 5.1% in the ischemic core, and −0.6 ± 7.6% in the contralateral striatum. Return to air ventilation for 20 min resulted in a reversal, with lactate increasing by 46 ± 25.3% in the PWI/DWI mismatch, 6.6 ± 6.2% in the ischemic core, and −5 ± 11.4% in the contralateral striatum. In Series 2 (n = 6), a novel form of spectroscopic imaging was used to acquire lactate change maps to spatially identify regions of lactate change within the ischemic brain. This technique has potential clinical utility by identifying tissue that displays anaerobic metabolism capable of recovering aerobic metabolism when oxygen delivery is increased, which could provide a more precise assessment of penumbra. Copyright © 2011 John Wiley & Sons, Ltd.
Generalized Structure for a Single Phase Switched-Capacitor Multilevel Inverter Using a New Multiple DC Link Producer With Reduced Number of Switches

In this paper, initially a new dc/dc converter is proposed which can produce boosted multiple dc link voltages by using the novel switched-capacitor converter (SCC) and with reduced number of switches. In the proposed SCC, voltage of all capacitors is charged by binary asymmetrical pattern as self-balancing and without using any auxiliary circuits. The proposed SCC will boost the input dc power supply voltage without transformer by switching the capacitors in series and in parallel. Next, a new single phase switched-capacitor multilevel inverter (SCMLI) topology which uses the proposed SCC units as virtual dc links have been proposed. The proposed topologies reduce the number of power switches, diodes, isolated dc power supplies, size, and the cost of the system in comparison with conventional similar topologies. For example, by contribution of proposed SCMLI structure, 49 and 137 output voltage levels are made by only 14 and18 power switches and 3 and 4 isolated dc power supplies, respectively. To confirm the performance of proposed topology, various simulation results by PSCAD/EMTDC software and experimental tests are given.
A Flexible Scheme of Self Recovery for Digital Image Protection

This paper proposes a self-embedding method with flexible restoration capability. We present a method of encoding DCT coefficients of each block into reference bits for self-embedding. In order to improve the restoration capability, we classify the selected coefficients into three types, and assign different bits for each type to generate reference bits. The generated reference bits are embedded into the original image, along with authentication bits derived from the content by hash function. On the receiver side, after identifying tampered blocks by authentication bits, reference bits are extracted from the reserved blocks to approximately reconstruct the principal content of the lost information. Three cases of flexible quality restoration are analyzed corresponding to different tampering rates. Even up to 75% of the protected image is tempered; the original content can
Black Holes, Entropy Bound and Causality Violation

The gauge theory - gravity duality has provided us a way of studying QCD at high energies or short distances from straightforward calculations in classical general relativity. Among numerous results obtained so far, one of the most striking is the universality of the ratio of the shear viscosity to the entropy density. For all gauge theories with Einstein gravity dual this ratio has been found to be η/s = 1/4π. In this note, we consider higher curvature-corrected black hole solutions for which η/s can be smaller than 1/4π, thus violating the conjecture bound. Here we shall argue that the Gauss-Bonnet gravity and (Riemann)2 gravity theories, in particular, provide concrete examples in which inconsistency of a theory, such as a violation of microcausality at short distances, and a classical limit on black hole entropy are correlated.
Plausible Repairs for Inconsistent Requirements

Knowledge-based recommenders support users in the identification of interesting items from large and potentially complex assortments. In cases where no recommendation could be found for a given set of requirements, such systems propose explanations that indicate minimal sets of faulty requirements. Unfortunately, such explanations are not personalized and do not include repair proposals which triggers a low degree of satisfaction and frequent cancellations of recommendation sessions. In this paper we present a personalized repair approach that integrates the calculation of explanations with collaborative problem solving techniques. In order to demonstrate the applicability of our approach, we present the results of an empirical study that show significant improvements in the accuracy of predictions for interesting repairs.
Taming Ambiguity in Natural Language Requirements

One of the main tasks of requirements engineering (RE) is the creation of a requirements document that precisely, consistently, and completely describes the functional and non-functional properties of the system to be built. At some point during the RE process, the requirements are written down using a natural language or a requirements specification language. On one hand, natural language is flexible, universal, and wide-spread. On the other hand, natural language requirements are recognized widely as being incomplete, inconsistent, and inherently ambiguous. Semi-formal and formal requirements specification techniques, such as UML [13] or SCR [5], have been proposed to overcome these deficiencies. Completeness and consistency of these specifications can be tackled to some degree mechanically by tools. However, as a recent study shows, ambiguity rarely surfaces during the development of a requirements model [10]. Thus, since a requirements specification technique enforces precision, the resulting requirements model becomes unambiguously wrong. In this paper, we show how to detect ambiguities in natural language requirements using a checklist. We distinguish between linguistic and RE-specific ambiguities. Linguistic ambiguities are those ambiguities that are usually discussed in RE textbooks such as ambiguous pronoun references. RE-specific ambiguities occur with respect to the RE context, which includes the application domain and the system domain. For example, the requirement (1) If the bank customer maintains a minimum balance in his or her checking account, there is no monthly service charge. is ambiguous not because of its linguistic representation, but because of the operational environment and application domain. In the requirements documents that we have investigated, RE-specific ambiguities account for the majority of ambiguities, while pure linguistic ambiguities played a less significant role. In this paper, we present also an approach that allows identifying types of RE-specific ambiguity from a metamodel, e.g., of a requirements specification technique. Based on the identified types of ambiguity, we have developed an improved inspection technique for natural language requirements on the basis of checklists and scenario-based reading.
Internal Fuzzy Neural Model for PID control tuning

This paper presents an internal fuzzy neural model for PID controller tuning. The designed model is used as a predictor in an optimization task for PID controller. It is used a simplified gradient algorithm during the training of the fuzzy neural architecture and for tuning of PID controller’s parameters. The designed tuning algorithm is used for level control of a two cascaded water tanks. The satisfactory results are obtained to prove the algorithm application.
The Information Bottleneck and Geometric Clustering

The information bottleneck (IB) approach to clustering takes a joint distribution P(X,Y) and maps the data X to cluster labels T, which retain maximal information about Y (Tishby, Pereira, & Bialek, 1999). This objective results in an algorithm that clusters data points based on the similarity of their conditional distributions P(Y∣X). This is in contrast to classic geometric clustering algorithms such as k-means and gaussian mixture models (GMMs), which take a set of observed data points {xi}i=1:N and cluster them based on their geometric (typically Euclidean) distance from one another. Here, we show how to use the deterministic information bottleneck (DIB) (Strouse & Schwab, 2017), a variant of IB, to perform geometric clustering by choosing cluster labels that preserve information about data point location on a smoothed data set. We also introduce a novel intuitive method to choose the number of clusters via kinks in the information curve. We apply this approach to a variety of simple clustering problems, showing that DIB with our model selection procedure recovers the generative cluster labels. We also show that, in particular limits of our model parameters, clustering with DIB and IB is equivalent to k-means and EM fitting of a GMM with hard and soft assignments, respectively. Thus, clustering with (D)IB generalizes and provides an information-theoretic perspective on these classic algorithms.
Convergent Numerical Scheme for Singular Stochastic Control with State Constraints in a Portfolio Selection Problem

We consider a singular stochastic control problem with state constraints that arises in problems of optimal consumption and investment under transaction costs. Numerical approximations for the value function using the Markov chain approximation method of Kushner and Dupuis are studied. The main result of the paper shows that the value function of the Markov decision problem (MDP) corresponding to the approximating controlled Markov chain converges to that of the original stochastic control problem as various parameters in the approximation approach suitable limits. All our convergence arguments are probabilistic; the main assumption that we make is that the value function be finite and continuous. In particular, uniqueness of the solutions of the associated HJB equations is neither needed nor available (in the generality under which the problem is considered). Specific features of the problem that make the convergence analysis nontrivial include unboundedness of the state and control space and the cost function; degeneracies in the dynamics; mixed boundary (Dirichlet-Neumann) conditions; and presence of both singular and absolutely continuous controls in the dynamics. Finally, schemes for computing the value function and optimal control policies for the MDP are presented and illustrated with a numerical study.