Miracle-dz/UniFAR-FTUs huggingface dataset:
Antimicrobial and Antibiofilm Activity of Unionid Mussels from the North of Portugal

ABSTRACT The populations of freshwater mussels belonging to the family Unionidae have been facing drastic changes in terms of diversity and numbers caused by constant aggressions on their natural habitat. Nevertheless, bivalves are capable of developing strategies of defense to overcome potential aggressors. The present work aimed to assess the potential antibacterial capacity of different species of unionid mussels from the north of Portugal. For this purpose, circulating cells (hemocytes), fluids, and mucus were obtained by nonlethal methods from the species Anodonta anatina (Linnaeus), Anodonta cygnea (Linnaeus), Potomida littoralis (Cuvier), and Unio delphinus (Spengler), and tested against bacterial reference strains and multidrug-resistant isolates. The cellular fraction of A. anatina, A. cygnea, and P. littoralis showed antibacterial activity, detected by the agar disc diffusion method, against Bacillus subtilis ATCC 6683, Pseudomonas aeruginosa ATCC 27853 and Acinetobacter baumannii ATCC 19606. Circulating cells from P. littoralis and A. anatina also inhibited Listeria monocytogenes ATCC 19111 and A. cygnea has also inhibited a multidrug-resistant isolate of Pseudomonas putida. The plasma of all mentioned freshwater mussels, used directly or diluted, showed great ability to hamper or inhibit the biofilm formation of Staphylococcus aureus ATCC 25923, P. aeruginosa ATCC 27853, and Escherichia coli ATCC 25922. Anodonta cygnea hampered the biofilm formation by Enterococcus faecalis ATCC 29212 as well. Overall, these results showed that not only cells play a relevant role in the immune system of these species but also the plasma, which likely contains antibiofilm substances. Anodonta cygnea stood out by presenting the best antibacterial inhibition potential.
Effect of 5'-UTR mutations on HCV replication

3 ACKNOWLEDGEMENTS . 5 CONTENTS . 6 LIST OF ABBREVIATIONS . 12 LIST OF TABLES . 16 LIST OF FIGURES . 17 INTRODUCTION . 22 CHAPTER 1 . 22 1.1 HCV BACKGROUND . 22 1.1.
The relationship between vascular endothelial growth factor and histological grade in intracranial meningioma

Background: Meningioma is the most common benign intracranial neoplasm, accounting for 30% of all primary brain tumors. In 90% of cases, meningiomas are benign. Several aspects of molecular biology, including potential biomarkers, have been studied in attempts to better understand the natural history of meningiomas. Vascular endothelial growth factor (VEGF) is a biomarker responsible for inducing physiological and pathological angiogenesis. VEGF expression has been investigated as a potential predictor of several tumor aspects, including growth rate, recurrence rate, brain tissue invasion, peritumoral edema and surgical prognosis, and also as a marker of histological grade. However, there is no consensus in the literature with respect to the association between this biological factor and meningioma. We digitally analyzed immunohistochemical images using ImageJ software with the aim of correlating VEGF expression with tumor histology. Methods: Tissue samples from patients presenting with meningioma who had undergone surgical removal between 2007 and 2016 at the Hospital de Clínicas de Porto Alegre (HCPA), in Southern Brazil, were analyzed to identify possible immunohistochemical associations between VEGF and histological grade and subtype. Results: Seventy-six patients were included; 82% were female, mean age was 59.9 years (range: 18–91). No statistically significant associations were found between VEGF expression and histological grade or subtype (P = 0.310). Conclusion: Our findings suggest that VEGF is frequently present in meningiomas regardless of histological grade and should not be used as a marker of severity or histological grade.
The systematic value of nuclear DNA content in Agave L. and some related genera of the Agavaceae

Summary: C-value was applied as a new criterion to investigate the relationships within the genus Agave L. (Agavaceae). Samples representing nearly 40 taxa were investigated, augmented with data from the literature. Species of Agave have the same basic chromosome number, x = 30, but there are several polyploids. Their somatic nuclear DNA contents (2C), as measured by flow cytometry with propidium iodide falls in a narrow range around 8 pg for the diploids. A comparison is made with nuclear DNA amounts of other related genera. Hosta, with a chromosome complement identical to that of Agave, with 5 large and 25 small chromosomes in the haploid set, is at the base of the Agavaceae clade and has two to three times the amount of nuclear DNA of the other genera.
Seasonal variation of arsenic and its accumulation in straw and grain of rice plant in Ambagarh Chowki block of Rajnandgaon district Chhattisgarh

Rice is the major food crop of this area, as the cultivation of rice requires huge volume of water and long term use of arsenic contaminated ground water for irrigation and arsenic contaminated soil may result into the bio-accumulation of arsenic in rice crop. Accumulation of arsenic was found in rice plant and results revealed that in rice straw arsenic content ranged from 0.006 to 0.082 mg kg with an average of 0.024±0.0198 mg kg and in rice grain, the content of arsenic ranged from 0.003 to 0.057 mg kg with an average of 0.011±0.0123 mg kg which is lower than the permissible limit of arsenic in rice plant that is 1 mg kg (WHO). It was observed that the accumulation of arsenic is high in straw as compared to grain of rice crop.
INVESTIGATION OF DISTURBANCES ON A NOVEL REINFORCEMENT LEARNING BASED CONTROL APPROACH

: Automatic manipulator control poses a complex challenge for control systems with various dynamic and nonlinear effects as well as high dimensionality issues. The aim of this paper is to analyze the behavior of a novel approach for a reinforcement learning based motion control of a 2-DOF robotic manipulator when it is subdues to the effect of a set of different disturbances. The implementation of the presented approach shows the performance of the manipulator when circumstances force him into unexpected situations. The experimental results are presented
Structural and thermodynamical properties of tungsten oxides from first-principles calculations

Tungsten as a material has obtained attention because of its prominent role in fusion reactor design, where it is employed in the divertor region of the first wall. In case of an accident, the tungsten tiles may be exposed to atmospheric conditions and high temperatures which would oxidize the material. Over the years there has been a lot of studies on tungsten oxides, specially WO3, but not from the perspective of tungsten oxidation. The mechanism of oxidation is unclear and a sound understanding of which oxides are formed is still lacking. In this work, first principles calculations have been employed to study the relative phase stabilities from a mechanical and thermodynamical perspective. Oxidation has been studied using a point defect approach to the formation and migration energies of oxygen in tungsten and tungsten oxides. Using the same approach, the role of Y substitutional defects has been studied. Tungsten trioxide is thermodynamically stable with respect to tungsten dioxide but is not as dynamically stable as tungsten dioxide. Oxygen interstitials have a low formation and migration energy in tungsten and several interstitials tend to pair up to form stable clusters, while interstitials in the oxide phases have higher formation energies. In the oxide phases the oxygen vacancy is associated with high formation energies. The difference in phonon frequencies between a pure system and the Y substitutional system is found to be small. The main oxide, tungsten trioxide, is predicted to be dynamically unstable with imaginary phonon frequencies. Therefore, the active components should be chosen such that the mechanical properties of the formed oxide are enhanced. In this study the Y substitutional is found to have no stabilizing effect on tungsten trioxide, however, the full phonon dispersion for the defect system has not been obtained yet.
All-in-One Transformer: Unifying Speech Recognition, Audio Tagging, and Event Detection

Automatic speech recognition (ASR), audio tagging (AT), and acoustic event detection (AED) are typically treated as separate problems, where each task is tackled using specialized system architectures. This is in contrast with the way the human auditory system uses a single (binaural) pathway to process sound signals from diﬀerent sources. In addition, an acoustic model trained to recognize speech as well as sound events could leverage multi-task learning to alleviate data scarcity problems in individual tasks. In this work, an all-in-one (AIO) acoustic model based on the Transformer architecture is trained to solve ASR, AT, and AED tasks simultaneously, where model parameters are shared across all tasks. For the ASR and AED tasks, the Transformer model is combined with the connectionist temporal classiﬁcation (CTC) objective to enforce a monotonic ordering and to utilize timing information. Our experiments demonstrate that the AIO Transformer achieves better performance compared to all baseline systems of various recent DCASE challenge tasks and is suitable for the total transcription of an acoustic scene, i.e., to simultaneously transcribe speech and recognize the acoustic events occurring in it. Abstract Automatic speech recognition (ASR), audio tagging (AT), and acoustic event detection (AED) are typically treated as separate problems, where each task is tackled using specialized system architectures. This is in contrast with the way the human auditory system uses a single (binaural) pathway to process sound signals from different sources. In addition, an acoustic model trained to recognize speech as well as sound events could leverage multi-task learning to alleviate data scarcity problems in individual tasks. In this work, an all-in-one (AIO) acoustic model based on the Transformer architecture is trained to solve ASR, AT, and AED tasks simultaneously, where model parameters are shared across all tasks. For the ASR and AED tasks, the Transformer model is combined with the connectionist temporal classiﬁcation (CTC) objective to enforce a monotonic ordering and to utilize timing information. Our experiments demonstrate that the AIO Transformer achieves better performance compared to all baseline systems of various recent DCASE challenge tasks and is suitable for the total transcription of an acoustic scene, i.e., to simultaneously transcribe speech and recognize the acoustic events occurring in it.
Continuous Object Representation Networks: Novel View Synthesis without Target View Supervision

Novel View Synthesis (NVS) is concerned with synthesizing views under camera viewpoint transformations from one or multiple input images. NVS requires explicit reasoning about 3D object structure and unseen parts of the scene to synthesize convincing results. As a result, current approaches typically rely on supervised training with either ground truth 3D models or multiple target images. We propose Continuous Object Representation Networks (CORN), a conditional architecture that encodes an input image's geometry and appearance that map to a 3D consistent scene representation. We can train CORN with only two source images per object by combining our model with a neural renderer. A key feature of CORN is that it requires no ground truth 3D models or target view supervision. Regardless, CORN performs well on challenging tasks such as novel view synthesis and single-view 3D reconstruction and achieves performance comparable to state-of-the-art approaches that use direct supervision. For up-to-date information, data, and code, please see our project page: this https URL
Making The Most Of Document Analytics

The volume of documents routinely subject to discovery poses challenges in investigations and litigation that extend beyond e-discovery. While predictive coding is gaining increased acceptance as a procedure for identifying responsive documents with less manual review, there is less appreciation of how document analytics can add value in answering document related research questions, or otherwise helping to identify and analyze documents in ways not practical with keywords alone. Having reduced reliance on manual document review to decide which documents to produce, the challenge is to determine quickly what the documents reveal about the critical issues in the case.
On the Maximal Energy of Integral Weighted Trees with Fixed Total Weight Sum

Let m be an integer and W = {w1, w2, . , wn−1} be a positive sequence. Denote by T (n,m) the set of all weighted trees of order n with positive integral weights and fixed total weight sum m. Let further T (n,W ) be the set of all weighted trees of order n with weight sequence W. We first introduce a new method to investigate the energy of weighted graphs, then using this method we determine the unique tree achieving maximal energy in T (n,W ) for w1 ≥ w2 ≥ w3 ≥ w4 > w5 = · · · = wn−1, which supports a conjecture of the present authors in MATCH Commun. Math. Comput. Chem. 75 (2016) 267. Finally, we determine the unique tree having maximal energy in T (n,m) with n ≤ m ≤ n+3, which supports a conjecture by Brualdi et al., Lin. Multilin. Algebra 60 (2012) 1255. ∗Corresponding author †Supported by the National Natural Science Foundation of China, (No. 11571315). ‡Supported by the National Natural Science Foundation of China, (No. 11371205). MATCH Communications in Mathematical and in Computer Chemistry MATCH Commun. Math. Comput. Chem. 76 (2016) 615-633 ISSN 0340 6253
Lessons to Learn from Post-Installation Pollution Levels Assessment of Some Distribution Insulators

Among the main causes of outdoor insulation failures is their poor specifications in terms of leakage distances. This happens when the selected criteria are unable to cope with all the stresses imposed by the changes in environmental pollutions. Therefore, it is important for utilities to fully understand the actual pollution characteristics of the service environment in which the insulators are operating. In this paper, the pollution severity and performance of some 13.2 kV ceramic insulators, sampled in different areas of a Canadian aluminum factory, are assessed. The investigations were performed taking into account the influence of air humidity. Various characteristics were investigated to assess the pollution levels of the insulators, such as equivalent salt deposit density (ESDD) and non-soluble deposit density (NSDD), surface resistance, and leakage current characteristics (density, 3rd harmonic amplitude, and phase). It was witnessed that the insulators, collected around the factory, were much more polluted in comparison to the initial expectation. The pollution level should not be considered static due to the environmental parameters’ dynamics. Lessons to learn: the reliability of an electrical grid is dependent on components whose own reliability is strongly affected by external factors, of which there is often a poor awareness. If care is not taken to re-evaluate the post-installation pollution levels of the insulators, the light may simply turn out!
Effect of different protocols for estrus synchronization on reproductive performance of Santa Inês ewes under Amazon environmental conditions

The objective of this study was to evaluate the effect of different hormonal protocols on the reproductive performance of Santa Inês ewes in Amazon environmental conditions. Twenty-two Santa Inês ewes between 3 and 4 years-old were distributed in a randomized block experimental design, where the treatments consisted of two protocols for estrus synchronization (short and long) with eleven animals each. Data on the occurrence of estrus were described for each protocol. Data of estrus, pregnancy, and prolificity were firstly subjected to ANOVA and a subsequent Tukey’s test. Results were considered significant at p ≤ 0.05. The short-term protocol presented an interesting successful rate, where above 70% ewes tested had estrus. The long-term protocol also achieved a high successful rate, where above 80% ewes tested had estrus. However, comparing the protocols, the long-term protocol presented better results of positive estrus and pregnancy rates in ewes. Thus, it can be concluded that both protocols presented satisfactory results regarding estrus manifestation, and prolificity (lambs produced per ewe). However, under Amazon environmental conditions, the long-term protocol presented better results regarding positive manifestation of estrus and pregnancy rate.
Application of Graphene in Anti-corrosive and Anti-fouling Coating

Graphene has excellent barrier, shielding and chemical stability, the application of graphene in anti-corrosion and anti-fouling coatings has been deeply studied. Studies have shown that adding a certain amount of graphene to traditional coatings can significantly reduce the permeability to corrosive media such as water, oxygen, etc., and can enhance the bioadhesion of coatings and inhibit microbial corrosion. However, some disadvantages also appear in applications of graphene. For example, the strong van der Waals force between graphene lamellae leads to poor agglomeration and dispersion of graphene in coatings; the high chemical stability and hydrophobicity of graphene lead to poor adhesion between graphene and film-forming materials; and the superconductivity of graphene leads to the acceleration of metal corrosion when graphene film fails. In order to diminish ·90· 表 面 技 术 2019 年 6 月 the disadvantages of graphene during application, many methods have been explored, in which modified graphene (GO, RGO, FG) and synthetic graphene composite particles (graphene modified nanoparticles: GO-Al2O3 particles, GO-TiO2 particles, GO-SiO2 particles, etc.; resin-supported graphene composite filler: graphene/polyaniline composite filler, etc.) are main methods. Finally, the development of graphene and its derivatives in anticorrosive and antifouling coatings is prospected.
DICTION INTERVAL ESTIMATION USING NOMINAL VARIABLES

Proposed methods for prediction interval estimation so far focus on cases where input variables are numerical. In datasets with solely nominal input variables, we observe records with the exact same input x, but different real valued outputs due to the inherent noise in the system. Existing prediction interval estimation methods do not use representations that can accurately model such inherent noise in the case of nominal inputs. We propose a new prediction interval estimation method tailored for this type of data, which is prevalent in biology and medicine. We call this method Distribution Adaptive Prediction Interval Estimation given Nominal inputs (DAPIEN) and has four main phases. First, we select a distribution function that can best represent the inherent noise of the system for all unique inputs. Then we infer the parameters θi (e.g. θi = [meani, variancei]) of the selected distribution function for all unique input vectors xi and generate a new corresponding training set using pairs of xi , θi. III). Then, we train a model to predict θ given a new xu. Finally, we calculate the prediction interval for a new sample using the inverse of the cumulative distribution function once the parameters θ is predicted by the trained model. We compared DAPIEN to the commonly used Bootstrap method on three synthetic datasets. Our results show that DAPIEN provides tighter prediction intervals while preserving the requested coverage when compared to Bootstrap. This work can facilitate broader usage of regression methods in medicine and biology where it is necessary to provide tight prediction intervals while preserving coverage when input variables are nominal.
NEUTRONICS AND THERMAL HYDRAULICS MODELLING FOR A SINGLE FUEL ELEMENT IMMERSED IN A HELIUM THERMAL FLUID FOR A DISTRIBUTED ENERGY SOURCE

Energy storage on the scale of the consumption by a city is a challenge. The sun may be seen as the sole source of all energy where the energy received converts from one form to another. Nuclear fuel is also a form of the sun’s energy, as it derives from energy rich nuclei created in some previous supernova. Nuclear fuel has the advantage of energy storage; one can package the fuel for use in future time, and it is a very dense form of energy indeed. The International Atomic Energy Association has embraced the concept of developing small modular reactors to form part of the energy mix of future carbon free electricity sources for the growing urban communities. It is expected that by 2050, the global population will exceed 10 billion citizens and that the citizens will be crowded into the urban cities and communities. Small modular and distributed nuclear energy reactors, complimented with intermittent solar and wind energy resources, could constitute the carbon free power stations for the future urban communities. This paper focuses on the development of the simulation model of a single simplified high temperature gas cooled reactor fuel element surrounded with a helium coolant. A study of the behavior of the neutron economy of the simulated reactor shows the inherent safety of the fuel pebbles. The study confirms that with the aid of computational simulations, engineers can promote strenuous testing of reactor and fuel designs to ensure the safety and sustainability of the plant. Small modular nuclear reactors are capable of having a radioactivity risk load of less than that, which currently prevails in the local community hospitals, and the economics of very long-term energy storage, will make the designs practical and affordable.