Rotational velocities of single and binary O-type stars in the Tarantula Nebula

Rotation is a key parameter in the evolution of massive stars, affecting their evolution, chemical yields, ionizing photon budget, and final fate. We determined the projected rotational velocity, υ e sin i, of ~330 O-type objects, i.e. ~210 spectroscopic single stars and ~110 primaries in binary systems, in the Tarantula nebula or 30 Doradus (30 Dor) region. The observations were taken using VLT/FLAMES and constitute the largest homogeneous dataset of multi-epoch spectroscopy of O-type stars currently available. The most distinctive feature of the υ e sin i distributions of the presumed-single stars and primaries in 30 Dor is a low-velocity peak at around 100 km s^-1. Stellar winds are not expected to have spun-down the bulk of the stars significantly since their arrival on the main sequence and therefore the peak in the single star sample is likely to represent the outcome of the formation process. Whereas the spin distribution of presumed-single stars shows a well developed tail of stars rotating more rapidly than 300 km s^-1, the sample of primaries does not feature such a high-velocity tail. The tail of the presumed-single star distribution is attributed for the most part - and could potentially be completely due - to spun-up binary products that appear as single stars or that have merged. This would be consistent with the lack of such post-interaction products in the binary sample, that is expected to be dominated by pre-interaction systems. The peak in this distribution is broader and is shifted toward somewhat higher spin rates compared to the distribution of presumed-single stars. Systems displaying large radial velocity variations, typical for short period systems, appear mostly responsible for these differences.

Effects of the thickness of cross-laminated timber (CLT) panels made from Irish Sitka spruce on mechanical performance in bending and shear

An investigation was carried out on CLT panels made from Sitka spruce in order to establish the effect of the thickness of CLT panels on the bending stiffness and strength and the rolling shear. Bending and shear tests on 3-layer and 5-layer panels were performed with loading in the out-of-plane and in-plane directions. ‘Global’ stiffness measurements were found to correlate well with theoretical values. Based on the results, there was a general tendency that both the bending strength and rolling shear decreased with panel thickness. Mean values for rolling shear ranged from 1.0 N/mm2 to 2.0 N/mm2 .

Design of binary polymeric systems containing ɩ-carrageenan and hydroxypropylcellulose for use in cataract surgery.

This study describes the design and characterisation of the rheological and mechanical properties of binary polymeric systems composed of 2-Hydroxypropylcellulose and ɩ-carrageenan, designed as ophthalmic viscoelastic devices (OVDs). Platforms were characterised using dilute solution, flow and oscillatory rheometry and texture profile analysis. Rheological synergy between the two polymers was observed both in the dilute and gel states. All platforms exhibited pseudoplastic flow. Increasing polymer concentrations significantly decreased the loss tangent and rate index yet increased the storage and loss moduli, consistency, gel hardness, compressibility and adhesiveness, the latter being related to the in-vivo retention properties of the platforms. Binary polymeric platforms exhibited unique physicochemical properties, properties that could not be engineered using mono-polymeric platforms. Using characterisation methods that provide information relevant to their clinical performance, low-cost binary platforms (3% hydroxypropylcellulose and either 1% or 2% ɩ-carrageenan) were identified that exhibited rheological, textural and viscoelastic properties advantageous for use as OVDs.

Development of sustainable, innovative and energy-efficient concrete, based on the integration of all-waste materials: SUS-CON panels for building applications

The building sector requires the worldwide production of 4 billion tonnes of cement annually, consuming more than 40% of global energy and accounting for about 8% of the total CO2 emissions. The SUS-CON project aimed at integrating waste materials in the production cycle of concrete, for both ready-mixed and pre-cast applications, resulting in an innovative light-weight, ecocompatible and cost-effective construction material, made by all-waste materials and characterized by enhanced thermal insulation performance and low embodied energy and CO2. Alkali activated “cementless” binders, which have recently emerged as eco-friendly construction materials, were used in conjunction with lightweight recycled aggregates to produce sustainable concrete for a range of applications. This paper presents some results from the development of a concrete made with a geopolymeric binder (alkali activated fly ash) and aggregate from recycled mixed plastic. Mix optimisation was achieved through an extensive investigation on production parameters for binder and aggregate. The mix recipe was developed for achieving the required fresh and hardened properties. The optimised mix gave compressive strength of about 7 MPa, flexural strength of about 1.3 MPa and a thermal conductivity of 0.34 W/mK. Fresh and hardened properties were deemed suitable for the industrial production of precast products. Precast panels were designed and produced for the construction of demonstration buildings. Mock-ups of about 2.5 x 2.5 x 2.5 m were built at a demo park in Spain both with SUS-CON and Portland cement concrete, monitoring internal and external temperatures. Field results indicate that the SUS-CON mock-ups have better insulation. During the warmest period of the day, the measured temperature in the SUS-CON mock-ups was lower.

Bayesian Dependence Tests for Continuous, Binary and Mixed Continuous-Binary Variables

Tests for dependence of continuous, discrete and mixed continuous-discrete variables are ubiquitous in science. The goal of this paper is to derive Bayesian alternatives to frequentist null hypothesis significance tests for dependence. In particular, we will present three Bayesian tests for dependence of binary, continuous and mixed variables. These tests are nonparametric and based on the Dirichlet Process, which allows us to use the same prior model for all of them. Therefore, the tests are “consistent” among each other, in the sense that the probabilities that variables are dependent computed with these tests are commensurable across the different types of variables being tested. By means of simulations with artificial data, we show the effectiveness of the new tests.

The use of binary polymeric networks in stabilising polyethylene oxide solid dispersions

The objective of this study was to determine if a high Tg polymer (Eudragit® S100) could be used to stabilize amorphous domains of polyethylene oxide (PEO) and hence improve the stability of binary polymer systems containing celecoxib (CX). We propose a novel method of stabilizing the amorphous PEO solid dispersion through inclusion of a miscible, high Tg polymer, namely, that can form strong inter-polymer interactions. The effects of inter-polymer interactions and miscibility between PEO and Eudragit S100 are considered. Polymer blends were first manufactured via hot-melt extrusion at different PEO/S100 ratios (70/30, 50/50, and 30/70 wt/wt). Differential scanning calorimetry and dynamic mechanical thermal analysis data suggested a good miscibility between PEO and S100 polymer blends, particularly at the 50/50 ratio. To further evaluate the system, CX/PEO/S100 ternary mixtures were extruded. Immediately after hot-melt extrusion, a single Tg that increased with increasing S100 content (anti-plasticization) was observed in all ternary systems. The absence of powder X-ray diffractometry crystalline Bragg’s peaks also suggested amorphization of CX. Upon storage (40°C/75% relative humidity), the formulation containing PEO/S100 at a ratio of 50:50 was shown to be most stable. Fourier transform infrared studies confirmed the presence of hydrogen bonding between Eudragit S100 and PEO suggesting this was the principle reason for stabilization of the amorphous CX/PEO solid dispersion system.

The use of binary mixtures of 1-butyl-1-methylpyrrolidinium bis{(trifluoromethyl)sulfonyl}imide and aliphatic nitrile solvents as electrolyte for supercapacitors

Abstract The development of high voltage electrolytes is one of the key aspects for increasing both energy and power density of electrochemical double layer capacitors (EDLCs). The usage of blends of ionic liquids and organic solvents has been considered as a feasible strategy since these electrolytes combine high usable voltages and good transport properties at the same time. In this work, the ionic liquid 1-butyl-1-methylpyrrolidinium bis{(trifluoromethyl)sulfonyl}imide ([Pyrr14][TFSI]) was mixed with two nitrile-based organic solvents, namely butyronitrile and adiponitrile, and the resulting blends were investigated regarding their usage in electrochemical double layer capacitors. Both blends have a high electrochemical stability, which was confirmed by prolonged float tests at 3.2 V, as well as, good transport properties. In fact, the butyronitrile blend reaches a conductivity of 17.14 mS·cm−1 and a viscosity of 2.46 mPa·s at 20 °C, which is better than the state-of-the-art electrolyte (1 mol·dm−3 of tetraethylammonium tetrafluoroborate in propylene carbonate).

Binary Mixtures of 1-Butyl-1-Methylpyrrolidinium Bis{(trifluoromethyl)Sulfonyl}Imide and Aliphatic Nitrile Solvents As Electrolyte for Electrochemical Double Layer Capacitors (Invited).

Electrochemical double layer capacitors (EDLCs), also known as supercapacitors, are promising energy storage devices, especially when considering high power applications [1]. EDLCs can be charged and discharged within seconds [1], feature high power (10 kW·kg-1) and an excellent cycle life (>500,000 cycles). All these properties are a result of the energy storage process of EDLCs, which relies on storing energy by charge separation instead of chemical redox reactions, as utilized in battery systems. Upon charging, double layers are forming at the electrode/electrolyte interface consisting of the electrolyte’s ions and electric charges at the electrode surface.In state-of-the-art EDLC systems activated carbons (AC) are used as active materials and tetraethylammonium tetrafluoroborate ([Et4N][BF4]) dissolved in organic solvents like propylene carbonate (PC) or acetonitrile (ACN) are commonly used as the electrolyte [2]. These combinations of materials allow operative voltages up to 2.7 V - 2.8 V and an energy in the order of 5 Wh·kg-1[3]. The energy of EDLCs is dependent on the square of the operative voltage, thus increasing the usable operative voltage has a strong effect on the delivered energy of the device [1]. Due to their high electrochemical stability, ionic liquids (ILs) were thoroughly investigated as electrolytes for EDLCs, as well as, batteries, enabling high operating voltages as high as 3.2 V - 3.5 V for the former [2]. While their unique ionic structure allows the usage of neat ILs as electrolyte in EDLCs, ILs suffer from low conductivity and high viscosity increasing the intrinsic resistance and, as a result, a lower power output of the device. In order to overcome this issue, the usage of blends of ionic liquids and organic solvents has been considered a feasible strategy as they combine high usable voltages, while still retaining good transport properties at the same time.In our recent work the ionic liquid 1-butyl-1-methylpyrrolidinium bis{(trifluoromethyl)sulfonyl}imide ([Pyrr14][TFSI]) was combined with two nitrile-based organic solvents, namely butyronitrile (BTN) and adiponitrile (ADN), and the resulting blends were investing regarding their usage in electrochemical double layer capacitors [4,5]. Firstly, the physicochemical properties were investigated, showing good transport properties for both blends, which are similar to the state-of-the-art combination of [Et4N][BF4] in PC. Secondly, the electrochemical properties for EDLC application were studied in depth revealing a high electrochemical stability with a maximum operative voltage as high as 3.7 V. In full cells these high voltage organic solvent based electrolytes have a good performance in terms of capacitance and an acceptable equivalent series resistance at cut-off voltages of 3.2 and 3.5 V. However, long term stability tests by float testing revealed stability issues when using a maximum voltage of 3.5 V for prolonged time, whereas at 3.2 V no such issues are observed (Fig. 1).Considering the obtained results, the usage of ADN and BTN blends with [Pyrr14][TFSI] in EDLCs appears to be an interesting alternative to state-of-the-art organic solvent based electrolytes, allowing the usage of higher maximum operative voltages while having similar transport properties to 1 mol∙dm-3 [Et4N][BF4] in PC at the same time.

Carbon Dioxide Uptake from Natural Gas by Binary Ionic Liquid-Water mixtures

Carbon dioxide solubility in a set of carboxylate ionic liquids formulated with stoicheiometric amounts of water is found to be significantly higher than for other ionic liquids previously reported. This is due to synergistic chemical and physical absorption. The formulated ionic liquid/water mixtures show greatly enhanced carbon dioxide solubility relative to both anhydrous ionic liquids and aqueous ionic liquid solutions, and are competitive with commercial chemical absorbers, such as activated N-methyldiethanolamine or monoethanolamine.

Multiclass Adaboost Based on an Ensemble of Binary Adaboosts

This paper presents a multi-class AdaBoost based on incorporating an ensemble of binary AdaBoosts which is organized as Binary Decision Tree (BDT). It is proved that binary AdaBoost is extremely successful in producing accurate classification but it does not perform very well for multi-class problems. To avoid this performance degradation, the multi-class problem is divided into a number of binary problems and binary AdaBoost classifiers are invoked to solve these classification problems. This approach is tested with a dataset consisting of 6500 binary images of traffic signs. Haar-like features of these images are computed and the multi-class AdaBoost classifier is invoked to classify them. A classification rate of 96.7% and 95.7% is achieved for the traffic sign boarders and pictograms, respectively. The proposed approach is also evaluated using a number of standard datasets such as Iris, Wine, Yeast, etc. The performance of the proposed BDT classifier is quite high as compared with the state of the art and it converges very fast to a solution which indicates it as a reliable classifier.

Durability performance of self-compacting concrete (SCC) with binary and ternary mixes of fly ash and limestone filler

The basic objective of this work is to evaluate the durability of self-compacting concrete (SCC) produced in binary and ternary mixes using fly ash (FA) and limestone filler (LF) as partial replacement of cement. The main characteristics that set SCC apart from conventional concrete (fundamentally its fresh state behaviour) essentially depend on the greater or lesser content of various constituents, namely: greater mortar volume (more ultrafine material in the form of cement and mineral additions); proper control of the maximum size of the coarse aggregate; use of admixtures such as superplasticizers. Significant amounts of mineral additions are thus incorporated to partially replace cement, in order to improve the workability of the concrete. These mineral additions necessarily affect the concrete's microstructure and its durability. Therefore, notwithstanding the many well-documented and acknowledged advantages of SCC, a better understanding its behaviour is still required, in particular when its composition includes significant amounts of mineral additions. An ambitious working plan was devised: first, the SCC's microstructure was studied and characterized and afterwards the main transport and degradation mechanisms of the SCC produced were studied and characterized by means of SEM image analysis, chloride migration, electrical resistivity, and carbonation tests. It was then possible to draw conclusions about the SCC's durability. The properties studied are strongly affected by the type and content of the additions. Also, the use of ternary mixes proved to be extremely favourable, confirming the expected beneficial effect of the synergy between LF and FA.

On the reduction theory of binary forms

Cremona developed a reduction theory for binary forms of degree 3 and 4 with integer coefficients, the motivation in the case of quartics being to improve 2-descent algorithms for elliptic curves over Q. In this paper we extend some of these results to forms of higher degree. One application of this is to the study of hyperelliptic curves.

A Binary Classifier for Test Case Feasibility Applied to Automatically Generated Tests of Event-Driven Software

Modern software application testing, such as the testing of software driven by graphical user interfaces (GUIs) or leveraging event-driven architectures in general, requires paying careful attention to context. Model-based testing (MBT) approaches first acquire a model of an application, then use the model to construct test cases covering relevant contexts. A major shortcoming of state-of-the-art automated model-based testing is that many test cases proposed by the model are not actually executable. These \textit{infeasible} test cases threaten the integrity of the entire model-based suite, and any coverage of contexts the suite aims to provide. In this research, I develop and evaluate a novel approach for classifying the feasibility of test cases. I identify a set of pertinent features for the classifier, and develop novel methods for extracting these features from the outputs of MBT tools. I use a supervised logistic regression approach to obtain a model of test case feasibility from a randomly selected training suite of test cases. I evaluate this approach with a set of experiments. The outcomes of this investigation are as follows: I confirm that infeasibility is prevalent in MBT, even for test suites designed to cover a relatively small number of unique contexts. I confirm that the frequency of infeasibility varies widely across applications. I develop and train a binary classifier for feasibility with average overall error, false positive, and false negative rates under 5\%. I find that unique event IDs are key features of the feasibility classifier, while model-specific event types are not. I construct three types of features from the event IDs associated with test cases, and evaluate the relative effectiveness of each within the classifier. To support this study, I also develop a number of tools and infrastructure components for scalable execution of automated jobs, which use state-of-the-art container and continuous integration technologies to enable parallel test execution and the persistence of all experimental artifacts.

Segregation predictions for a binary mixture of granular material under flow conditions in a continuum mechanics framework

Abstract not available