French version of the Family Attitude Scale : psychometric properties and relation of attitudes to the respondent's psychiatric status

The Family Attitude Scale (FAS) is a self-report measure of critical or hostile attitudes and behaviors towards another family member, and demonstrates an ability to predict relapse in psychoses. Data are not currently available on a French version of the scale. The present study developed a French version of the FAS, using a large general population sample to test its internal structure, criterion validity and relationships with the respondents' symptoms and psychiatric diagnoses, and examined the reciprocity of FAS ratings by respondents and their partners. A total of 2072 adults from an urban population undertook a diagnostic interview and completed self-report measures, including an FAS about their partner. A subset of participants had partners who also completed the FAS. Confirmatory factor analyses revealed an excellent fit by a single-factor model, and the FAS demonstrated a strong association with dyadic adjustment. FAS scores of respondents were affected by their anxiety levels and mood, alcohol and anxiety diagnoses, and moderate reciprocity of attitudes and behaviors between the partners was seen. The French version of the FAS has similarly strong psychometric properties to the original English version. Future research should assess the ability of the French FAS to predict relapse of psychiatric disorders.

Tensile properties of graphene nanotube hybrid structures : a molecular dynamics study

Graphene has been reported with record-breaking properties which have opened up huge potential applications. A considerable research has been devoted to manipulate or modify the properties of graphene to target a more smart nanoscale device. Graphene and carbon nanotube hybrid structure (GNHS) is one of the promising graphene derivates, while their mechanical properties have been rarely discussed in literature. Therefore, such a studied is conducted in this paper basing on the large-scale molecular dynamics simulation. The target GNHS is constructed by considering two separate graphene layers that being connected by single-wall carbon nanotubes (SWCNTs) according to the experimental observations. It is found that the GNHSs exhibit a much lower yield strength, Young’s modulus, and earlier yielding comparing with a bilayer graphene sheet. Fracture of studied GNHSs is found to fracture located at the connecting region between carbon nanotubes (CNTs) and graphene. After failure, monatomic chains are normally observed at the front of the failure region, and the two graphene layers at the failure region without connecting CNTs will adhere to each other, generating a bilayer graphene sheet scheme (with a layer distance about 3.4 Å). This study will enrich the current understanding of the mechanical performance of GNHS, which will guide the design of GNHS and shed lights on its various applications.

Synthesis, photophysical and electrochemical properties of aza-boron-diquinomethene complexes

A series of aza-boron-diquinomethene (aza-BODIQU) complexes with different aryl-substituents (B1–B6) were synthesized and characterized. Their photophysical properties were investigated systematically via spectroscopic and theoretical methods. All complexes exhibit strong 1π–π* absorption bands and intense fluorescent emission bands in the visible spectral region at room temperature. The fluorescence spectra in solution show the mirror image features of the S0→S1 absorption bands, which can be assigned to the 1π–π*/1ICT (intramolecular charge transfer) emitting states. Except for B6, all complexes exhibit high photoluminescence quantum yields (ΦPL = 0.47–0.93). The spectroscopic studies and theoretical calculations indicate that the photophysical properties of these aza-BODIQUs can be tuned by the appended aryl-substituents, which would be useful for rational design of boron–fluorine complexes with high emission quantum yield for organic light-emitting applications.

Controlling whole blood activation and resultant clot properties by carboxyl and alkyl functional groups on material surfaces : a possible therapeutic approach for enhancing bone healing

Most research virtually ignores the important role of a blood clot in supporting bone healing. In this study, we investigated the effects of surface functional groups carboxyl and alkyl on whole blood coagulation, complement activation and blood clot formation. We synthesised and tested a series of materials with different ratios of carboxyl (–COOH) and alkyl (–CH3, –CH2CH3 and –(CH2)3CH3) groups. We found that surfaces with –COOH/–(CH2)3CH3 induced a faster coagulation activation than those with –COOH/– CH3 and –CH2CH3, regardless of the –COOH ratios. An increase in –COOH ratios on –COOH/–CH3 and –CH2CH3 surfaces decreased the rate of coagulation activation. The pattern of complement activation was entirely similar to that of surface-induced coagulation. All material coated surfaces resulted in clots with thicker fibrin in a denser network at the clot/material interface and a significantly slower initial fibrinolysis when compared to uncoated glass surfaces. The amounts of platelet-derived growth factor-AB (PDGF-AB) and transforming growth factor-b (TGF-b1) released from an intact clot were higher than a lysed clot. The release of PDGF-AB was found to be correlated with the fibrin density. This study demonstrated that surface chemistry can significantly influence the activation of blood coagulation and complement system, resultant clot structure, susceptibility to fibrinolysis as well as release of growth factors, which are important factors determining the bone healing process.

University Students Depression Inventory : measurement model and psychometric properties

Depression is a serious condition that impacts the academic success and emotional well-being of the university students globally. Keeping in view the debilitating nature of this condition, the present study examined the stability of the factor structure and psychometric properties of the University Student Depression Inventory (USDI; Khawaja and Bryden, 2006). There is a need to translate and validate the scale for Persian speaking students, who live in Iran, its neighboring countries and in many other Western countries. The scale was translated into the Persian language and was used as part of a battery consisting of the scales measuring suicide, depression, stress, happiness and academic achievement. The battery was administered to 359 undergraduate students, and an additional 150 students who had been referred to the mental health center of the University of Tehran as clinical sample. Confirmatory factor analysis upheld the original three-factor structure. The results exhibited internal consistency, test-retest reliability, convergent, and divergent validity, and discriminant validity. There were gender differences and male had higher mean scores on Lethargy, Cognitive\emotion, and Academic motivation subscales than female students. Findings supported the Persian version of the USDI for cross-cultural use as a valid and reliable measure in the diagnosis of depression.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Formal analysis of security properties in trusted computing protocols

This research introduces a general methodology in order to create a Coloured Petri Net (CPN) model of a security protocol. Then standard or user-defined security properties of the created CPN model are identified. After adding an attacker model to the protocol model, the security property is verified using state space method. This approach is applied to analyse a number of trusted computing protocols. The results show the applicability of proposed method to analyse both standard and user-defined properties.

Measuring the mechanical properties of ground ophthalmic polymer surfaces using nanoindentation

This work is motivated by the need to efficiently machine the edges of ophthalmic polymer lenses for mounting in spectacle or instrument frames. The polymer materials used are required to have suitable optical characteristics such high refractive index and Abbe number, combined with low density and high scratch and impact resistance. Edge surface finish is an important aesthetic consideration; its quality is governed by the material removal operation and the physical properties of the material being processed. The wear behaviour of polymer materials is not as straightforward as for other materials due to their molecular and structural complexity, not to mention their time-dependent properties. Four commercial ophthalmic polymers have been studied in this work using nanoindentation techniques which are evaluated as tools for probing surface mechanical properties in order to better understand the grinding response of polymer materials.

Atomistic simulation of surface functionalization on the interfacial properties of graphene-polymer nanocomposites

Graphene has been increasingly used as nano sized fillers to create a broad range of nanocomposites with exceptional properties. The interfaces between fillers and matrix play a critical role in dictating the overall performance of a composite. However, the load transfer mechanism along graphene-polymer interface has not been well understood. In this study, we conducted molecular dynamics simulations to investigate the influence of surface functionalization and layer length on the interfacial load transfer in graphene polymer nanocomposites. The simulation results show that oxygen-functionalized graphene leads to larger interfacial shear force than hydrogen-functionalized and pristine ones during pull-out process. The increase of oxygen coverage and layer length enhances interfacial shear force. Further increase of oxygen coverage to about 7% leads to a saturated interfacial shear force. A model was also established to demonstrate that the mechanism of interfacial load transfer consists of two contributing parts, including the formation of new surface and relative sliding along the interface. These results are believed to be useful in development of new graphene-based nanocomposites with better interfacial properties.

Mechanochemical synthesis of aluminium nanoparticles and their deuterium sorption properties to 2 kbar

A mechanochemical synthesis process has been used to synthesise aluminium nanoparticles. The aluminium is synthesised via a solid state chemical reaction which is initiated inside a ball mill at room temperature between either lithium (Li) or sodium (Na) metal which act as reducing agents with unreduced aluminium chloride (AlCl3). The reaction product formed consists of aluminium nanoparticles embedded within a by-product salt phase (LiCl or NaCl, respectively). The LiCl is washed with a suitable solvent resulting in aluminium (Al) nanoparticles which are not oxidised and are separated from the byproduct phase. Synthesis and washing was confirmed using X-ray diffraction (XRD). Nanoparticles were found to be ∼25–100nm from transmission electron microscopy (TEM) and an average size of 55nm was determined fromsmall angle X-ray scattering (SAXS) measurements. As synthesised Al/NaCl composites, washed Al nanoparticles, and purchased Al nanoparticles were deuterium (D2) absorption tested up to 2 kbar at a variety of temperatures, with no absorption detected within system resolution.

Tensile properties of a boron/nitrogen-doped carbon nanotube–graphene hybrid structure

Doping is an effective approach that allows for the intrinsic modification of the electrical and chemical properties of nanomaterials. Recently, a graphene and carbon nanotube hybrid structure (GNHS) has been reported, which extends the excellent properties of carbon-based materials to three dimensions. In this paper, we carried out a first-time investigation on the tensile properties of the hybrid structures with different dopants. It is found that with the presence of dopants, the hybrid structures usually exhibit lower yield strength, Young’s modulus, and earlier yielding compared to that of a pristine hybrid structure. For dopant concentrations below 2.5% no significant reduction of Young’s modulus or yield strength could be observed. For all considered samples, the failure is found to initiate at the region where the nanotubes and graphene sheets are connected. After failure, monatomic chains are normally observed around the failure region. Dangling graphene layers without the separation of a residual CNT wall are found to adhere to each other after failure with a distance of about 3.4 Å. This study provides a fundamental understanding of the tensile properties of the doped graphene–nanotube hybrid structures, which will benefit the design and also the applications of graphene-based hybrid materials.

A derivation of high-frequency asymptotic values of 3D added mass and damping based on properties of the Cummins' equation

This brief paper provides a novel derivation of the known asymptotic values of three-dimensional (3D) added mass and damping of marine structures in waves. The derivation is based on the properties of the convolution terms in the Cummins's Equation as derived by Ogilvie. The new derivation is simple and no approximations or series expansions are made. The results follow directly from the relative degree and low-frequency asymptotic properties of the rational representation of the convolution terms in the frequency domain. As an application, the extrapolation of damping values at high frequencies for the computation of retardation functions is also discussed.

Numerical investigation of mechanical and thermal dynamic properties of the industrial transformer

Industrial transformer is one of the most critical assets in the power and heavy industry. Failures of transformers can cause enormous losses. The poor joints of the electrical circuit on transformers can cause overheating and results in stress concentration on the structure which is the major cause of catastrophic failure. Few researches have been focused on the mechanical properties of industrial transformers under overheating thermal conditions. In this paper, both mechanical and thermal properties of industrial transformers are jointly investigated using Finite Element Analysis (FEA). Dynamic response analysis is conducted on a modified transformer FEA model, and the computational results are compared with experimental results from literature to validate this simulation model. Based on the FEA model, thermal stress is calculated under different temperature conditions. These analysis results can provide insights to the understanding of the failure of transformers due to overheating, therefore are significant to assess winding fault, especially to the manufacturing and maintenance of large transformers.

Moisture and tensile strength properties of starch-sugar cane nanofibre films

There is an increasing need for biodegradable, environmentally friendly plastics to replace the petroleum-based non-degradable plastics which litter and pollute the environment. Starch-based plastic film composites are becoming a popular alternative because of their low cost, biodegradability, the abundance of starch, and ease with which starch-based films can be chemically modified. This paper reports on the results of using sugar cane bagasse nanofibres to improve the physicochemical properties of starch-based polymers. The addition of bagasse nanofibre (2.5, 5, 10 or 20 wt%) to (modified) potato starch (‘Soluble starch’) reduced the moisture uptake by up to 17 % at 58 % relative humidity (RH). The film’s tensile strength and Young’s Modulus increased by up to 100 % and 200 % with 10 wt% and 20 wt% nanofibre respectively at 58% RH. The tensile strain reduced by up to 70 % at 20 wt% fibre loading. These results indicate that addition of sugar cane bagasse nanofibres significantly improved the properties of starch-based plastic films