Computer-assisted measurements of coronal knee joint laxity in vitro are related to low-stress behavior rather than structural properties of the collateral ligaments

The relationship between coronal knee laxity and the restraining properties of the collateral ligaments remains unknown. This study investigated correlations between the structural properties of the collateral ligaments and stress angles used in computer-assisted total knee arthroplasty (TKA), measured with an optically based navigation system. Ten fresh-frozen cadaveric knees (mean age: 81 ± 11 years) were dissected to leave the menisci, cruciate ligaments, posterior joint capsule and collateral ligaments. The resected femur and tibia were rigidly secured within a test system which permitted kinematic registration of the knee using a commercially available image-free navigation system. Frontal plane knee alignment and varus-valgus stress angles were acquired. The force applied during varus-valgus testing was quantified. Medial and lateral bone-collateral ligament-bone specimens were then prepared, mounted within a uni-axial materials testing machine, and extended to failure. Force and displacement data were used to calculate the principal structural properties of the ligaments. The mean varus laxity was 4 ± 1° and the mean valgus laxity was 4 ± 2°. The corresponding mean manual force applied was 10 ± 3 N and 11 ± 4 N, respectively. While measures of knee laxity were independent of the ultimate tensile strength and stiffness of the collateral ligaments, there was a significant correlation between the force applied during stress testing and the instantaneous stiffness of the medial (r = 0.91, p = 0.001) and lateral (r = 0.68, p = 0.04) collateral ligaments. These findings suggest that clinicians may perceive a rate of change of ligament stiffness as the end-point during assessment of collateral knee laxity.

Non-invasive clinical measurement of the viscoelastic properties of tendon using acoustic wave transmission

Background. In isotropic materials, the speed of acoustic wave propagation is governed by the bulk modulus and density. For tendon, which is a structural composite of fluid and collagen, however, there is some anisotropy requiring an adjustment for Poisson's ratio. This paper explores these relationships using data collected, in vivo, on human Achilles tendon and then compares estimates of elastic modulus and hysteresis against published values from in vitro mechanical tests. Methods. Measurements using conventional B-model ultrasound imaging, inverse dynamics and acoustic transmission techniques were used to determine dimensions, loading conditions and longitudinal speed of sound in the Achilles tendon during a series of isometric plantar flexion exercises against body weight. Upper and lower bounds for speed of sound versus tensile stress in the tendon were then modelled and estimates of the elastic modulus and hysteresis of the Achilles tendon derived. Results. Axial speed of sound varied between 1850 and 2090 ms-1 with a non-linear, asymptotic dependency on the level of tensile stress (5-35 MPa) in the tendon. Estimates derived for the elastic modulus of the Achilles tendon ranged between 1-2 GPa. Hysteresis derived from models of the stress-strain relationship, ranged from 3-11%. Discussion. Estimates of elastic modulus agree closely with those previously reported from direct measurements obtained via mechanical tensile tests on major weight bearing tendons in vitro [1,2]. Hysteresis derived from models of the stress-strain relationship is consistent with direct measures from various mamalian tendon (7-10%) but is lower than previous estimates in human tendon (17-26%) [3]. This non-invasive method would appear suitable for monitoring changes in tendon properties during dynamic sporting activities.

Deformation properties of single red blood cell in a stenosed microchannel

Red Blood Cells (RBCs) exhibit different types of motions and different deformed shapes, when they move through capillaries. RBCs can travel through capillaries having smaller diameters than RBCs’ diameter, due to the capacity of high deformability of the viscoelastic RBC membrane. The motion and the steady state shape of the RBCs depend on many factors, such as the geometrical parameters of the microvessel through which blood flows, the RBC membrane bending stiffness and the flow velocity. In this study, the effect of the RBC’s membrane stiffness on the deformation of a single RBC in a stenosed capillary is comprehensively examined. Smoothed Particle Hydrodynamics (SPH) in combination with the two-dimensional spring network membrane model is used to investigate the motion and the deformation property of the RBC. The simulation results demonstrate that the membrane bending stiffness of the RBC has a significant impact on the RBCs’ deformability.

A Near-Infrared Reflectance Spectroscopy Method for Direct Analysis of Several Chemical Components and Properties of Fruit, for Example, Chinese Hawthorn

Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of Chinese hawthorn (Crataegus pinnatifida Bge. var. major) fruit from three geographical regions as well as for the estimation of the total sugar, total acid, total phenolic content, and total antioxidant activity. Principal component analysis (PCA) was used for the discrimination of the fruit on the basis of their geographical origin. Three pattern recognition methods, linear discriminant analysis, partial least-squares-discriminant analysis, and back-propagation artificial neural networks, were applied to classify and compare these samples. Furthermore, three multivariate calibration models based on the first derivative NIR spectroscopy, partial least-squares regression, back-propagation artificial neural networks, and least-squares-support vector machines, were constructed for quantitative analysis of the four analytes, total sugar, total acid, total phenolic content, and total antioxidant activity, and validated by prediction data sets.

Effect of cell wall properties of plant tissue on porosity and shrinkage of dried apple

In this study cell wall properties; moisture distribution, stiffness, thickness and cell dimension have been taken into consideration. Cell wall stiffness dependent on complex combination of plant cell microstructures, composition and water holding capacity of the cell. In this work, some preliminary steps taken by investing cell wall properties of apple in order to predict change of porosity and shrinkage during drying. Two different types of apple cell wall characteristic were investigated to correlate with porosity and shrinkage after convective drying. A scanning electron microscope (SEM), 2N Intron, a pyncometer and image J software were used in order to measure and analyze cell characteristics, water dynamics, porosity and shrinkage. Cell stiffness of red delicious apple was found higher than granny smith apples. A significant relationship has found between cell wall characteristics and both heat and mass transfer. Consequently, evolution of porosity and shrinkage noticeably influenced during convective drying by the nature of cell wall. This study has brought better understanding of porosity and shrinkage of dried food stuff in microscopic (cell) level and would provide better insight to attain energy effective drying process and quality food stuff.

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.

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.