Flexible Multibody Simulation Approach in the Dynamic Analysis of Bone Strains Activity

The objective of this study is to show that bone strains due to dynamic mechanical loading during physical activity can be analysed using the flexible multibody simulation approach. Strains within the bone tissue play a major role in bone (re)modeling. Based on previous studies, it has been shown that dynamic loading seems to be more important for bone (re)modeling than static loading. The finite element method has been used previously to assess bone strains. However, the finite element method may be limited to static analysis of bone strains due to the expensive computation required for dynamic analysis, especially for a biomechanical system consisting of several bodies. Further, in vivo implementation of strain gauges on the surfaces of bone has been used previously in order to quantify the mechanical loading environment of the skeleton. However, in vivo strain measurement requires invasive methodology, which is challenging and limited to certain regions of superficial bones only, such as the anterior surface of the tibia. In this study, an alternative numerical approach to analyzing in vivo strains, based on the flexible multibody simulation approach, is proposed. In order to investigate the reliability of the proposed approach, three 3-dimensional musculoskeletal models where the right tibia is assumed to be flexible, are used as demonstration examples. The models are employed in a forward dynamics simulation in order to predict the tibial strains during walking on a level exercise. The flexible tibial model is developed using the actual geometry of the subject’s tibia, which is obtained from 3 dimensional reconstruction of Magnetic Resonance Images. Inverse dynamics simulation based on motion capture data obtained from walking at a constant velocity is used to calculate the desired contraction trajectory for each muscle. In the forward dynamics simulation, a proportional derivative servo controller is used to calculate each muscle force required to reproduce the motion, based on the desired muscle contraction trajectory obtained from the inverse dynamics simulation. Experimental measurements are used to verify the models and check the accuracy of the models in replicating the realistic mechanical loading environment measured from the walking test. The predicted strain results by the models show consistency with literature-based in vivo strain measurements. In conclusion, the non-invasive flexible multibody simulation approach may be used as a surrogate for experimental bone strain measurement, and thus be of use in detailed strain estimation of bones in different applications. Consequently, the information obtained from the present approach might be useful in clinical applications, including optimizing implant design and devising exercises to prevent bone fragility, accelerate fracture healing and reduce osteoporotic bone loss.

Teaching cross-cultural competence and CLIL: a CLIL approach in International Relations University Courses

International relations professionals need cross-cultural competence and English language communication skills to function in the international arena (Graddol 1997). English language communication skills are necessary not only to communicate with foreign colleagues (Bocanegra-Valle 2014) but also to access the vast amount of knowledge transmitted in English over the internet (Ku, Zussman 2010). This work reports the use of CLIL and cross-cultural training in the University of Messina International Relations Advanced Degree Program as a method to raise students’ level of English as quickly as possible while giving them the essential intercultural skills for work in the international field. The researchbased course program combined cross-cultural communication training (Storti, 1997; Lewis, 1999; Gannon, 2004, Harris and Moran, 2007; U.S Peace Corps Training Handbook 2012,) and intercultural competence skill development (Bennett, 1998). Two objectives were proposed: 1) develop cross-cultural communication competence; 2) bring students up to a B2 level as fast as possible. The final exam demonstrated significant growth in the areas of cross-cultural competence as well as an increase in European Common Framework level ranging from .5 to 1.0 depending on the student. Students expressed their belief that what they had learned would be useful for their future career. Combining CLIL with intercultural competence building seems to be effective in meeting two objectives: increasing English language fluency and developing cross-cultural communication competence. More research is recommended to further document this method for increasing English communication proficiency while developing interculturally competent international professionals.

Optimization of OSEM parameters in myocardial perfusion imaging reconstruction as a function of body mass index: a clinical approach

AbstractObjective:The present study is aimed at contributing to identify the most appropriate OSEM parameters to generate myocardial perfusion imaging reconstructions with the best diagnostic quality, correlating them with patients' body mass index.Materials and Methods:The present study included 28 adult patients submitted to myocardial perfusion imaging in a public hospital. The OSEM method was utilized in the images reconstruction with six different combinations of iterations and subsets numbers. The images were analyzed by nuclear cardiology specialists taking their diagnostic value into consideration and indicating the most appropriate images in terms of diagnostic quality.Results:An overall scoring analysis demonstrated that the combination of four iterations and four subsets has generated the most appropriate images in terms of diagnostic quality for all the classes of body mass index; however, the role played by the combination of six iterations and four subsets is highlighted in relation to the higher body mass index classes.Conclusion:The use of optimized parameters seems to play a relevant role in the generation of images with better diagnostic quality, ensuring the diagnosis and consequential appropriate and effective treatment for the patient.

Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.

A nonparametric method for the measurement of size diversity with emphasis on data standardization

The most suitable method for estimation of size diversity is investigated. Size diversity is computed on the basis of the Shannon diversity expression adapted for continuous variables, such as size. It takes the form of an integral involving the probability density function (pdf) of the size of the individuals. Different approaches for the estimation of pdf are compared: parametric methods, assuming that data come from a determinate family of pdfs, and nonparametric methods, where pdf is estimated using some kind of local evaluation. Exponential, generalized Pareto, normal, and log-normal distributions have been used to generate simulated samples using estimated parameters from real samples. Nonparametric methods include discrete computation of data histograms based on size intervals and continuous kernel estimation of pdf. Kernel approach gives accurate estimation of size diversity, whilst parametric methods are only useful when the reference distribution have similar shape to the real one. Special attention is given for data standardization. The division of data by the sample geometric mean is proposedas the most suitable standardization method, which shows additional advantages: the same size diversity value is obtained when using original size or log-transformed data, and size measurements with different dimensionality (longitudes, areas, volumes or biomasses) may be immediately compared with the simple addition of ln k where kis the dimensionality (1, 2, or 3, respectively). Thus, the kernel estimation, after data standardization by division of sample geometric mean, arises as the most reliable and generalizable method of size diversity evaluation

A Sparse Bayesian Approach for Joint Feature Selection and Classifier Learning

Peer-reviewed

A Co-Processor Approach for Efficient Java Execution in Embedded Systems

This thesis deals with a hardware accelerated Java virtual machine, named REALJava. The REALJava virtual machine is targeted for resource constrained embedded systems. The goal is to attain increased computational performance with reduced power consumption. While these objectives are often seen as trade-offs, in this context both of them can be attained simultaneously by using dedicated hardware. The target level of the computational performance of the REALJava virtual machine is initially set to be as fast as the currently available full custom ASIC Java processors. As a secondary goal all of the components of the virtual machine are designed so that the resulting system can be scaled to support multiple co-processor cores. The virtual machine is designed using the hardware/software co-design paradigm. The partitioning between the two domains is flexible, allowing customizations to the resulting system, for instance the floating point support can be omitted from the hardware in order to decrease the size of the co-processor core. The communication between the hardware and the software domains is encapsulated into modules. This allows the REALJava virtual machine to be easily integrated into any system, simply by redesigning the communication modules. Besides the virtual machine and the related co-processor architecture, several performance enhancing techniques are presented. These include techniques related to instruction folding, stack handling, method invocation, constant loading and control in time domain. The REALJava virtual machine is prototyped using three different FPGA platforms. The original pipeline structure is modified to suit the FPGA environment. The performance of the resulting Java virtual machine is evaluated against existing Java solutions in the embedded systems field. The results show that the goals are attained, both in terms of computational performance and power consumption. Especially the computational performance is evaluated thoroughly, and the results show that the REALJava is more than twice as fast as the fastest full custom ASIC Java processor. In addition to standard Java virtual machine benchmarks, several new Java applications are designed to both verify the results and broaden the spectrum of the tests.

Occlusal and dentofacial characteristics of the deciduous dentition and treatment effects of the eruption guidance appliance in the early mixed dentition

The aim of this investigation was to analyze the dental occlusion in the deciduous dentition, and the effects of orthodontic treatment carried out in the early mixed dentition with the eruption guidance appliance. The deciduous occlusion and craniofacial morphology of 486 children (244 girls and 242 boys) were investigated at the onset of the mixed dentition period (mean age 5.1 years, range 4.0-7.8 years). Treatment in the treatment group and follow-up in the control group were started when the first deciduous incisor was exfoliated (T1) and ended when all permanent incisors and first molars were fully erupted (T2). The mean age of the children was 5.1 years (SD 0.5) at T1 and 8.4 years (SD 0.5) at T2. Treatment was carried out with the eruption guidance appliance. Occlusal changes that took place in 167 children were compared with those of 104 untreated control children. Pre- and post-treatment cephalometric radiographs were taken, and the craniofacial morphology of 115 consecutively treated children was compared with that of 104 control children. The prevalence of malocclusion in the deciduous dentition was 68% or 93% depending on how the cut-off value between the acceptable and non-acceptable occlusal characteristic was defined. The early dentofacial features of children with distal occlusion, large overjet and deepbite differed from those with normal occlusion. However, the skeletal pattern of these three malocclusions showed considerable similarity each being characterized by a retrusive mandible, small maxillo-mandibular difference, convex profile, retrusive lower incisors, and large interincisal angle. In the treatment group, overjet and overbite decreased significantly from T1 to T2. Following treatment, a tooth-to-tooth contact was found in 99% of the treated children but only in 24% of the controls. A Class I molar relationship was observed in 90% of the children in the treatment group, and in 48% in the control group. Good alignment of the incisors was observed in 98% of the treated children, whereas upper crowding was found in 32% and lower crowding in 47% of the controls. A significant difference between the groups was found in the mandibular length, midfacial length and maxillo-mandibular differential. The occlusal correction, brought about by the eruption guidance appliance, was achieved mainly through changes in the dentoalveolar region of the mandible. In addition, the appliance seemed to enhance the growth of the mandible. Treatment in the early mixed dentition using the eruption guidance appliance is an effective method to normalize occlusion and reduce further need of orthodontic treatment. Only few spontaneous corrective changes can be expected without active intervention.

A hybrid feature selection approach for the early diagnosis of Alzheimer's disease

Objective. Recently, significant advances have been made in the early diagnosis of Alzheimer’s disease from EEG. However, choosing suitable measures is a challenging task. Among other measures, frequency Relative Power and loss of complexity have been used with promising results. In the present study we investigate the early diagnosis of AD using synchrony measures and frequency Relative Power on EEG signals, examining the changes found in different frequency ranges. Approach. We first explore the use of a single feature for computing the classification rate, looking for the best frequency range. Then, we present a multiple feature classification system that outperforms all previous results using a feature selection strategy. These two approaches are tested in two different databases, one containing MCI and healthy subjects (patients age: 71.9 ± 10.2, healthy subjects age: 71.7 ± 8.3), and the other containing Mild AD and healthy subjects (patients age: 77.6 ± 10.0; healthy subjects age: 69.4± 11.5). Main Results. Using a single feature to compute classification rates we achieve a performance of 78.33% for the MCI data set and of 97.56 % for Mild AD. Results are clearly improved using the multiple feature classification, where a classification rate of 95% is found for the MCI data set using 11 features, and 100% for the Mild AD data set using 4 features. Significance. The new features selection method described in this work may be a reliable tool that could help to design a realistic system that does not require prior knowledge of a patient's status. With that aim, we explore the standardization of features for MCI and Mild AD data sets with promising results.

The effect on prices of the attributes of holiday hotels: a hedonic prices approach

This article examines the effect on price of different characteristics of holiday hotels in the sun-and-beach segment. The effect on price is estimated under the hedonic function perspective by means of random effect models, known also as mixed or panel models. Some 82,000 prices were gathered between 1991 and 1998 from tour operator catalogues. The study reveals huge price differences between 4-star hotels and the rest, coupled with practically no difference between 1-star and 2-star hotels. Other attributes with a significant effect on price are town, hotel size, distance to the beach and availability of parking place. The results can assist hotel managers in shaping pricing and investment strategies

The attenuation of concentrations model: a new method for assessing mercury mobility in sediments

In this work we propose a new approach for the determination of the mobility of mercury in sediments based on spatial distribution of concentrations. We chose the Tainheiros Cove, located in the Todos os Santos Bay, Brazil, as the study area, for it has a history of mercury contamination due to a chloro-alkali plant that was active during 12 years. Twenty-six surface sediment samples were collected from the area and mercury concentrations were measured by cold vapour atomic absorption spectrophotometry. A contour map was constructed from the results, indicating that mercury accumulated in a "hot spot" where concentrations reach more than 1 µg g-1. The model is able to estimate mobility of mercury in the sediments based on the distances between iso-concentration contours that determines an attenuation of concentrations factor. Values of attenuation ranged between 0.0729 (East of the hot spot, indicating higher mobility) to 0.7727 (North of the hot spot, indicating lower mobility).

Impedance field and noise of submicrometer n+ nn+ diodes: analytical approach

A theoretical model for the noise properties of n+nn+ diodes in the drift-diffusion framework is presented. In contrast with previous approaches, our model incorporates both the drift and diffusive parts of the current under inhomogeneous and hot-carrier conditions. Closed analytical expressions describing the transport and noise characteristics of submicrometer n+nn+ diodes, in which the diode base (n part) and the contacts (n+ parts) are coupled in a self-consistent way, are obtained

A state-space approach for measuring regional manufacturing production indices

In this paper we propose a latent variable model, in the spirit of Israilevich and Kuttner (1993), to measure regional manufacturing production. To test the validity of the proposed methodology, we have applied it for those Spanish regions that have a direct quantitative index. The results demonstrate the accuracy of the methodology proposed and show that it can overcome some of the difficulties of the indirect method applied by the INE, the Spanish National Institute of Statistics.

Dynamic patterns of flow in the workplace: characterizing within-individual variability using a complexity science approach

As a result of the growing interest in studying employee well-being as a complex process that portrays high levels of within-individual variability and evolves over time, this present study considers the experience of flow in the workplace from a nonlinear dynamical systems approach. Our goal is to offer new ways to move the study of employee well-being beyond linear approaches. With nonlinear dynamical systems theory as the backdrop, we conducted a longitudinal study using the experience sampling method and qualitative semi-structured interviews for data collection; 6981 registers of data were collected from a sample of 60 employees. The obtained time series were analyzed using various techniques derived from the nonlinear dynamical systems theory (i.e., recurrence analysis and surrogate data) and multiple correspondence analyses. The results revealed the following: 1) flow in the workplace presents a high degree of within-individual variability; this variability is characterized as chaotic for most of the cases (75%); 2) high levels of flow are associated with chaos; and 3) different dimensions of the flow experience (e.g., merging of action and awareness) as well as individual (e.g., age) and job characteristics (e.g., job tenure) are associated with the emergence of different dynamic patterns (chaotic, linear and random).