The Bioaccumulation and Physiological Effects of Heavy Metals in Carrots,Onions, and Potatoes and Dietary Implications for Cr and Ni: A Review

The bioaccumulation of heavy metals in food tubers (carrots, onions, and potatoes) as a result of polluted irrigation water has been studied in this review paper. Given that heavy metals can cause a considerable oxidative stress, the impact of these metals to the physiology of the plants has also been assessed. The consumption of vegetables cross‐contaminated with heavy metals carries a considerable risk for humans (especially for children and pregnant women) and these dietary implications are discussed while European Food Safety Authority has been urged to look into this matter of concern.     

DNA replication in the fission yeast: robustness in the face of uncertainty

DNA replication, the process of duplication of a cell's genetic content, must be carried out with great precision every time the cell divides, so that genetic information is preserved. Control mechanisms must ensure that every base of the genome is replicated within the allocated time (S-phase) and only once per cell cycle, thereby safeguarding genomic integrity. In eukaryotes, replication starts from many points along the chromosome, termed origins of replication, and then proceeds continuously bidirectionally until an opposing moving fork is encountered. In contrast to bacteria, where a specific site on the genome serves as an origin in every cell division, in most eukaryotes origin selection appears highly stochastic: many potential origins exist, of which only a subset is selected to fire in any given cell, giving rise to an apparently random distribution of initiation events across the genome. Origin states change throughout the cell cycle, through the ordered formation and modification of origin-associated multisubunit protein complexes. State transitions are governed by fluctuations of cyclin-dependent kinase (CDK) activity and guards in these transitions ensure system memory. We present here DNA replication dynamics, emphasizing recent data from the fission yeast Schizosaccharomyces pombe, and discuss how robustness may be ensured in spite of (or even assisted by) system randomness.     

Semantic-based taxonomy for immersive product design using VR techniques

This work focuses on the design of products related to the aircraft industry. It combines the functionalities and features of an immersive simulation environment, for product design and review, with the existing knowledge about such products and their components. Effort is put in augmenting simulation and design knowledge on virtual geometries, through XML syntax. An immersive environment is developed, which enables the user to design and review a virtual product through highly usable interfaces coupled with product semantics. The semantics are based on a taxonomy defined by certain characteristics/properties of the geometrical objects and the environment. The concept and implementation is tested in an aircraft cabin design use-case.     

A 3D face and hand biometric system for robust user-friendly authentication

A complete authentication system based on fusion of 3D face and hand biometrics is presented and evaluated in this paper. The system relies on a low cost real-time sensor, which can simultaneously acquire a pair of depth and color images of the scene. By combining 2D and 3D facial and hand geometry features, we are able to provide highly reliable user authentication robust to appearance and environmental variations. The design of the proposed system addresses two basic requirements of biometric technologies: dependable performance under real-world conditions along with user convenience. Experimental evaluation on an extensive database recorded in a real working environment demonstrates the superiority of the proposed multimodal scheme against unimodal classifiers in the presence of numerous appearance and environmental variations, thus making the proposed system an ideal solution for a wide range of real-world applications, from high-security to personalization of services and attendance control.     

A novel codification scheme based on the "VITAL" and "DICOM" Standards for telemedicine applications

The field of interest discussed in this study is a novel codification scheme for (vital signs) medical device communication and patient monitoring data interchange, into the context of effective home care service provisioning. With medical technology having developed in isolation and major manufacturers developing their own proprietary communication protocols, which preclude connection to devices from different manufacturers, and with healthcare trends having evolved, pointing to primary care, telecare and home care monitoring, there is an increasing need for technical standardization in healthcare environments and the development of protocols that enable communication in a structured and open way. In this study, a novel codification scheme has been developed, based on two healthcare informatics standards, the VITAL and DICOM Sup. 30, in addressing the robust interchange of waveform and medical data for a home care application. Based on this scheme, we created a real-time facility, consisting of a base unit and a telemedicine (mobile) unit, that enables home telemonitoring, by installing the telemedicine unit at the patient's home while the base unit remains at the physician's office or hospital. The system allows the transmission of vital biosignals (3-lead ECG, pulse rate, blood pressure and SpO2) of the patient. This paper presents an object-oriented design with unified modeling language (UML) of a class hierarchy for exchanging the acquired medical data and performing alert management, and investigates the applicability of the proposed scheme into a commercial patient-connected medical device, thus addressing service and functionality requirements with focus on home-care applications. The system has been validated for technical performance over several telecommunication means and for clinical validity via real patient-involved pilot trials.     

Real-time 2D+3D facial action and expression recognition

This paper presents a completely automated facial action and facial expression recognition system using 2D+3D images recorded in real-time by a structured light sensor. It is based on local feature tracking and rule-based classification of geometric, appearance and surface curvature measurements. Several experiments conducted under relatively non-controlled conditions demonstrate the accuracy and robustness of the approach.     

Improved parameterisation for the numerical modelling of air pollution within an urban street canyon

Numerical modelling for application to wind flow and dispersion in urban environments has noticeably progressed in recent years, to currently represent a widely used tool for simulating mechanical processes governing air pollution in complex geometries. In particular, Computational Fluid Dynamic (CFD) techniques based on RANS (Reynolds-Averaged Navier–Stokes equations) models, are extensively used to produce detailed simulations of the wind flow and turbulence in the urban canopy. However, several studies have indicated that RANS models, and in particular the widely used standard k–? turbulence model, are sensitive to the particular form of inlet profiles for turbulence and velocity. In the present study, simulations of the wind flow and dispersion within an idealised street canyon were carried out using the standard k–? turbulence model provided by the commercial software FLUENT. The aim of this study was to improve the standard k–? model performance by modifying the model parameters according to the chosen form of inlet profiles for velocity and turbulence. Capability of the model to reproduce real wind flow fields, turbulence and concentration patterns was evaluated by comparing the model results against recently published wind tunnel data. Results for turbulent kinetic energy and concentration showed that the redefinition of the default dispersive parameters can significantly enhance the model performance. The newly proposed parameterisations of the standard k–? turbulence model can be readily implemented within commercial CFD software packages, offering a reliable modelling tool for application to urban air pollution and other environmental studies.     

Increasing the accuracy of incremental naive bayes classifier using instance based learning

Along with the increase of data and information, incremental learning ability turns out to be more and more important for machine learning approaches. The online algorithms try not to remember irrelevant information instead of synthesizing all available information (as opposed to classic batch learning algorithms). In this study, we attempted to increase the prediction accuracy of an incremental version of Naive Bayes model by integrating instance based learning. We performed a large-scale comparison of the proposed method with other state-of-the-art algorithms on several datasets and the proposed method produce better accuracy in most cases.     

Expander properties and the cover time of random intersection graphs

We investigate important combinatorial and algorithmic properties of _Gn,m,p$G_{n,m,p}$ random intersection graphs. In particular, we prove that with high probability (a) random intersection graphs are expanders, (b) random walks on such graphs are “rapidly mixing” (in particular they mix in logarithmic time) and (c) the cover time of random walks on such graphs is optimal (i.e. it is Θ(nlogn)$\Theta (nlogn)$). All results are proved for p$p$ very close to the connectivity threshold and for the interesting, non-trivial range where random intersection graphs differ from classical _Gn,p$G_{n,p}$ random graphs.