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Image fusion of infrared and visible images to obtain high-quality fusion images with prominent infrared targets has important applications in various engineering fields. However, current fusion processes encounter problems such as unclear texture details and imbalanced infrared targets and texture detailed information, which lead to information loss. To address these issues, this paper proposes a method for infrared and visible image fusion based on a specific dual-attention mechanism (SDAM). This method employs an end-to-end network structure, which includes the design of channel attention and spatial attention mechanisms. Through these mechanisms, the method can fully exploit the texture details in the visible images while preserving the salient information in the infrared images. Additionally, an optimized loss function is designed to combine content loss, edge loss, and structure loss to achieve better fusion effects. This approach can fully utilize the texture detailed information of visible images and prominent information in infrared images, while maintaining better brightness and contrast, which improves the visual effect of fusion images. Through conducted ablation experiments and comparative evaluations on public datasets, our research findings demonstrate that the SDAM method exhibits superior performance in both subjective and objective assessments compared to the current state-of-the-art fusion methods. [ABSTRACT FROM AUTHOR]

The capitalisation on and transfer of technological, engineering and scientific knowledge associated with empirical know-how is an important issue for the sustainability and development of manufacturing. Indeed, certain sectors of industry are facing the increasing ageing of the labour force, recruitment difficulties and high staff turnover, leading to a loss of knowledge and know-how. In a context of numerical and digital transition and the migration of processes to industry 4.0, one of major challenges manufacturers face today is their capacity to build intelligent platforms for acquiring, storing and transferring their know-how and knowledge. It is crucial to create new media and tools for staff training and development capable of capturing knowledge and reusing it to create a project history through expertise and data collection. This paper presents the methodology and guidelines for implementing electronic knowledge books (eK-Books), along with their uses. The eK-Book is a semantic web-based hypertext medium (channel) allowing stakeholders to capitalise on, structure and transfer knowledge by using concept maps, process maps, influence graphs, downloadable documents, web pages and hypermedia knowledge sheets. They are intended for engineers, expert or novice technicians, manufacturers, sector coordinators and plant managers, as well as trainers and learners. They are usable and manageable in all types of environments and with different levels of accessibility. This paper highlights (1) the transfer knowledge capacity of eK-Books and (2) their usability in two agri-food sectors namely (1) the cheese sector with protected designation of origin (PDO) and protected geographical indication (PGI), and (2) the butchery and cold meat sectors. [ABSTRACT FROM AUTHOR]

This study demonstrates the effect of nitrogen doping on the surface state densities (Nss) of monolayer MoS2 and its effect on the responsivity and the response time of the photodetector. Our experimental results shows that by doping monolayer MoS2 by nitrogen, the surface state (Nss) increases thereby increasing responsivity. The mathematical model included in the paper supports the relation of photocurrent gain and its dependency on trap level which states that the increasing the trap density increases the photocurrent gain and the same is observed experimentally. The experimental results at room temperature revealed that nitrogen doped MoS2 have a high NSS of 1.63 X 1013 states/m2/eV compared to undoped MoS2 of 4.2 x 1012 states/m2/eV. The increase in Nss in turn is the cause for rise in trap states which eventually increases the value of photo responsivity from 65.12 A/W (undoped MoS2) to 606.3 A/W (nitrogen doped MoS2). The response time calculated for undoped MoS2 was 0.85 sec and for doped MoS2 was 0.35 sec. Finally, to verify the dependence of surface states on the responsivity, the surface states were varied by varying temperature and it was observed that upon increment in temperature, the surface states decreases which causes the responsivity values also to decrease. [ABSTRACT FROM AUTHOR]

This paper presents the design and construction of vacuum preloading incorporated with electroosmosis (VPE) engineering application for the treatment of soft soil on complex terrain for sluice foundation excavation in order to reduce the amount of cement used in construction. Monitoring was conducted during the VPE treatment and laboratory geotechnical tests were carried out once the treatment came to an end. Results show that the electrification mode has a significant influence on electric energy consumption. Stepped-up voltage helped in saving electric energy while electrode conversion consumed a lot of electric energy. The dispersion of soil parameters became larger after VPE treatment. The stability of physical parameters is better than the mechanical parameters, and the latter is better than the deformation parameters. Soil water content has a linear relationship with density and compression coefficient. The given linear fitting equations can help in simplifying the calculation and acquisition of these indexes. Although the mean values of the soil index parameters slightly improved, their coefficient of variation (COV) significantly increased. These locations with improved index parameters scattering in the construction site ensured that the subsequent construction tasks such as pit slope and excavation were successfully realized in this area. [ABSTRACT FROM AUTHOR]

The inherent weakly damped resonant modes of the piezoelectric nanopositioning platform and the presence of model uncertainty seriously affect the performance of the system. A structured H∞ design is used in this paper to solve the accuracy and robustness problems respectively using a two-loop control structure. The multiple performance requirements of the system are constituted into an H∞ optimization matrix containing multi-dimensional performance diagonal decoupling outputs, and an inner damping controller d is set according to the damping of the resonant modes; the second-order robust feedback controller is preset in the inner loop to improve the robustness of the system; the tracking controller is connected in series in the outer loop to achieve high accuracy scanning; finally, the structured H∞ controller is designed to meet the multiple performance requirements. To verify the effectiveness of the proposed structured H∞ control, simulation comparison experiments are done with the integral resonant control (IRC) and H∞ controller. The results demonstrate that the designed structured H∞ controller achieves higher tracking accuracy compared to the IRC and H∞ controllers under grating input signals of 5, 10, and 20 Hz. Moreover, it has good robustness under 600g and 1000g loads and high frequency disturbances close to the resonant frequency of the system, meeting multiple performance requirements. Compared with the traditional H∞ control, yet with lower complexity and transparency, which is more suitable for engineering practice applications. [ABSTRACT FROM AUTHOR]

Since its inception in the mid-eighties, the field of construction grammar has been steadily growing and constructionist approaches to language have by now become a mainstream paradigm for linguistic research. While the construction grammar community has traditionally focused on theoretical, experimental and corpus-based research, the importance of computational methodologies is now rapidly increasing. This movement has led to the establishment of a number of exploratory computational construction grammar formalisms, which facilitate the implementation of construction grammars, as well as their use for language processing purposes. Yet, implementing large grammars using these formalisms still remains a challenging task, partly due to a lack of powerful and user-friendly tools for computational construction grammar engineering. In order to overcome this obstacle, this paper introduces the FCG Editor, a dedicated and innovative integrated development environment for the Fluid Construction Grammar formalism. Offering a straightforward installation and a user-friendly, interactive interface, the FCG Editor is an accessible, yet powerful tool for construction grammarians who wish to operationalise their construction grammar insights and analyses in order to computationally verify them, corroborate them with corpus data, or integrate them in language technology applications. [ABSTRACT FROM AUTHOR]

The mass digitization of books is changing the way information is created, disseminated and displayed. Electronic book readers (e-readers) generally refer to two main display technologies: the electronic ink (E-ink) and the liquid crystal display (LCD). Both technologies have advantages and disadvantages, but the question whether one or the other triggers less visual fatigue is still open. The aim of the present research was to study the effects of the display technology on visual fatigue. To this end, participants performed a longitudinal study in which two last generation e-readers (LCD, E-ink) and paper book were tested in three different prolonged reading sessions separated by - on average - ten days. Results from both objective (Blinks per second) and subjective (Visual Fatigue Scale) measures suggested that reading on the LCD (Kindle Fire HD) triggers higher visual fatigue with respect to both the E-ink (Kindle Paperwhite) and the paper book. The absence of differences between E-ink and paper suggests that, concerning visual fatigue, the E-ink is indeed very similar to the paper. [ABSTRACT FROM AUTHOR]

Input-output analysis has been proven to be a powerful instrument for estimating embodied (direct plus indirect) energy usage through economic sectors. Using 9 economic input-output tables of years 1987, 1990, 1992, 1995, 1997, 2000, 2002, 2005, and 2007, this paper analyzes energy flows for the entire city of Beijing and its 30 economic sectors, respectively. Results show that the embodied energy consumption of Beijing increased from 38.85 million tonnes of coal equivalent (Mtce) to 206.2 Mtce over the past twenty years of rapid urbanization; the share of indirect energy consumption in total energy consumption increased from 48% to 76%, suggesting the transition of Beijing from a production-based and manufacturing-dominated economy to a consumption-based and service-dominated economy. Real estate development has shown to be a major driving factor of the growth in indirect energy consumption. The boom and bust of construction activities have been strongly correlated with the increase and decrease of system-side indirect energy consumption. Traditional heavy industries remain the most energy-intensive sectors in the economy. However, the transportation and service sectors have contributed most to the rapid increase in overall energy consumption. The analyses in this paper demonstrate that a system-wide approach such as that based on input-output model can be a useful tool for robust energy policy making. [ABSTRACT FROM AUTHOR]

In this paper, we propose designing transportation network topology and traffic distribution under fluctuating conditions using a bio-inspired algorithm. The algorithm is inspired by the adaptive behavior observed in an amoeba-like organism, plasmodial slime mold, more formally known as plasmodium of Physarum plycephalum. This organism forms a transportation network to distribute its protoplasm, the fluidic contents of its cell, throughout its large cell body. In this process, the diameter of the transportation tubes adapts to the flux of the protoplasm. The Physarum algorithm, which mimics this adaptive behavior, has been widely applied to complex problems, such as maze solving and designing the topology of railroad grids, under static conditions. However, in most situations, environmental conditions fluctuate; for example, in power grids, the consumption of electric power shows daily, weekly, and annual periodicity depending on the lifestyles or the business needs of the individual consumers. This paper studies the design of network topology and traffic distribution with oscillatory input and output traffic flows. The network topology proposed by the Physarum algorithm is controlled by a parameter of the adaptation process of the tubes. We observe various rich topologies such as complete mesh, partial mesh, Y-shaped, and V-shaped networks depending on this adaptation parameter and evaluate them on the basis of three performance functions: loss, cost, and vulnerability. Our results indicate that consideration of the oscillatory conditions and the phase-lags in the multiple outputs of the network is important: The building and/or maintenance cost of the network can be reduced by introducing the oscillating condition, and when the phase-lag among the outputs is large, the transportation loss can also be reduced. We use stability analysis to reveal how the system exhibits various topologies depending on the parameter. [ABSTRACT FROM AUTHOR]

Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH) plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures–all key capabilities of biological nervous systems and modern machine learning algorithms with real world application. [ABSTRACT FROM AUTHOR]

In 1979 Haralick famously introduced a method for analyzing the texture of an image: a set of statistics extracted from the co-occurrence matrix. In this paper we investigate novel sets of texture descriptors extracted from the co-occurrence matrix; in addition, we compare and combine different strategies for extending these descriptors. The following approaches are compared: the standard approach proposed by Haralick, two methods that consider the co-occurrence matrix as a three-dimensional shape, a gray-level run-length set of features and the direct use of the co-occurrence matrix projected onto a lower dimensional subspace by principal component analysis. Texture descriptors are extracted from the co-occurrence matrix evaluated at multiple scales. Moreover, the descriptors are extracted not only from the entire co-occurrence matrix but also from subwindows. The resulting texture descriptors are used to train a support vector machine and ensembles. Results show that our novel extraction methods improve the performance of standard methods. We validate our approach across six medical datasets representing different image classification problems using the Wilcoxon signed rank test. The source code used for the approaches tested in this paper will be available at: http://www.dei.unipd.it/wdyn/?IDsezione=3314&IDgruppo_pass=124&preview=. [ABSTRACT FROM AUTHOR]

This paper proposed a novel bionic selective visual attention mechanism to quickly select regions that contain salient objects to reduce calculations. Firstly, lateral inhibition filtering, inspired by the limulus’ ommateum, is applied to filter low-frequency noises. After the filtering operation, we use Artificial Bee Colony (ABC) algorithm based selective visual attention mechanism to obtain the interested object to carry through the following recognition operation. In order to eliminate the camera motion influence, this paper adopted ABC algorithm, a new optimization method inspired by swarm intelligence, to calculate the motion salience map to integrate with conventional visual attention. To prove the feasibility and effectiveness of our method, several experiments were conducted. First the filtering results of lateral inhibition filter were shown to illustrate its noise reducing effect, then we applied the ABC algorithm to obtain the motion features of the image sequence. The ABC algorithm is proved to be more robust and effective through the comparison between ABC algorithm and popular Particle Swarm Optimization (PSO) algorithm. Except for the above results, we also compared the classic visual attention mechanism and our ABC algorithm based visual attention mechanism, and the experimental results of which further verified the effectiveness of our method. [ABSTRACT FROM AUTHOR]

Background: The current strategies for making electronic devices are generally time, water, material and energy consuming. Here, the direct writing of composite functional circuits through comprehensive use of GaIn10-based liquid metal inks and matching material is proposed and investigated, which is a rather easy going and cost effective electronics fabrication way compared with the conventional approaches. Methods: Owing to its excellent adhesion and electrical properties, the liquid metal ink was demonstrated as a generalist in directly making various basic electronic components such as planar resistor, inductor and capacitor or their combination and thus composing circuits with expected electrical functions. For a precise control of the geometric sizes of the writing, a mask with a designed pattern was employed and demonstrated. Mechanisms for justifying the chemical components of the inks and the magnitudes of the target electronic elements so as to compose various practical circuits were disclosed. Results: Fundamental tests on the electrical components including capacitor and inductor directly written on paper with working time up to 48 h and elevated temperature demonstrated their good stability and potential widespread adaptability especially when used in some high frequency circuits. As the first proof-of-concept experiment, a typical functional oscillating circuit including an integrated chip of 74HC04 with a supply voltage of 5 V, a capacitor of 10 nF and two resistors of 5 kΩ and 1 kΩ respectively was directly composed on paper through integrating specific electrical elements together, which presented an oscillation frequency of 8.8 kHz. Conclusions: The present method significantly extends the roles of the metal ink in recent works serving as only a single electrical conductor or interconnecting wires. It opens the way for directly writing out complex functional circuits or devices on different substrates. Such circuit composition strategy has generalized purpose and can be extended to more areas, even daily pervasive electronics. [ABSTRACT FROM AUTHOR]

The reliability of the electrical distribution system is a contemporary research field due to diverse applications of electricity in everyday life and diverse industries. However a few research papers exist in literature. This paper proposes a methodology for assessing the reliability of 33/11 Kilovolt high-power stations based on average time between failures. The objective of this paper is to find the optimal fit for the failure data via time between failures. We determine the parameter estimation for all components of the station. We also estimate the reliability value of each component and the reliability value of the system as a whole. The best fitting distribution for the time between failures is a three parameter Dagum distribution with a scale parameter and shape parameters and . Our analysis reveals that the reliability value decreased by 38.2% in each 30 days. We believe that the current paper is the first to address this issue and its analysis. Thus, the results obtained in this research reflect its originality. We also suggest the practicality of using these results for power systems for both the maintenance of power systems models and preventive maintenance models. [ABSTRACT FROM AUTHOR]

Background: The confirmatory diagnosis of Osteogenesis Imperfecta (OI) requires invasive, commonly bone biopsy, time consuming and destructive methods. This paper proposes an alternative method using a combination of two-photon excitation fluorescence (TPEF) and second-harmonic generation (SHG) microscopies from easily obtained human skin biopsies. We show that this method can distinguish subtypes of human OI. Methodology/Principal Findings: Different aspects of collagen microstructure of skin fresh biopsies and standard H&E-stained sections of normal and OI patients (mild and severe forms) were distinguished by TPEF and SHG images. Moreover, important differences between subtypes of OI were identified using different methods of quantification such as collagen density, ratio between collagen and elastic tissue, and gray-level co-occurrence matrix (GLCM) image-pattern analysis. Collagen density was lower in OI dermis, while the SHG/autofluorescence index of the dermis was significantly higher in OI as compared to that of the normal skin. We also showed that the energy value of GLCM texture analysis is useful to discriminate mild from severe OI and from normal skin. Conclusions/Significance: This work demonstrated that nonlinear microscopy techniques in combination with image-analysis approaches represent a powerful tool to investigate the collagen organization in skin dermis in patients with OI and has the potential to distinguish the different types of OI. The procedure outlined in this paper requires a skin biopsy, which is almost painless as compared to the bone biopsy commonly used in conventional methods. The data presented here complement existing clinical diagnostic techniques and can be used as a diagnostic procedure to confirm the disease, evaluate its severity and treatment efficacy. [ABSTRACT FROM AUTHOR]

In some large-scale face recognition task, such as driver license identification and law enforcement, the training set only contains one image per person. This situation is referred to as one sample problem. Because many face recognition techniques implicitly assume that several (at least two) images per person are available for training, they cannot deal with the one sample problem. This paper investigates principal component analysis (PCA), Fisher linear discriminant analysis (LDA), and locality preserving projections (LPP) and shows why they cannot perform well in one sample problem. After that, this paper presents four reasons that make one sample problem itself difficult: the small sample size problem; the lack of representative samples; the underestimated intra-class variation; and the overestimated inter-class variation. Based on the analysis, this paper proposes to enlarge the training set based on the inter-class relationship. This paper also extends LDA and LPP to extract features from the enlarged training set. The experimental results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Distributed hash tables (DHTs) are usually used in the open networking environment, where they are vulnerable to Sybil attacks. Pebble-Rotating Game (PRG) mixes the nodes of the honest and the adversarial randomly, and can resist the Sybil attack efficiently. However, the adversary may have some tricks to corrupt the rule of PRG. This paper proposes a set of mechanisms to make the rule of PRG be obliged to obey. A new joining node must ask the Certificate Authority (CA) for its signature and certificate, which records the complete process on how a node joins the network and obtains the legitimacy of the node. Then, to prevent the adversary from accumulating identifiers, any node can make use of the latest certificate to judge whether one identifier is expired with the help of the replacement property of RPG. This paper analyzes in details the number of expired certificates which are needed to store in every node, and gives asymptotic solution of this problem. The analysis and simulations show that the mean number of the certificates stored in each node are , where n is the size of the network. [ABSTRACT FROM AUTHOR]

This paper proposes three synthetic-type control charts to monitor the mean time-between-events of a homogenous Poisson process. The first proposed chart combines an Erlang (cumulative time between events, Tr) chart and a conforming run length (CRL) chart, denoted as Synth-Tr chart. The second proposed chart combines an exponential (or T) chart and a group conforming run length (GCRL) chart, denoted as GR-T chart. The third proposed chart combines an Erlang chart and a GCRL chart, denoted as GR-Tr chart. By using a Markov chain approach, the zero- and steady-state average number of observations to signal (ANOS) of the proposed charts are obtained, in order to evaluate the performance of the three charts. The optimal design of the proposed charts is shown in this paper. The proposed charts are superior to the existing T chart, Tr chart, and Synth-T chart. As compared to the EWMA-T chart, the GR-T chart performs better in detecting large shifts, in terms of the zero- and steady-state performances. The zero-state Synth-T4 and GR-Tr (r = 3 or 4) charts outperform the EWMA-T chart for all shifts, whereas the Synth-Tr (r = 2 or 3) and GR-T2 charts perform better for moderate to large shifts. For the steady-state process, the Synth-Tr and GR-Tr charts are more efficient than the EWMA-T chart in detecting small to moderate shifts. [ABSTRACT FROM AUTHOR]

Although many endo-ß-1,4-glucanases have been isolated in invertebrates, their cellulolytic systems are not fully understood. In particular, gastropod feeding on seaweed is considered an excellent model system for production of bioethanol and renewable bioenergy from third-generation feedstocks (microalgae and seaweeds). In this study, enzymes involved in the conversion of cellulose and other polysaccharides to glucose in digestive fluids of the sea hare (Aplysia kurodai) were screened and characterized to determine how the sea hare obtains glucose from sea lettuce (Ulva pertusa). Four endo-ß-1,4-glucanases (21K, 45K, 65K, and 95K cellulase) and 2 ß-glucosidases (110K and 210K) were purified to a homogeneous state, and the synergistic action of these enzymes during cellulose digestion was analyzed. All cellulases exhibited cellulase and lichenase activities and showed distinct cleavage specificities against cellooligosaccharides and filter paper. Filter paper was digested to cellobiose, cellotriose, and cellotetraose by 21K cellulase, whereas 45K and 65K enzymes hydrolyzed the filter paper to cellobiose and glucose. 210K ß-glucosidase showed unique substrate specificity against synthetic and natural substrates, and 4-methylumbelliferyl (4MU)-ß-glucoside, 4MU–ß-galactoside, cello-oligosaccharides, laminarin, and lichenan were suitable substrates. Furthermore, 210K ß-glucosidase possesses lactase activity. Although ß-glucosidase and cellulase are necessary for efficient hydrolysis of carboxymethylcellulose to glucose, laminarin is hydrolyzed to glucose only by 210K ß-glucosidase. Kinetic analysis of the inhibition of 210K ß-glucosidase by D-glucono-1,5-lactone suggested the presence of 2 active sites similar to those of mammalian lactase-phlorizin hydrolase. Saccharification of sea lettuce was considerably stimulated by the synergistic action of 45K cellulase and 210K ß-glucosidase. Our results indicate that 45K cellulase and 210K ß-glucosidase are the core components of the sea hare digestive system for efficient production of glucose from sea lettuce. These findings contribute important new insights into the development of biofuel processing biotechnologies from seaweed. [ABSTRACT FROM AUTHOR]

In this paper, we develop two automated authorship attribution schemes, one based on Multiple Discriminant Analysis (MDA) and the other based on a Support Vector Machine (SVM). The classification features we exploit are based on word frequencies in the text. We adopt an approach of preprocessing each text by stripping it of all characters except a-z and space. This is in order to increase the portability of the software to different types of texts. We test the methodology on a corpus of undisputed English texts, and use leave-one-out cross validation to demonstrate classification accuracies in excess of 90%. We further test our methods on the Federalist Papers, which have a partly disputed authorship and a fair degree of scholarly consensus. And finally, we apply our methodology to the question of the authorship of the Letter to the Hebrews by comparing it against a number of original Greek texts of known authorship. These tests identify where some of the limitations lie, motivating a number of open questions for future work. An open source implementation of our methodology is freely available for use at https://github.com/matthewberryman/author-detection. [ABSTRACT FROM AUTHOR]

There has been considerable effort in the last decade to increase the participation of women in engineering through various policies. However, there has been little empirical research on gender disparities in engineering which help underpin the effective preparation, co-ordination, and implementation of the science and technology (S&T) policies. This article aims to present a comprehensive gendered analysis of engineering publications across different specialties and provide a cross-gender analysis of research output and scientific impact of engineering researchers in academic, governmental, and industrial sectors. For this purpose, 679,338 engineering articles published from 2008 to 2013 are extracted from the Web of Science database and 974,837 authorships are analyzed. The structures of co-authorship collaboration networks in different engineering disciplines are examined, highlighting the role of female scientists in the diffusion of knowledge. The findings reveal that men dominate 80% of all the scientific production in engineering. Women engineers publish their papers in journals with higher Impact Factors than their male peers, but their work receives lower recognition (fewer citations) from the scientific community. Engineers—regardless of their gender—contribute to the reproduction of the male-dominated scientific structures through forming and repeating their collaborations predominantly with men. The results of this study call for integration of data driven gender-related policies in existing S&T discourse. [ABSTRACT FROM AUTHOR]

The Student's-t mixture model, which is heavily tailed and more robust than the Gaussian mixture model, has recently received great attention on image processing. In this paper, we propose a robust non-rigid point set registration algorithm using the Student's-t mixture model. Specifically, first, we consider the alignment of two point sets as a probability density estimation problem and treat one point set as Student's-t mixture model centroids. Then, we fit the Student's-t mixture model centroids to the other point set which is treated as data. Finally, we get the closed-form solutions of registration parameters, leading to a computationally efficient registration algorithm. The proposed algorithm is especially effective for addressing the non-rigid point set registration problem when significant amounts of noise and outliers are present. Moreover, less registration parameters have to be set manually for our algorithm compared to the popular coherent points drift (CPD) algorithm. We have compared our algorithm with other state-of-the-art registration algorithms on both 2D and 3D data with noise and outliers, where our non-rigid registration algorithm showed accurate results and outperformed the other algorithms. [ABSTRACT FROM AUTHOR]

This paper describes osmotically-driven pressure generation in a membrane-bound compartment while taking into account volume expansion, solute dilution, surface area to volume ratio, membrane hydraulic permeability, and changes in osmotic gradient, bulk modulus, and degree of membrane fouling. The emphasis lies on the dynamics of pressure generation; these dynamics have not previously been described in detail. Experimental results are compared to and supported by numerical simulations, which we make accessible as an open source tool. This approach reveals unintuitive results about the quantitative dependence of the speed of pressure generation on the relevant and interdependent parameters that will be encountered in most osmotically-driven pressure generators. For instance, restricting the volume expansion of a compartment allows it to generate its first 5 kPa of pressure seven times faster than without a restraint. In addition, this dynamics study shows that plants are near-ideal osmotic pressure generators, as they are composed of many small compartments with large surface area to volume ratios and strong cell wall reinforcements. Finally, we demonstrate two applications of an osmosis-based pressure generator: actuation of a soft robot and continuous volume delivery over long periods of time. Both applications do not need an external power source but rather take advantage of the energy released upon watering the pressure generators. [ABSTRACT FROM AUTHOR]

Depending on the amount of aeolian sediment input and dune erosion, dune size and morphology change over time. Since coastal foredunes play an important role in the Dutch coastal defence, it is important to have good insight in the main factors that control these changes. In this paper the temporal variations in foredune erosion and accretion were studied in relation to proxies for aeolian transport potential and storminess using yearly elevation measurements from 1965 to 2012 for six sections of the Dutch coast. Longshore differences in the relative impacts of erosion and accretion were examined in relation to local beach width. The results show that temporal variability in foredune accretion and erosion is highest in narrow beach sections. Here, dune erosion alternates with accretion, with variability displaying strong correlations with yearly values of storminess (maximum sea levels). In wider beach sections, dune erosion is less frequent, with lower temporal variability and stronger correlations with time series of transport potential. In erosion dominated years, eroded volumes decrease from narrow to wider beaches. When accretion dominates, dune-volume changes are relatively constant alongshore. Dune erosion is therefore suggested to control spatial variability in dune-volume changes. On a scale of decades, the volume of foredunes tends to increase more on wider beaches. However, where widths exceed 200 to 300 m, this trend is no longer observed. [ABSTRACT FROM AUTHOR]

Early stage detection of lymphoma cells is invaluable for providing reliable prognosis to patients. However, the purity of lymphoma cells in extracted samples from human patients' marrow is typically low. To address this issue, we report here our work on using optically-induced dielectrophoresis (ODEP) force to rapidly purify Raji cells' (a type of Burkitt's lymphoma cell) sample from red blood cells (RBCs) with a label-free process. This method utilizes dynamically moving virtual electrodes to induce negative ODEP force of varying magnitudes on the Raji cells and RBCs in an optically-induced electrokinetics (OEK) chip. Polarization models for the two types of cells that reflect their discriminate electrical properties were established. Then, the cells' differential velocities caused by a specific ODEP force field were obtained by a finite element simulation model, thereby established the theoretical basis that the two types of cells could be separated using an ODEP force field. To ensure that the ODEP force dominated the separation process, a comparison of the ODEP force with other significant electrokinetics forces was conducted using numerical results. Furthermore, the performance of the ODEP-based approach for separating Raji cells from RBCs was experimentally investigated. The results showed that these two types of cells, with different concentration ratios, could be separated rapidly using externally-applied electrical field at a driven frequency of 50 kHz at 20 Vpp. In addition, we have found that in order to facilitate ODEP-based cell separation, Raji cells' adhesion to the OEK chip's substrate should be minimized. This paper also presents our experimental results of finding the appropriate bovine serum albumin concentration in an isotonic solution to reduce cell adhesion, while maintaining suitable medium conductivity for electrokinetics-based cell separation. In short, we have demonstrated that OEK technology could be a promising tool for efficient and effective purification of Raji cells from RBCs. [ABSTRACT FROM AUTHOR]

Color is one of the most powerful aspects of a psychological counseling environment. Little scientific research has been conducted on color design and much of the existing literature is based on observational studies. Using design of experiments and response surface methodology, this paper proposes an optimal color design approach for transforming patients’ perception into color elements. Six indices, pleasant-unpleasant, interesting-uninteresting, exciting-boring, relaxing-distressing, safe-fearful, and active-inactive, were used to assess patients’ impression. A total of 75 patients participated, including 42 for Experiment 1 and 33 for Experiment 2. 27 representative color samples were designed in Experiment 1, and the color sample (L = 75, a = 0, b = -60) was the most preferred one. In Experiment 2, this color sample was set as the ‘central point’, and three color attributes were optimized to maximize the patients’ satisfaction. The experimental results show that the proposed method can get the optimal solution for color design of a counseling room. [ABSTRACT FROM AUTHOR]

The evaluation of engineered nanomaterial safety has been hindered by conflicting reports demonstrating differential degrees of toxicity with the same nanoparticles. The unique properties of these materials increase the likelihood that they will interfere with analytical techniques, which may contribute to this phenomenon. We tested the potential for: 1) nanoparticle intrinsic fluorescence/absorbance, 2) interactions between nanoparticles and assay components, and 3) the effects of adding both nanoparticles and analytes to an assay, to interfere with the accurate assessment of toxicity. Silicon, cadmium selenide, titanium dioxide, and helical rosette nanotubes each affected at least one of the six assays tested, resulting in either substantial over- or under-estimations of toxicity. Simulation of realistic assay conditions revealed that interference could not be predicted solely by interactions between nanoparticles and assay components. Moreover, the nature and degree of interference cannot be predicted solely based on our current understanding of nanomaterial behaviour. A literature survey indicated that ca. 95% of papers from 2010 using biochemical techniques to assess nanotoxicity did not account for potential interference of nanoparticles, and this number had not substantially improved in 2012. We provide guidance on avoiding and/or controlling for such interference to improve the accuracy of nanotoxicity assessments. [ABSTRACT FROM AUTHOR]

During the last decade markerless motion capture techniques have gained an increasing interest in the biomechanics community. In the clinical field, however, the application of markerless techniques is still debated. This is mainly due to a limited number of papers dedicated to the comparison with the state of the art of marker based motion capture, in term of repeatability of the three dimensional joints' kinematics. In the present work the application of markerless technique to data acquired with a marker-based system was investigated. All videos and external data were recorded with the same motion capture system and included the possibility to use markerless and marker-based methods simultaneously. Three dimensional markerless joint kinematics was estimated and compared with the one determined with traditional marker based systems, through the evaluation of root mean square distance between joint rotations. In order to compare the performance of markerless and marker-based systems in terms of clinically relevant joint angles estimation, the same anatomical frames of reference were defined for both systems. Differences in calibration and synchronization of the cameras were excluded by applying the same wand calibration and lens distortion correction to both techniques. Best results were achieved for knee flexion-extension angle, with an average root mean square distance of 11.75 deg, corresponding to 18.35% of the range of motion. Sagittal plane kinematics was estimated better than on the other planes also for hip and ankle (root mean square distance of 17.62 deg e.g. 44.66%, and 7.17 deg e.g. 33.12%), meanwhile estimates for hip joint were the most incorrect. This technique enables users of markerless technology to compare differences with marker-based in order to define the degree of applicability of markerless technique. [ABSTRACT FROM AUTHOR]

Computational strain design protocols aim at the system-wide identification of intervention strategies for the enhanced production of biochemicals in microorganisms. Existing approaches relying solely on stoichiometry and rudimentary constraint-based regulation overlook the effects of metabolite concentrations and substrate-level enzyme regulation while identifying metabolic interventions. In this paper, we introduce k-OptForce, which integrates the available kinetic descriptions of metabolic steps with stoichiometric models to sharpen the prediction of intervention strategies for improving the bio-production of a chemical of interest. It enables identification of a minimal set of interventions comprised of both enzymatic parameter changes (for reactions with available kinetics) and reaction flux changes (for reactions with only stoichiometric information). Application of k-OptForce to the overproduction of L-serine in E. coli and triacetic acid lactone (TAL) in S. cerevisiae revealed that the identified interventions tend to cause less dramatic rearrangements of the flux distribution so as not to violate concentration bounds. In some cases the incorporation of kinetic information leads to the need for additional interventions as kinetic expressions render stoichiometry-only derived interventions infeasible by violating concentration bounds, whereas in other cases the kinetic expressions impart flux changes that favor the overproduction of the target product thereby requiring fewer direct interventions. A sensitivity analysis on metabolite concentrations shows that the required number of interventions can be significantly affected by changing the imposed bounds on metabolite concentrations. Furthermore, k-OptForce was capable of finding non-intuitive interventions aiming at alleviating the substrate-level inhibition of key enzymes in order to enhance the flux towards the product of interest, which cannot be captured by stoichiometry-alone analysis. This study paves the way for the integrated analysis of kinetic and stoichiometric models and enables elucidating system-wide metabolic interventions while capturing regulatory and kinetic effects. [ABSTRACT FROM AUTHOR]

This paper describes the design and implementation of a wireless neural telemetry system that enables new experimental paradigms, such as neural recordings during rodent navigation in large outdoor environments. RoSco, short for Rodent Scope, is a small lightweight user-configurable module suitable for digital wireless recording from freely behaving small animals. Due to the digital transmission technology, RoSco has advantages over most other wireless modules of noise immunity and online user-configurable settings. RoSco digitally transmits entire neural waveforms for 14 of 16 channels at 20 kHz with 8-bit encoding which are streamed to the PC as standard USB audio packets. Up to 31 RoSco wireless modules can coexist in the same environment on non-overlapping independent channels. The design has spatial diversity reception via two antennas, which makes wireless communication resilient to fading and obstacles. In comparison with most existing wireless systems, this system has online user-selectable independent gain control of each channel in 8 factors from 500 to 32,000 times, two selectable ground references from a subset of channels, selectable channel grounding to disable noisy electrodes, and selectable bandwidth suitable for action potentials (300 Hz–3 kHz) and low frequency field potentials (4 Hz–3 kHz). Indoor and outdoor recordings taken from freely behaving rodents are shown to be comparable to a commercial wired system in sorting for neural populations. The module has low input referred noise, battery life of 1.5 hours and transmission losses of 0.1% up to a range of 10 m. [ABSTRACT FROM AUTHOR]

Functional magnetic resonance imaging (fMRI) is a thriving field that plays an important role in medical imaging analysis, biological and neuroscience research and practice. This manuscript gives a didactic introduction to the statistical analysis of fMRI data using the R project, along with the relevant R code. The goal is to give statisticians who would like to pursue research in this area a quick tutorial for programming with fMRI data. References of relevant packages and papers are provided for those interested in more advanced analysis. [ABSTRACT FROM AUTHOR]

The β1-adrenergic signaling system plays an important role in the functioning of cardiac cells. Experimental data shows that the activation of this system produces inotropy, lusitropy, and chronotropy in the heart, such as increased magnitude and relaxation rates of [Ca2+]i transients and contraction force, and increased heart rhythm. However, excessive stimulation of β1-adrenergic receptors leads to heart dysfunction and heart failure. In this paper, a comprehensive, experimentally based mathematical model of the β1-adrenergic signaling system for mouse ventricular myocytes is developed, which includes major subcellular functional compartments (caveolae, extracaveolae, and cytosol). The model describes biochemical reactions that occur during stimulation of β1-adrenoceptors, changes in ionic currents, and modifications of Ca2+ handling system. Simulations describe the dynamics of major signaling molecules, such as cyclic AMP and protein kinase A, in different subcellular compartments; the effects of inhibition of phosphodiesterases on cAMP production; kinetics and magnitudes of phosphorylation of ion channels, transporters, and Ca2+ handling proteins; modifications of action potential shape and duration; magnitudes and relaxation rates of [Ca2+]i transients; changes in intracellular and transmembrane Ca2+ fluxes; and [Na+]i fluxes and dynamics. The model elucidates complex interactions of ionic currents upon activation of β1-adrenoceptors at different stimulation frequencies, which ultimately lead to a relatively modest increase in action potential duration and significant increase in [Ca2+]i transients. In particular, the model includes two subpopulations of the L-type Ca2+ channels, in caveolae and extracaveolae compartments, and their effects on the action potential and [Ca2+]i transients are investigated. The presented model can be used by researchers for the interpretation of experimental data and for the developments of mathematical models for other species or for pathological conditions. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel cell counting method accomplished using a single-cell array fabricated on an image sensor, complementary metal oxide semiconductor sensor. The single-cell array was constructed using a microcavity array, which can trap up to 7,500 single cells on microcavities periodically arranged on a plane metallic substrate via the application of a negative pressure. The proposed method for cell counting is based on shadow imaging, which uses a light diffraction pattern generated by the microcavity array and trapped cells. Under illumination, the cell-occupied microcavities are visualized as shadow patterns in an image recorded by the complementary metal oxide semiconductor sensor due to light attenuation. The cell count is determined by enumerating the uniform shadow patterns created from one-on-one relationships with single cells trapped on the microcavities in digital format. In the experiment, all cell counting processes including entrapment of non-labeled HeLa cells from suspensions on the array and image acquisition of a wide-field-of-view of 30 mm2 in 1/60 seconds were implemented in a single integrated device. As a result, the results from the digital cell counting had a linear relationship with those obtained from microscopic observation (r2 = 0.99). This platform could be used at extremely low cell concentrations, i.e., 25–15,000 cells/mL. Our proposed system provides a simple and rapid miniaturized cell counting device for routine laboratory use. [ABSTRACT FROM AUTHOR]

Brain computer interfaces (BCIs) offer a broad class of neurologically impaired individuals an alternative means to interact with the environment. Many BCIs are “synchronous” systems, in which the system sets the timing of the interaction and tries to infer what control command the subject is issuing at each prompting. In contrast, in “asynchronous” BCIs subjects pace the interaction and the system must determine when the subject’s control command occurs. In this paper we propose a new idea for BCI which draws upon the strengths of both approaches. The subjects are externally paced and the BCI is able to determine when control commands are issued by decoding the subject’s intention for initiating control in dedicated time slots. A single task with randomly interleaved trials was designed to test whether it can be used as stimulus for inducing initiation and non-initiation states when the sensory and motor requirements for the two types of trials are very nearly identical. Further, the essential problem on the discrimination between initiation state and non-initiation state was studied. We tested the ability of EEG spectral power to distinguish between these two states. Among the four standard EEG frequency bands, beta band power recorded over parietal-occipital cortices provided the best performance, achieving an average accuracy of 86% for the correct classification of initiation and non-initiation states. Moreover, delta band power recorded over parietal and motor areas yielded a good performance and thus could also be used as an alternative feature to discriminate these two mental states. The results demonstrate the viability of our proposed idea for a BCI design based on conventional EEG features. Our proposal offers the potential to mitigate the signal detection challenges of fully asynchronous BCIs, while providing greater flexibility to the subject than traditional synchronous BCIs. [ABSTRACT FROM AUTHOR]

Multiple sequence alignment is a crucial task in a number of biological analyses like secondary structure prediction, domain searching, phylogeny, etc. MSAProbs is currently the most accurate alignment algorithm, but its effectiveness is obtained at the expense of computational time. In the paper we present QuickProbs, the variant of MSAProbs customised for graphics processors. We selected the two most time consuming stages of MSAProbs to be redesigned for GPU execution: the posterior matrices calculation and the consistency transformation. Experiments on three popular benchmarks (BAliBASE, PREFAB, OXBench-X) on quad-core PC equipped with high-end graphics card show QuickProbs to be 5.7 to 9.7 times faster than original CPU-parallel MSAProbs. Additional tests performed on several protein families from Pfam database give overall speed-up of 6.7. Compared to other algorithms like MAFFT, MUSCLE, or ClustalW, QuickProbs proved to be much more accurate at similar speed. Additionally we introduce a tuned variant of QuickProbs which is significantly more accurate on sets of distantly related sequences than MSAProbs without exceeding its computation time. The GPU part of QuickProbs was implemented in OpenCL, thus the package is suitable for graphics processors produced by all major vendors. [ABSTRACT FROM AUTHOR]

Detection of dysphonia is useful for monitoring the progression of phonatory impairment for patients with Parkinson’s disease (PD), and also helps assess the disease severity. This paper describes the statistical pattern analysis methods to study different vocal measurements of sustained phonations. The feature dimension reduction procedure was implemented by using the sequential forward selection (SFS) and kernel principal component analysis (KPCA) methods. Four selected vocal measures were projected by the KPCA onto the bivariate feature space, in which the class-conditional feature densities can be approximated with the nonparametric kernel density estimation technique. In the vocal pattern classification experiments, Fisher’s linear discriminant analysis (FLDA) was applied to perform the linear classification of voice records for healthy control subjects and PD patients, and the maximum a posteriori (MAP) decision rule and support vector machine (SVM) with radial basis function kernels were employed for the nonlinear classification tasks. Based on the KPCA-mapped feature densities, the MAP classifier successfully distinguished 91.8% voice records, with a sensitivity rate of 0.986, a specificity rate of 0.708, and an area value of 0.94 under the receiver operating characteristic (ROC) curve. The diagnostic performance provided by the MAP classifier was superior to those of the FLDA and SVM classifiers. In addition, the classification results indicated that gender is insensitive to dysphonia detection, and the sustained phonations of PD patients with minimal functional disability are more difficult to be correctly identified. [ABSTRACT FROM AUTHOR]

In this paper, intercalation of nanoclay in the miscible polymer blend of poly(vinylidene fluoride) (PVDF) and acrylic rubber(ACM) was studied. X-ray diffraction was used to investigate the formation of nanoscale polymer blend/clay hybrid. Infrared spectroscopy and X-ray analysis revealed the coexistence of β and γ crystalline forms in PVDF/Clay nanocomposite while α crystalline form was found to be dominant in PVDF/ACM/Clay miscible hybrids. Flory-Huggins interaction parameter (B) was used to further explain the miscibility phenomenon observed. The B parameter was determined by combining the melting point depression and the binary interaction model. The estimated B values for the ternary PVDF/ACM/Clay and PVDF/ACM pairs were all negative, showing both proper intercalation of the polymer melt into the nanoclay galleries and the good miscibility of PVDF and ACM blend. The B value for the PVDF/ACM blend was almost the same as that measured for the PVDF/ACM/Clay hybrid, suggesting that PVDF chains in nanocomposite hybrids interact with ACM chains and that nanoclay in hybrid systems is wrapped by ACM molecules. [ABSTRACT FROM AUTHOR]

In this paper, we propose a theoretical model to simulate microbial growth on contaminated air filters and entrainment of bioaerosols from the filters to an indoor environment. Air filter filtration and antimicrobial efficiencies, and effects of dust particles on these efficiencies, were evaluated. The number of bioaerosols downstream of the filter could be characterized according to three phases: initial, transitional, and stationary. In the initial phase, the number was determined by filtration efficiency, the concentration of dust particles entering the filter, and the flow rate. During the transitional phase, the number of bioaerosols gradually increased up to the stationary phase, at which point no further increase was observed. The antimicrobial efficiency and flow rate were the dominant parameters affecting the number of bioaerosols downstream of the filter in the transitional and stationary phase, respectively. It was found that the nutrient fraction of dust particles entering the filter caused a significant change in the number of bioaerosols in both the transitional and stationary phases. The proposed model would be a solution for predicting the air filter life cycle in terms of microbiological activity by simulating the microbial contamination of the filter. [ABSTRACT FROM AUTHOR]

Cortical circuits in the brain have long been recognised for their information processing capabilities and have been studied both experimentally and theoretically via spiking neural networks. Neuromorphic engineers are primarily concerned with translating the computational capabilities of biological cortical circuits, using the Spiking Neural Network (SNN) paradigm, into in silico applications that can mimic the behaviour and capabilities of real biological circuits/systems. These capabilities include low power consumption, compactness, and relevant dynamics. In this paper, we propose a new accelerated-time circuit that has several advantages over its previous neuromorphic counterparts in terms of compactness, power consumption, and capability to mimic the outcomes of biological experiments. The presented circuit simulation results demonstrate that, in comparing the new circuit to previous published synaptic plasticity circuits, reduced silicon area and lower energy consumption for processing each spike is achieved. In addition, it can be tuned in order to closely mimic the outcomes of various spike timing- and rate-based synaptic plasticity experiments. The proposed circuit is also investigated and compared to other designs in terms of tolerance to mismatch and process variation. Monte Carlo simulation results show that the proposed design is much more stable than its previous counterparts in terms of vulnerability to transistor mismatch, which is a significant challenge in analog neuromorphic design. All these features make the proposed design an ideal circuit for use in large scale SNNs, which aim at implementing neuromorphic systems with an inherent capability that can adapt to a continuously changing environment, thus leading to systems with significant learning and computational abilities. [ABSTRACT FROM AUTHOR]

Using statistical textons for texture classification has shown great success recently. The maximal response 8 (Statistical_MR8), image patch (Statistical_Joint) and locally invariant fractal (Statistical_Fractal) are typical statistical texton algorithms and state-of-the-art texture classification methods. However, there are two limitations when using these methods. First, it needs a training stage to build a texton library, thus the recognition accuracy will be highly depended on the training samples; second, during feature extraction, local feature is assigned to a texton by searching for the nearest texton in the whole library, which is time consuming when the library size is big and the dimension of feature is high. To address the above two issues, in this paper, three binary texton counterpart methods were proposed, Binary_MR8, Binary_Joint, and Binary_Fractal. These methods do not require any training step but encode local feature into binary representation directly. The experimental results on the CUReT, UIUC and KTH-TIPS databases show that binary texton could get sound results with fast feature extraction, especially when the image size is not big and the quality of image is not poor. [ABSTRACT FROM AUTHOR]

Burn scar extraction using remote sensing data is an efficient way to precisely evaluate burn area and measure vegetation recovery. Traditional burn scar extraction methodologies have no well effect on burn scar image with blurred and irregular edges. To address these issues, this paper proposes an automatic method to extract burn scar based on Level Set Method (LSM). This method utilizes the advantages of the different features in remote sensing images, as well as considers the practical needs of extracting the burn scar rapidly and automatically. This approach integrates Change Vector Analysis (CVA), Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR) to obtain difference image and modifies conventional Level Set Method Chan-Vese (C-V) model with a new initial curve which results from a binary image applying K-means method on fitting errors of two near-infrared band images. Landsat 5 TM and Landsat 8 OLI data sets are used to validate the proposed method. Comparison with conventional C-V model, OSTU algorithm, Fuzzy C-mean (FCM) algorithm are made to show that the proposed approach can extract the outline curve of fire burn scar effectively and exactly. The method has higher extraction accuracy and less algorithm complexity than that of the conventional C-V model. [ABSTRACT FROM AUTHOR]

: Prediction and classification techniques have been well studied by machine learning researchers and developed for several real-word problems. However, the level of acceptance and success of prediction models are still below expectation due to some difficulties such as the low performance of prediction models when they are applied in different environments. Such a problem has been addressed by many researchers, mainly from the machine learning community. A second problem, principally raised by model users in different communities, such as managers, economists, engineers, biologists, and medical practitioners, etc., is the prediction models’ interpretability. The latter is the ability of a model to explain its predictions and exhibit the causality relationships between the inputs and the outputs. In the case of classification, a successful way to alleviate the low performance is to use ensemble classiers. It is an intuitive strategy to activate collaboration between different classifiers towards a better performance than individual classier. Unfortunately, ensemble classifiers method do not take into account the interpretability of the final classification outcome. It even worsens the original interpretability of the individual classifiers. In this paper we propose a novel implementation of classifiers combination approach that does not only promote the overall performance but also preserves the interpretability of the resulting model. We propose a solution based on Ant Colony Optimization and tailored for the case of Bayesian classifiers. We validate our proposed solution with case studies from medical domain namely, heart disease and Cardiotography-based predictions, problems where interpretability is critical to make appropriate clinical decisions. Availability: The datasets, Prediction Models and software tool together with supplementary materials are available at http://faculty.uaeu.ac.ae/salahb/ACO4BC.htm. [ABSTRACT FROM AUTHOR]

The delivery of drugs to specific neural targets faces two fundamental problems: (1) most drugs do not cross the blood-brain barrier, and (2) those that do, spread to the entire brain. To date, there exists only one non-invasive methodology with the potential to solve these problems: selective blood-brain barrier (BBB) opening using micro-bubble enhanced focused ultrasound. We have recently developed a single-element 500-kHz spherical transducer ultrasound setup for targeted BBB opening in the non-human primate that does not require simultaneous MRI monitoring. So far, however, the targeting accuracy that can be achieved with this system has not been quantified systematically. In this paper, the accuracy of this system was tested by targeting caudate nucleus and putamen of the basal ganglia in two macaque monkeys. The average lateral targeting error of the system was ∼2.5 mm while the axial targeting error, i.e., along the ultrasound path, was ∼1.5 mm. We have also developed a real-time treatment monitoring technique based on cavitation spectral analysis. This technique also allowed for delineation of a safe and reliable acoustic parameter window for BBB opening. In summary, the targeting accuracy of the system was deemed to be suitable to reliably open the BBB in specific sub-structures of the basal ganglia even in the absence of MRI-based verification of opening volume and position. This establishes the method and the system as a potentially highly useful tool for brain drug delivery. [ABSTRACT FROM AUTHOR]

The majority of next-generation sequencing short-reads can be properly aligned by leading aligners at high speed. However, the alignment quality can still be further improved, since usually not all reads can be correctly aligned to large genomes, such as the human genome, even for simulated data. Moreover, even slight improvements in this area are important but challenging, and usually require significantly more computational endeavor. In this paper, we present CUSHAW3, an open-source parallelized, sensitive and accurate short-read aligner for both base-space and color-space sequences. In this aligner, we have investigated a hybrid seeding approach to improve alignment quality, which incorporates three different seed types, i.e. maximal exact match seeds, exact-match k-mer seeds and variable-length seeds, into the alignment pipeline. Furthermore, three techniques: weighted seed-pairing heuristic, paired-end alignment pair ranking and read mate rescuing have been conceived to facilitate accurate paired-end alignment. For base-space alignment, we have compared CUSHAW3 to Novoalign, CUSHAW2, BWA-MEM, Bowtie2 and GEM, by aligning both simulated and real reads to the human genome. The results show that CUSHAW3 consistently outperforms CUSHAW2, BWA-MEM, Bowtie2 and GEM in terms of single-end and paired-end alignment. Furthermore, our aligner has demonstrated better paired-end alignment performance than Novoalign for short-reads with high error rates. For color-space alignment, CUSHAW3 is consistently one of the best aligners compared to SHRiMP2 and BFAST. The source code of CUSHAW3 and all simulated data are available at http://cushaw3.sourceforge.net. [ABSTRACT FROM AUTHOR]

The vasculature of body tissues is continuously subject to remodeling processes originating at the micro-vascular level. The formation of new blood vessels (angiogenesis) is essential for a number of physiological and pathophysiological processes such as tissue regeneration, tumor development and the integration of artificial tissues. There are currently no time-lapsed in vivo imaging techniques providing information on the vascular network at the capillary level in a non-destructive, three-dimensional and high-resolution fashion. This paper presents a novel imaging framework based on contrast enhanced micro-computed tomography (micro-CT) for hierarchical in vivo quantification of blood vessels in mice, ranging from largest to smallest structures. The framework combines for the first time a standard morphometric approach with densitometric analysis. Validation tests showed that the method is precise and robust. Furthermore, the framework is sensitive in detecting different perfusion levels after the implementation of a murine ischemia-reperfusion model. Correlation with both histological data and micro-CT analysis of vascular corrosion casts confirmed accuracy of the method. The newly developed time-lapsed imaging approach shows high potential for in vivo monitoring of a number of different physiological and pathological conditions in angiogenesis and vascular development. [ABSTRACT FROM AUTHOR]

The regulation of chromosome separation during mitosis is not fully understood yet. Microtubules forming mitotic spindles are targets of treatment strategies which are aimed at (i) the triggering of the apoptosis or (ii) the interruption of uncontrolled cell division. Despite these facts, only few physical models relating to the dynamics of mitotic spindles exist up to now. In this paper, we present the first electromechanical model which enables calculation of the electromagnetic field coupled to acoustic vibrations of the mitotic spindle. This electromagnetic field originates from the electrical polarity of microtubules which form the mitotic spindle. The model is based on the approximation of resonantly vibrating microtubules by a network of oscillating electric dipoles. Our computational results predict the existence of a rapidly changing electric field which is generated by either driven or endogenous vibrations of the mitotic spindle. For certain values of parameters, the intensity of the electric field and its gradient reach values which may exert a not-inconsiderable force on chromosomes which are aligned in the spindle midzone. Our model may describe possible mechanisms of the effects of ultra-short electrical and mechanical pulses on dividing cells—a strategy used in novel methods for cancer treatment. [ABSTRACT FROM AUTHOR]

Background: In developing countries hip osteoarthritis constitutes a major public health issue as it is highly prevalent in all age ranges of population, including the young. It often remains untreated because of the low accessibility of total hip prostheses. Hip arthrodesis still represents a major treatment option, but, for several reasons which are discussed in this paper, is nowadays infrequently performed. By means of reporting the results of a new simple technique, using a self-devised plate, the relevancy of hip arthrodesis in this particular environment is emphasized. Methods and Findings: Our series included 35 patients with painful hip osteoarthritis who underwent a hip fusion with the anterolateral arthrodesis plate. Two of them had a concurrent femoral osteotomy for correction of a vicious position of the limb and another patient had a femoral diaphysis osteotomy and placement of a Wagner elongating device in order to proceed with a limb lengthening by callotasis. The follow-up period averaged 16,9 months (9 to 34). All hips, except two, achieved solid fusion between 6 and 15 months after surgery. One failure of fusion was in the oldest patient, who presented a loosening of plate and screws due to an advanced degree of osteoporosis; the other was in a young patient who admitted having walked on his leg too soon. Patient satisfaction was high. We concluded that this technique is reliable and effective. Conclusions: The results of this study should convince the hesitant surgeon and patient to consider hip arthrodesis an acceptable treatment option for disabling hip arthritis, compared to no treatment at all. [ABSTRACT FROM AUTHOR]

Posture segmentation plays an essential role in human motion analysis. The state-of-the-art method extracts sufficiently high-dimensional features from 3D depth images for each 3D point and learns an efficient body part classifier. However, high-dimensional features are memory-consuming and difficult to handle on large-scale training dataset. In this paper, we propose an efficient two-stage dimension reduction scheme, termed biview learning, to encode two independent views which are depth-difference features (DDF) and relative position features (RPF). Biview learning explores the complementary property of DDF and RPF, and uses two stages to learn a compact yet comprehensive low-dimensional feature space for posture segmentation. In the first stage, discriminative locality alignment (DLA) is applied to the high-dimensional DDF to learn a discriminative low-dimensional representation. In the second stage, canonical correlation analysis (CCA) is used to explore the complementary property of RPF and the dimensionality reduced DDF. Finally, we train a support vector machine (SVM) over the output of CCA. We carefully validate the effectiveness of DLA and CCA utilized in the two-stage scheme on our 3D human points cloud dataset. Experimental results show that the proposed biview learning scheme significantly outperforms the state-of-the-art method for human posture segmentation. [ABSTRACT FROM AUTHOR]

Purpose: This paper describes a novel method to automatically segment the human brainstem into midbrain and pons, called LABS: Landmark-based Automated Brainstem Segmentation. LABS processes high-resolution structural magnetic resonance images (MRIs) according to a revised landmark-based approach integrated with a thresholding method, without manual interaction. Methods: This method was first tested on morphological T1-weighted MRIs of 30 healthy subjects. Its reliability was further confirmed by including neurological patients (with Alzheimer's Disease) from the ADNI repository, in whom the presence of volumetric loss within the brainstem had been previously described. Segmentation accuracies were evaluated against expert-drawn manual delineation. To evaluate the quality of LABS segmentation we used volumetric, spatial overlap and distance-based metrics. Results: The comparison between the quantitative measurements provided by LABS against manual segmentations revealed excellent results in healthy controls when considering either the midbrain (DICE measures higher that 0.9; Volume ratio around 1 and Hausdorff distance around 3) or the pons (DICE measures around 0.93; Volume ratio ranging 1.024–1.05 and Hausdorff distance around 2). Similar performances were detected for AD patients considering segmentation of the pons (DICE measures higher that 0.93; Volume ratio ranging from 0.97–0.98 and Hausdorff distance ranging 1.07–1.33), while LABS performed lower for the midbrain (DICE measures ranging 0.86–0.88; Volume ratio around 0.95 and Hausdorff distance ranging 1.71–2.15). Conclusions: Our study represents the first attempt to validate a new fully automated method for in vivo segmentation of two anatomically complex brainstem subregions. We retain that our method might represent a useful tool for future applications in clinical practice. [ABSTRACT FROM AUTHOR]

Background: In recent years, several path-breaking findings on human mobility patterns point out a novel issue which is of important theoretical significance and great application prospects. The empirical analysis of the data which can reflect the real-world human mobility provides the basic cognition and verification of the theoretical models and predictive results on human mobility. One of the most noticeable findings in previous studies on human mobility is the wide-spread scaling anomalies, e.g. the power-law-like displacement distributions. Understanding the origin of these scaling anomalies is of central importance to this issue and therefore is the focus of our discussion. Methodology/Principal Findings: In this paper, we empirically analyze the real-world human movements which are based on GPS records, and observe rich scaling properties in the temporal-spatial patterns as well as an abnormal transition in the speed-displacement patterns together with an evidence to the real-world traffic jams. In addition, we notice that the displacements at the population level show a significant positive correlation, indicating a cascading-like nature in human movements. Furthermore, our analysis at the individual level finds that the displacement distributions of users with stronger correlations usually are closer to the power law, suggesting a correlation between the positive correlation of the displacement series and the form of an individual's displacement distribution. Conclusions/Significance: These empirical findings make connections between the two basic properties of human mobility, the scaling anomalies on displacement distributions and the positive correlations on displacement series, implying the cascading-like dynamics which is exhibited by the positive correlations would cause the emergence of scaling properties on human mobility patterns. Our findings would inspire further researches on mechanisms and predictions of human mobility. [ABSTRACT FROM AUTHOR]