ALBERT

Description: : As sequencing becomes cheaper and more widely available, there is a greater need to quickly and effectively analyze large-scale genomic data. While the functionality of AVIA v1.0, whose implementation was based on ANNOVAR, was comparable with other annotation web servers, AVIA v2.0 represents an enhanced web-based server that extends genomic annotations to cell-specific transcripts and protein-level functional annotations. With AVIA’s improved interface, users can better visualize their data, perform comprehensive searches and categorize both coding and non-coding variants. Availability and implementation : AVIA is freely available through the web at http://avia.abcc.ncifcrf.gov . Contact : Hue.Vuong@fnlcr.nih.gov Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : As new methods for multivariate analysis of genome wide association studies become available, it is important to be able to combine results from different cohorts in a meta-analysis. The R package MultiMeta provides an implementation of the inverse-variance-based method for meta-analysis, generalized to an n -dimensional setting. Availability and implementation: The R package MultiMeta can be downloaded from CRAN. Contact: dragana.vuckovic@burlo.trieste.it ; vi1@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Description: To prevent an overheating of the workpiece material and to increase the productivity in hot aluminum extrusion, the application of extrusion dies with conformal cooling channels manufactured additively by selective laser melting is known. Since, to date, the additive manufacturing processes are often accompanied with higher manufacturing time and costs in comparison to conventional subtractive methods, a new concept for a hybrid extrusion die is presented. Here, the large volume but geometrically simple die part, the die bridge, is manufactured conventionally by subtractive methods, and the smaller part with geometrical complexity, the tip of the mandrel, is built-up on it additively by laser melting. A further novelty of the developed die is the isolated feeding of the coolant up to the target area, close to die bearings, where the cooling shall be localized. Numerical and experimental investigations revealed that the profile’s exit temperature can be reduced locally and controlled which leads only to a moderate increase of the extrusion force. The experimental results show that the hybrid tools withstand the high mechanical and thermal loads which occur during hot aluminum extrusion.

Description: Machine tools have an impact on the environment due to their energy consumption. New strategies with focus on the reduction of the energy consumed by manufacturing processes have received significant attention owing to the rise of the electricity costs. This paper presents an experimental study related to the optimization of cutting parameters in turning of AISI 1018 steel. The aim of the study was to minimize the quantity of electrical energy required by the machine tool in order to perform the cutting operation. The material removal rate was set to a constant value in all the experimental trials so as to analyze the effect that the cutting parameters have on the energy consumed. Robust Design was used to determine the effects of the depth of cut, feed rate, and cutting speed on the energy required by the machine tool, considering two sources of noise in the experimental trials. The results of this work show that the techniques covered by the concept of Robust Design can be used to minimize the energy consumed and variation of the machining process.

Description: We propose a model for the statistical design of a variable sample size chi-squared control chart (VSS χ 2 control chart) for monitoring linear profiles. Performance measures of the proposed adaptive control chart are obtained through a Markov chain approach. Through a numerical example, which consists of a calibration application in a production process of semiconductors, the proposed chart is compared to the fixed parameter chi-squared control chart (FP χ 2 chart) to monitor the intercept and slope of the linear profile. From this example, it is possible to assess the potential benefits provided by the proposed chart. Also, considering simultaneous shifts in the intercept, the slope, and the standard deviation, a sensitivity analysis of the proposed chart for monitoring linear profiles is presented.

Description: The present investigation analyses the force and torque developing during friction stir spot welding (FSSW) of thermoplastic sheets varying the main process parameters. In addition, measurements of the tool temperature and those of the material close to the welding region were carried out to better understand the variation of the forces during FSSW and quality of the joints. Experimental tests involving an instrumented drilling machine were performed on polycarbonate sheets. The study involved the variation of dwell time, tool plunge rate and rotational speed. Mechanical characterization and dimensional analysis of the joints were performed in order to assess the influence of the process parameters on the joint quality under considered processing conditions. According to the achieved results, using low values of the plunging speed has beneficial effects on both the process (reduction in the force and torque) and the mechanical behaviour of the joints. Increasing the tool rotational speed results in reduced processing forces and higher material mixing and temperature. The dwell time has a negligible effect on developing forces while it highly influences the material temperature, dimension of the welded region and consequently the mechanical behaviour of the joint.

Description: This research studies the cellular manufacturing system (CMS) controlled by kanban mechanism which defective items are produced in any production run of each product and rework is carried out to transform them into serviceable items. We consider and compare two different policies for rework where in the first policy rework is completed within the same production cycle and in the second policy rework done after N production cycles. Recently Aghajani et al. (2012) explain policy 2 and proposed a mixed-integer nonlinear programming (MINLP) model for this policy. In order to minimize total cost, MINLP model was developed for policy 1 to find simultaneously the optimal number of kanban, batch size, and number of batches. The cost function includes the cost of setup, holding, and transportation. Due to the high combinatorial structure of the problem, particle swarm optimization (PSO), and simulated annealing (SA) algorithms as meta-heuristic methods are proposed to solve the problem and numerical experiments are conducted to demonstrate the efficiency of the proposed algorithms. It is shown that both PSO and SA result are in a near optimal solution but the PSO algorithm gives a better performance than the SA method. Also, sensitivity analysis is carried out to study the effect of defective rate, holding cost, and setup cost variations on the total system cost is discussed the performance of these policies in different conditions.

Description: Tool condition monitoring has found its importance to meet the requirement of quality production in industries. Machined surface is directly affected by the extent of tool wear. Hence, by analyzing the machined surface, the information about the cutting tool condition can be obtained. This paper presents a novel technique for multi-classification of tool wear states using a kernel-based support vector machine (SVM) technique applied on the features extracted from the gray-level co-occurrence matrix (GLCM) of machined surface images. The tool conditions are classified into sharp, semi-dull, and dull tool states by using Gaussian and polynomial kernels. The proposed method is found to be cost-effective and reliable for online tool wear classification.

Description: This study proposes a high-precision compensation system using an on-machine noncontact measuring system to improve the manufacturing accuracy and efficiency of large-diameter aspheric mirrors by reducing profile errors arising from tool setting errors and machine positioning errors. By measuring a standard hemisphere, the assembly tilt angle of the measurement sensor can be calibrated. The grinding wheel setting offset can be calculated by comparing the measured profile and the ideal profile, and the profile error caused by wheel offset can be reduced by adjusting the grinding origin coordinate. According to the normal unit vector and residual error in the Z direction of the measuring points, the normal residual errors corresponding to the grinding points could be generated as well as the compensation grinding numerical control (NC) program. An 800-mm-diameter K9 mirror was ground to verify the proposed compensation grinding method. The profile error was reduced from 65 to 35 μm during the semi-finish grinding stage. By using the compensation grinding path, the profile accuracy was improved from 35 to 8 μm in the fine grinding stage. The proposed compensation method effectively improves the profile accuracy and manufacturing efficiency for grinding large-diameter aspheric mirrors.

Description: In this paper, we will perform a comparison between two approaches of dimensional synthesis of parallel robots. The first one concerns the single-objective optimization approach; in this case, the dimensional synthesis is expressed by taking into account only one performance criterion but enables to get a final solution if it exists. The second one concerns the multi-objective optimization approach; it enables to simultaneously take into account several performance criteria. However, this approach appears to provide a set of solutions instead of a single expected final solution which should directly enable to carry out the structural synthesis. In fact, the search of a single final solution is postponed to a further step where the designers have to impose and/or restrict certain parameters. And we will establish if it is really necessary to make a multi-objective optimization approach or if a single-objective is sufficient to reach the objectives set in the specifications (user requirements). A discussion is proposed concerning the arising questions related to each approach and leading to the optimal dimensional synthesis. The PAR2 robot with two degree-of-freedom is used to exemplify the analysis and the comparison of the two approaches. The proposed comparison can be applied to any classes of parallel robots.

Description: In order to generate efficient tool path with given precision requirements, scallop height should be kept under a given limit, while the tool path should be as short as possible to reduce machining time. Traditional methods generate CC curves one by one, which makes the final tool path far from being globally optimal. This paper presents an optimal tool path generation model for a ball-end tool which strives to globally optimize a tool path with various objectives and constraints. Two scalar functions are constructed over the part surface to represent the path intervals and the feedrate (with directions). Using the finite element method (FEM), the tool path length minimization model and the machining time minimization model are solved numerically. The proposed method is also suitable for tool path generation on mesh surfaces. Simulation results show that the generated tool path can be direction parallel or contour parallel with different boundary conditions. Compared to most of the conventional tool path generation methods, the proposed method is able to generate more effective tool paths due to the global optimization strategy.

Description: Ultrasonic-assisted grinding, a promising processing technique for machining hard and brittle materials, is already quite extensively employed in manufacturing industries. However, the material removal mechanism in ultrasonic-assisted grinding is not yet fully understood, which hinders its further application. This study investigates the material removal process in ultrasonic-assisted scratching (UAS) of SiC ceramics using both simulation and experiment method, in order to detail the material removal mechanism in ultrasonic-assisted grinding. A conventional scratching (CS) test was also carried out, but without ultrasonic vibration for comparison. The simulated workpiece is modeled by smooth particle hydrodynamic (SPH) particles. Results show the following: (1) the SPH method is suitable to investigate the material removal mechanism during ultrasonic-assisted grinding of hard and brittle materials. (2) The profile of scratching trace in ultrasonic vibration (UV) is a sinusoidal path. UV vibrating in the direction vertical to the workpiece results in material removed in either a continuous or a discontinuous mode. UV vibrating in the direction parallel to the workpiece expands the cutting area. (3) The groove depth in UAS is much bigger than that in CS. (4) UV results in the impact of the abrasive grain on the workpiece, causing the deformation field to spread from the impact site and leading to deeper scratching depths and larger radial and lateral cracks.

Description: With the emergence of new materials, personalized requirements for product performance, and new application background in polymer material industry, a new manufacturing mode is supposed to be studied. Based on cloud computing (CC) and big data techniques, a specific cloud manufacturing (CMfg) mode of polymer material industry has been proposed, which is different from that of continuous industries and that of discrete industries. The critical technologies of CMfg, including forecasting and demand management, storage and transportation management, advanced process control, manufacturing execution system, enterprise resource planning, etc., have been discussed. Besides the service composition optimal-selection (SCOS) algorithm for flexible manufacturing and the flexible polymer manufacturing system (FPMS), a typical product mode of CMfg is studied. Finally as a case, computer-aided process planning for blending material (CAPP-BM) was explored and a kind of fast searching algorithm for blending material crafts was proposed. The algorithm was applied to search target craft in more than 60,000 sections of the standard processes, production data, and environmental data, and finished its search within 10 min.

Description: In this paper, an inverse heat conduction method is applied to estimate the amount of the energy ( F c ) transferred to the workpiece during electric discharge machining (EDM) process. Embedded thermocouples which were connected to a four channel data logger were utilized to measure the temperature of a specific location on a rectangular workpiece during the EDM process. After temperature measurements were done, the 2-D heat conduction model of the workpiece and the Levenberg-Marquardt (LM) scheme were used to determine the energy transferred to the workpiece. This inverse procedure facilitates the determination of the heat energy at discharge-workpiece interface in EDM processes, which yet is a challenge for existing numerical models. The obtained results showed that the energy transferred to the workpiece varies with the discharge current and pulse duration from 5 % up to 45 %, which shows that the value of F c is a function of discharge current and pulse duration and that the fixed value of energy assumed in majority of the previous researches is not in accordance with real EDM conditions. Furthermore, the effects of machining parameters such as discharge current and pulse duration on F c were studied. It was evident that the F c has a direct but non-linear relationship with both discharge current and pulse duration, while discharge current has a higher impact on F c .

Description: Thermal errors are major contributor to dimensional errors of a part during precision machining. Error compensation is an effective method to reduce thermal errors. Accurate modeling of thermal errors is a prerequisite for thermal error compensation. In this paper, five key temperature points of a computer numerical control (CNC) machine tool were selected based on grey relational analysis method (GRAM). One thermal error model based on the five key temperature points was proposed using artificial fish swarm and ant colony algorithm-based back-propagation neural network (AFSACA-BPN). AFS is applied to generate initial pheromone value of ACA, which improves the computational efficiency of BPNs and prediction accuracy of thermal error modeling. One thermal error real-time compensation system was developed based on the proposed model. An experiment was carried out to verify the performance of the compensation system. Experiment results show that the diameter error of the workpiece reduced from 23 to 10 μm after compensation.

Description: Experimental and viscoplastic finite element analysis (FEA) of thermo-mechanical plastic deformation in nonisothermal warm deep drawing is studied using SS304. A nonisothermal deep drawing tool is used in a servo-motor-controlled press. Drawability window of SS304 under elevated temperatures (25–225 °C) and low to high strain rates (drawing speeds of 2.5, 25, and 50 mm/s) were determined. A viscoplastic thermal material model is adopted for nonwork softening material behaviors, as seen in low-temperature forming of SS304, and found to be easily applicable and quite satisfactory. Tensile and equi-biaxial bulge tests were conducted for more accurate flow stress data to be used in FEA. Measured punch load–stroke and cup’s curvilinear thickness (rolling/transverse) curves were successfully compared with predictions from the nonisothermal FE model of the warm deep drawing.

Description: In this article, the effect of cooling media on the residual stresses (RS) induced by a solid-state welding process is scrutinized through measuring and comparing RS caused by friction stir welding (FSW) underwater and in open air using the non-destructive ultrasonic method for aluminum AA7075-T6. Underwater FSW as a solid-state welding method can extend the application of solid-state welding techniques in marine industry. Results reveal that the longitudinal and transverse RS reduce under the water compared to open air. This reduction in the longitudinal RS is the maximum within the nugget zone (about 17 %). Meanwhile, such reduction for the transverse RS reaches 70 % within the heat-affected zone. In addition, under both air and water, the longitudinal RS is several times greater than the transverse RS and is in tensile and compressive states inside and outside the nugget zone, respectively.

Description: Machining-induced residual stress is important for the part performance. In the literature, various predictive models have been proposed for residual stress in one-pass machining without considering the multi-pass aspect. This study describes the regeneration of residual stress in multi-pass machining with thermo-mechanical loadings, in the full elasto-plastic state, captured using the Neumann-Duhamel principle. The residual stress is then analysed satisfying elastic-plastic relaxation in-between layers and at the boundaries. Large experimental data in milling of AA2121-T3 agreed well with model predictions, thus supporting the consideration of initial stress functions, materials cyclic plasticity and compatibility to allow for residual stress prediction in multi-pass machining.

Description: Different calibration strategies based on network measurements have been studied to improve the accuracy of a laser tracker having the beam source in the rotating head, thus allows us to determine if nominal distances are needed. Moreover, the minimum gauge needed to ensure a calibration valid result is characterised. First, the laser tracker calibration performance, using only network measurements without any nominal data known, has been studied. Different strategies have then been carried out, using reflector gauges as nominal data in the calibration procedure to determine the more suitable gauge in terms of accuracy and efficiency. The reflectors have been measured from different positions of the laser tracker. The gauge reflectors have been measured too with a coordinate measuring machine for obtaining the nominal data. The objective function to be minimised in the identification parameter procedure has been developed for every strategy for the distance criterion (distances between every pair of reflectors must be constant regardless of the laser tracker position from which they are measured). Then, two criteria, distance criterion and coordinate criterion (the reflector positions measured by the laser tracker are expressed in the same reference system and are then compared), have been used to evaluate the calibration performance. The analysis developed shows the improvement accuracy of every strategy studied.

Description: by Eliseo Ferrante, Ali Emre Turgut, Edgar Duéñez-Guzmán, Marco Dorigo, Tom Wenseleers Division of labor is ubiquitous in biological systems, as evidenced by various forms of complex task specialization observed in both animal societies and multicellular organisms. Although clearly adaptive, the way in which division of labor first evolved remains enigmatic, as it requires the simultaneous co-occurrence of several complex traits to achieve the required degree of coordination. Recently, evolutionary swarm robotics has emerged as an excellent test bed to study the evolution of coordinated group-level behavior. Here we use this framework for the first time to study the evolutionary origin of behavioral task specialization among groups of identical robots. The scenario we study involves an advanced form of division of labor, common in insect societies and known as “task partitioning”, whereby two sets of tasks have to be carried out in sequence by different individuals. Our results show that task partitioning is favored whenever the environment has features that, when exploited, reduce switching costs and increase the net efficiency of the group, and that an optimal mix of task specialists is achieved most readily when the behavioral repertoires aimed at carrying out the different subtasks are available as pre-adapted building blocks. Nevertheless, we also show for the first time that self-organized task specialization could be evolved entirely from scratch, starting only from basic, low-level behavioral primitives, using a nature-inspired evolutionary method known as Grammatical Evolution. Remarkably, division of labor was achieved merely by selecting on overall group performance, and without providing any prior information on how the global object retrieval task was best divided into smaller subtasks. We discuss the potential of our method for engineering adaptively behaving robot swarms and interpret our results in relation to the likely path that nature took to evolve complex sociality and task specialization.

Description: by Patrícia Santos-Oliveira, António Correia, Tiago Rodrigues, Teresa M Ribeiro-Rodrigues, Paulo Matafome, Juan Carlos Rodríguez-Manzaneque, Raquel Seiça, Henrique Girão, Rui D. M. Travasso Sprouting angiogenesis, where new blood vessels grow from pre-existing ones, is a complex process where biochemical and mechanical signals regulate endothelial cell proliferation and movement. Therefore, a mathematical description of sprouting angiogenesis has to take into consideration biological signals as well as relevant physical processes, in particular the mechanical interplay between adjacent endothelial cells and the extracellular microenvironment. In this work, we introduce the first phase-field continuous model of sprouting angiogenesis capable of predicting sprout morphology as a function of the elastic properties of the tissues and the traction forces exerted by the cells. The model is very compact, only consisting of three coupled partial differential equations, and has the clear advantage of a reduced number of parameters. This model allows us to describe sprout growth as a function of the cell-cell adhesion forces and the traction force exerted by the sprout tip cell. In the absence of proliferation, we observe that the sprout either achieves a maximum length or, when the traction and adhesion are very large, it breaks. Endothelial cell proliferation alters significantly sprout morphology, and we explore how different types of endothelial cell proliferation regulation are able to determine the shape of the growing sprout. The largest region in parameter space with well formed long and straight sprouts is obtained always when the proliferation is triggered by endothelial cell strain and its rate grows with angiogenic factor concentration. We conclude that in this scenario the tip cell has the role of creating a tension in the cells that follow its lead. On those first stalk cells, this tension produces strain and/or empty spaces, inevitably triggering cell proliferation. The new cells occupy the space behind the tip, the tension decreases, and the process restarts. Our results highlight the ability of mathematical models to suggest relevant hypotheses with respect to the role of forces in sprouting, hence underlining the necessary collaboration between modelling and molecular biology techniques to improve the current state-of-the-art.

Description: by Sayed-Rzgar Hosseini, Aditya Barve, Andreas Wagner All biological evolution takes place in a space of possible genotypes and their phenotypes. The structure of this space defines the evolutionary potential and limitations of an evolving system. Metabolism is one of the most ancient and fundamental evolving systems, sustaining life by extracting energy from extracellular nutrients. Here we study metabolism’s potential for innovation by analyzing an exhaustive genotype-phenotype map for a space of 10 15 metabolisms that encodes all possible subsets of 51 reactions in central carbon metabolism. Using flux balance analysis, we predict the viability of these metabolisms on 10 different carbon sources which give rise to 1024 potential metabolic phenotypes. Although viable metabolisms with any one phenotype comprise a tiny fraction of genotype space, their absolute numbers exceed 10 9 for some phenotypes. Metabolisms with any one phenotype typically form a single network of genotypes that extends far or all the way through metabolic genotype space, where any two genotypes can be reached from each other through a series of single reaction changes. The minimal distance of genotype networks associated with different phenotypes is small, such that one can reach metabolisms with novel phenotypes – viable on new carbon sources – through one or few genotypic changes. Exceptions to these principles exist for those metabolisms whose complexity (number of reactions) is close to the minimum needed for viability. Increasing metabolic complexity enhances the potential for both evolutionary conservation and evolutionary innovation.

Description: Motivation: Stem cell differentiation is largely guided by master transcriptional regulators, but it also depends on the expression of other types of genes, such as cell cycle genes, signaling genes, metabolic genes, trafficking genes, etc. Traditional approaches to understanding gene expression patterns across multiple conditions, such as principal components analysis or K-means clustering, can group cell types based on gene expression, but they do so without knowledge of the differentiation hierarchy. Hierarchical clustering can organize cell types into a tree, but in general this tree is different from the differentiation hierarchy itself. Methods: Given the differentiation hierarchy and gene expression data at each node, we construct a weighted Euclidean distance metric such that the minimum spanning tree with respect to that metric is precisely the given differentiation hierarchy. We provide a set of linear constraints that are provably sufficient for the desired construction and a linear programming approach to identify sparse sets of weights, effectively identifying genes that are most relevant for discriminating different parts of the tree. Results: We apply our method to microarray gene expression data describing 38 cell types in the hematopoiesis hierarchy, constructing a weighted Euclidean metric that uses just 175 genes. However, we find that there are many alternative sets of weights that satisfy the linear constraints. Thus, in the style of random-forest training, we also construct metrics based on random subsets of the genes and compare them to the metric of 175 genes. We then report on the selected genes and their biological functions. Our approach offers a new way to identify genes that may have important roles in stem cell differentiation. Contact: tperkins@ohri.ca Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Principal component analysis (PCA) is a basic tool often used in bioinformatics for visualization and dimension reduction. However, it is known that PCA may not consistently estimate the true direction of maximal variability in high-dimensional, low sample size settings, which are typical for molecular data. Assuming that the underlying signal is sparse, i.e. that only a fraction of features contribute to a principal component (PC), this estimation consistency can be retained. Most existing sparse PCA methods use L1-penalization, i.e. the lasso , to perform feature selection. But, the lasso is known to lack variable selection consistency in high dimensions and therefore a subsequent interpretation of selected features can give misleading results. Results: We present S4VDPCA, a sparse PCA method that incorporates a subsampling approach, namely stability selection. S4VDPCA can consistently select the truly relevant variables contributing to a sparse PC while also consistently estimate the direction of maximal variability. The performance of the S4VDPCA is assessed in a simulation study and compared to other PCA approaches, as well as to a hypothetical oracle PCA that ‘knows’ the truly relevant features in advance and thus finds optimal, unbiased sparse PCs. S4VDPCA is computationally efficient and performs best in simulations regarding parameter estimation consistency and feature selection consistency. Furthermore, S4VDPCA is applied to a publicly available gene expression data set of medulloblastoma brain tumors. Features contributing to the first two estimated sparse PCs represent genes significantly over-represented in pathways typically deregulated between molecular subgroups of medulloblastoma. Availability and implementation: Software is available at https://github.com/mwsill/s4vdpca . Contact: m.sill@dkfz.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Glycans play critical roles in many biological processes, and their structural diversity is key for specific protein-glycan recognition. Comparative structural studies of biological molecules provide useful insight into their biological relationships. However, most computational tools are designed for protein structure, and despite their importance, there is no currently available tool for comparing glycan structures in a sequence order- and size-independent manner. Results: A novel method, GS-align, is developed for glycan structure alignment and similarity measurement. GS-align generates possible alignments between two glycan structures through iterative maximum clique search and fragment superposition. The optimal alignment is then determined by the maximum structural similarity score, GS-score, which is size-independent. Benchmark tests against the Protein Data Bank (PDB) N -linked glycan library and PDB homologous/non-homologous N -glycoprotein sets indicate that GS-align is a robust computational tool to align glycan structures and quantify their structural similarity. GS-align is also applied to template-based glycan structure prediction and monosaccharide substitution matrix generation to illustrate its utility. Availability and implementation: http://www.glycanstructure.org/gsalign . Contact: wonpil@ku.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Impedance-based technologies are advancing methods for measuring proliferation of adherent cell cultures non-invasively and in real time. The analysis of the resulting data has so far been hampered by inappropriate computational methods and the lack of systematic data to evaluate the characteristics of the assay. Results: We used a commercially available system for impedance-based growth measurement (xCELLigence) and compared the reported cell index with data from microscopy. We found that the measured signal correlates linearly with the cell number throughout the time of an experiment with sufficient accuracy in subconfluent cell cultures. The resulting growth curves for various colon cancer cells could be well described with the empirical Richards growth model, which allows for extracting quantitative parameters (such as characteristic cycle times). We found that frequently used readouts like the cell index at a specific time or the area under the growth curve cannot be used to faithfully characterize growth inhibition. We propose to calculate the average growth rate of selected time intervals to accurately estimate time-dependent IC50 values of drugs from growth curves. Contact: nils.bluethgen@charite.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: by Pengxing Cao, Ada W. C. Yan, Jane M. Heffernan, Stephen Petrie, Robert G. Moss, Louise A. Carolan, Teagan A. Guarnaccia, Anne Kelso, Ian G. Barr, Jodie McVernon, Karen L. Laurie, James M. McCaw Influenza is an infectious disease that primarily attacks the respiratory system. Innate immunity provides both a very early defense to influenza virus invasion and an effective control of viral growth. Previous modelling studies of virus–innate immune response interactions have focused on infection with a single virus and, while improving our understanding of viral and immune dynamics, have been unable to effectively evaluate the relative feasibility of different hypothesised mechanisms of antiviral immunity. In recent experiments, we have applied consecutive exposures to different virus strains in a ferret model, and demonstrated that viruses differed in their ability to induce a state of temporary immunity or viral interference capable of modifying the infection kinetics of the subsequent exposure. These results imply that virus-induced early immune responses may be responsible for the observed viral hierarchy. Here we introduce and analyse a family of within-host models of re-infection viral kinetics which allow for different viruses to stimulate the innate immune response to different degrees. The proposed models differ in their hypothesised mechanisms of action of the non-specific innate immune response. We compare these alternative models in terms of their abilities to reproduce the re-exposure data. Our results show that 1) a model with viral control mediated solely by a virus-resistant state, as commonly considered in the literature, is not able to reproduce the observed viral hierarchy; 2) the synchronised and desynchronised behaviour of consecutive virus infections is highly dependent upon the interval between primary virus and challenge virus exposures and is consistent with virus-dependent stimulation of the innate immune response. Our study provides the first mechanistic explanation for the recently observed influenza viral hierarchies and demonstrates the importance of understanding the host response to multi-strain viral infections. Re-exposure experiments provide a new paradigm in which to study the immune response to influenza and its role in viral control.

Description: Crystallographic texture considerably affects the formability of crystalline materials. In this paper, the effects of BCC ideal rolling fibers—including α ,

Description: In the processing of large and ultra-large forgings, the heated billets need to be properly placed on the lower forging die as quickly as possible before the plastic forming, or else the cooling of billets incurs enormous risks to the operation. This paper presents a novel methodology for examining the positioning status of billets on a forging die based on multi-body dynamics simulation and design of experiment (DOE). Using this method, the position and posture of a billet can be theoretically predicted after falling into the cavity of lower die from a manipulator with varying initial states. The method can also clarify the initial geometrical position parameters of the billet that should be strictly controlled in the operation of the manipulator above the lower die. Furthermore, finite element method (FEM) simulation can be used to analyze plastic deformations of the billets on the lower die surface with varying states, to attain in-depth understanding of the influence of the geometric states of billets in forming processes. A case study of forging with Al 7050 indicates that the method can provide a valuable reference for the rapid positioning of billets on the lower die.

Description: The ANSYS software is used to establish the electromagnetic-structural coupling model and predict the electromagnetic sheet forming process. In comparison with experimental result, the maximum simulation error, about 4.5 %, occurs at the sheet center. Then, the simulation method is used to analyze the effect of discharge voltage on thickness distribution. The results indicated that the location of the maximum thickness reduction transfers from sheet center to the region near the sheet center (A region) and then to the region corresponding to the die corner (B region) with the voltage increases, which also cause the first principle strain changed. In addition, lager magnetic force and the material at sheet flange restrained to flow are the two reasons for the thickness reduction at B region. While the direction of material flows changed by inertial effect is the reason for thickness reduction at A region.

Description: In this paper, the formability of two-layer (aluminum-st12 steel) sheets in the deep drawing process was investigated through numerical simulations and experiments. The purpose of this research was to obtain more formability in deep drawing process. The limit drawing ratio (LDR) was obtained in deep drawing of two-layer metallic sheets, with aluminum inner layer which was in contact with the punch and steel outer layer which was in contact with the die. Finite element simulations were performed to study the effect of parameters such as the thickness of each layer, value of die arc radius, friction coefficient between blank and punch, friction coefficient between blank and die, and lay up on the LDR. Experiments were conducted to verify the finite element simulations. The results indicated that the LDR was dependent on the mentioned parameters, so the LDR and as a result the two-layer metallic sheet formability could be increased by improvement of these parameters in deep drawing process.

Description: This study aims to investigate two peel demolding schemes through numerical simulations and experimental studies in order to improve the yield rate of the automated system for demolding of the polydimethylsiloxane (PDMS) micropillars with aspect ratio of 6. Numerical models based on the explicit dynamic finite element analysis by using LS-DYNA are developed to identify an optimal demolding scheme which can minimize the maximum stress of microstructures during demolding. A scale-up modeling approach is proposed to increase the numerical time-step for microscale problems in order to reduce the computational time. The experimental tests are also carried out which agree with the findings from numerical simulations. From this study, the roller-based demolding system is identified as the optimal approach in our analysis cases which can minimize the distortion and collapse of micropillars. The yield rate of the roller-based demolding system in our experimental study can be up to 99 %.

Description: The size effect in cutting process that the specific cutting energy increases rapidly and nonlinearly as the undeformed chip thickness (UCT) decrease is discussed. To facilitate the discussion, the specific cutting energy is analyzed by separating the cutting mechanism into two parts: shearing and extrusion. The size effect of materials such as dislocation starvation was introduced to explain the increase of specific cutting energy. In conventional cutting, shearing dominates the size effect. And as the UCT reduces, the effect of tool radius is not ignorable, and extrusion participates more in describing the size effect. When the UCT is on the nanometric scale, extrusion dominates the cutting process. Besides that, the cutting energy was further separated into surface generation energy, material disorder energy, and heat generation energy. Each of them was discussed individually. The results show that the size effect of materials plays a major role in the change of specific cutting energy. And the other aspects like surface generation and material disorder also determine the size effect in cutting process.

Description: Based on the crack mechanism of hot forming, the causes of cracks occurring during the hot forming of complex structural parts were investigated in this study. High temperature flow stress model of ultrahigh strength steel (UHSS) BR1500HS was established using the true stress–strain curves of BR1500HS in high-temperature tensile. A finite element model (FEM) was built to investigate the causes of defects in hot forming, particularly the necking occurring at the end parts in plan stress status. Then, hot forming process and structure optimizing methods were proposed. According to the results of numerical simulation, it can be concluded that the indirect hot forming process can avoid forming defects and optimize preforming drawing height to 24.5 mm. Through changing the end size of blank to control the metal flow, crack occurring at the end of parts can be solved, since the material in two-way tensile stress state can flow compensation in one direction and therefore reduce the flow resistance. The experimental results are in good agreement with numerical simulation results, which indicates that the proposed method can avoid defects and meet the design requirements.

Description: The deforming zone in the die determined by the cross-sectional shape of the final product plays a key role in the extrusion process affecting the extrusion pressure and product quality. Therefore, prediction of the optimal profile of the deforming region is the main objective for an effective extrusion process. In this study, using the analogy between the conventional plasticity theorem and electrostatics, the notion of equi-potential lines (EPLs) was applied to accurate representation and 3D design of the deforming region in the extrusion process of a complex section. To implement the analogy in the extrusion, the initial and final shapes were considered, and two different potentials were assigned between the inlet and outlet surfaces. Then, the EPLs were drawn that show the minimum work path between the entry and exit sections. The drawn EPLs were connected to build up a 3D-profile for the deforming region in the extrusion process. In addition, the EPLs were used in accurate representation of the deforming region using high-order polynomial curves. The effectiveness of the proposed method was examined using a complex section (U-shaped) from the literature. Then, the extrusion pressure for different profiles in the deforming region was analyzed numerically and experimentally. Moreover, the obtained polynomial curves were used in the upper bound (UB) solution for prediction of the extrusion pressure. There were reasonable agreements between the analytical, numerical, and experimental results. An acceptable reduction in the extrusion pressure for 3D modelling of the deforming region with the EPLs was reported. It was shown that the EPLs could be used for accurate representation of the deforming region in the extrusion of complex sections.

Description: by Paul M. Harrison, Laurent Badel, Mark J. Wall, Magnus J. E. Richardson Models of neocortical networks are increasingly including the diversity of excitatory and inhibitory neuronal classes. Significant variability in cellular properties are also seen within a nominal neuronal class and this heterogeneity can be expected to influence the population response and information processing in networks. Recent studies have examined the population and network effects of variability in a particular neuronal parameter with some plausibly chosen distribution. However, the empirical variability and covariance seen across multiple parameters are rarely included, partly due to the lack of data on parameter correlations in forms convenient for model construction. To addess this we quantify the heterogeneity within and between the neocortical pyramidal-cell classes in layers 2/3, 4, and the slender-tufted and thick-tufted pyramidal cells of layer 5 using a combination of intracellular recordings, single-neuron modelling and statistical analyses. From the response to both square-pulse and naturalistic fluctuating stimuli, we examined the class-dependent variance and covariance of electrophysiological parameters and identify the role of the h current in generating parameter correlations. A byproduct of the dynamic I-V method we employed is the straightforward extraction of reduced neuron models from experiment. Empirically these models took the refractory exponential integrate-and-fire form and provide an accurate fit to the perisomatic voltage responses of the diverse pyramidal-cell populations when the class-dependent statistics of the model parameters were respected. By quantifying the parameter statistics we obtained an algorithm which generates populations of model neurons, for each of the four pyramidal-cell classes, that adhere to experimentally observed marginal distributions and parameter correlations. As well as providing this tool, which we hope will be of use for exploring the effects of heterogeneity in neocortical networks, we also provide the code for the dynamic I-V method and make the full electrophysiological data set available.

Description: Motivation: The storage and transmission of high-throughput sequencing data consumes significant resources. As our capacity to produce such data continues to increase, this burden will only grow. One approach to reduce storage and transmission requirements is to compress this sequencing data. Results: We present a novel technique to boost the compression of sequencing that is based on the concept of bucketing similar reads so that they appear nearby in the file. We demonstrate that, by adopting a data-dependent bucketing scheme and employing a number of encoding ideas, we can achieve substantially better compression ratios than existing de novo sequence compression tools, including other bucketing and reordering schemes. Our method, Mince, achieves up to a 45% reduction in file sizes (28% on average) compared with existing state-of-the-art de novo compression schemes. Availability and implementation : Mince is written in C++11, is open source and has been made available under the GPLv3 license. It is available at http://www.cs.cmu.edu/~ckingsf/software/mince . Contact: carlk@cs.cmu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : Current methods for motif discovery from chromatin immunoprecipitation followed by sequencing (ChIP-seq) data often identify non-targeted transcription factor (TF) motifs, and are even further limited when peak sequences are similar due to common ancestry rather than common binding factors. The latter aspect particularly affects a large number of proteins from the Cys 2 His 2 zinc finger (C2H2-ZF) class of TFs, as their binding sites are often dominated by endogenous retroelements that have highly similar sequences. Here, we present recognition code-assisted discovery of regulatory elements (RCADE) for motif discovery from C2H2-ZF ChIP-seq data. RCADE combines predictions from a DNA recognition code of C2H2-ZFs with ChIP-seq data to identify models that represent the genuine DNA binding preferences of C2H2-ZF proteins. We show that RCADE is able to identify generalizable binding models even from peaks that are exclusively located within the repeat regions of the genome, where state-of-the-art motif finding approaches largely fail. Availability and implementation: RCADE is available as a webserver and also for download at http://rcade.ccbr.utoronto.ca/ . Supplementary information: Supplementary data are available at Bioinformatics online. Contact: t.hughes@utoronto.ca

Description: Motivation: Phylogenetic estimates from published studies can be archived using general platforms like Dryad (Vision, 2010) or TreeBASE (Sanderson et al. , 1994). Such services fulfill a crucial role in ensuring transparency and reproducibility in phylogenetic research. However, digital tree data files often require some editing (e.g. rerooting) to improve the accuracy and reusability of the phylogenetic statements. Furthermore, establishing the mapping between tip labels used in a tree and taxa in a single common taxonomy dramatically improves the ability of other researchers to reuse phylogenetic estimates. As the process of curating a published phylogenetic estimate is not error-free, retaining a full record of the provenance of edits to a tree is crucial for openness, allowing editors to receive credit for their work and making errors introduced during curation easier to correct. Results : Here, we report the development of software infrastructure to support the open curation of phylogenetic data by the community of biologists. The backend of the system provides an interface for the standard database operations of creating, reading, updating and deleting records by making commits to a git repository. The record of the history of edits to a tree is preserved by git’s version control features. Hosting this data store on GitHub ( http://github.com/ ) provides open access to the data store using tools familiar to many developers. We have deployed a server running the ‘phylesystem-api’, which wraps the interactions with git and GitHub. The Open Tree of Life project has also developed and deployed a JavaScript application that uses the phylesystem-api and other web services to enable input and curation of published phylogenetic statements. Availability and implementation : Source code for the web service layer is available at https://github.com/OpenTreeOfLife/phylesystem-api . The data store can be cloned from: https://github.com/OpenTreeOfLife/phylesystem . A web application that uses the phylesystem web services is deployed at http://tree.opentreeoflife.org/curator . Code for that tool is available from https://github.com/OpenTreeOfLife/opentree . Contact : mtholder@gmail.com

Description: Motivation: Chromatin Immunoprecipitation followed by sequencing (ChIP-seq) detects genome-wide DNA–protein interactions and chromatin modifications, returning enriched regions (ERs), usually associated with a significance score. Moderately significant interactions can correspond to true, weak interactions, or to false positives; replicates of a ChIP-seq experiment can provide co-localised evidence to decide between the two cases. We designed a general methodological framework to rigorously combine the evidence of ERs in ChIP-seq replicates, with the option to set a significance threshold on the repeated evidence and a minimum number of samples bearing this evidence. Results : We applied our method to Myc transcription factor ChIP-seq datasets in K562 cells available in the ENCODE project. Using replicates, we could extend up to 3 times the ER number with respect to single-sample analysis with equivalent significance threshold. We validated the ‘rescued’ ERs by checking for the overlap with open chromatin regions and for the enrichment of the motif that Myc binds with strongest affinity; we compared our results with alternative methods (IDR and jMOSAiCS), obtaining more validated peaks than the former and less peaks than latter, but with a better validation. Availability and implementation : An implementation of the proposed method and its source code under GPLv3 license are freely available at http://www.bioinformatics.deib.polimi.it/MSPC/ and http://mspc.codeplex.com/ , respectively. Contact : marco.morelli@iit.it Supplementary information: Supplementary Material are available at Bioinformatics online.

Description: : We announce the release of kSNP3.0, a program for SNP identification and phylogenetic analysis without genome alignment or the requirement for reference genomes. kSNP3.0 is a significantly improved version of kSNP v2. Availability and implementation : kSNP3.0 is implemented as a package of stand-alone executables for Linux and Mac OS X under the open-source BSD license. The executable packages, source code and a full User Guide are freely available at https://sourceforge.net/projects/ksnp/files/ Contact: barryghall@gmail.com

Description: Motivation: We have created an R package named phylogeo that provides a set of geographic utilities for sequencing-based microbial ecology studies. Although the geographic location of samples is an important aspect of environmental microbiology, none of the major software packages used in processing microbiome data include utilities that allow users to map and explore the spatial dimension of their data. phylogeo solves this problem by providing a set of plotting and mapping functions that can be used to visualize the geographic distribution of samples, to look at the relatedness of microbiomes using ecological distance, and to map the geographic distribution of particular sequences. By extending the popular phyloseq package and using the same data structures and command formats, phylogeo allows users to easily map and explore the geographic dimensions of their data from the R programming language. Availability and Implementation: phylogeo is documented and freely available http://zachcp.github.io/phylogeo Contact : zcharlop@rockefeller.edu

Description: : Gener is a development module for programming chemical controllers based on DNA strand displacement. Gener is developed with the aim of providing a simple interface that minimizes the opportunities for programming errors: Gener allows the user to test the computations of the DNA programs based on a simple two-domain strand displacement algebra, the minimal available so far. The tool allows the user to perform stepwise computations with respect to the rules of the algebra as well as exhaustive search of the computation space with different options for exploration and visualization. Gener can be used in combination with existing tools, and in particular, its programs can be exported to Microsoft Research’s DSD tool as well as to LaTeX. Availability and implementation : Gener is available for download at the Cosbi website at http://www.cosbi.eu/research/prototypes/gener as a windows executable that can be run on Mac OS X and Linux by using Mono. Contact : ozan@cosbi.eu

Description: Motivation: Molecular dynamics simulations provide atomic insight into the physicochemical characteristics of lipid membranes and hence, a wide range of force field families capable of modelling various lipid types have been developed in recent years. To model membranes in a biologically realistic lipid composition, simulation systems containing multiple different lipids must be assembled. Results: We present a new web service called MemGen that is capable of setting up simulation systems of heterogenous lipid membranes. MemGen is not restricted to certain lipid force fields or lipid types, but instead builds membranes from uploaded structure files which may contain any kind of amphiphilic molecule. MemGen works with any all-atom or united-atom lipid representation. Availability and implementation: MemGen is freely available without registration at http://memgen.uni-goettingen.de . Contact: jhub@gwdg.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: by Ariel Afek, Hila Cohen, Shiran Barber-Zucker, Raluca Gordân, David B. Lukatsky Recent genome-wide experiments in different eukaryotic genomes provide an unprecedented view of transcription factor (TF) binding locations and of nucleosome occupancy. These experiments revealed that a large fraction of TF binding events occur in regions where only a small number of specific TF binding sites (TFBSs) have been detected. Furthermore, in vitro protein-DNA binding measurements performed for hundreds of TFs indicate that TFs are bound with wide range of affinities to different DNA sequences that lack known consensus motifs. These observations have thus challenged the classical picture of specific protein-DNA binding and strongly suggest the existence of additional recognition mechanisms that affect protein-DNA binding preferences. We have previously demonstrated that repetitive DNA sequence elements characterized by certain symmetries statistically affect protein-DNA binding preferences. We call this binding mechanism nonconsensus protein-DNA binding in order to emphasize the point that specific consensus TFBSs do not contribute to this effect. In this paper, using the simple statistical mechanics model developed previously, we calculate the nonconsensus protein-DNA binding free energy for the entire C . elegans and D . melanogaster genomes. Using the available chromatin immunoprecipitation followed by sequencing (ChIP-seq) results on TF-DNA binding preferences for ~100 TFs, we show that DNA sequences characterized by low predicted free energy of nonconsensus binding have statistically higher experimental TF occupancy and lower nucleosome occupancy than sequences characterized by high free energy of nonconsensus binding. This is in agreement with our previous analysis performed for the yeast genome. We suggest therefore that nonconsensus protein-DNA binding assists the formation of nucleosome-free regions, as TFs outcompete nucleosomes at genomic locations with enhanced nonconsensus binding. In addition, here we perform a new, large-scale analysis using in vitro TF-DNA preferences obtained from the universal protein binding microarrays (PBM) for ~90 eukaryotic TFs belonging to 22 different DNA-binding domain types. As a result of this new analysis, we conclude that nonconsensus protein-DNA binding is a widespread phenomenon that significantly affects protein-DNA binding preferences and need not require the presence of consensus (specific) TFBSs in order to achieve genome-wide TF-DNA binding specificity.

Description: In this study, induction brazing was performed on diamond grits coated with amorphous NiCrBSi alloy (1.6-μm thick) deposited by physical vapor deposition (PVD). The brazing alloy exhibited better wetting toward the coated diamond grits than toward the uncoated diamond grits during induction brazing. The fine chromium-carbon compounds were evenly distributed between the brazed diamond grits with coating and the brazing alloy. However, the bulky chromium-carbon compounds were unevenly distributed between the brazed uncoated diamond grits and the brazing alloy. Cylindrical grinding of casting aluminum ZL102 plate with thickness of 15 mm was also performed using the brazed diamond burs fabricated with the coated diamond grits and uncoated diamond grits, respectively. The falloff percentage of brazed coated diamond grits was lower than that of brazed uncoated diamond grits. Accordingly, the temperature of processing arc area of the brazed diamond bur fabricated with the coated diamond grits was lower than that of the brazed diamond bur fabricated with the uncoated diamond grits, and its rate of removal of material was higher than that of the brazed diamond bur fabricated with the uncoated diamond grits.

Description: by The PLOS Computational Biology Staff

Description: by James Tamerius, Cécile Viboud, Jeffrey Shaman, Gerardo Chowell While a relationship between environmental forcing and influenza transmission has been established in inter-pandemic seasons, the drivers of pandemic influenza remain debated. In particular, school effects may predominate in pandemic seasons marked by an atypical concentration of cases among children. For the 2009 A/H1N1 pandemic, Mexico is a particularly interesting case study due to its broad geographic extent encompassing temperate and tropical regions, well-documented regional variation in the occurrence of pandemic outbreaks, and coincidence of several school breaks during the pandemic period. Here we fit a series of transmission models to daily laboratory-confirmed influenza data in 32 Mexican states using MCMC approaches, considering a meta-population framework or the absence of spatial coupling between states. We use these models to explore the effect of environmental, school–related and travel factors on the generation of spatially-heterogeneous pandemic waves. We find that the spatial structure of the pandemic is best understood by the interplay between regional differences in specific humidity (explaining the occurrence of pandemic activity towards the end of the school term in late May-June 2009 in more humid southeastern states), school vacations (preventing influenza transmission during July-August in all states), and regional differences in residual susceptibility (resulting in large outbreaks in early fall 2009 in central and northern Mexico that had yet to experience fully-developed outbreaks). Our results are in line with the concept that very high levels of specific humidity, as present during summer in southeastern Mexico, favor influenza transmission, and that school cycles are a strong determinant of pandemic wave timing.

Description: by Alireza Alemi, Carlo Baldassi, Nicolas Brunel, Riccardo Zecchina Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored patterns.

Description: Motivation: In practice, identifying and interpreting the functional impacts of the regulatory relationships between micro-RNA and messenger-RNA is non-trivial. The sheer scale of possible micro-RNA and messenger-RNA interactions can make the interpretation of results difficult. Results: We propose a supervised framework, pMim, built upon concepts of significance combination, for jointly ranking regulatory micro-RNA and their potential functional impacts with respect to a condition of interest. Here, pMim directly tests if a micro-RNA is differentially expressed and if its predicted targets, which lie in a common biological pathway, have changed in the opposite direction. We leverage the information within existing micro-RNA target and pathway databases to stabilize the estimation and annotation of micro-RNA regulation making our approach suitable for datasets with small sample sizes. In addition to outputting meaningful and interpretable results, we demonstrate in a variety of datasets that the micro-RNA identified by pMim, in comparison to simpler existing approaches, are also more concordant with what is described in the literature. Availability and implementation: This framework is implemented as an R function, pMim , in the package sydSeq available from http://www.ellispatrick.com/r-packages . Contact: jean.yang@sydney.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Cellular mRNA levels originate from the combined action of multiple regulatory processes, which can be recapitulated by the rates of pre-mRNA synthesis, pre-mRNA processing and mRNA degradation. Recent experimental and computational advances set the basis to study these intertwined levels of regulation. Nevertheless, software for the comprehensive quantification of RNA dynamics is still lacking. Results: INSPEcT is an R package for the integrative analysis of RNA- and 4sU-seq data to study the dynamics of transcriptional regulation. INSPEcT provides gene-level quantification of these rates, and a modeling framework to identify which of these regulatory processes are most likely to explain the observed mRNA and pre-mRNA concentrations. Software performance is tested on a synthetic dataset, instrumental to guide the choice of the modeling parameters and the experimental design. Availability and implementation: INSPEcT is submitted to Bioconductor and is currently available as Supplementary Additional File S1 . Contact: mattia.pelizzola@iit.it Supplementary Information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Experimentally determined gene regulatory networks can be enriched by computational inference from high-throughput expression profiles. However, the prediction of regulatory interactions is severely impaired by indirect and spurious effects, particularly for eukaryotes. Recently, published methods report improved predictions by exploiting the a priori known targets of a regulator (its local topology) in addition to expression profiles. Results: We find that methods exploiting known targets show an unexpectedly high rate of false discoveries. This leads to inflated performance estimates and the prediction of an excessive number of new interactions for regulators with many known targets. These issues are hidden from common evaluation and cross-validation setups, which is due to Simpson’s paradox. We suggest a confidence score recalibration method (CoRe) that reduces the false discovery rate and enables a reliable performance estimation. Conclusions: CoRe considerably improves the results of network inference methods that exploit known targets. Predictions then display the biological process specificity of regulators more correctly and enable the inference of accurate genome-wide regulatory networks in eukaryotes. For yeast, we propose a network with more than 22 000 confident interactions. We point out that machine learning approaches outside of the area of network inference may be affected as well. Availability and implementation: Results, executable code and networks are available via our website http://www.bio.ifi.lmu.de/forschung/CoRe . Contact: robert.kueffner@helmholtz-muenchen.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Stoichiometric and constraint-based methods of computational strain design have become an important tool for rational metabolic engineering. One of those relies on the concept of constrained minimal cut sets (cMCSs). However, as most other techniques, cMCSs may consider only reaction (or gene) knockouts to achieve a desired phenotype. Results : We generalize the cMCSs approach to constrained regulatory MCSs (cRegMCSs), where up/downregulation of reaction rates can be combined along with reaction deletions. We show that flux up/downregulations can virtually be treated as cuts allowing their direct integration into the algorithmic framework of cMCSs. Because of vastly enlarged search spaces in genome-scale networks, we developed strategies to (optionally) preselect suitable candidates for flux regulation and novel algorithmic techniques to further enhance efficiency and speed of cMCSs calculation. We illustrate the cRegMCSs approach by a simple example network and apply it then by identifying strain designs for ethanol production in a genome-scale metabolic model of Escherichia coli. The results clearly show that cRegMCSs combining reaction deletions and flux regulations provide a much larger number of suitable strain designs, many of which are significantly smaller relative to cMCSs involving only knockouts. Furthermore, with cRegMCSs, one may also enable the fine tuning of desired behaviours in a narrower range. The new cRegMCSs approach may thus accelerate the implementation of model-based strain designs for the bio-based production of fuels and chemicals. Availability and implementation: MATLAB code and the examples can be downloaded at http://www.mpi-magdeburg.mpg.de/projects/cna/etcdownloads.html . Contact : krishna.mahadevan@utoronto.ca or klamt@mpi-magdeburg.mpg.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Lipids are a large and diverse group of biological molecules with roles in membrane formation, energy storage and signaling. Cellular lipidomes may contain tens of thousands of structures, a staggering degree of complexity whose significance is not yet fully understood. High-throughput mass spectrometry-based platforms provide a means to study this complexity, but the interpretation of lipidomic data and its integration with prior knowledge of lipid biology suffers from a lack of appropriate tools to manage the data and extract knowledge from it. Results: To facilitate the description and exploration of lipidomic data and its integration with prior biological knowledge, we have developed a knowledge resource for lipids and their biology—SwissLipids. SwissLipids provides curated knowledge of lipid structures and metabolism which is used to generate an in silico library of feasible lipid structures. These are arranged in a hierarchical classification that links mass spectrometry analytical outputs to all possible lipid structures, metabolic reactions and enzymes. SwissLipids provides a reference namespace for lipidomic data publication, data exploration and hypothesis generation. The current version of SwissLipids includes over 244 000 known and theoretically possible lipid structures, over 800 proteins, and curated links to published knowledge from over 620 peer-reviewed publications. We are continually updating the SwissLipids hierarchy with new lipid categories and new expert curated knowledge. Availability: SwissLipids is freely available at http://www.swisslipids.org/ . Contact: alan.bridge@isb-sib.ch Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Both the quantitative real-time polymerase chain reaction (qPCR) and quantitative isothermal amplification (qIA) are standard methods for nucleic acid quantification. Numerous real-time read-out technologies have been developed. Despite the continuous interest in amplification-based techniques, there are only few tools for pre-processing of amplification data. However, a transparent tool for precise control of raw data is indispensable in several scenarios, for example, during the development of new instruments. Results: chipPCR is an R package for the pre-processing and quality analysis of raw data of amplification curves. The package takes advantage of R ’s S 4 object model and offers an extensible environment. chipPCR contains tools for raw data exploration: normalization, baselining, imputation of missing values, a powerful wrapper for amplification curve smoothing and a function to detect the start and end of an amplification curve. The capabilities of the software are enhanced by the implementation of algorithms unavailable in R , such as a 5-point stencil for derivative interpolation. Simulation tools, statistical tests, plots for data quality management, amplification efficiency/quantification cycle calculation, and datasets from qPCR and qIA experiments are part of the package. Core functionalities are integrated in GUIs (web-based and standalone shiny applications), thus streamlining analysis and report generation. Availability and implementation: http://cran.r-project.org/web/packages/chipPCR . Source code: https://github.com/michbur/chipPCR . Contact : stefan.roediger@b-tu.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : A key to understanding RNA function is to uncover its complex 3D structure. Experimental methods used for determining RNA 3D structures are technologically challenging and laborious, which makes the development of computational prediction methods of substantial interest. Previously, we developed the iFoldRNA server that allows accurate prediction of short (〈50 nt) tertiary RNA structures starting from primary sequences. Here, we present a new version of the iFoldRNA server that permits the prediction of tertiary structure of RNAs as long as a few hundred nucleotides. This substantial increase in the server capacity is achieved by utilization of experimental information such as base-pairing and hydroxyl-radical probing. We demonstrate a significant benefit provided by integration of experimental data and computational methods. Availability and implementation: http://ifoldrna.dokhlab.org Contact: dokh@unc.eu

Description: : The ms-data-core-api is a free, open-source library for developing computational proteomics tools and pipelines. The Application Programming Interface, written in Java, enables rapid tool creation by providing a robust, pluggable programming interface and common data model. The data model is based on controlled vocabularies/ontologies and captures the whole range of data types included in common proteomics experimental workflows, going from spectra to peptide/protein identifications to quantitative results. The library contains readers for three of the most used Proteomics Standards Initiative standard file formats: mzML, mzIdentML, and mzTab. In addition to mzML, it also supports other common mass spectra data formats: dta, ms2, mgf, pkl, apl (text-based), mzXML and mzData (XML-based). Also, it can be used to read PRIDE XML, the original format used by the PRIDE database, one of the world-leading proteomics resources. Finally, we present a set of algorithms and tools whose implementation illustrates the simplicity of developing applications using the library. Availability and implementation: The software is freely available at https://github.com/PRIDE-Utilities/ms-data-core-api . Supplementary information: Supplementary data are available at Bioinformatics online Contact: juan@ebi.ac.uk

Description: : Scanning probe microscopy (SPM) is already a relevant tool in biological research at the nanoscale. We present ‘Flatten plus’, a recent and helpful implementation in the well-known WSxM free software package. ‘Flatten plus’ allows reducing low-frequency noise in SPM images in a semi-automated way preventing the appearance of typical artifacts associated with such filters. Availability and implementation: WSxM is a free software implemented in C++ supported on MS Windows, but it can also be run under Mac or Linux using emulators such as Wine or Parallels. WSxM can be downloaded from http://www.wsxmsolutions.com/ . Contact: ignacio.horcas@wsxmsolutions.com

Description: : Despite the plethora of methods available for the functional analysis of omics data, obtaining comprehensive-yet detailed understanding of the results remains challenging. This is mainly due to the lack of publicly available tools for the visualization of this type of information. Here we present an R package called GOplot, based on ggplot2, for enhanced graphical representation. Our package takes the output of any general enrichment analysis and generates plots at different levels of detail: from a general overview to identify the most enriched categories (bar plot, bubble plot) to a more detailed view displaying different types of information for molecules in a given set of categories (circle plot, chord plot, cluster plot). The package provides a deeper insight into omics data and allows scientists to generate insightful plots with only a few lines of code to easily communicate the findings. Availability and Implementation: The R package GOplot is available via CRAN-The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/GOplot . The shiny web application of the Venn diagram can be found at: https://wwalter.shinyapps.io/Venn/ . A detailed manual of the package with sample figures can be found at https://wencke.github.io/ Contact: fscabo@cnic.es or mricote@cnic.es

Description: Motivation: Horizontal transfer of transposable (HTT) elements among eukaryotes was discovered in the mid-1980s. As then, 〉300 new cases have been described. New findings about HTT are revealing the evolutionary impact of this phenomenon on host genomes. In order to provide an up to date, interactive and expandable database for such events, we developed the HTT-DB database. Results: HTT-DB allows easy access to most of HTT cases reported along with rich information about each case. Moreover, it allows the user to generate tables and graphs based on searches using Transposable elements and/or host species classification and export them in several formats. Availability and implementation: This database is freely available on the web at http://lpa.saogabriel.unipampa.edu.br:8080/httdatabase . HTT-DB was developed based on Java and MySQL with all major browsers supported. Tools and software packages used are free for personal or non-profit projects. Contact: bdotto82@gmail.com or gabriel.wallau@gmail.com

Description: by Sander Land, Steven A. Niederer Biophysical models of cardiac tension development provide a succinct representation of our understanding of force generation in the heart. The link between protein kinetics and interactions that gives rise to high cooperativity is not yet fully explained from experiments or previous biophysical models. We propose a biophysical ODE-based representation of cross-bridge (XB), tropomyosin and troponin within a contractile regulatory unit (RU) to investigate the mechanisms behind cooperative activation, as well as the role of cooperativity in dynamic tension generation across different species. The model includes cooperative interactions between regulatory units (RU-RU), between crossbridges (XB-XB), as well more complex interactions between crossbridges and regulatory units (XB-RU interactions). For the steady-state force-calcium relationship, our framework predicts that: (1) XB-RU effects are key in shifting the half-activation value of the force-calcium relationship towards lower [Ca 2+ ], but have only small effects on cooperativity. (2) XB-XB effects approximately double the duty ratio of myosin, but do not significantly affect cooperativity. (3) RU-RU effects derived from the long-range action of tropomyosin are a major factor in cooperative activation, with each additional unblocked RU increasing the rate of additional RU’s unblocking. (4) Myosin affinity for short (1–4 RU) unblocked stretches of actin of is very low, and the resulting suppression of force at low [Ca 2+ ] is a major contributor in the biphasic force-calcium relationship. We also reproduce isometric tension development across mouse, rat and human at physiological temperature and pacing rate, and conclude that species differences require only changes in myosin affinity and troponin I/troponin C affinity. Furthermore, we show that the calcium dependence of the rate of tension redevelopment k tr is explained by transient blocking of RU’s by a temporary decrease in XB-RU effects.

Description: by Jonas Paulsen, Odin Gramstad, Philippe Collas The three-dimensional (3D) structure of the genome is important for orchestration of gene expression and cell differentiation. While mapping genomes in 3D has for a long time been elusive, recent adaptations of high-throughput sequencing to chromosome conformation capture (3C) techniques, allows for genome-wide structural characterization for the first time. However, reconstruction of "consensus" 3D genomes from 3C-based data is a challenging problem, since the data are aggregated over millions of cells. Recent single-cell adaptations to the 3C-technique, however, allow for non-aggregated structural assessment of genome structure, but data suffer from sparse and noisy interaction sampling. We present a manifold based optimization (MBO) approach for the reconstruction of 3D genome structure from chromosomal contact data. We show that MBO is able to reconstruct 3D structures based on the chromosomal contacts, imposing fewer structural violations than comparable methods. Additionally, MBO is suitable for efficient high-throughput reconstruction of large systems, such as entire genomes, allowing for comparative studies of genomic structure across cell-lines and different species.

Description: by Hiroo Kenzaki, Shoji Takada Nucleosomes, basic units of chromatin, are known to show spontaneous DNA unwrapping dynamics that are crucial for transcriptional activation, but its structural details are yet to be elucidated. Here, employing a coarse-grained molecular model that captures residue-level structural details up to histone tails, we simulated equilibrium fluctuations and forced unwrapping of single nucleosomes at various conditions. The equilibrium simulations showed spontaneous unwrapping from outer DNA and subsequent rewrapping dynamics, which are in good agreement with experiments. We found several distinct partially unwrapped states of nucleosomes, as well as reversible transitions among these states. At a low salt concentration, histone tails tend to sit in the concave cleft between the histone octamer and DNA, tightening the nucleosome. At a higher salt concentration, the tails tend to bound to the outer side of DNA or be expanded outwards, which led to higher degree of unwrapping. Of the four types of histone tails, H3 and H2B tail dynamics are markedly correlated with partial unwrapping of DNA, and, moreover, their contributions were distinct. Acetylation in histone tails was simply mimicked by changing their charges, which enhanced the unwrapping, especially markedly for H3 and H2B tails.

Description: by Sebastian Bitzer, Jelle Bruineberg, Stefan J. Kiebel Even for simple perceptual decisions, the mechanisms that the brain employs are still under debate. Although current consensus states that the brain accumulates evidence extracted from noisy sensory information, open questions remain about how this simple model relates to other perceptual phenomena such as flexibility in decisions, decision-dependent modulation of sensory gain, or confidence about a decision. We propose a novel approach of how perceptual decisions are made by combining two influential formalisms into a new model. Specifically, we embed an attractor model of decision making into a probabilistic framework that models decision making as Bayesian inference. We show that the new model can explain decision making behaviour by fitting it to experimental data. In addition, the new model combines for the first time three important features: First, the model can update decisions in response to switches in the underlying stimulus. Second, the probabilistic formulation accounts for top-down effects that may explain recent experimental findings of decision-related gain modulation of sensory neurons. Finally, the model computes an explicit measure of confidence which we relate to recent experimental evidence for confidence computations in perceptual decision tasks.

Description: When machining titanium alloys at cutting speeds higher than 60 m/min using cemented carbide cutting tools, the tool wears out rapidly. With the ever-increasing use of titanium alloys, it is essential to address this issue of rapid tool wear in order to reduce manufacturing costs. Therefore, the intention of this study was to investigate all possible tool wear mechanisms involved when using uncoated carbide cutting tools to machine Ti6Al4V titanium alloy at a cutting speed of 150 m/min under dry cutting conditions. Adhesion, diffusion, attrition, and abrasion were found to be the mechanisms associated with the cratering of the rake surface of the cutting tool. The plastic deformation of the cutting edge was also noticed which resulted in weakening of the rake surface and clear evidence has been presented. Based on this evidence, the process of the formation of the crater wear has been described in detail.

Description: Temperature and material flow behavior during friction spot welding of Alclad 7B04-T74 aluminum alloy were studied by both numerical simulation and welding experiment. The Alclad 7B04-T74 aluminum alloy sequentially experienced solid solution treatment at 465 °C, low temperature artificial aging at 120 °C, and high temperature artificial aging at 180 °C. During welding, the material which flowed into the sleeve cavity suffered from higher temperature, and the peak temperature in the stir zone was higher than the incipient melting temperature of the base material. Accordingly, the eutectic films along the grain boundaries can be observed in the stir zone after welding. The peak temperatures in the thermo-mechanically affected zone and the heat affected zone were lower than the solution temperature and higher than the artificial aging temperature of the base material. In the sleeve retreating stage of the welding process, the material in the sleeve cavity flowed downward out of the sleeve cavity, and then it flowed laterally and upward to fill the gap left by the retreating sleeve. Such a material flow path resulted in the “U-shaped” morphology of the bonding ligament, the upward curving of the hook, and the upward distortion of the grains in the thermo-mechanically affected zone.

Description: In order to reduce the adverse effects on environment and avoid health problems caused by the excessively used cutting fluids, a green machining technology, minimum quantity lubrication (MQL), is drawing more and more attention. The cryogenic minimum quantity lubrication (CMQL) technique which combines the advantages of cryogenic air and MQL can improve cooling and lubricating performances during machining H13 steel. Internal cooling cutters have been widely employed to feed the cutting medium to the cutting zone directly. In this research work, cutting forces and tool wear were analyzed during side milling H13 steel with three kinds of internal cooling milling cutters under CMQL condition. The experimental results showed that the milling cutter with double straight channel (DSC) performed best in extending tool life and reducing cutting forces. In the perspective of economy and environmental protection, internal cooling cutter with DSC is recommended in cutting of H13 steel under CMQL condition.

Description: Considering the traditional power amplifier has the disadvantage of poor reliability and flexibility, a three-level pulse-width modulation (PWM) power amplifier which is based on a novel field-programmable logic gate array (FPGA) algorithm and hardware solution is proposed. The power amplifier can provide various signals flexibly and realize rapid response of the magnetic suspension spindle in micro-electrical discharge machining (EDM). In this paper, the principle of three-level PWM amplifier with half bridge and full bridge power circuit is introduced. According to different functions, the amplifier is divided into four function modules which include PWM signal generator module, voltage signal convert module, bootstrap drive module, and power bridge module. PWM signal generator module is also divided into four sub-modules in term of a new FPGA algorithm. Voltage signals are converted by high-speed photo coupler HCPL-2630. IR2110S chips are applied to drive the half bridge and full bridge power circuits. According to Kirchhoff voltage law, when the period of PWM signals is 50 μs and the duty cycles are larger than 0.76 and 0.665, the average current of half bridge and full bridge are more than 3 and 4 A; however, the ripple of the half bridge and full bridge are still less than 0.25 and 0.2 A, this advantage is suitable for the control system of magnetic suspension spindle. Test results of the average current and ripple are close to theoretical value. The axial response frequency of the spindle can reach 125 Hz, using this power amplifier and the magnetic suspension spindle, micro EDM can be achieved in Z axis with 1.2 mm stroke.

Description: This paper presents an improved methodology for evaluating the position and orientation errors of airfoil sections of a manufactured aero-engine blade. The existing method estimates these errors by finding rigid-body transformations with translational and rotational parameters altogether to best match the inspection data points onto the design airfoil profiles. Such transformations lead to unreliable evaluation results due to combining the position and orientation errors with each other. This paper proposes to decouple the position and orientation errors in their evaluation in order to avoid the combining effect. To isolate the position error from the orientation error, an important location tolerance evaluation feature, the centroid of a manufactured airfoil section, must be correctly identified from the sectional inspection data points. Identifying the centroid location directly from discrete data points is subject to an error caused by biased area calculations on the pressure and suction sides of an airfoil. This work proposes to reconstruct a valid airfoil profile from the inspection data points for each airfoil section to overcome the area bias problem and to maintain consistency in identifying the centroid. With the centroid of each inspected airfoil section identified, the position error and the orientation error can then be evaluated in sequence. A series of case studies has been performed to demonstrate the effectiveness of the proposed methodology and how it is able to prevent wrongful rejection/acceptance of geometrically acceptable/unacceptable blades as well as incorrect modification of the related manufacturing processes.

Description: A three-dimensional (3D) micromechanical finite element (FE) model of machining of fiber-reinforced polymer (FRP) composites was developed in the paper. The FE modeling considers the three phases of a composite, in which the interphase between the fiber and matrix can realize interfacial debonding to represent the failure of composites and allow heat transfer. The machined surface observations and surface roughness measurements of carbon fiber-reinforced polymer (CFRP) composites at different fiber orientations were done firstly, and then, the model predictions of the machining responses, such as cutting force, temperature, and surface roughness, at different fiber orientations were compared with various experimental data for model validation. It is indicated that the three-phase micromechanical model is capable of precisely predicting machining responses and describing the failure modes of fiber shearing or bending related with fiber orientations in the chip formation process. To investigate the complex coupling influences of multiple machining parameters on the key responses of CFRP composites, the single-factor analyses of each machining parameter were first carried out, and then, the multi-factorial analysis of multiple machining parameters was performed based on the orthogonal design of experiment and the analysis of variance (ANOVA) to quantitatively compare the influences of these key machining parameters on the cutting force and surface roughness. It was found that the fiber orientation angle, depth of cut, and cutting speed prove to be the important factors affecting the cutting force and surface roughness and that the coupling effects of these machining parameters all are relatively negligible in the machining of CFRP composites.

Description: Assembly system complexity, especially welding system complexity introduced by auto-body product personalization is regarded as a major contributor of uncertainty in the system planning and designing. The welding system complexity is defined based on information entropy theory, the station-level integrated complexity model, and system-level complexity flow model are established to obtain the complexity source of welding system. Complexity source sensitivity indices are proposed to indentify key station and key equipment that contribute most to the complexity. Based on the application of auto-body side welding line case, the result indicates that the proposed complexity model and key complexity source identifying and diagnosing process can be used as the decision support tool of auto-body welding system.

Description: Single point incremental forming (SPIF) is a relatively new manufacturing process that has been recently used to form medical grade titanium sheets for implant devices. However, one limitation of the SPIF process may be characterized by dimensional inaccuracies of the final part as compared with the original designed part model. Elimination of these inaccuracies is critical to forming medical implants to meet required tolerances. Prior work on accuracy characterization has shown that feature behavior is important in predicting accuracy. In this study, a set of basic geometric shapes consisting of ruled and freeform features were formed using SPIF to characterize the dimensional inaccuracies of grade 1 titanium sheet parts. Response surface functions using multivariate adaptive regression splines (MARS) are then generated to model the deviations at individual vertices of the STL model of the part as a function of geometric shape parameters such as curvature, depth, distance to feature borders, wall angle, etc. The generated response functions are further used to predict dimensional deviations in a specific clinical implant case where the curvatures in the part lie between that of ruled features and freeform features. It is shown that a mixed-MARS response surface model using a weighted average of the ruled and freeform surface models can be used for such a case to improve the mean prediction accuracy within ±0.5 mm. The predicted deviations show a reasonable match with the actual formed shape for the implant case and are used to generate optimized tool paths for minimized shape and dimensional inaccuracy. Further, an implant part is then made using the accuracy characterization functions for improved accuracy. The results show an improvement in shape and dimensional accuracy of incrementally formed titanium medical implants.

Description: In electrical discharge machining (EDM) process, one of the most important aspects is the surface quality of the workpiece. When a uniform and thick recast layer is achieved with characteristics of low roughness, high hardness, and the absence of pores and micro-cracks, it acts as a kind of coating. Such surface is required by mold-making industry, where the molds are subjected to chemical and abrasive wear, and the surface needs to present high resistance against corrosion and abrasive forces. The use of powder particles suspended in the dielectric is a way to provide such improvement and, at the same time, avoiding the need for subsequent polishing. This work investigated the influence of silicon and manganese powders with fine particle sizes, using two different concentrations, suspended in the dielectric when EDM machining AISI H13 tool steel. It evaluated the surface roughness, hardness, and the chemical composition and micro-structure of the recast layer; using X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS) techniques. The best results were obtained for silicon powder; presenting the surface roughness improved about five times, when compared to the conventional EDM process, as well as a thick and uniform recast layer without micro-cracks and pores. The silicon and the manganese powders also promoted an increase of the recast layer hardness of about 40 % when compared to the conventional EDM process.

Description: It has been proven that error compensation is a key technique to improve machining accuracy. However, existing iteration and recursive compensation algorithm is difficult to realize. Hence, a simple and rapid compensation method is considerably necessary for engineering application. In this paper, a novel compensation strategy just by algebraic operation was first proposed for machining accuracy improvement. Error motion transformation was introduced to build the position-independent geometric error (PIGE) model according to homogeneous transformation matrix (HTM). Then, the analytical numerical control (NC) code expression with error compensation was derived and used for NC code generation. In addition, the presented method is appropriate for post-processing of non-orthogonal machine tool. At last, simulation and cutting experiment were demonstrated to verify the feasibility and effectiveness of the proposed method. Taking hemisphere surface as the test object, the simulation results showed that the effects of PIGEs could be eliminated by the proposed method. The experiment results with compensation indicated that the machining accuracy improved to about 14 % compared with those without compensation.

Description: The study aims to obtain the effect of forming parameters on multi-stage cold forging with 20MnTiB steel by performing a series of physical simulation and then verified by producing experiment of high-strength bolt. Physical simulation was performed through Gleeble 3500 compression tests; the mainly forming parameters such as strain rate (10 0 ∼10 1 ), deformation degree (20∼80 %), and number of stages were discussed. The results showed that the strain rate has little effect on the microstructure and the mechanical property. However, the number of stages and the deformation degree have an appreciable effect on the sample microstructure, of which the pearlite grain is fined and ferrite grain is elongated as fiber. The adiabatic thermal temperature rises from 20 to 142 °C with a 60 % deformation degree at a strain rate of 10 s −1 . Finally, the deformation properties of bolts can compare with the physical simulation results.

Description: In this paper, a visual, data-driven operational level lean maturity model is developed. The model can be used to assess level of lean maturity and to compare it to performance results in different axes of manufacturing cells in order to evaluate lean effectiveness. As demonstrated in this paper, to measure effectiveness of lean manufacturing, both inputs (tools and processes) and outputs (performance) are measured separately and analyzed together. A case study is carried out for gathering data, analysis, and explanatory study of results. Qualitative and quantitative data on lean capability and performance of two manufacturing cells is collected using historical data and audit. A scoring system based on the major and minor non-conformances is suggested to quantify the indicators of leanness. Minimum of fuzzy membership values is selected to calculate overall performance. Then, the results of leanness are compared with performance to highlight the gaps of lean effectiveness. Results of the study show that the developed model can be used to measure both leanness and lean effectiveness through assessment of lean performance. The model can be applied by practitioners as a framework to design and develop a company-specific lean maturity model.

Description: by Malachi Griffith, Jason R. Walker, Nicholas C. Spies, Benjamin J. Ainscough, Obi L. Griffith Massively parallel RNA sequencing (RNA-seq) has rapidly become the assay of choice for interrogating RNA transcript abundance and diversity. This article provides a detailed introduction to fundamental RNA-seq molecular biology and informatics concepts. We make available open-access RNA-seq tutorials that cover cloud computing, tool installation, relevant file formats, reference genomes, transcriptome annotations, quality-control strategies, expression, differential expression, and alternative splicing analysis methods. These tutorials and additional training resources are accompanied by complete analysis pipelines and test datasets made available without encumbrance at www.rnaseq.wiki.

Description: by Arjun Bharioke, Dmitri B. Chklovskii Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs.

Description: by Murat Alp, Vipan K. Parihar, Charles L. Limoli, Francis A. Cucinotta In this work, a stochastic computational model of microscopic energy deposition events is used to study for the first time damage to irradiated neuronal cells of the mouse hippocampus. An extensive library of radiation tracks for different particle types is created to score energy deposition in small voxels and volume segments describing a neuron’s morphology that later are sampled for given particle fluence or dose. Methods included the construction of in silico mouse hippocampal granule cells from neuromorpho.org with spine and filopodia segments stochastically distributed along the dendritic branches. The model is tested with high-energy 56 Fe, 12 C, and 1 H particles and electrons. Results indicate that the tree-like structure of the neuronal morphology and the microscopic dose deposition of distinct particles may lead to different outcomes when cellular injury is assessed, leading to differences in structural damage for the same absorbed dose. The significance of the microscopic dose in neuron components is to introduce specific local and global modes of cellular injury that likely contribute to spine, filopodia, and dendrite pruning, impacting cognition and possibly the collapse of the neuron. Results show that the heterogeneity of heavy particle tracks at low doses, compared to the more uniform dose distribution of electrons, juxtaposed with neuron morphology make it necessary to model the spatial dose painting for specific neuronal components. Going forward, this work can directly support the development of biophysical models of the modifications of spine and dendritic morphology observed after low dose charged particle irradiation by providing accurate descriptions of the underlying physical insults to complex neuron structures at the nano-meter scale.

Description: by Brinda Vallat, Carlos Madrid-Aliste, Andras Fiser Predicting the three-dimensional structure of proteins from their amino acid sequences remains a challenging problem in molecular biology. While the current structural coverage of proteins is almost exclusively provided by template-based techniques, the modeling of the rest of the protein sequences increasingly require template-free methods. However, template-free modeling methods are much less reliable and are usually applicable for smaller proteins, leaving much space for improvement. We present here a novel computational method that uses a library of supersecondary structure fragments, known as Smotifs, to model protein structures. The library of Smotifs has saturated over time, providing a theoretical foundation for efficient modeling. The method relies on weak sequence signals from remotely related protein structures to create a library of Smotif fragments specific to the target protein sequence. This Smotif library is exploited in a fragment assembly protocol to sample decoys, which are assessed by a composite scoring function. Since the Smotif fragments are larger in size compared to the ones used in other fragment-based methods, the proposed modeling algorithm, SmotifTF, can employ an exhaustive sampling during decoy assembly. SmotifTF successfully predicts the overall fold of the target proteins in about 50% of the test cases and performs competitively when compared to other state of the art prediction methods, especially when sequence signal to remote homologs is diminishing. Smotif-based modeling is complementary to current prediction methods and provides a promising direction in addressing the structure prediction problem, especially when targeting larger proteins for modeling.

Description: Motivation : The majority of variation identified by genome wide association studies falls in non-coding genomic regions and is hypothesized to impact regulatory elements that modulate gene expression. Here we present a statistically rigorous software tool GREGOR (Genomic Regulatory Elements and Gwas Overlap algoRithm) for evaluating enrichment of any set of genetic variants with any set of regulatory features. Using variants from five phenotypes, we describe a data-driven approach to determine the tissue and cell types most relevant to a trait of interest and to identify the subset of regulatory features likely impacted by these variants. Last, we experimentally evaluate six predicted functional variants at six lipid-associated loci and demonstrate significant evidence for allele-specific impact on expression levels. GREGOR systematically evaluates enrichment of genetic variation with the vast collection of regulatory data available to explore novel biological mechanisms of disease and guide us toward the functional variant at trait-associated loci. Availability and implementation : GREGOR, including source code, documentation, examples, and executables, is available at http://genome.sph.umich.edu/wiki/GREGOR . Contact : cristen@umich.edu Supplementary information : Supplementary data are available at Bioinformatics online.

Description: Motivation: Genome and transcriptome analyses can be used to explore cancers comprehensively, and it is increasingly common to have multiple omics data measured from each individual. Furthermore, there are rich functional data such as predicted impact of mutations on protein coding and gene/protein networks. However, integration of the complex information across the different omics and functional data is still challenging. Clinical validation, particularly based on patient outcomes such as survival, is important for assessing the relevance of the integrated information and for comparing different procedures. Results: An analysis pipeline is built for integrating genomic and transcriptomic alterations from whole-exome and RNA sequence data and functional data from protein function prediction and gene interaction networks. The method accumulates evidence for the functional implications of mutated potential driver genes found within and across patients. A driver-gene score (DGscore) is developed to capture the cumulative effect of such genes. To contribute to the score, a gene has to be frequently mutated, with high or moderate mutational impact at protein level, exhibiting an extreme expression and functionally linked to many differentially expressed neighbors in the functional gene network. The pipeline is applied to 60 matched tumor and normal samples of the same patient from The Cancer Genome Atlas breast-cancer project. In clinical validation, patients with high DGscores have worse survival than those with low scores ( P = 0.001). Furthermore, the DGscore outperforms the established expression-based signatures MammaPrint and PAM50 in predicting patient survival. In conclusion, integration of mutation, expression and functional data allows identification of clinically relevant potential driver genes in cancer. Availability and implementation: The documented pipeline including annotated sample scripts can be found in http://fafner.meb.ki.se/biostatwiki/driver-genes/ . Contact: yudi.pawitan@ki.se Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: With improvements in next-generation sequencing technologies and reductions in price, ordered RNA-seq experiments are becoming common. Of primary interest in these experiments is identifying genes that are changing over time or space, for example, and then characterizing the specific expression changes. A number of robust statistical methods are available to identify genes showing differential expression among multiple conditions, but most assume conditions are exchangeable and thereby sacrifice power and precision when applied to ordered data. Results: We propose an empirical Bayes mixture modeling approach called EBSeq-HMM. In EBSeq-HMM, an auto-regressive hidden Markov model is implemented to accommodate dependence in gene expression across ordered conditions. As demonstrated in simulation and case studies, the output proves useful in identifying differentially expressed genes and in specifying gene-specific expression paths. EBSeq-HMM may also be used for inference regarding isoform expression. Availability and implementation: An R package containing examples and sample datasets is available at Bioconductor. Contact: kendzior@biostat.wisc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Sequence discovery tools play a central role in several fields of computational biology. In the framework of Transcription Factor binding studies, most of the existing motif finding algorithms are computationally demanding, and they may not be able to support the increasingly large datasets produced by modern high-throughput sequencing technologies. Results: We present FastMotif, a new motif discovery algorithm that is built on a recent machine learning technique referred to as Method of Moments. Based on spectral decompositions, our method is robust to model misspecifications and is not prone to locally optimal solutions. We obtain an algorithm that is extremely fast and designed for the analysis of big sequencing data. On HT-Selex data, FastMotif extracts motif profiles that match those computed by various state-of-the-art algorithms, but one order of magnitude faster. We provide a theoretical and numerical analysis of the algorithm’s robustness and discuss its sensitivity with respect to the free parameters. Availability and implementation: The Matlab code of FastMotif is available from http://lcsb-portal.uni.lu/bioinformatics . Contact: vlassis@adobe.com Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Next-generation high-throughput sequencing has become a state-of-the-art technique in genome assembly. Scaffolding is one of the main stages of the assembly pipeline. During this stage, contigs assembled from the paired-end reads are merged into bigger chains called scaffolds. Because of a high level of statistical noise, chimeric reads, and genome repeats the problem of scaffolding is a challenging task. Current scaffolding software packages widely vary in their quality and are highly dependent on the read data quality and genome complexity. There are no clear winners and multiple opportunities for further improvements of the tools still exist. Results: This article presents an efficient scaffolding algorithm ScaffMatch that is able to handle reads with both short (〈600 bp) and long (〉35 000 bp) insert sizes producing high-quality scaffolds. We evaluate our scaffolding tool with the F score and other metrics (N50, corrected N50) on eight datasets comparing it with the most available packages. Our experiments show that ScaffMatch is the tool of preference for the most datasets. Availability and implementation: The source code is available at http://alan.cs.gsu.edu/NGS/?q=content/scaffmatch . Contact: mandric@cs.gsu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Identifying protein subchloroplast localization in chloroplast organelle is very helpful for understanding the function of chloroplast proteins. There have existed a few computational prediction methods for protein subchloroplast localization. However, these existing works have ignored proteins with multiple subchloroplast locations when constructing prediction models, so that they can predict only one of all subchloroplast locations of this kind of multilabel proteins. Results: To address this problem, through utilizing label-specific features and label correlations simultaneously, a novel multilabel classifier was developed for predicting protein subchloroplast location(s) with both single and multiple location sites. As an initial study, the overall accuracy of our proposed algorithm reaches 55.52%, which is quite high to be able to become a promising tool for further studies. Availability and implementation: An online web server for our proposed algorithm named MultiP-SChlo was developed, which are freely accessible at http://biomed.zzuli.edu.cn/bioinfo/multip-schlo/ . Contact: pandaxiaoxi@gmail.com or gzli@tongji.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Loops in proteins are often involved in biochemical functions. Their irregularity and flexibility make experimental structure determination and computational modeling challenging. Most current loop modeling methods focus on modeling single loops. In protein structure prediction, multiple loops often need to be modeled simultaneously. As interactions among loops in spatial proximity can be rather complex, sampling the conformations of multiple interacting loops is a challenging task. Results: In this study, we report a new method called m ulti-loop Di stance-guided S equential chain- Gro wth Monte Carlo ( M -D i SG ro ) for prediction of the conformations of multiple interacting loops in proteins. Our method achieves an average RMSD of 1.93 Å for lowest energy conformations of 36 pairs of interacting protein loops with the total length ranging from 12 to 24 residues. We further constructed a data set containing proteins with 2, 3 and 4 interacting loops. For the most challenging target proteins with four loops, the average RMSD of the lowest energy conformations is 2.35 Å. Our method is also tested for predicting multiple loops in β-barrel membrane proteins. For outer-membrane protein G, the lowest energy conformation has a RMSD of 2.62 Å for the three extracellular interacting loops with a total length of 34 residues (12, 12 and 10 residues in each loop). Availability and implementation : The software is freely available at: tanto.bioe.uic.edu/m-DiSGro. Contact: jinfeng@stat.fsu.edu or jliang@uic.edu Supplementary information : Supplementary data are available at Bioinformatics online.

Description: Motivation: Network comparison is a computationally intractable problem with important applications in systems biology and other domains. A key challenge is to properly quantify similarity between wiring patterns of two networks in an alignment-free fashion. Also, alignment-based methods exist that aim to identify an actual node mapping between networks and as such serve a different purpose. Various alignment-free methods that use different global network properties (e.g. degree distribution) have been proposed. Methods based on small local subgraphs called graphlets perform the best in the alignment-free network comparison task, due to high level of topological detail that graphlets can capture. Among different graphlet-based methods, Graphlet Correlation Distance (GCD) was shown to be the most accurate for comparing networks. Recently, a new graphlet-based method called NetDis was proposed, which was claimed to be superior. We argue against this, as the performance of NetDis was not properly evaluated to position it correctly among the other alignment-free methods. Results : We evaluate the performance of available alignment-free network comparison methods, including GCD and NetDis. We do this by measuring accuracy of each method (in a systematic precision-recall framework) in terms of how well the method can group (cluster) topologically similar networks. By testing this on both synthetic and real-world networks from different domains, we show that GCD remains the most accurate, noise-tolerant and computationally efficient alignment-free method. That is, we show that NetDis does not outperform the other methods, as originally claimed, while it is also computationally more expensive. Furthermore, since NetDis is dependent on the choice of a network null model (unlike the other graphlet-based methods), we show that its performance is highly sensitive to the choice of this parameter. Finally, we find that its performance is not independent on network sizes and densities, as originally claimed. Contact : natasha@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: The functional impact of small molecules is increasingly being assessed in different eukaryotic species through large-scale phenotypic screening initiatives. Identifying the targets of these molecules is crucial to mechanistically understand their function and uncover new therapeutically relevant modes of action. However, despite extensive work carried out in model organisms and human, it is still unclear to what extent one can use information obtained in one species to make predictions in other species. Results: Here, for the first time, we explore and validate at a large scale the use of protein homology relationships to predict the targets of small molecules across different species. Our results show that exploiting target homology can significantly improve the predictions, especially for molecules experimentally tested in other species. Interestingly, when considering separately orthology and paralogy relationships, we observe that mapping small molecule interactions among orthologs improves prediction accuracy, while including paralogs does not improve and even sometimes worsens the prediction accuracy. Overall, our results provide a novel approach to integrate chemical screening results across multiple species and highlight the promises and remaining challenges of using protein homology for small molecule target identification. Availability and implementation: Homology-based predictions can be tested on our website http://www.swisstargetprediction.ch . Contact: david.gfeller@unil.ch or vincent.zoete@isb-sib.ch . Supplementary information: Supplementary data are available at Bioinformatics online.

Description: The wall thickness of hollow turbine blade has emerged as a significant cause of blade retirement. The precision of the final wall thickness of blade is mainly inherited from its corresponding wax pattern. The layout scheme of ceramic locators has a great influence on the wall thickness of wax pattern. A good layout of ceramic locators can significantly reduce the wall thickness shifting. To address this issue, a stable locator layout is needed to reduce the error transferring. The main purpose of this study is to find an optimal localization scheme for ceramic core. Firstly, the mathematical model of ceramic core localization was built based on the fixture design theory. Then, the optimal algorithm of locator layout design was studied. The D-optimality criterion has been chosen as optimal design criterion. Finally, two demonstration cases were presented. A localization scheme for real ceramic core was achieved and verified by using Monte-Carlo method. Moreover, the localization scheme was validated through experiments. Both simulation and experimental results indicated that the optimal localization can significantly reduce the input error.

Description: Inaccuracies in conventional tolerance characterization methods, which are based on worst-case and root-square-error methods, as well as inefficiencies in Monte Carlo computational methods of statistical tolerance analysis, require an accurate and efficient method of statistical analysis of geometric tolerances. Here, we describe a unified error distribution model for various types of geometric tolerance to obtain the distribution of the deviations in different directions. The displacement distributions of planes, straight lines, and points are analyzed based on distributions within tolerance zones. The distribution of the displacements of clearance fits is then determined according to the precedence of the assembly constraints. We consider the accumulated assembly variations and displacement distributions, and an analytical model is constructed to calculate the distribution of the deviations of the control points and the process capability index to validate the functional requirements. The efficiency of the method is shown by applying it to the assembly of a single-rod piston cylinder. The results are compared with other statistical methods of tolerance analysis. We find an improvement of approximately 20 % in tolerance analysis, and the process capability index of the assembly procedure was reduced by 10 %.

Description: This paper aims to reveal the material removal mechanisms of the elliptical vibration cutting (EVC) and present the predicted model of orthogonal cutting force. Further study of mechanism will be helpful to explain the phenomena that EVC can reduce the cutting force, lower cutting temperature, and improve the surface integrity. In each overlapping EVC cycle, almost all the parameters are time-varying, of which two important factors are focused: (i) transient thickness of cut and (ii) transient shear angle. The analysis model simplified the complex process of the EVC as conventional cutting (CC) which considering two transient variables. This paper presents a non-equidistant shear zone model to predict the shear angle, tool–chip friction angle, and shear stress in CC under the same conditions of the EVC. Then, the transient thickness of cut and transient shear angle are investigated. Thus, an analytical model of the force in EVC is proposed. The model is available to predict the cutting force of the EVC accurately without any experimental parameters in CC. In addition, experimental results available in the literature are conducted for comparison, which are in well agreement with the analysis model.

Description: by Po-Wei Chen, Luis L. Fonseca, Yusuf A. Hannun, Eberhard O. Voit The article demonstrates that computational modeling has the capacity to convert metabolic snapshots, taken sequentially over time, into a description of cellular, dynamic strategies. The specific application is a detailed analysis of a set of actions with which Saccharomyces cerevisiae responds to heat stress. Using time dependent metabolic concentration data, we use a combination of mathematical modeling, reverse engineering, and optimization to infer dynamic changes in enzyme activities within the sphingolipid pathway. The details of the sphingolipid responses to heat stress are important, because they guide some of the longer-term alterations in gene expression, with which the cells adapt to the increased temperature. The analysis indicates that all enzyme activities in the system are affected and that the shapes of the time trends in activities depend on the fatty-acyl CoA chain lengths of the different ceramide species in the system.

Description: With pervasive applications of new information technology, a larger number of manufacturing big data is generated. This paper considers the unrelated parallel scheduling problem within the background of “big data and cloud technology for manufacturing.” Traditional unrelated parallel problem has been extensively investigated, and the main objective has been to improve production efficiency. With regard to the environmental concern, there has been limited literature. Therefore, this paper considers an unrelated parallel machine scheduling problem with the objective of minimization to the total tardiness and energy consumption where the energy consumption on each machine is also unrelated parallel. First, we give a mathematical model of this problem. Second, ten heuristic algorithms are, respectively, proposed based on the priority rules, the energy consumption, and the combinational rules due to the complexity of this problem. Finally, in order to test the performance of these ten algorithms, computational experiments are designed. In the computational experiments, lots of instances are generated, and the computational results indicate that the algorithms based on the combinational rules outperform the ones based on the priority rules and energy consumption, with respect to the unrelated parallel scheduling problem proposed in this paper.

Description: by Pengyi Yang, Xiaofeng Zheng, Vivek Jayaswal, Guang Hu, Jean Yee Hwa Yang, Raja Jothi Cell signaling underlies transcription/epigenetic control of a vast majority of cell-fate decisions. A key goal in cell signaling studies is to identify the set of kinases that underlie key signaling events. In a typical phosphoproteomics study, phosphorylation sites (substrates) of active kinases are quantified proteome-wide. By analyzing the activities of phosphorylation sites over a time-course, the temporal dynamics of signaling cascades can be elucidated. Since many substrates of a given kinase have similar temporal kinetics, clustering phosphorylation sites into distinctive clusters can facilitate identification of their respective kinases. Here we present a knowledge-based CLUster Evaluation (CLUE) approach for identifying the most informative partitioning of a given temporal phosphoproteomics data. Our approach utilizes prior knowledge, annotated kinase-substrate relationships mined from literature and curated databases, to first generate biologically meaningful partitioning of the phosphorylation sites and then determine key kinases associated with each cluster. We demonstrate the utility of the proposed approach on two time-series phosphoproteomics datasets and identify key kinases associated with human embryonic stem cell differentiation and insulin signaling pathway. The proposed approach will be a valuable resource in the identification and characterizing of signaling networks from phosphoproteomics data.

Description: Increasing use of the nitinol (NiTi), the nickel titanium alloy is primarily due to the fact that the medical fraternity is looking more toward less invasive medical procedures. Microengineering features such as microslots, grooves, and profiles of size 0.5 mm and below are required in the NiTi alloy-based medical components, but the material offers tremendous manufacturing difficulty due to its superior mechanical properties. High-speed micro machining was viewed as a possible way to process the NiTi-based medical components without compromising the productivity and quality of the machined surface textures. A study was undertaken to characterize the high-speed micromachining process for the NiTi alloy. More specifically, the optimization of the machining process parameters with the objective of reducing the milling forces and burr formation was focused upon. The study unveiled that the understanding the tool-work interface behavior is critically important for maximizing the machining performance of the NiTi alloy. Machining behavior characterized in terms of low cutting forces and reduced burr size was achieved at 15 m/min of cutting speed when the NiTi alloy undergoes a transition from B2 phase to B19 phase.