Two–three orders of saving in computational cost, at the expense of some accuracy in prediction, especially in the prediction of the components of local tensor field quantities and the quantities near the grain boundaries, was obtained with GMC. Finally, the capability of the developed multiscale model linking FEA and GMC to solve real-life-sized structures is demonstrated by successfully analyzing an engine disc component and determining the microstructural scale details of the field quantities.A multiscale computational model is developed for determining the elasto-plastic behavior of polycrystal metals by employing a single crystal plasticity constitutive model that can capture the microstructural scale stress field on a finite element analysis (FEA) framework. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, the stand-alone GMC is applied for studying simple material microstructures such as a repeating unit cell (RUC) containing single grain or two grains under uniaxial loading conditions. For verification, the results obtained by the stand-alone GMC are compared to those from an analogous FEA model incorporating the same single crystal plasticity constitutive model. This verification is then extended to samples containing tens to hundreds of grains. The results demonstrate that the GMC homogenization combined with the crystal plasticity constitutive framework is a promising approach for failure analysis of structures as it allows for properly predicting the von Mises stress in the entire RUC, in an average sense, as well as in the local microstructural level,  Engine fan blades and discs are subjected to extreme temperatures and mechanical stresses during their operation. The prediction of damage initiation and propagation is important in these engine components, not only to avoid potential catastrophic mission failures, but for developing optimal and economical designs as well. Developing such prediction capabilities requires development of stress analysis models that can incorporate the interaction of various microstructural features, such as grain boundaries and dislocations.For metals and metallic alloys, the major deformation mechanism at the microstructural scale is the dislocation motion causing plasticity. Two key characteristics that define plasticity are the permanent strain due to slipping of atomic layers under shear stress and the strain hardening, both contributing to the macroscale nonlinear stress-strain behavior. In the single crystal plasticity models, the dislocation motion is implemented as permanent shear strain in the various slip systems (slip plane and slip direction) with the aid of a set of state variables ,2. The sThe major challenge in implementing microstructure-based plasticity models in real-sized structural components is the excessive computational cost, as it requires solving governing equations at both the microstructural and macrostructural length scales. Even for modeling a small subscale volume consisting of tens to a few hundred grains, the computational cost for executing a finite element model incorporating the physics of dislocation at the microscale motion is exorbitant. To address this challenge, the development of various multiscale models, broadly classified under three major methods, namely, sequential , computational homogenization scheme  The Representative Volume Element (RVE) method based on statistical homogenization theories considering the random distribution of the microstructural features; and (2) The Repeating Unit Cells (RUC) method based on periodicity in the microstructure. The definition of RVE requires the equivalent homogenized displacement and traction boundary conditions to be simultaneously satisfied. The RUC-based methods were proposed to address the difficulty in satisfying the required homogenous traction–displacement boundary condition for arbitrarily chosen, statistically homogeneous, microstructures in the RVE concept. Besides analytical methods, those mainly developed for elastic materials, the numerical solutions of the RUC using boundary element method , the disSemi-analytical techniques such as the generalized method of cells (GMC) have also been developed for RUC homogenization ,33,34,35In this article, GMC is evaluated as a potential method of homogenization to develop a multiscale model that can capture microscale plastic deformation in polycrystal metals and metallic alloys. This work is an extension of a previous study by authors ,39 on thF is then given by:The kinematics for the deformation mechanics of crystals follows the pioneering work of Taylor , and HilBased on the deformation gradient definition, the total velocity gradient p), respectively.In which the symmetric stretch rate m is the unit normal to the slip plane; and n is the unit vector parallel to slip direction. The incremental formulation of plasticity theory is based on (1) the evolution of Cauchy stress in the corotational frame of reference that rotates with the crystal lattice, i.e.,The velocity gradient associated with the plastic deformation therwise .(8) hααThe latent hardening modulus is given by:For the numerical implementation of a single crystal plasticity model, a User MATerial (UMAT) subroutine in the form of for Abaqus  is used.The generalized method of cells is a micromechanical formulation for predicting the overall thermo-inelastic behavior of the multiscale composites. There are four steps involved in this homogenization process ,44. FirsAs the second step, the relationships between the macroscopic average stresses and strains with the microscopic fields are established. A linearly variable displacement, The definition of strain tensor in each subcell Then, the average strain in the RUC is defined as:Considering a general constitutive equation for thermo-elastic-plastic materials in each subcell Based on the volumetric summation of the average stresses in all subcells, the average stress in the entire unit-cell can be written as:In the third step, the continuity of strain and traction is applied. It is considered that the RUCs are periodic, and the interfaces of the subcells and the boundaries of the RUCs follow the displacement and traction continuity. Applying these conditions results in elimination of the microvariables in the displacement definition and produces a set of continuity relationships. As a result, a set of The continuity of tractions, results in:The strain and traction continuity conditions (Equations (17) and (18)) can be combined as:Rewriting this equation for each subcell as:In the fourth step, the overall macroscopic constitutive equations of the material are obtained based on the effective properties. The average (homogenized) constitutive equation for the RUC is:The global inelastic strain tensor It should be noted that GMC was reformulated to solve for subcell tractions, as opposed to strains, to improve computational efficiency .The Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC), developed by NASA Glenn Research Center , which pThe main objective for a multiscale analysis is to provide an accurate constitutive response to the higher scale, being the average stress and strain behaviors of the microscale. In addition, for a failure study of a structure, it is helpful to be able to predict the field quantities at a microstructural length scale. In the results and discussion section of this study it has been attempted to evaluate the GMC homogenized solution combined with the crystal plasticity framework in polycrystalline materials with regard to both the entire RUC and the local microstructural behaviors.z direction, were considered. In the FEA model, periodic boundary conditions were applied in all three directions to simulate the periodicity of the unit cell in a bulk domain. At first, the stress–strain behaviors of a single crystal sample under uniaxial loading was analyzed and compared with FEA. This was followed by a polycrystalline sample made up of two grains. Both the global stress–strain curves obtained from the entire domain and the local stress-strain curves of the individual grains were compared. Then, the analyses of polycrystals with 27, 64 and 125 grains were implemented. A face-centered-cubic (FCC) copper sample with 12 active slip systems ({111} <110> family) and the cubic material properties , was considered. The corresponding results in terms of the variation of average axial stress (zzσ) vs. the average axial strain (zzε) are shown in A 100 × 10 × 10 The GMC convergence was studied by varying time increments, number of iterations and permitted error (ERR) for the convergence. It is observed that the GMC solution can converge to the solution from FEA, either by refining the load increments without changing the number of iterations, or, for the smaller number of load increments, by allowing for more iterations.Applicability of the GMC base homogenization approach for polycrystalline samples are studied in this section. At first, in A simple polycrystal consisting of two grains, as shown in zzε), the average axial stress component (zzσ) and the average von Mises stress plotted against the load-step for the entire domain are shown in The average axial strain component  in each dimension with a total of n3 grains (exact) in the sample. The The GMC and FEA results are compared for the 3 × 3 × 3 grain sample under the uniaxial applied tensile loading .The average stress-strain behaviors obtained from both these methods, in all the three directions, are shown in z-direction, are further studied by comparing the behavior of three arbitrarily chosen grains  obtained by GMC and FEA , while the other (element 145) was in the region near boundary between the grains. The GMC and FEA results of the axial strain show significant difference a in eachIn the case of von Mises, element 628 has excellent agreement, while element 145, closer to the grain boundary, shows reasonable agreement. Even in the elastic regime, the GMC and FEA von Mises stresses differ because of additional shear stresses introduced through normal-shear coupling in the FEA model. A more detailed comparison is provided in In addition, the von Mises stress distribution on the cross-section is compared in The computational speeds were compared between GMC and FEA for three different cases: Case (1) a single crystal with one element/subcell; Case (2) 27-grain polycrystal with 1000 elements/subcells and Case (3) 125-grain polycrystal with 2744 elements/subcells . GMC demi.e., “handshake”) between the macro- and microscales. Thus, the good agreement in the prediction of the average RUC fields demonstrates that GMC is a viable subscale tool for integration in a multiscale framework.The significant savings in the computational cost in addition to the capability to predict the average RUC field quantities with minimal error make GMC homogenization a reliable and efficient method for analyzing large-size problems. Large stress gradients near the grain boundaries due to the abrupt change in the orientation of the grains adversely impact the local prediction accuracy of GMC due to the lack of normal-shear coupling, especially for the components of field tensor quantities averaged over the grains. However, the error on the prediction of effective quantities such as von Mises is within a reasonable range. The local values of the stress tensor components and the von Mises stress, determined at the element integration points, showed higher accuracy for the elements away from the grain boundary. Though the prediction error of the stress tensor components were relatively high for elements near the grain boundary, the error associated with the von Mises remained within reasonable limits. It is also important to note that the stress gradients near grain boundaries in real materials are not as sharp as that predicted by FEA due to various grain boundary deformation mechanisms and smoother grain boundaries. Hence, difference in the prediction between FEA and GMC decreases in a more realistic case than that observed in the present study. In summary, it can be stated based on the results from the present study that the GMC method can be used for extracting the effective von Mises stress  at microscale with a reasonable accuracy, while reducing the computational cost significantly. Moreover, it is the average RUC stresses and strains that provide the link  to develop the multiscale model that can analyze structural scale problems consisting of millions of grains. The macroscale strain, updated in each time-step, is determined at the integration points of the macroscale FEA elements. These integration point quantities are applied to the RUCs  homogenized by GMC, providing the average stresses, stiffness and inelastic strains back to the FEA  integration point. For the purpose of demonstrating this functionality, a segment of a real-size turbine disk is analyzed. The disk is 254 The von Mises stress distributions shown in The distribution of the grain orientations on the chosen cross-section of the RUC and the von Mises stress distribution on this cross-section for two of the integration points of a random element (here Element 112) are demonstrated in A multiscale computational model was developed by employing the single crystal plasticity constitutive model at the microscale, in conjunction with GMC for homogenization, coupled to an FEA framework at the macroscale. In order to verify the effectiveness of GMC as a homogenization tool, the microscale behavior of single and polycrystalline samples were determined using the stand-alone GMC, and compared to that obtained from the standard FEA utilizing higher-order elements. For the polycrystals consisting of tens to hundreds of grains, GMC analysis achieved two–three orders of savings in computational cost at a minimal expense of accuracy in the components of both average and local tensor field quantities. The results based on GMC homogenization demonstrated reasonably good agreement with the FEA solution in terms of the von Mises and stress tensor components for the entire studied polycrystalline domain, the grain-averaged von Mises, von Mises and stress tensor components for elements away from the grain boundaries and von Mises for elements near the grain boundary. Therefore, the von Mises stress was found to be in a reasonably good agreement for all cases, making GMC a promising method for failure analysis applications.Although the large gradient near the grain boundaries was not captured by GMC, the applicability of GMC homogenization is expected to be more effective in real materials where behavior does not vary at the grain boundaries as drastically as in the model due to various grain boundary deformation mechanisms. In addition, the accuracy of the local fields may not be pertinent in the absence of failure localization, as long as the average stress and strain quantities are accurate, since this is the mode for transmitting information across the scales in this multiscale framework.Finally, the multiscale aspect of the model was demonstrated by implementing GMC as a homogenization tool on an FEA platform and investigating a real life turbine engine disc problem. The macroscale results demonstrated the expected stress distribution when compared to the FEA-based analysis, thereby verifying the method. The microscale distribution of von Mises stress was extracted on the cross-section of an arbitrarily selected element. The results demonstrated the multiscale capability of the developed multiscale model and may allow engineers to model variability in the microstructure spatially within a structural component and tailor the microstructure for different structural applications.


R), and zero crossing (ZC) from the epileptic signal. The k-nearest neighbours (k-NN) algorithm is used for the classification of epilepsy then regression analysis is used for the prediction of the epilepsy level at different ages of the patients. Using the statistical parameters and regression analysis, a prototype mathematical model is proposed which helps to find the epileptic randomness with respect to the age of different subjects. The accuracy of this prototype equation depends on proper analysis of the dynamic information from the epileptic EEG.Electroencephalographic signal is a representative signal that contains information about brain activity, which is used for the detection of epilepsy since epileptic seizures are caused by a disturbance in the electrophysiological activity of the brain. The prediction of epileptic seizure usually requires a detailed and experienced analysis of EEG. In this paper, we have introduced a statistical analysis of EEG signal that is capable of recognizing epileptic seizure with a high degree of accuracy and helps to provide automatic detection of epileptic seizure for different ages of epilepsy. To accomplish the target research, we extract various epileptic features namely approximate entropy (ApEn), standard deviation (SD), standard error (SE), modified mean absolute value (MMAV), roll-off ( Epilepsy is a long-lasting neurological disorder categorized by repeated, gratuitous seizures, electrophysiological disturbances in the human brain which may range from brief gaps of attention or muscle bumps to severe and prolonged seizures. Epileptic seizures are the visible or apparent manifestations that are produced when the brain briefly becomes dysfunctional because of abnormal paroxysmal discharge of the nerve cells in the cerebral cortex –3. AlterThe brain may get impairment from injuriesInherited abnormalities with associated brain defectsA severe head injuryStroke may limit the amount of oxygen to the brainSome infection like meningitis and encephalitis of the human brainA brain tumour which creates more randomness.The sodium and potassium channels are associated with a depolarizing phase which occupy the medium position by sodium channel opening and a repolarizing phase due to potassium-channel opening and sodium-channel inactivation. On the other hand, remaining potassium channels contribute to a longer-term repolarization that acts as the prevention of repetitive excitation of the neuron. In There are several methods to diagnose epilepsy such as electroencephalography (EEG), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), single-photon emission computed tomography (SPECT), positron emission tomography (PET), and magnetoencephalography (MEG). As EEG has speed, high time resolution, and non-invasive advantages, still now it remains one of the most useful and effective tools in the treatment of epilepsy. Prediction of epileptic seizure based on EEG signals can be separated into three classes: time domain, frequency domain, and the nonlinear methods . In recek-NN) and statistical features (approximate entropy (ApEn), standard deviation (SD), standard error (SE), modified mean absolute value (MMAV), roll-off (R), and zero crossing (ZC)) are described below.Mathematical background for the classifier (k-nearest neighbours (k-NN) algorithm is a nonparametric learning algorithm mechanism mainly used for the classification of signal pattern or pattern recognition as shown in k-nearest neighbours within the training sets of data [The  of data , 17.k-NN is the best classifier statistical pattern recognition or neighbour cluster selection as shown in k-NN classifier extends this idea by taking the k-nearest points and assigning the sign of the majority [k” indicates how many neighbours guide the classification. The default value k = 1 is called the nearest neighbour algorithm. In the classification analysis, k-NN is the supervised learning algorithm [k-NN for the classification of any data set X is described below step by step. i numbers of categories in a training set which is denoted by  C1, C2, C3,…, Ci. The summation makes m-dimensional feature vector.Consider that training categories is the column vector of training set. If there are X should have the same dimensional vector for the proper classification which is denoted by X1, X2, X3,…, Xm.The sample data set jth sample  dj . The similarity SIM is mentioned inIn this state, the similarity between training set and data set should be calculated. Taking k which is larger from N similarity of SIM  . Now, the probability function has the following mathematical form:(4) Select the value of y  is the category of attribute function which satisfies the following mathematics:X to categories which have larger value of .(5) Finally, justification of sample Among all of the method of classification like support vector machine (SVM), artificial neural network (ANN), linear discriminant analysis (LDA), naive Bayes (NB), and RBF neural network (RBFNN), majority . The poslgorithm , 20. Thek-NN classifier, the distance between two sets of data points is measured by some distance vectors, which are Euclidean distance, cityblock distance, cosine distance, and correlation distance.In the dst, is inIn statistical mathematics, the Euclidean distance is the distance between two points in Euclidean space, which becomes a metric space whose norm form is commonly known as Euclidean norm. The Euclidean distance, dst is represented inThe distance between two points is the sum of the absolute differences of their Cartesian coordinates known as the cityblock distance which is also known as Manhattan length . CitybloDc = 1 − Sc. Cosine distance dst is represented inCosine distance is the distance which is used for the complement in positive space, that is, dst is represented inCorrelation distance is the measure of statistical distance between two random variables or two random vectors of arbitrary, not necessarily equal dimension. Correlation distance k-NN classifier in this research are described below.The statistical features used for the classification using ApEn is a statistical feature that indicates the predictability of the current amplitude values of a physiological signal, for example, EEG based on its earlier amplitude. The value of ApEn drops sharply during an epileptic seizure, and this property is used to detect the epileptic seizures. A high value of approximate entropy signifies more irregularity; on the contrary, a low value signifies that the time series is deterministic which reflects the intracortical information flow in the brain when applied to EEG signals , 23. TheMathematical procedures of approximate entropy (ApEn) calculation are described in a flow chart , 24 in FN is the number of samples in data sets, xn is the actual value of the nth term in data sets, and μ is the average value of those data sets. The standard error (SE) is define as the standard deviation (SD) of a sample data set which is the estimation of sample mean based on the population mean. SE is the mean which is calculated usingThe measurements of square root of a variance of random variable, statistical population, any kinds of data set, or probability distribution is known as the standard deviation (SD) which is also known as absolute deviation. The standard deviation can be defined for any distribution with finite first two moments, which can be measured mathematically by usingWn [Mean absolute value (MAV) is the moving average of full-wave rectified data sets which is the measurement of average value by taking the average of absolute value of data sets. So, MMAV is the extension of MAV, in which the individual value is multiplied by weighting function Wn  that canRoll-off is the steepness of a transmission function with frequency, particularly used in signal feature extraction. The roll-off can be defined as the frequency below which 85% of the magnitude distribution of the data sets is intense . It is ay-axis [Zero crossing (ZC) is the frequency domain features of the data sets which measures the number of times that the amplitude value of data sets crosses the zero y-axis . It can Y represents predicted outcome value for the polynomial model with regression coefficients b1 to bk for the kth order polynomial and Y intercept b0.In mathematics, regression analysis is the procedure to find out the mathematical relationship between dependent variables with independent variables. In limited conditions, regression analysis can be used to infer causal relationships between the independent and dependent variables. However, in many applications, especially with small effects or questions of causality based on observational data, regression methods can give misleading results. The function which fits a polynomial regression model by the method of linear least squares is mentioned below. R), and zero crossing (ZC). These feature vectors are classified according to the standard feature vector using k-NN classifier. After classification of epilepsy, regression equation is used to find the level of ApEn for different ages of epilepsy from epileptic EEG. High irregular time series EEG signal gives higher value of ApEn and vice-versa. Moreover, higher value of ApEn indicates more irregularity of the epileptic EEG signal. The level of ApEn is increased with the increase of the age of epileptic patients. Finally, error for each interpretation is measured to find out the best fitted equation for the interpretation which is most suitable and optimized regression equation for the prediction.The overall proposed methodology is mentioned in a flow diagram as shown in k-NN network. In k-NN network in which all the arrows indicate the nearest neighbour where blue squares indicate the train features set and red diamond are the desired points whose nearest neighbour is our goal. On the other hand, in k-NN classifier. To accomplish the research goal, one desired standard feature point is set as a reference and then the k-NN network is trained; its clustering circle is determined around the point of interest. In k = 10 nearest neighbour is determined inside the circle to find out the close approximation of epileptic EEG signal using feature vectors  for that one feature of vector from the normal EEG data (free from the epilepsy) from the patient is required.The epileptic EEG data is processed for the achievement of the feature vector and then a template as mentioned in k values is also analysed keeping corresponding parameters constant. The performance of the k-NN classifier which is a confusion matrix is shown in Tables k = 1 and the classifier rule is smallest neighbour (SN).In this research work, four distance parameters namely cityblock, correlation, cosine, and Euclidean are used in our analysis and their performance is analysed by considering other parameters keep constant. Similarly, the performance of classifier rule namely nearest neighbour (NN), random neighbour (RN), and smallest neighbour (SN) as well as different The 3rd-order fittings of the approximate entropy (ApEn) is shown in The modification between the predicted value and actual value of the independent value is called the residual which is the measure of accuracy of prediction. The residual of the 3rd-order fitting is shown in In a similar manner, 4th-order fittings of the approximate entropy (ApEn) is shown in The residual of 4th-order fitting is shown in y = mx + c which has more error probability and also it has a larger value of residual than other types of fitting of ApEn. From the table, it is noticed that the increase of order of fitting may reduce the error probability, but after the 3rd-order fitting, the error probability as well as the computational complexity is increased. Hence, optimum prediction equation for the epileptic seizure is the 3rd-order which has less computational complexity and less error probability than the 4th-order fitting. Form the table, it is also remarkable that at the smaller age of the epileptic people, the prediction error is more because at the increasing ages of the epileptic persons the EEG (epileptic) is more severe.In The electrophysiological activity of the brain called EEG signal can analyze for the prediction and diagnosis of epilepsy of the living animals. The epileptic EEG signal is more and more random and this EEG containing epilepsy is not suitable for the perfect brain-computer interface (BCI) paradigms. Hence, prediction of epilepsy is a vital issue in the modern biomedical field of research. For the prediction of epilepsy, a statistical approach was explained in this manuscript. In our research, the epileptic EEG signals for different aged epileptic subjects was analyzed and one of the vital features Approximate entropy (ApEn) was measured which was the indicator of randomness of any time domain signal. The regression equation of ApEn with respect to different ages of the epileptic persons may help the BCI researchers or the neural researcher to predict the randomness, namely, level of epilepsy corresponding to different ages. This may help the clinical person to provide the treatment of the epileptic person after finding the level of randomness.


Composite material structures are commonly used in many industrial sectors , and can operate in harsh environments where impacts with other parts or debris may cause critical safety and functionality issues. This work presents a method for improving the accuracy of impact position determination using acoustic source triangulation schemes based on the data collected by piezoelectric sensors attached to the structure. A novel approach is used to estimate the Differential Time-of-Arrival (DToA) between the impact response signals collected by a triplet of sensors, overcoming the limitations of classical methods that rely on amplitude thresholds calibrated for a specific sensor type. An experimental evaluation of the proposed technique was performed with specially made circular piezopolymer (PVDF) sensors designed for Structural Health Monitoring (SHM) applications, and compared with commercial piezoelectric SHM sensors of similar dimensions. Test impacts at low energies from 35 mJ to 600 mJ were generated in a laboratory by free-falling metal spheres on a 500 mm × 500 mm × 1.25 mm quasi-isotropic Carbon Fiber Reinforced Polymer (CFRP) laminate plate. From the analysis of many impact signals, the resulting localization error was improved for all types of sensors and, in particular, for the circular PVDF sensor an average error of 20.3 mm and a standard deviation of 8.9 mm was obtained. Interest in the detection and measurement of impact position on critical structures and components is growing in the scientific community. Composite materials are now commonly used in the aerospace, automotive, and transportation industries. Several authors have proposed impact localization methods based on acoustic/ultrasonic sensing. Kundu et al. have studied the minimization of transducers to be installed on the structure by leveraging the direction of arrival of the localized acoustic source . Other aThe influence of medium anisotropy, which results in different propagation velocities along different directions, was investigated in . MoreoveStructural Health Monitoring (SHM) provides real-time integrity monitoring of in-service structures to prolong their life and reduce maintenance costs. The Structure Health Monitoring system includes active sensing and passive sensing techniques: (1) passive sensing is where all of the sensors listen to the structure response caused by impacts to the structure. This becomes useful for analyzing impact events and impact force-time history; (2) active sensing is an excitation signal is sent to an actuator and other sensors pick up the structure response from the excitation signal. This type of sensing can detect damages on metal or composite structures including cracks, corrosion, delamination, and debonding, etc. By combining the active sensing and passive sensing technology together, a comprehensive scheme can be provided to detect any abnormally of the structure in real-time. Localization accuracy is important for correlating specific impact events with damage detection data and monitoring their progression over time, especially when using prognostic models .In ,9,10,11,The work hereby presented aimed at improving the impact localization performance of previous systems with novel signal analysis techniques.In its most basic form, impact localization through triangulation is performed by observing the instants at which an impact response signal is recorded by (at least) three sensing elements placed at known positions, and inferring the source location by knowing the propagation velocity of each signal. Since the position of the sensing elements is generally fixed by design, the main sources of error in this calculation are the identification of the Differential Time-of-Arrival (DToA) between the sensors, and the propagation velocity of the impact response signal. The issues related to Lamb wave propagation velocity were already addressed in , howeverWhen performing impact localization on a plate-like structure by detecting guided (Lamb) wave ultrasound signals, the problem is further complicated by a series of factors that are related to both the mechanical properties of the medium, and to the intrinsic characteristics of the propagating modes. The aim of this work was developing a versatile impact localization algorithm that could address both issues, and provide accurate and predictable results regardless of the sensor technology and with limited knowledge of the propagating modes group velocities into the material.The research started by empirically investigating the behavior of a Carbon Fiber Reinforced Polymer (CFRP) laminate plate when subject to impacts. This helped in understanding the characteristics of impact response signals that were relevant to the process of impact localization.Afterwards, the propagation velocity profiles of Lamb waves on the plate were characterized to understand the extent of their influence on impact response signals, and to extrapolate the data needed to perform a triangulation on such a structure. This preliminary experimental phase led to the development of a new method for extracting the DToA from the impact response signal, based on the identification and selection of specific features from these signals. The proposed DToA extraction method was thus integrated with the triangulation algorithm and evaluated with a series of controlled impact localization tests using different sensor technologies and impact energies.The proposed approach is to generate a data base of impact signals for the following analysis of the average error and the standard deviation of each sensor type. We believe that such performance analysis based on an experimental database is not common in related works in the literature, and is very useful for the laboratory investigation of real composite material structures. The paper starts by describing the experimental setup used for performing impact tests and acquiring the response signals from the sensors. Impact response signals are analyzed in m of the impactor and the height h from the plate surface defined the impact energy according to the equationm is the mass of the sphere, g is the gravitational acceleration and h the drop height. Considering m = 8.5 g, g = 9.8 m/s2 and h = 420 mm, the impact energy was E = 35 mJ. The precision of the impact test rig was evaluated using carbon paper to trace the actual point of impact of the falling sphere, resulting in a repeatability better than 4 mm.Repeatable impacts were generated on the test plate by a free-falling (unguided) metal sphere released by an electromagnet. The mass The data acquisition system, described in , is showS = 10 MSps, with 10,000 samples acquired per trace . A hardware impact detection procedure ensured that the time traces from all the channels were captured synchronously within a time window including at least 100 μs of signal before the triggering event occurred, which corresponded to the first leading wave detected by any one of the sensors . The data were then transferred to a computer and processed using MATLAB.The sampling rate was fixed at fWhile the hardware impact detection procedure used a fixed threshold (in the order of dozen of mV) to capture the impact response within a certain time window, this information was later ignored by the proposed localization algorithm, and, as will be explained below, a different approach was used to extract a better estimate of the DToA from the recorded traces.Impact tests were performed with three types of sensors triplets attached to the plate surface using double-sided tape (Tesa 4972) and interleaved at regularly spaced angles over a circle of diameter 340 mm, resulting in 120° spacing between sensors of the same kind  and they confirmed that the impact response signals were mostly constituted by AVisual inspection of the time-domain trace of Guided-wave group velocities along the main directions of the CFRP plate were measured using the method reported in ,14.0 Lamb waves that were picked up by the other transducer. The selected center frequency range used for these measurements (20 kHz to 100 kHz) was chosen to cover the results of the spectral analysis performed in Two type C transducers (Acellent SML-SP-1/4-0) were coupled to the plate surface using an ultrasonic shear-wave couplant (Panametrics NPD-053-8002). One transducer was fixed at the center of the plate and used to transmit Morlet wavelets with different central frequencies, exciting AMeasurements were performed at all of the selected central frequencies for different directions  and using a level four times greater than that value. The actual crossings of the impact response signals could thus be identified reliably without presetting a threshold.d” in d. The resulting value, which was dubbed “frequency hook”, was used to characterize the signal swing across the zero-crossings of the waveform. Note that this “frequency hook” parameter does not measure the spectral content of a specific portion of the waveform, because given the non-stationary nature of the waveforms (which are not pure sine waves), their actual bandwidth will be broader.The proposed algorithm thus proceeded by identifying the first threshold crossing, and then searching for the previous local minimum and the successive local maximum of the waveform, and extrapolating their time difference  was calculated for every one of the grid nodes  according to Equation (2), proposed by Kundu et al. in [ix, iy) and , while the term DToAij represents the quantity (it − jt), that is the difference of the absolute time of arrival detected with the proposed algorithm on the waveforms acquired with sensors i and j. The absolute minimum of E was then found, and its coordinates represented the best estimate of the impact location.After obtaining the DToAs byusing the method described above, the impact position coordinates were found by solving a triangulation scheme with a brute-force minimization approach. The target surface was divided in a quadrangular grid with fixed step size of 1 mm, and an error function TN = 3, corresponding to the experimental conditions described in this paper, but this method can accommodate an arbitrary number of inputs.The minimum number of sensors needed to univocally solve the problem is v. However, as explained above, this parameter depended on both the frequency (since guided waves are dispersive) and direction (the guiding medium is anisotropic), becoming a function The DToA values extrapolated from the time-domain traces needed to be converted into a distance to solve Equation (2), requiring the knowledge of a propagation velocity x, y):  mm,  mm,  mm,  mm, and  mm, respectively. Every impact test was repeated ten times for each combination of impact point and sensor type.To evaluate the performance of the proposed algorithm, five impact tests were carried out at different coordinates on the CFRP test plate using the setup described in The beneficial effects of the proposed algorithm are best understood by analyzing how certain impact response signals were processed, and how the DToAs were extracted.Moreover we can evaluate the improvement of the proposed algorithm compared to the case of the DToA estimation with the automatic threshold. An analysis of the complex nature of the impact response signals acquired with various sensors highlighted the need for robust processing in the estimation of DToA. The authors thus developed an algorithm capable of extracting an accurate DToA by exploiting the oscillatory characteristics of the received signals.To solve the impact triangulation Formula (2), two parameters that depend on the characteristics of both the medium and of the guided waves were needed: the DToAs and the propagation velocity. Measurements showed that the dispersion and anisotropy caused a variation of up to ±22% of the velocity profiles within the bandwidth of interest and over different directions. The extraction of DToA was also affected by error, however acting on it does not require extensive characterization of the guiding medium, and therefore can represent an overarching improvement of impact triangulation accuracy.To confirm the results shown in This paper presented a novel method for recognizing the differential time-of-arrival of impact response signals that improves the impact localization accuracy when using triangulation. This method was applied to guided-wave impact localization in CFRP plates, where dispersive and anisotropic behavior are non-negligible.It was found that approximating the propagation velocity of the received signals with a constant value has an influence on the results similar to the error introduced by a DToA estimated affected by a significant error. Missing the correct zero-crossing can lead to large errors, especially in the presence of spurious contributions within the impact response signals. Therefore, improving the DToA extraction method resulted in a net improvement of the localization performance, comparable to knowing the actual propagation velocities to a good accuracy.The proposed method was successfully applied to different type of piezoelectric sensors without tuning its parameters to the specific sensors type.Finally, the proposed method for the DToA estimation can be integrated with other methods already presented in the literature that provide an accurate estimation of the


The machinery of translation is one of the most common targets of antibiotics. The development and screening of new antibiotics usually proceeds by testing antimicrobial activity followed by laborious studies of the mechanism of action. High-throughput methods for new antibiotic screening based on antimicrobial activity have become routine; however, identification of molecular targets is usually a challenge. Therefore, it is highly beneficial to combine primary screening with the identification of the mechanism of action. In this review, we describe a collection of methods for screening translation inhibitors, with a special emphasis on methods which can be performed in a high-throughput manner. Each year the number of resistant bacterial strains increases, so finding new antibiotics is one of the principal goals of modern biochemistry. Both natural extracts and chemically synthesized compounds can be used in the high-throughput screening of antimicrobial agents . These mThe most effective known methods for initial screening are to use biosensor bacterial strains with different reporter systems detecting the presence of specific antibiotics. . While slucGR from Pyrophorus plagiophthalamus, luxAB from Photorhabdus luminescens, and luxAB from Vibrio harveyi—were cloned under the main leftward promoter pL from bacteriophage λ [Pyrophorus plagiophthalamus was found to be the best measure among these three test systems. The presence of translation inhibitors, such as tetracycline and chloramphenicol, was vividly shown by this method. The authors also showed that with the use of lyophilized bacteria, the test could be done in one hour without cultivation. The replacement of a strong pL promoter by an inducible tetracycline promoter allowed the authors to significantly increase the sensitivity of transcriptional and translational antibiotic detection [Three different luciferase systems—ophage λ . This pretection . These aE. coli is cultivated at 37 °C [ibpA and cspA genes were placed upstream to the lacZ gene and these constructs were integrated into the genome of wild-type E. coli K-12. CspA is major cold shock protein of E. coli [cspA increases dramatically in the conditions of cold shock. The expression of cspA::lacZ fusion was activated as expected by chloramphenicol and tetracycline. IbpA is a small heat shock protein and its expression increases significantly under temperature upshift; the expression of ibpA::lacZ fusion is induced by streptomycin, neomycin (aminoglycoside antibiotics) and polymyxin B . Both reporters can be used in a liquid culture and on agar plates.An antibiotic’s action on a cell typically induces a specific stress response, which can be used to classify an antibiotic’s mode of action . Temperaat 37 °C . To crea E. coli , and duetolC gene [lacZ with luc  [lacZ and luc in one biosensor strain.The inactivation of the olC gene  in theseiferase)  makes thPhotorhabdus luminescens and firefly Photinus pyralis luciferase) [luc genes on a plasmid. In the absence of tetracycline, the repressor protein binds the promotor and inhibits expression. The binding of tetracycline to the repressor leads to dissociation of its complex with DNA, and activates downstream gene expression. Both sensors can be used for the detection of tetracyclines in veterinary samples, or for the screening natural compounds. The quality of sensors is not shown to decrease through lyophilization and freezing. These sensors are very sensitive (10 ng), but can detect only one class of antibiotics.One specific detection system is based on the tetracycline response element from transposon Tn10 plus two different bioluminescence systems  . A tetramphA is dependent on the presence of macrolides. MphR is a transcriptional repressor of mphA. The binding of a macrolide to MphR leads to a dissociation of the repressor from the mphA promoter, and expression increases. An mphA promoter was placed upstream to the luciferase genes of Vibrio fischeri, and made the biosensor dependent on the presence of classical 12- and 14-membered macrolides, or semisynthetic clarithromycin and azithromycin [MphA is a macrolide 2′-phosphotransferase. This enzyme inactivates 14-membered macrolides, such as erythromycin. The expression of hromycin . This asermC is a specific RNA methyltransferase which is expressed in response to macrolide exposure [ermC(L) was placed upstream of the lacZ gene, which made the expression of the reporter gene dependent on the presence of macrolides and ketolides [exposure  and modietolides . By meantrpL and cerulean fluorescent protein [tolC knock-out strain with this reporter system was demonstrated. The minimal detectable concentration of the tested substances decreased significantly. A new translation inhibitor, amicoumacin A, was identified by means of this reporter system [A broad-specificity system for the detection of translation inhibitors was developed on the basis of the tryptophan attenuator  protein . Two tryr system . This apE. coli strain helps to avoid the antibiotic resistance marker. Further, 14 promoters  were placed upstream to the luxCDABE operon, and 14 reporter strains were created [soxS reporter was specifically induced in the presence of the ribosomal antibiotics tetracycline, oxytetracycline and chloramphenicol. The exact mechanism linking this reporter with translation inhibition is still unknown, but empirically it can be used for the detection of at least two types of translation inhibitors.The majority of antibiotic sensor strains have one significant drawback: they are resistant to at least one antibiotic used to maintain a reporter plasmid. This method is not useful for broad screening, since some potential antibiotics will be missed. A tryptophan auxotroph  created . The autB. subtilis genes were cloned upstream to the firefly luciferase gene, and these reporters were tested with a large panel of the antibiotics with various mechanisms of action. The yheI-based reporter [yheI gene expression is still lacking. This protein has a similarity to multidrug-resistant ABC pump proteins. In spite of the absence of a complete understanding of the mechanism, this reporter can be used in screening new potential antibiotics.Promoters of several reporter  specificSalmonella typhimurium was fragmented and cloned upstream of luxCDABE in order to produce a library of more than 6000 individual “promoter clones” [The DNA of  clones” . For a lAfter finding a new translation inhibitor by means of any reporter assay, an in vitro confirmation of the mechanism of action is necessary. There is a broad spectrum of various in vitro techniques. Inhibition of in vitro translation is the easiest way to indicate the mechanism of action of a potential translation inhibitor. Such a reaction can be carried out in a coupled transcription/translation reaction, either supplied by DNA or in a translation reaction supplied by mRNA. Either cell extracts  or pure To simplify the procedure of measurement, to avoid the purification of the synthesized protein or the separation of proteins in gel, luciferase mRNA was used. Adding the luciferin after a reaction allows the detection of luminescence, and measures translation inhibition. The significant reduction of the reaction volume to 2 μL allowed the authors to use this in vitro inhibition assay for high-throughput screening . By meanThe mRNA-ribosome complex can be analyzed by means of reverse transcription with an oligonucleotide annealed downstream to a bound ribosome; the stopping of reverse transcriptase indicates the location of the ribosome on the mRNA. Various translation antibiotics inhibit specific functions of ribosomes, and the site of an arrested ribosome is dependent on the mechanism of the antibiotic’s action. A toe-printing assay can be done directly in a translation reaction in a cell-free transcriptional/translational system composed of purified components. A large set of translation inhibitors affecting the 50S and 30S subunits were tested, and specific patterns of reverse transcription stops were detected . Some anPeptide bond formation is a key stage in protein synthesis. If one participant of peptidyl transferase reaction is tritiated and the other is biotin-tagged, the efficiency of peptide bond formation can be easily measured . The decThe insertion of a fluorescent label into a ribosome provides the possibility to study the binding of small molecules such as antibiotics. Such a fluorescent label was added to the S12 protein near the drug’s binding site. The binding of the antibiotic changed the environment of the fluorophore and changed the fluorescence . For strBoth large and small ribosomal subunits were labeled with fluorescent proteins EGFP and mCherry, respectively . MicroscSeveral antibiotics which affect translocation, such as viomycin, spectinomycin, streptomycin and hygromycin B, could be detected by observation of translocation kinetics . Labelin6-tagged biosensor proteins. Following the addition of tested substances, the case of a specific interaction of an antibiotic with the protein leads to dissociation of the protein complex with immobilized DNA. The amount of the biosensor protein bound to the immobilized DNA was detected by antibodies in a specific ELISA assay. This sensor system was created to detect tetracycline, streptogramin and macrolide antibiotics in different solutions, including milk and serum at ng/mL concentrations. This approach is very sensitive, but allows the detection of only one antibiotic, and could not be used in de novo screening.There are proteins which can specifically bind certain antibiotics, and usually these proteins regulate the expression of resistance genes. Based on these proteins, specific biosensors were produced . BiotinyThe inhibition of protein synthesis leads to strong changes in the majority of cell processes, but for different antibiotics the effect is different. Studying changes in synthesized proteins, cell shape and the ratio between cell metabolites can help us to classify an antibiotic’s mode of action.By means of specifically labeling bacterial DNA and the cell membrane, it is possible to characterize the bacterial state by the shapes of the membrane and the nucleoid form. If performed after adding an antibiotic, specific changes will be detected . This meB. subtilis proteome were measured [The addition of an antibiotic leads to specific changes in proteomes, so the study of proteomic changes could also be used for the identification of the mechanism of action of new antibiotics . Two-dimmeasured . There ade novo proteome by means of a radio-labeled or fluorescent-labeled amino acid [de novo proteome of the cells treated with an antibiotic with that of untreated cells [The 2D protein gel can be used for analysis of the ino acid , while ued cells .Antibiotic resistance is usually a significant problem in antibacterial treatment, but it also could be used for the identification of the mechanism of action of a new antibiotic. The cultivation of bacteria at the inhibitory concentration of a tested antibiotic leads to the appearance of resistant mutations, and the following sequencing of their genomes gives us information about the mutant genes, and can help researchers understand the mechanism of action. For searching translation inhibitors, a mutant strain with only one ribosomal operon was created, and the chance of the appearance of a resistant mutation in ribosomal RNA in such a strain is much larger . The locRaman spectroscopy can be used for phenotypic profiling of bacterial cells treated with a different class of antibiotics . Cells tThere are many good methods for studying translation inhibitors, and any of them can be used for studying a particular compound. However, only a subset of methods can efficiently be used for screening thousands of compounds with the aim of finding a new antibiotic targeting translation. Based on this study, one principal scheme of translation inhibitor screening could be suggested . Reporte


The incidence of adenocarcinoma of the uterine cervix is increasing. It poses the affected women in risk and the definitive treatment requires hysterectomy. Here we describe a case of adenocarcinoma in situ of the uterine cervix successfully managed by minilaparoscopic hysterectomy using interchangeable 5-mm end effectors. Its incidence has been increasing, even in developed countries    .in situ of the uterine cervix.Our objective is to demonstrate the feasibility of the use of mini-laparoscopic hysterectomy interchangeable 5-mm end effectors in a case of adenocarcinoma 2 was referred to our department for atypical squamous cells of undetermined significance in the Pap smear with a human papillomavirus test positive for the genotype 16. The patient had no symptoms. She underwent colposcopy with biopsy and the result was cervical intraepithelial neoplasia type 1 with suspicion of a glandular lesion. Cervical conisation was made using LASER and the histology revealed adenocarcinoma in situ of the uterine cervix. Her transvaginal ultrasound was normal.A 53-year-old otherwise healthy post-menopausal woman with no previous surgeries and a body mass index of 21 kg/mTM system  whose instruments are introduced through the abdominal wall without trocar.After discussion of the therapeutic options with the patient, it was decided to perform a total hysterectomy with bilateral adnexectomy. Given the fact that she was a healthy woman with no previous abdominal surgeries, the approach chosen was mini- laparoscopy complemented with the PercuvanceTM Percutaneous Surgical System (PSS)  were then inserted under direct visualization, one at the right anterosuperior iliac spine and another at the left anterosuperior iliac spine  to allow the use of the 3.5 mm bipolar coagulator (Karl Storz Robi) and the mini-laparoscopic needle holder (Karl Storz mini- laparoscopy set). The entire pelvis was inspected for invasive disease, which was not found. The end effectors were then introduced through the umbilical port and coupled to the rest of the instrument, with the possibility of changing the tool tips to grasp, cut, and manipulate tissue, as needed.The procedure was undertaken using the 10 steps methodology: coagulation and section of the round ligament bilaterally; opening of the anterior leaf of the broad ligament; fenestration of the posterior leaf of broad ligaments to displace the ureter laterally; coagulation and section of the infundibulopelvic ligaments; coagulation and section of the utero- ovarian ligaments bilaterally; vesical-uterine and posterior dissection; uterine vessels dissection, coagulation and section; opening of the vagina; uterus and adnexa extraction by vaginal route; vaginal closure with laparoscopic figure of eight sutures. In the uterine vascular pedicle, coagulation was made with a 3.5 mm bipolar grasper (Karl Storz Robi) and to close the vagina a mini-laparoscopic needle holder assisted by a PSS instrument.The estimated blood loss was 30 mL and the operative time was 60 minutes. There were no intra or postoperative complications and the patient was discharged home 48 hours after surgery without pain. Post-operatively, she needed 1000 mg of oral paracetamol 6 hours after the end of the procedure. No need to repeat the analgesia afterwards. On histology, there was evidence of low-grade squamous intraepithelial lesion, but with no evidence of glandular lesions. Post-operatively, the patient had a rapid recovery and she has been kept on follow-up with vaginal cytology, which was normal (after 6 and 12 months). At 12 months, the human papillomavirus test was negative. One year later, no visible scars were observed.Endoscopic surgery has undergone a major and rapid development, which has led to increasing complexity of the procedures undertaken by this approach. The advances in surgical techniques and instruments have made mini-laparoscopy a viable way to perform hysterectomies . Even inAlthough the benefit of moving from laparoscopy to mini-laparoscopy is by no means as marked as the benefit of going from laparotomy to laparoscopy, the truth is that there also appear to be no disadvantages with its application: surgical time does not seem to increase, the rate of postoperative complications has been shown to be lower and cosmetic results are better. It is far more difficult to discuss whether we should use mini-laparoscopy, single-site surgery or even natural orifice transluminal endoscopic surgery as the best approach to our patients. All these techniques can be safely performed by skilled laparoscopic surgeons . There aTM system there are no such limitations and it is possible to maintain the advantages of mini-laparoscopic surgery without losing the precision and strength necessary to perform surgical procedures of some complexity. This novel device permits surgeons to maintain a standard setting and it represents a significant advance in minimally invasive surgery (TM system was a good alternative to a 5-mm port, the change of the end effectors was technically simple and we did not experience any disengagement of instrument tips during this procedure. (The limitations of natural orifice surgery or single incision surgery include reduced surgeon ergonomics and difficulty in instrument triangulation, which can compromise the ability to suture correctly, endangering patient safety. With the use of the innovative Percuvance surgery . As descocedure. . The onlSurgeons need to adapt themselves to this rapidly- changing world, deciding which new technology or technique they will adopt. The goal will be to make technology bring health benefits. We strongly believe that this was what happened with our patient, a healthy and asymptomatic woman who was cured from an oncologic disease, practically without having visible marks of the surgery she was submitted to. Some people may understand these marks as a pure aesthetic problem, but we believe this helps achieve a complete physical and psychological well-being.The authors report no declarations of interest and confirm that they have obtained the written permission of the patient whose case is being presented.in situ of the uterine cervix. It is never enough to emphasize its advantages, especially the minimization of surgical trauma, the refinement of the surgical movements and the higher patient satisfaction.Percutaneous mini-laparoscopic hysterectomy is technically feasible and is a viable alternative to surgical treatment of women with adenocarcinoma We hope our case to encourage more surgeons to learn and apply mini-laparoscopy, percutaneous systems and other new endoscopic techniques in favour of the patients.


One of the rarest ankle injuries is the Bosworth fracture-dislocation, whereby the distal fibula fractures and is lodged behind the tibia and is often unable to be reduced in a closed fashion. Even more rarely, a Bosworth dislocation without any accompanying fractures may occur. In this case, a 19-year-old male presented with a Bosworth dislocation, with the ipsilateral tibia having previously undergone intramedullary nailing. After closed reduction was attempted, open reduction and fixation was performed, directly reducing the fibula and fixing the unstable syndesmosis with 2 quadricortical screws. Bosworth injuries are rare, yet severe, and should be treated in a timely manner. We were able to provide good reduction and fixation without requiring removal of the intramedullary nail, and we support the use of 2 quadricortical screws as a valid treatment option for the fixation of Bosworth dislocations. Bosworth fracture-dislocations are a rare occurrence , 2. ThisA 19-year-old male with a history of a right tibial stress fracture with intramedullary nail fixation 14 months before presented to the emergency department after jumping into a shallow lake and immediately suffering severe right ankle pain and inability to bear weight. He had had the proximal intramedullary nail screw removed 3 months prior to presentation due to discomfort but reported no other medical problems. On exam, there was significant swelling of the ankle, with global tenderness to palpation. The fibula was noted to be displaced, as palpation of the lateral aspect of the ankle resulted in contact with the tibia, and palpation at the normal region of the peroneal groove revealed the distal fibula. Motion of the ankle was limited in all planes; however, the foot was neurovascularly intact and sensitive to light touch. A 3-view X-ray of the ankle confirmed the dislocation of the fibula posterior to the tibia and posterior dislocation of the talus, while showing the stable intramedullary nail and distal screw with no apparent lucencies . AdditioThis case is a rare variant of an already rare phenomenon. We are aware of 67 reported cases of Bosworth fracture-dislocations in the literature , 4. Of tBosworth fracture-dislocations are a rare and severe injury that must be recognized and evaluated in an expedient manner. Understanding that timely operative reduction of these injuries minimizes the risk of further injury is paramount, and no more than one closed reduction attempt should be made before proceeding to the operating room. This case shows support for the fixation of the unstable syndesmosis after reduction with 2 quadricortical screws, showing that this fixation can be performed safely if there is hardware in the ipsilateral tibia.


The measurement of ultra-precision freeform surfaces commonly requires several datasets from different sensors to realize holistic measurements with high efficiency. The effectiveness of the technology heavily depends on the quality of the data registration and fusion in the measurement process. This paper presents methods and algorithms to address these issues. An intrinsic feature pattern is proposed to represent the geometry of the measured datasets so that the registration of the datasets in 3D space is casted as a feature pattern registration problem in a 2D plane. The accuracy of the overlapping area is further improved by developing a Gaussian process based data fusion method with full consideration of the associated uncertainties in the measured datasets. Experimental studies are undertaken to examine the effectiveness of the proposed method. The study should contribute to the high precision and efficient measurement of ultra-precision freeform surfaces on multi-sensor systems. Ultra-precision freeform surfaces with sub-micrometer-form accuracy and surface finish in the nanometric range are now widely adopted in opto-mechatronic applications, due to their superior mechanical and optical properties in improving the performance of the products in both functionality and size reduction . The treIn the past decades, many precision measurement instruments have been developed with respect to specific and varying metrological needs. Many existing precision measurement instruments only possess limited measuring range at one single measurement, and are difficult to perform the high precision measurement of large size with both high resolution and efficiency. This is particularly true for some freeform surfaces with high slopes or large sizes ,5. MultiMulti-sensor datasets may come from different spaces with different scales, resolutions, and associated uncertainties. The effectiveness of the multi-sensor metrology heavily depends on the quality of the data registration and fusion, which are further steps for sensor integration, and are responsible for combining the measured datasets from different sensors into a common representation, in order that the measurement can benefit from the technical merits of all the involved sensors. Data registration and fusion has been an emerging technology since the 1990s, and it has previously been used for target tracking, automated identification of targets, and limited automated reasoning applications . GeneralFusion is responsible for processing the redundant data in the overlapping area of the datasets. Considering that the fused datasets may have different resolutions with different associated uncertainties, proper fusion process should be carried out to fuse the datasets which may have different resolutions with different associated uncertainties. Wang et al.  reviewedThis paper presents a study of data registration and fusion for measuring ultra-precision freeform surfaces on multi-sensor instruments. The method performs the data registration by representing the geometry of each dataset based on intrinsic surface features which are invariant to coordinate transformation, and free from the implicit parameterization of the surface. Data fusion is then performed at the overlapping area based on a Gaussian process model, to further reduce the measurement uncertainty. Experimental studies are presented to demonstrate the validity of the proposed method.Intrinsic surface features (ISFs) refer to those surface features whose values are invariant under the transformation (rotation/translation) of the embedded coordinate frame, and also free from the implicit parameterization of the surface. Surface registration can be performed without the need to consider the misalignment of the coordinate frames and the parameterization of the surfaces when the two surfaces are represented by ISFs. Two of the important ISFs are Gaussian and mean curvature. They uniquely determine the surface shape according to the Gaussian Curvature Uniqueness Theorem and the Mean Curvature Uniqueness Theorem ,20.Before registration of the datasets, the format of different datasets was unified by a re-sampling strategy. This was realized by the process as shown in In the present research, Gaussian curvature or mean curvature was chosen as the ISF. Direct calculation of the ISF, such as Gaussian curvature, from the measured datasets is sensitive to the measurement noise. Hence, in the present study, the B-spline surface was used to fit the discrete points so that the measurement noise could be rejected during the surface fitting process and the ISF could be safely calculated . SupposeThe second fundamental form of K and mean curvature H of the surface Then, Gaussian curvature The surface registration problem was then converted to ISF registration. That is, the corresponding searching in 3D Cartesian coordinate frame by solving six parameters (three translations plus three rotations) was now performed in 2D space by finding three parameters (two translations plus one rotation), as shown in Suppose From Equation (9), the translation is recovered, and the rotation causes the spectral magnitude to be rotated at the same angle, which can be determined in polar coordinates .(10)PM2The established correspondence by ISF registration was then used to evaluate the coordinate transformation matrix lgorithm .After data registration, the overlapped area of the two registered datasets were processed to form one fused dataset. Challenges exist for overlapped data fusion when the data sets are from different sources , due to the variety of data density and uncertainty involved. In the current study, the Gaussian process (GP) model  was usedIn the actual measurement, the zero-offset mean function was used, since no prior knowledge on the surface geometry is available. A prediction of  follows :(16)m=K was machined by a four-axis ultra-precision machining system (Moore Nanotech 350). To fully capture the geometric information, including the surface form and texture, the workpiece was measured by a 3D optical profiler (Zygo NexView) with two different objectives i.e., 5.5× and 20× magnifications (zoom was 2.0×). The field of view of the two objectives were 0.76 × 0.76 mmThe two datasets had different resolutions and were embedded in two different coordinate frames, since they were measured by two different objectives in two steps. As a result, the proposed method was used to perform data stitching and fusion, so as to obtain a unique representation of the machined surface. It started by registering the dataset measured by the 5.5× and 20× objectives to the nominal surface, using the proposed ISF based data stitching method. Filtering was carried out to remove outliers and noise before the calculation of the intrinsic surface feature. To further evaluate the capability of the proposed method, an actual measurement was conducted on another general freeform surface. The combined use of large scale fast inspection sensors, e.g., laser scanner and photogrammetry, with micro scale pointwise measuring sensors, e.g., coordinate measuring machines, are currently the most common scenarios for multi-sensor surface metrology. Therefore, in the present study, a high precision coordinate measuring machine (CMM) and a laser scanner were combined to measure the freeform surface for efficient and reliable measurement. The CMM possessed a length measurement uncertainty with U =  μm, and a probing error with u = 0.9 μm . The uncertainty of the laser scanner was identified to be u = 3.4 μm  by a reference ball. The measurement was carried out in two steps. Firstly, CMM was used to measure the surface with spacing 1 mm in both X and Y directions. A total of 6456 points were uniformly sampled with 1 mm spacing over the entire surface. Secondly, multi-sensor measurement strategy was carried out. CMM was used to measure the surface with 4 mm spacing in both X and Y directions. Laser scanning was used to perform dense measurements of the surface. The proposed method was then used to process the measured datasets. ISF-based data registration method was used to precisely register the measured datasets by the two sensors into a common coordinate system. The datasets at the identified overlapping area were then fused based on the GP model. To verify the effectiveness of the proposed method, only the overlapping part was used for the form error evaluation of the machined surface. A summary of the experimental results is shown in As a fast measurement sensor, the laser scanner has the highest measurement efficiency, while its accuracy is relatively low compared with CMM. For CMM measurements with loose sampling, the measurement time became acceptable, while the inadequate sampling of the surface would underestimate the form error of the machined surface, especially the PV, which was determined by extreme points. Hybrid measurement on the other hand, had the best overall performance. It was shown from results that, by registering and fusing the datasets from the laser scanner and the CMM, accuracy was dramatically improved, while the measurement efficiency was maintained as well. The experiment verified the capability of the multi-sensor measurement in freeform surface measurement, and further confirmed the effectiveness of the proposed method in addressing the key issues in the measurement process.Freeform data stitching and fusion technology provides a practical solution for multi-sensor measurement of freeform surfaces, and also for enhancing the measuring ability of some high precision measurement instruments. This paper presented methods and algorithms for data stitching and fusion for measuring ultra-precision freeform surfaces based on the registration of ISFs. Some important algorithms involved in the registration algorithms were explained, including data format unification, calculation of ISFs such as Gaussian curvatures and mean curvatures, registration of the ISF map, Gaussian process-based data fusion for the overlapping area, etc. Experimental studies were conducted and the results were discussed. The proposed method and algorithms of data stitching and fusion intend to eliminate or alleviate the effect of noise and outliers, and provide a robust registration and fusion method, which is helpful for multi-scale and multi-sensor measurement of ultra-precision freeform surfaces.


This paper presents a comprehensive review of the structure and function of DNA polymerase e. Together with DNA polymerases a and d, this enzyme replicates the nuclear DNA in the eukaryotic cell. During this process, DNA polymerase a lays down RNA-DNA primers that are utilized by DNA polymerases d and e for the bulk DNA synthesis. Attempts have been made to assign these two enzymes specifically to the synthesis of the leading and the lagging strand. Alternatively, the two DNA polymerases may be needed to replicate distinct regions depending on chromatin structure. Surprisingly, the essential function of DNA polymerase e does not depend on its catalytic activity, but resides in the nonenzymatic carboxy-terminal domain. This domain not only mediates the interaction of the catalytic subunit with the three smaller regulatory subunits, but also links the replication machinery to the S phase checkpoint. In addition to its role in DNA replication, DNA polymerase e fulfils roles in the DNA synthesis step of nucleotide excision and base excision repair, and has been implicated in recombinational processes in the cell.


The use of massive multiple-input multiple-output (MIMO) techniques for communication at millimeter-Wave (mmW) frequency bands has become a key enabler to meet the data rate demands of the upcoming fifth generation (5G) cellular systems. In particular, analog and hybrid beamforming solutions are receiving increasing attention as less expensive and more power efficient alternatives to fully digital precoding schemes. Despite their proven good performance in simple setups, their suitability for realistic cellular systems with many interfering base stations and users is still unclear. Furthermore, the performance of massive MIMO beamforming and precoding methods are in practice also affected by practical limitations and hardware constraints. In this sense, this paper assesses the performance of digital precoding and analog beamforming in an urban cellular system with an accurate mmW channel model under both ideal and realistic assumptions. The results show that analog beamforming can reach the performance of fully digital maximum ratio transmission under line of sight conditions and with a sufficient number of parallel radio-frequency (RF) chains, especially when the practical limitations of outdated channel information and per antenna power constraints are considered. This work also shows the impact of the phase shifter errors and combiner losses introduced by real phase shifter and combiner implementations over analog beamforming, where the former ones have minor impact on the performance, while the latter ones determine the optimum number of RF chains to be used in practice. Nowadays, one of the most active research areas in the wireless communication field is the design of communication techniques for fifth generation (5G) cellular systems. Although the final technical components of the 5G system are still under discussion, important progress has already been made towards the definition of the set of scenarios and requirements to be addressed by these systems. In particular, the European project Mobile Enablers for the Twenty-Twenty Information Society (METIS) played a key role in this direction by stating that, among other goals, the 5G system shall boost the user data rate of 4G cellular systems by a factor ranging from 10 to 100  :(6)δi∈[−entation ,15 and tThis work focuses on phase shifter errors constant over the bandwidth of interest but variable with time. Note that phase shifter errors that are constant with time are mainly caused by manufacturing imperfections, and, thus, they could be estimated in the uplink and their effect could be compensated in the beamforming stage. Otherwise, phase shifter errors variable with time cause a random and unpredictable error that cannot be estimated and compensated. The reason for selecting the latter assumption is to emulate the effect of using different beams for the channel estimation and transmission phases due to the inclusion of different phase-shifter errors in each of them. This may happen in frequency division duplex (FDD) systems. As a result, when the phase-shifter error varies over time, the beam selected from the codebook during the scheduling phase can result in a suboptimum beam for the transmission phase. Note that this is a worst-case scenario for the evaluation of the impact of phase-shifter errors.us works ,15, the L the power loss of the basic combiner with two input branches, i.e., whose output power is given by the sum of the two input powers divided by L. Then, we assume that a combiner for a generic number P of RF chains is implemented by means of a cascade of logIn the analog beamforming scheme, the signals of the different RF chains are mixed together by means of a combiner to feed the antenna array. Non-ideal combiners are known to introduce a power loss in their outputs , which iNote that, differently from the results with ideal hardware shown in L values, note that the case without any compensation of losses corresponds to Regarding the selection of o L=3 dB , where hThe results in Finally, it is worth noting that the optimum number of RF chains is different for the users in LoS and NLoS conditions. In fact, for This paper has presented a thorough performance evaluation of digital precoding and analog beamforming schemes in a massive MIMO multi-cell deployment operating in the mmW frequency band. In the first part, a comparison among analog and digital precoding schemes has been carried out under ideal assumptions, namely, perfect and timely CSI at the transmitters, ideal phase-shifters and combiners in the analog scheme and lack of PAPC in digital precoding. MU schemes have been compared against ABF without spatial multiplexing of users, considered here as the baseline scheme. It was observed that by scheduling multiple users at a time, the throughput is substantially increased. Simulation results have further shown that analog beamforming schemes can reach the performance of fully digital precoders when working under LoS conditions and with a sufficient number of parallel RF chains. On the other hand, analog schemes have been shown to be more sensitive to interference and, thus, more degraded in NLoS conditions, in which increasing the number of RF chains can not provide any advantage.After the initial performance comparison, the effect of several realistic impairments has been included in the simulation setup. To this aim, the effect of having only outdated CSI for precoding at the BS has been firstly analyzed by considering a more realistic period to update the channel in all the evaluated schemes. In addition, PAPC have been set in the two considered digital precoding variants to also see the effect of this realistic constraint. Lastly, the errors introduced by both the phase shifters and combiners in the analog architecture have been modeled.From the results with outdated channel information, it can be concluded that digital precoding schemes are more sensitive to imperfections on the CSI knowledge at the BS, presenting large losses (up to 34%) when the CSI update period is increased. On the other hand, analog beamforming schemes have shown to be robust against the channel information inaccuracy, presenting a negligible reduction of performance when the channel reporting period is increased.The results with PAPC have exhibited a performance reduction in digital precoding schemes based on MRT of about 4%, which leads to a small reduction of the performance gap between digital and analog implementations. In practice, the performance loss due to the PAPC could be compensated, for instance, by means of a more elaborated scheduler with a more frequent update of precoders.Regarding the effect of phase-shifter errors, simulation results have shown that this impairment has little impact on the ABF performance, even when the magnitude of the introduced phase error is significantly higher than current state-of-the-art values known from manufacturing. Nevertheless, LoS UEs suffer a stronger degradation due to this impairment when compared to the NLoS UEs, due to their narrower received beams. Conversely, combiner losses have indeed a great impact on the system performance, mainly when the number of RF chains in the analog scheme is high. In fact, the magnitude of the power loss introduced by the combiner determines in the end the optimum number of RF chains to be selected for analog beamforming. Overall, it is more suitable to employ a low number of RF chains when the losses introduced by the combiner are large.Future work includes studying the performance of mmW beamforming methods with different planar array solutions and also the evaluation of more advanced hybrid precoding designs with an optimized baseband processing stage. In addition, analyzing the performance in the presence of more realistic user mobility would be of future interest.


Our work identifies potential combinations of enzyme knockdown, metabolite inhibition, and extracellular conditions that impede cell proliferation. Excitingly, the model predicts novel targets that can be tested experimentally. Therefore, the model is a tool to predict the effects of inhibiting specific metabolic reactions within pancreatic cancer cells, which is difficult to measure experimentally, as well as test further hypotheses toward targeted therapies.Reprogramming of energy metabolism is a hallmark of cancer that enables the cancer cells to meet the increased energetic requirements due to uncontrolled proliferation. One prominent example is pancreatic ductal adenocarcinoma, an aggressive form of cancer with an overall 5-year survival rate of 5%. The reprogramming mechanism in pancreatic cancer involves deregulated uptake of glucose and glutamine and other opportunistic modes of satisfying energetic demands in a hypoxic and nutrient-poor environment. In the current study, we apply systems biology approaches to enable a better understanding of the dynamics of the distinct metabolic alterations in KRAS-mediated pancreatic cancer, with the goal of impeding early cell proliferation by identifying the optimal metabolic enzymes to target. We have constructed a kinetic model of metabolism represented as a set of ordinary differential equations that describe time evolution of the metabolite concentrations in glycolysis, glutaminolysis, tricarboxylic acid cycle and the pentose phosphate pathway. The model is comprised of 46 metabolites and 53 reactions. The mathematical model is fit to published enzyme knockdown experimental data. We then applied the model to perform  Pancreatic ductal adenocarcinoma (PDAC) is a particularly aggressive and challenging form of cancer Hidalgo,  that is Pancreatic cancer cells are particularly reliant on glutamine to sustain proliferation and promote cell survival. Glutamine is a conditionally essential amino acid that fuels the tricarboxylic acid (TCA) cycle. Upon being taken up by the cell, glutamine is converted to glutamate by the glutaminase (GLS) enzyme, and then enters the TCA cycle as α-ketoglutarate , also known as alanine amino-transferase, transfers nitrogen from glutamate to pyruvate to make alanine and α-ketoglutarate. This nitrogen supports amino acid synthesis needed to produce cellular building blocks . The α-ketoglutarate obtained by the conversion of glutamate promotes citrate production and lipid biosynthesis  are modeled to have 20% basal activity, while 80% of their activity is due to activation by AKT .In order to predict how the intracellular metabolic pathways influence cell growth, we incorporate cell number with the enzyme-catalyzed reactions. Specifically, the model is augmented to include a 47th ODE that describes the time evolution of the number of cancer cells, The number of cancer cells is directly linked to the metabolism, where the growth rate depends on the intracellular concentrations of three primary metabolites known to influence cell proliferation: glucose, glutamine and ATP . The reaction velocities reflect the amount of enzyme present and the corresponding enzyme activity. Conventionally, the reaction velocities are thought to distinguish the metabolism across different cell types. Therefore, of the many kinetic parameters included in the reaction rate equations, only the reaction velocities were fit to the training data, and the other rate constants were held at their literature values. We also fit the cell growth parameters shown in Equations (1) and (2). Below, we describe the experimental data used to train the model and the method used to perform the parameter estimation.The baseline model, adapted from literature, has a total of 372 parameters, which includes 71 reaction velocities  . Each run of the PSO algorithm executes 2, 500 iterations, a user-defined value to balance the computational expense of the parameter search. We performed the parameter estimation twice for each set of initial conditions  and, for each case, selected the set of parameters that generated the lowest error. This gave a total of 50 best-fit parameter sets, one set for each initial condition.Particle swarm optimization (PSO) was used to identify the parameter values needed to enable the model predictions to best fit the data and minimize the WSSR. PSO  that allow the model predictions to best match the available experimental data. As described in the Methods, the complete model is constructed using equations from multiple sources, each of which contains parameters that characterize the rates of the metabolic reactions. Therefore, we fit the model to data specific to pancreatic cancer in order to obtain a validated model that can be used to predict the dynamics of metabolism in pancreatic cancer cells.We performed parameter estimation to fit the model to quantitative experimental data and estimate the reaction velocities  for a particular reaction are shown to be highly correlated for multiple sets of initial conditions, we fit the Vf and calculate Vr using the equilibrium constant, Veq. We performed the PI analysis once using the baseline model and all 71 reaction velocities, identifying 10 correlated pairs (“round 1”). We then performed the analysis again, after specifying the Vr values found to be correlated in round 1, which identified another two correlated pairs (“round 2"). Through this analysis, we reduced the number of reaction velocities to be fit from 71 to 59. The results of the parameter identifiability are shown in Figures We first performed parameter identifiability (PI) to determine the pairs of correlated parameters. Specifically, we aimed to identify which of the total 71 forward and reverse reaction velocities are mathematically correlated. Completing this analysis allowed us to fit the forward rate, and calculate the reverse rate using the equilibrium constant. Initially 100 sets of initial conditions are chosen from Latin Hypercube Sampling. We sum the calculated correlation coefficients for each of the 100 initial conditions and subsequently normalized the estimated correlation coefficients. When the forward and reverse reaction velocities  to calculate the sensitivity of the fold-change in the metabolite concentrations given variance in the 59 reaction velocities included in the model, for each set of initial conditions. The cumulative result of the sensitivity analysis is shown in Figure Finally, we used particle swarm optimization (PSO) to find the optimal values for each reaction velocity that allow the fold-changes in the metabolite concentrations predicted by the model to accurately match the fold-changes measured experimentally. By performing the model training, the predicted fold-changes match very closely to the experimental data, as shown in Figure We incorporated growth kinetics with the trained metabolic model to predict the number of cells over time. The cell growth is simulated in the presence of complete media (35 mM of glucose and 6 mM of glutamine) for a total time period of 5 days. The model is able to match the training data for the growth curves measured by Son et al.  Figure . By traiWe validated the model with available experimental measurements for cell proliferation under conditions of nutrient deprivation. The validation step confirms that the model is able to predict data not used in the model training. Two initial conditions with their corresponding fitted parameters (reaction velocities and growth parameters) could successfully validate the experimental growth curves measured under minimal glucose and glutamine concentrations Figure . These vglc and kgc, vary as widely as seven orders of magnitude between the two sets of best-fit parameter values estimated using the two validated initial conditions. These parameters characterize the contribution of glucose to the overall rate of cell proliferation. However, the ratio of α to k for glucose is very similar across the two sets of initial conditions, again pointing to the robustness of the estimated parameter values. The occurrence of high variability in the best-fit parameters is to be expected in highly nonlinear and complex kinetic models  by 85%, either alone or in combination with GOT1 knockdown. We first targeted enzymes that directly influence the three metabolites involved in the cell proliferation rate . These enzymes include GLUT1, which catalyzes glucose uptake by the cell, GLS, the enzyme that converts glutamine to glutamate, and OXPHOS, the reaction simulating oxidative phosphorylation. The model predicts that inhibiting these enzymes influences cell growth to varying degrees. GLUT1 knockdown alone is not as effective in reducing cell growth as GOT1 knockdown  as a representative example. MALPi is responsible for phosphate shuttle across the cytoplasmic and mitochondrial compartment and hence for the conversion of ATP and ADP. MALPi, in conjunction with the citrate malate shuttle (CITMAL), generates citrate required for lipid synthesis. Therefore, targeting MALPi exhibits is expected to reduce tumor growth, which the model predicts . This enzyme promotes synthesis of OAA by AKG via glutamate. The expression level and activity of the GOT2 enzyme has been found to be highly elevated in pancreatic and breast cancer cells . Thus, when combined with experimental studies, the model can prove useful in designing and understanding pre-clinical trials.Our approach of fitting the model with different sets of initial conditions to generate multiple parameter sets is akin to ensemble modeling for metabolic systems .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.