This study sought to determine whether several metatarsophalangeal (MTP) fusion techniques require complete immobilization or if some level of weight-bearing could be recommended after surgery. A comparison of synthetic composite to actual bone was included in order to examine the validity of the testing conditions.Four MTP fusion modalities were tested in synthetic composite bone models: unlocked plating, locked plating, crossed lag screws, and an unlocked plate with a single lag screw. Stiffness was calculated and then used to find the two most rigid constructs; the load to failure was recorded. Stiffness and load to failure testing for the two more rigid constructs in paired cadaveric bones were followed.p < 0.008). Loads to failure of the unlocked plate plus screw and crossed screws in synthetic bone were 131 and 101 N, respectively and in cadaveric bone were 154 and 94 N, respectively, which are less than the estimated 25% body weight required at the MTP joint. The plate plus screws were statistically more stiff than crossed screws (p = 0.008), but there was no statistical difference between synthetic and cadaveric bone in load to failure (p = 0.296).The unlocked plate plus screw and crossed screw constructs were stiffest (The plate plus screw offered the greatest stiffness; the failure test showed that no construct could withstand weight-bearing as tolerated; and, synthetic composite models of the MTP joint did not provide the consistent results in stiffness and failure. Late stage hallux valgus and hallux rigidus are commonly treated in osteoarthritic patients with arthrodesis using mechanical hardware to stabilize the joint –4. Post-Studies have suggested immediate weight-bearing may be acceptable and is preferable , 9, thouThe overall goal of the current research was to estimate allowable post-operative weight-bearing with four MTP fusion techniques with the purpose of providing sound reasoning for post-operative weight-bearing recommendations. The comparison of four different fixation modalities complicated paired specimen testing conditions. Literature has shown composite bones, in particular, fourth generation synthetic composite models, and human bones can behave similarly under cyclic and failure loading if the tests are carefully designed –14. EvenThe basic research questions for the study concerned the problems of weight-bearing. First, we sought to determine which common fixation was the stiffest, offering the most resistance in repetitive loading to the opening of the fused joint, and whether the stiffest constructs could tolerate post-operative weight-bearing. Additionally, the work sought to contribute to the understanding of test methodology by considering whether synthetic composite bones provide an adequate means for comparison of MTP fixation techniques. The underlying null hypotheses were that no differences existed between MTP fixation techniques or between testing in cadaveric or synthetic composite bone.Four commonly used hardware configurations were compared: (i) an unlocked plate held by four screws, (ii) a locked plate held by four screws and two locking washers, (iii) an unlocked plate held by four screws combined with a single lag screw, and (iv) a pair of lag screws for crossed screw fixation across the joint. First metatarsal and proximal phalanx synthetic bones were obtained  and prepared for metatarsal-phalangeal fusion. Prior to fixation, the outer layer of the synthetic bone material was removed from the articular surface.A board certified, fellowship-trained orthopaedic surgeon reamed the surfaces, determined appropriately sized hardware, and completed the fixation. For cases of plate fixation, the metatarsal and proximal phalanx were templated for hole placement and screw length. The plate was implanted and, in the case of the locked plate, a locking screw construct was placed in the first and fourth holes of the plate. For lag screw fixation, a Kirschner wire was obliquely inserted into the proximal end of the lateral phalanx to guide the cannulated lag screw through the joint line into the distal medial metatarsal. In the case of plate fixation with a single crossed screw, the screw was added after plate fixation.After painting all specimens white to assist in subsequent optical tracking, the proximal end of the metatarsal was placed into a 2-inch-diameter polyvinyl chloride pipe filled with polymer resin and organic peroxide . Upon hardening, the metatarsal was firmly held in the polyvinyl cylinder. For measurement of the opening of the joint space between the phalanx and metatarsal, black spherical markers (1.5 mm in diameter) were fixed at the joint line of the construct with a cyanoacrylate-based adhesive . Four 3-mm-diameter spheres were fixed laterally to both the metatarsal and phalanx to simplify gross measurement of the movement of each bone, as needed for tracking each body  All specimens were from ambulatory donors with neither foot or ankle pathology nor any disease that would affect bone quality, such as cancer or long-term complete immobilization. A dorsal medial incision was made to expose the metatarsophalangeal joint for fixation. As in the preparation of the synthetic bones, the lag screw fixation followed plate fixation in the unlocked plate plus screw case and Kirschner wires were used to guide both lag screws in the use of crossed screws. After implantation, the first and second rays of each cadaveric foot were excised from the whole foot. The intact hallux, the cuneiforms, phalanx, and metatarsal were removed together. The proximal ends of the metatarsal and the cuneiforms were placed into 2-inch-diameter polyvinyl chloride pipe and filled with polymer resin and organic peroxide . Black spherical markers for tracking of joint opening and body movement were placed laterally along the joint line  with the metatarsal positioned 15° from the horizontal to simulate the position of the metatarsal with respect to the ground during upright standing. Based on the literature , 18, 19,Based on the results of composite bone testing, the two stiffest constructs were applied to paired cadaveric feet, and the two least stiff were set aside for use in an unrelated experiment. The cadaveric specimens were tested with the joint opening protocol. Finally, each of the constructs was mounted in the uniaxial load frame and linearly increasing load was applied until the specimen failed, e.g., screw cutout or pullout occurred. The largest load was recorded for each specimen.The joint opening during cyclic loading was calculated using the movement occurring between the phalanx and the metatarsal at the joint line. The opening at the plantar edge of the joint line that occurred with the maximum load of each cycle in the group was always the largest and was extracted from the data for each case. The stiffness was determined by dividing the load difference between the peak and minimum load values of each cycle by the displacement occurring between the peak and minimum with the average taken over 30 s intervals at the beginning, middle, and end of the test. All calculations and analysis were performed in Matlab.t tests. A p value of less than 0.05 in comparison was considered significant.A Kruskal-Wallis test was performed to examine the relationship of stiffness (the dependent variable) with fixation type (the independent variable) using IBM SPSS, Version 23 . If the initial comparison showed significance, individual Mann-Whitney comparisons with Bonferroni correction were used as post hoc tests to compare each pairing of fixation types. Failure loads were compared with The use of synthetic composite bones was necessary to maintain the same conditions for each of four fixation methods. The subsequent tests in paired cadaveric bone of two of the four fixations were performed to estimate whether the composite bone results were replicated in actual specimens. After the cyclic loading of the synthetic composite specimens, the two stiffest constructs proved to be the plate plus screw and the use of two crossed screws. These fixation techniques were tested to failure in the paired cadaveric specimens and both the two stiffest synthetic composite bone paired cadaveric specimens were loaded to failure.p = 0.0001). Individual multiple comparisons tests on the pairs of data sets showed differences between all pairs of fixation types  except for the locked to unlocked plate fixation comparison, which showed no significance, p = 0.463.The tests of the composite bones with 40 N of loading showed 1) that the largest displacement occurred in the case of the unlocked plate, and (2) that the two stiffest constructs were the dorsal plate with the single screw across the joint and the crossed screws (Table  that thep = 0.001) The stiffnesses of the plate plus screw and crossed screws in cadaveric bone were not statistically different from each other (p = 0.08). The plate plus screw in synthetic bone was stiffer than the crossed screws, but the opposite was true in cadaveric bone. Individual Mann-Whitney tests on the pairs of data sets showed differences between all pairs of fixation types  except for the locked to unlocked plate fixation comparison, which showed no significance, p = 0.403.Comparing the stiffness measured at the beginning of the test with the stiffness at the end of the test, stiffness was unchanged over 1000 cycles of loading in either synthetic composite or cadaveric bone. The stiffnesses in cadaveric specimens were not within 20% of the stiffnesses in synthetic bone (Table p = 0.296). Moreover, neither the synthetic composite nor the cadaveric bones could reach weight-bearing load levels without catastrophic failure  should be expected because the plate plus screw fixation forms a composite beam structure when implanted, with bone between the plate and screw. This structure is much like an I-beam, where the flanges forming the top and bottom of the beam are stiffer in bending than the web between them. The location of the crossed screws in the central region of the bones meant that the distance from the hardware to the measurement site was smaller for the screws than for the single plates. Although the use of the joint opening as the measure of displacement may have favored the use of lag screws over the single, anteriorly mounted plates, in each fixation case, the measurements were taken at the point where maximal displacement would occur. In effect, the single plates only resisted bending due to the plate and rotation of the bones about the hardware location occurred, as it would in vivo. A greater distance to the plantar edge of the joint meant, that for the same amount of rotation, the single plates would have greater opening. Assuming that the lag screws are on the midline and the plate is on the dorsal surface, the single plates are approximately twice as far from the point of measurement as the lag screws. Then, despite the seeming advantage of bone sandwiched between a plate and screw, the cadaveric tests of comparison found that the crossed-screw fixation was stiffer than the plate plus screw, although without statistical significance. This difference between the cadaveric and the composite bone could be due the extent to which lag screw fixation can join the MTP joint: if the lag screw is the limiting factor, the advantage of location for the crossed screws could dominate the positive effect of the hardware separation distance of the plate and screw construct.That the plate plus lag screw was stiffest construct (The failure loads of plate plus screw and crossed screws were smaller and considerably less than the estimated load arising in weight-bearing gait. Simply stated, none of the constructs could sustain the weight-bearing load of 25% body weight of an average male, as evidenced by both the failure loads in synthetic composite and cadaveric bone. Thus, none of the constructs would suffice for weight-bearing similar to normal gait.The results from the synthetic composite and cadaveric bones testing compared favorably in failure loads. The constructs failed at similar loads and showed that the plate plus screw is stronger than crossed screws in both cases. The stiffness result in synthetic composite was not replicated in cadaveric bone, however. Not only were the calculated values in synthetic composite and cadaveric bone dissimilar, but the crossed screws were stiffer than a plate plus screw in the cadaveric bone, contrary to the synthetic composite result. Much like the explanation for the differences in stiffness between the MTP fusion techniques, one possible explanation would be a difference in the lag screw fixation in the two materials. While Heiner  found geThe use of synthetic composite bone could have been the major limitation of this work. The comparison to cadaveric bone, however, offered a means to assess the results and offer a separate measurement. Another potential limitation was that the sample size of five in each group of synthetic bone could potentially limit the study’s scope, but stiffness results proved to be statistically significant. This significance may have been the direct result of the more uniform specimens provided by the synthetic composite bone and then by the use of paired cadaveric specimens. A statistically significant outcome provides more confidence in the result. The lack of any real fusion also forms a limitation of the current study. As an in vitro study, only the period of time immediately after surgery could be tested. The strength of the in vivo construct will be time dependent, in that as fusion progresses over 6 weeks, and there is additional strength added to the construct by the progressive bone fusion. Finally, as a limitation, the estimate of the maximum required load borne by the hallux was derived from values in other research. However, the predictions of Gefen et al.  indicateWhile the current results clearly advise against full weight-bearing at time zero, the stiffness and strength of a plate plus screw and of the crossed screws might tolerate protected weight-bearing if some means to ensure patient compliance were available. Single dorsal plates, whether locked or unlocked, would not be advisable for any form of weight-bearing. The orthopaedic literature has previously described the stiffness and strength of various first metatarsophalangeal constructs used in fusion. While this literature often suggests that the strongest construct would also have the best rate of fusion, to our knowledge, the relationship of stiffness and strength to fusion success has never been proven.


Heterogeneous wireless sensor networks (HWSNs) are widely adopted in structural health monitoring systems due to their potential for implementing sophisticated algorithms by integrating a diverse set of devices and improving a network’s sensing performance. However, deploying such a HWSN is still in a challenge due to the heterogeneous nature of the data and the energy constraints of the network. To respond to these challenges, an optimal deployment framework in terms of both modal information quality and energy consumption is proposed in this study. This framework generates a multi-objective function aimed at maximizing the quality of the modal information identified from heterogeneous data while minimizing the consumption of energy within the network at the same time. Particle swarm optimization algorithm is then implemented to seek solutions to the function effectively. After laying out the proposed sensor-optimization framework, a methodology is present to determine the clustering of the sensors to further conserve energy. Finally, a numerical verification is performed on a four-span pre-stressed reinforced concrete box-girder bridge. Results show that a set of strategically positioned heterogeneous sensors can maintain a balanced trade-off between the modal information accuracy and energy consumption. It is also observed that an appropriate cluster-tree network topology can further achieve energy saving in HWSNs. Structural health monitoring (SHM) has been widely used to monitor and diagnose the health status of civil structures/infrastructures in real-time . TypicalTraditional SHM systems rely on wired sensors. The installation and maintenance cost of these sensors represents a large portion of the total cost of the system. With the advances in technology, the development of wireless sensor technology in recent years offers new opportunities for SHM applications ,3,4,5. WAs a large amount of existing structures are suffering from deterioration, excessive loadings and unpredicted incidents, the development of dense, yet low-cost wireless sensor arrays to monitor the operation of structural systems has become an attractive research subject in recent years. Some notable experimental applications implemented on large-scale structures can be seen, for instance, in the Golden Gate Bridge  and the In this paper, a study attempting to implement optimal sensor deployment (OSD) techniques to determine the number and locations of heterogeneous wireless sensors on a structure of interest has been performed. This implementation of such system intends to produce reliable information about the structure’s health status while maintaining reasonable energy consumption.As an important issue in SHM, the OSD techniques have been demonstrated to be effective in helping to achieve accurate estimation of modal parameters by placing the sensors properly. Within the context of OSD, quite a few methods, such as the Effective Influence (EI) method , Modifiei. Placement performance metrics issueIn a multi-type sensor network, the orthogonality of the modal vectors cannot be exploited as in single-type sensor networks. Therefore, approaches that do not rely on the orthogonality of the modal vectors are needed.ii. Network topology issueNetwork heterogeneity allows for sophisticated operations over a larger region. As most of the energy costs come from the transmission and receiving of data packets, network topology optimization is a challenging issue for energy efficient coordination when WSNs become heterogeneous.MCI) , respectively. The PSO is run for 10 times to generate the network layouts. The objective function values, accelerometers, strain gauges, and coverage ranges of the layouts obtained in the ten cases are listed in The proposed OSD techniques are applied to determine both the optimal number of heterogeneous sensors and their best sensing locations. In order to solve the multi-objective function established in Herein, the mean values are used as the optimal sensor layout deployed on the bridge plan. The optimal number of accelerometers, strain gauges, and coverage range are 14, 10, and 96.7 m, respectively. The sensor placement layout found from the analysis is shown in The study herein is aimed to determine the best data transmission path of the HWSN based on the sensor configuration from initial optimization results, and to compare the performance of network topology effects on energy consumption. The related network parameters on the bridge monitoring system are listed in x, y, z) of the CH nodes is the reverse of the HWSN space V, the distance expectation toBsd is calculated using Equation (35):Since the probability density ρ, the optimal number of clusters is obtained as five. That is, the wireless sensors selected to monitor the bridge are divided into five clusters. Nevertheless, finding specific member nodes that result in best data transmission path in a large-scale HWSN with multiple clusters is a quite complex problem. In this study, for fast optimization, the nodes close to the base station are assumed to be selected as CH nodes and the member nodes in each cluster are allocated as even as possible. In order to evaluate the effectiveness of clustering optimization, the simulation results using the proposed method are compared to those obtained by a flat network topology (one layer). According to Equation (14) derived in In the data transmission path produced by the cluster-tree HWSN topology, the coverage radius is increased by 28.3% compared to that of the flat topology. In addition, it is also found that the energy consumption of the sensors is significantly lower than that of the flat topology (33.3%). This reduction is expected since, although the coverage radius increases, the transmission distance of data packets is reduced in a cluster-tree routing path, which indicates that the energy consumption depends not only on the coverage radius of network, but also other factors such as the data transmission distance and the amount of transmitted data packets. Since there exists a linear relationship between energy consumption and the square of data transmission distance, the energy saving in a cluster-tree topology can be achieved by reducing total data transmission distance through suitable clustering mechanism, and, therefore, it is independent of the network size.It should be emphasized that the optimization of network topology in this study only involves a fast selection of CH nodes according to the algorithm proposed. Further determination of specific member nodes in each cluster will lead to another complex problem which is out of the scope of this paper. In the expense of larger amount of computation time, the data packets transmission path shown in this study could be further optimized. However, the OSD framework proposed is applicable to other monitoring scenarios that the deployment of multi-type wireless sensors is based on the principle of modal information quality and minimum of energy consumption.The increasing interest in employing HWSNs for SHM applications requires an efficient sensor placement methodology. In this study, first, an OSD framework for HWSNs is proposed. A multi-objective layout optimization problem is presented and resolved using the PSO algorithm to determine the trade-off between modal information quality and energy consumption with the consideration of the application requirements. Furthermore, a clustering optimization approach is proposed to conserve extra energy through selecting appropriate CH nodes in multi-hop HWSNs. A continuous-span bridge is used as an example to evaluate the performance of the proposed approach for designing a wireless SHM system comprised of acceleration nodes and strain nodes on the bridge.The proposed optimization approaches can effectively determine the best number and location of heterogeneous wireless sensors for the purpose of SHM. Simulation results demonstrate that a set of strategically positioned heterogeneous sensors can maintain an optimal balance between the modal information accuracy and energy consumption. With the determined sensor deployment configuration, the proposed clustering optimization approach can be easily implemented to further conserve energy by selecting appropriate CH nodes in a multi-hop HWSN.


The authors would like to correct following typing errors: For (3) and (4), the correct expressions are given asfp, parameter The authors would like to express their gratitude to Anna-Lena Hammer from Ruhr University Bochum, Germany for finding this error.The changes do not affect the results. The manuscript will be updated, and the original one will remain available on the article webpage.


In oil and gas and geothermal installations, open channels followed by sieves for removal of drill cuttings, are used to monitor the quality and quantity of the drilling fluids. Drilling fluid flow rate is difficult to measure due to the varying flow conditions  and the presence of drilling cuttings and gas bubbles. Inclusion of a Venturi section in the open channel and an array of ultrasonic level sensors above it at locations in the vicinity of and above the Venturi constriction gives the varying levels of the drilling fluid in the channel. The time series of the levels from this array of ultrasonic level sensors are used to estimate the drilling fluid flow rate, which is compared with Coriolis meter measurements. Fuzzy logic, neural networks and support vector regression algorithms applied to the data from temporal and spatial ultrasonic level measurements of the drilling fluid in the open channel give estimates of its flow rate with sufficient reliability, repeatability and uncertainty, providing a novel soft sensing of an important process variable. Simulations, cross-validations and experimental results show that feedforward neural networks with the Bayesian regularization learning algorithm provide the best flow rate estimates. Finally, the benefits of using this soft sensing technique combined with Venturi constriction in open channels are discussed. One of the important phases in extracting oil and gas is drilling from the surface down to the reservoir. Due to high temperature and pressure conditions in the bottom-hole, there is a high risk of failure while drilling. Drilling fluid circulation plays a vital role in safe and efficient drilling operations. The drilling fluid can be water-based or oil-based depending on the type of reservoir. While drilling, the drilling fluid is continuously pumped down into the wellbore through the drill pipe. The circulating drilling fluid returns to the surface through the annulus, i.e., the space between the drill pipe and the wellbore. The drilling fluid circulation continues until the desired depth is reached. The primary functions of drilling fluid circulation are stabilizing the wellbore, the cleaning borehole and transporting rock cuttings. These functions are dependent on the properties of drilling fluid, among which density, viscosity and flow rate are the most important ones. The viscosity and other rheological properties of circulating fluid regulate the hole cleaning and transportation of rock cuttings .In the context of this paper, variations of viscosity are not taken into account. The drilling fluid density is responsible for wellbore stability. For any reservoir, there exists a certain pressure window where the drilling operation can be performed safely. The pressure window extends from formation pressure  by a timely and preventive alarm, so that the operator takes the necessary actions to limit material damages and hazards to personnel. The early detection of these problems can lead to less fluid loss, less formation damage, lower drilling costs and, above all, increased safety with minimized maintenance costs. One of the simplest methods for early detection is the so-called delta flow method, which utilize the difference between inflow and outflow measurements in a circulation loop. To implement the delta flow method, two flow measurements for drilling fluid entering the well (inflow) and drilling fluid returning from the well (outflow) are needed. When the inflow exceeds outflow, lost circulation in the loop is a possibility. On the other hand, for inflow less than outflow, the possible occurrence of kick is indicated. Other different methods for kick and lost circulation detection are discussed in ,4,5,6.Therefore, the aim is to accurately determine the delta flow in the circulation loop. There are different types of flow measurement systems for delta flow measurement in the literature ,9,10,11.In an open channel with Venturi constriction, the upstream pressure relative to the level in the control section is used to estimate the flow rate of the fluid . Fluids P, u, z, g are fluid pressure, fluid velocity, elevation of the channel relative to the datum, fluid density and acceleration due to gravity, respectively, with the subscripts indicating two distinct positions in the inclined channel. The further simplification of Equation , Campus Kjølnes, Norway. As a part of this study, the Computational Fluid Dynamics (CFD) simulation study is investigated in ,17. The In theory, the simplified equation (Equation ) can be The system description is presented in Over the full range of flow, the reliability and accuracy of measurements are guaranteed.In the common drilling operational environment, an accuracy of 1.5–3 L/s for flow rates up to 75 L/s.For any type of drilling fluids (water and oil based) in the viscosity range 1–200 cP and density range of 1000–2160 kg/mIn an earlier paper , addressThe methods presented here may be used for non-intrusive measurements of drilling fluids in many sectors satisfying all these requirements. Although some changes in these expected features may be seen in the practices of different operators, these can be used as design guidelines.In this study, an accurate Coriolis mass flowmeter is used as a reference meter for all comparisons of results from empirical models. The open channel has a trapezoidal cross-section with Venturi constriction. The upstream length is long enough to ensure fully developed flow before entering the constriction. Further, the channel can be inclined to the horizontal at different angles to analyze different flow conditions. Three different ultrasonic level sensors are installed over the open channel, giving levels of fluid in the channel, which will be used for flow measurements, as discussed in the following sections. For the current study, a model-drilling fluid consisting of potassium carbonate (as the densifier) and xanthan gum (as the viscosifier) is used. The fluid is viscoplastic in nature with a density of 1153 kg/mThis water-based non-Newtonian fluid with the properties given above is used in assessing the performance of a method of estimating its volumetric flow by sampling the levels of the open surface of the fluid flowing in the Venturi channel with an array of non-invasive ultrasonic level sensors. The performance of this soft sensing of the flow rate should satisfy the criteria outlined in The first step in conceiving of a suitable empirical model is the identification of suitable input feature space for estimating the mass flow rate of a drilling fluid. The Partial Least Square (PLS) method used in steady state conditions from earlier studies  shows thFor developing models, about 1800 data samples are used for each of the three input variables (ultrasonic levels) and the single output variable (Coriolis flow rate). The samples are obtained at the data sampling rate of one sample per second using compactDAQ in the LabVIEW environment. The ranges, units and input/output types of each variable considered for modeling are tabulated in In this work, different Artificial Intelligence (AI) methods are used to estimate the flow rate of the non-Newtonian fluid. Under this section, AI methods like Fuzzy Logic (FL), feedforward and feedback ANN and Support Vector Regression (SVR) are briefly discussed.Fuzzy Logic (FL) is an approach where the computing is based on degrees of truth rather than crisp true or false values. The FL tool can be considered as a function that receives inputs and gives an output based on the defined rules and membership functions. Analysis of the literature ,24,25,26ANN is a kind of non-linear mapping system suitable for pattern recognition, regression problems, image compression, etc. ,31,32,33J represents the cost function, which is a function of weights (w) and bias (b). Parameters n, p and T represent the number of samples, model prediction and target value, respectively. W is the weight parameter vector and In this paper, feedforward ANN with three different learning algorithms, Levenberg–Marquardt (LM) learning, Bayesian Regularization (BR) learning and Scaled Conjugate Gradient (SCG) learning, are investigated. The cost function for LM learning and SCG learning algorithms is the mean squared error defined by Equation , and theA feedback ANN is a dynamic ANN that uses previous inputs and outputs to estimate current outputs. The architecture of a fully-connected feedback ANN consisting of feedback loops and self-feedback loops is shown in In this paper, feedback ANN with three different learning algorithms, Back Propagation Through Time (BPTT), Real-Time Recurrent Learning (RTRL) and Extended Kalman Filter Learning (EKF), is studied. BPTT is an extension of the classical gradient-based back-propagation algorithm where the feedback ANN architecture is unfolded into feedforward ANN with a different number of folds ,36,37,38k representing the kernel function) is the mapping function from the input space to the feature space, b is the bias term, x represents the input, y represents the output and The Support Vector Machine (SVM) technique is applied in applications like classification problems, pattern recognition, time series predictions and regression problems ,40,41,42(a)% Get and normalize dataset(b)% Divide dataset into training, validation and testing sets(c)% Construct two arrays of different AI techniques and corresponding learning algorithms(d)% Train different AI techniques using training data set(e)% Validate all the AI techniques using the validation dataset(f)% Test all the AI techniques using test setDifferent AI models are developed using the data from three ultrasonic level measurements LT-1, LT-2 and LT-3 as inputs and Coriolis mass flow readings as the output. The dataset is normalized and divided into three sets for training, validation and testing. Different empirical relations (hypothesis) between inputs and output are developed using the training dataset. The empirical models developed are then validated leading to the final hypothesis with associated optimal model parameters. Finally, the eight models are tested for their performance. The flowchart for training, validating and testing all the AI models is shown in k number of folds  and loss of circulation fluid. One of the best ways to detect these problems is the delta flow method, which utilizes the difference in inflow and outflow measurements of drilling fluid in a flow loop. There are different methods to perform accurate inflow measurements discussed in the literature. However, it is complicated to measure the outflow measurement accurately, particularly so for non-Newtonian fluids. In this paper, we introduce different empirical models and present both simulation and experimental results based on the comparison to readings from the Coriolis mass flowmeter. The starting point for this particular investigation is the set of three ultrasonic height measurements. The question is whether we can estimate the bulk flow velocity based only on these three parameters using non-invasive techniques. This is where soft sensor models come into play. The results from extensive experiments with non-Newtonian model-drilling fluids in the research laboratory of Statoil and in the flow loop at USN are used to develop the soft sensor models presented in this paper.Different empirical models presented in this work are: the Sugeno-type fuzzy logic model, feedforward ANN models with three learning algorithms , feedback ANN models with three learning algorithms  and support vector regression model with the radial basis function as the kernel function. For these models, the partial least square method is used to identify the inputs and output variables. In the simulation study, feedforward ANN with LM learning and BR learning are found to be the best models based on the MAPE and ified in .For future work, the quality and quantity of the training and validating datasets can be improved. As the proposed modeling is mainly dependent on the type of data, we believe that improvement in data measurement and extraction will improve the performance of the models. For this purpose, the first step will be filtering the noise from the data and performing other signal processing techniques to improve the signal information.The technique presented here paves the way for realizing a simple and effective soft sensing system for monitoring a commonly-occurring module in the fossil fuel and renewable industries, viz. the operational unit for transport, cleaning recovery and mass balance budgeting of a costly and environmentally-hazardous drilling fluid, which is non-Newtonian. The soft sensing of the fluid flow rate using an array of non-intrusive and non-invasive ultrasonic transducers could spare the operators expensive maintenance costs and improve autonomous operation of plants in conventional fossil fuel and emerging renewable energy industries. For interested researchers, the data used in this study are made available in the web portal of this journal.


Bubbly flows are commonly used in various applications and their measurement is an important research topic. The ultrasound pulse-echo technique allows for the detection of each bubble and the measurement of the position of its surface. However, so far it has been used only to measure single bubbles. This paper investigates whether the pulse-echo technique can be applied for measuring multiple bubbles concurrently. The ultrasonic transducer wavelength and diameter were selected based on expected bubble diameters so that each bubble produced a strong reflection. The pulse-echo was implemented to obtain good accuracy without sacrificing the signal processing speed. A tracking technique was developed for the purpose of connecting detected reflections to trajectories. The technique was tested experimentally by measuring the horizontal position of rising air bubbles in a water tank. The results show that the pulse-echo technique can detect multiple bubbles concurrently. The pulse-echo technique detected almost the same number of bubbles as a high-speed video. For average void fractions up to around  Various industrial applications require the accurate prediction of bubbly flows, which are typically described using some averaged parameters . However, prediction based on the averaged parameters is limited to simple flow geometries and conditions. Overcoming this limit requires going beyond the average parameters, in other words observing each individual bubble, understanding its dynamics and the mechanisms of bubble interaction. Such an observation requires a measurement technique with the ability to resolve each bubble individually. Some intrusive techniques, such as optical probe  , resistUltrasound measurement techniques apply an ultrasonic transducer (TDX) with a piezoelectric element to generate ultrasonic waves from an electric signal (emit) and vice versa (receive). Ultrasound measurement techniques for bubbly flows can be classified into three groups: transmission techniques, Doppler techniques, and pulse-echo techniques. Transmission techniques measure average void fraction from attenuation and delay of ultrasonic pulses caused by bubbles  and DoppWhile common in the medical, non-destructive testing, and other fields, the pulse-echo has not been applied often to bubble measurement. The pulse-echo technique was used in ,14 to meIn the above-mentioned studies, the pulse-echo technique was limited to measuring a single bubble surface at a time. The reason for this is that in many configurations, the bubble closest to the TDX is the only one that can be detected accurately. This was explained in , where tIn this paper, we hypothesise that the pulse-echo technique is capable of detecting multiple bubbles simultaneously. In other words, even bubbles which are not the closest to the TDX can be detected and positions of their surfaces can be measured with a reasonable accuracy. In order to do so, it is necessary to apply a TDX with a suitable diameter and wavelength of the ultrasound beam, the selection of which is explained in this paper. Moreover, this paper explains the signal processing developed for the purpose of this measurement. The key point of our signal processing is the tracking technique, which distinguishes between different bubbles using the measurement time (number of the ultrasound pulse emissions), position (transit time), and the reflection strength (related to amplitude). In contrast with that, previous reports have applied only the measurement time, which was enough for measuring single bubbles.The aim of this paper is to confirm our hypothesis experimentally by comparing the results of our technique with a reference measurement by an HSC. The technique was tested using a horizontal measurement of bubble vertex positions for various bubble number densities and constant bubble diameters. Testing the technique under varying bubble diameters, TDX wavelengths, and TDX diameters is beyond the scope of this paper. The authors have been developing this technique and have presented it in ,21,22,23n periods of a basic frequency T, which relates to the distance x between the bubble and the TDX as:c. The pulse-echo technique measures the transit time of reflections and thus the positions of bubble surfaces. According to [T corresponds to the position of the bubble vertex, the surface point closest to the TDX.In the pulse-echo technique, ultrasonic pulses  in the shadow. The exact description of how TDX parameters affect the diffraction and the ability of bubbles to reflect from the diffraction zone is a topic that is worth its own paper and should be examined in more detail so that the optimal TDX can be chosen for the pulse-echo. However, in this paper, we focused only on the experimental proof of our hypothesis. Regarding the diffraction, we assumed that unless the wavelength First, the TDX diameter was selected so thatThe reflection strength depends on the type of ultrasound reflection, which changes with the ratio of wavelength and bubble diameter as described in . In ordeher with  for selek was chosen to include all the peaks higher than 5% of the highest peak in the reference signal.Each waveform was analysed to detect reflections from bubbles and to measure the positions of bubble vertices. The positions were calculated using  from traThe implementation of the thresholding followed the typical scheme described in  with a fnce with  as an avM , was found and its corresponding lag M was chosen otherwise) in each pulse repetition’s waveform. Finally, all bubbles detected in the pulse were saved for the tracking as a point t (the time when the pulse was emitted from the TDX), the transit time T, and the signal strength M.The cross-correlation is commonly applied to detect the delay of a signal with a known or assumed waveform ,28,29,30The pulse-echo technique was implemented to analyse multiple pulse repetition waveforms in parallel. As a result of the parallel implementation and the fast combination of the thresholding and the cross-correlation, data could be processed online even with a mid-range processor . Moreover, the amount of data to save was reduced by 2–3 orders of magnitude to ~100 kB per second of the measurement, which could be handled by a regular hard drive and which makes it easy to conduct very long measurements.t and transit time T (corresponding to the position) to connect points to trajectories and then divided some of these trajectories using the signal strength M. Unlike in [The task of the tracking technique was to connect detected bubble points . Instantaneous velocities varied but stayed small, which was confirmed from the measured trajectories . Assuming the real velocity was smaller than The performance of the presented technique was evaluated experimentally using a reference concurrent measurement by an HSC. The experimental apparatus showed in Ultrasonic pulses were generated by the pulse generator/receiver  and repeated with frequency rding to , the beax in Equation (c changes not only due to temperature (which can be accounted for) but also due to impurities in the water. These issues are usually ignored due to their small effect. However, the current technique allowed achieving such a high level of accuracy that these issues became relevant. A calibration was performed to achieve as high measurement accuracy as possible.It was explained that the position Equation  correspoEquation  does notc were obtained by measuring reflections from an acrylic plate and analysing their transit times using the cross-correlation method with the same reference signal as for bubbles (only opposite since bubbles reflect with opposite phase compared to the acrylic plate). First, the acrylic plate was placed on the TDX holder surface (around 20 mm from the TDX) and the transit time Transit times were measured as relative to a TDX holder surface x of each reflection was obtained from the corrected transit time T asFinally, the position An HSC  was used as a reference measurement technique to assess the pulse-echo performance. The HSC was positioned in front of the water box and was mounted with a Micro  60 mm lens . The video was recorded at 1000 fps with the shutter speed of 1/20,000 s and the resolution of 1024 × 320 px. The backlight imaging method was used; the test section was illuminated from the rear by a metal-halide light  and bubbles in the test section cast a shadow, which was recorded by the HSC.The HSC footage was analysed using Matlab. The grey-scale threshold was applied to obtain a binary image from each video frame, which was then filtered using a morphological opening and closing. Bubble boundaries were detected at each frame using the Moore neighbour tracing algorithm with Jacob’s stopping criteria . BubblesThe plug with a 4 mm × 36.4 mm- wide channel c directeN points and a trajectory L points. The metric was calculated asIn order to compare pulse-echo trajectories to HSC trajectories bubble-by-bubble, each trajectory was associated with its counterpart. A metric Bubble vertex trajectories were measured for nine different cases. Different air flow rates were applied in each case, which led to different bubble number densities (and void fractions). Out of 9 measurement cases, 6 cases were ~70 s long and 3 cases with high bubble number densities were ~30 s long; 250–750 bubbles were measured in each case. Bubbles were close to oblates in shape and their average horizontal and vertical lengths (around 3.9 × 2.1 mm based on HSC data) changed less than 2% between different measurement cases. The experimental condition is shown in The To confirm that the performance of the pulse-echo coupled with the tracking technique is reasonably good, results were compared with results of the HSC measurement. The number of trajectories (bubbles passing the measurement volume) was calculated for each case and divided by the total measurement time for both pulse-echo and HSC , Table 2le rates , Table 2le rates . Second,le rates . Therefole rates  for deteThe bubble rate discussed previously is not a commonly used two-phase flow parameter. Instead, the bubble number density is. In order to obtain the bubble number density, bubbles lying in a given volume have to be counted at each instant and their number divided by the volume. In two horizontal dimensions, the narrow inlet channel restricted the bubble positions. The HSC data confirmed that bubble vertices stayed uniformly distributed in a For the pulse-echo, bubbles were detected only in the ultrasound field, which does not have a clear boundary a. The boThe same volume was used for the HSC. The projection of the volume on the HSC image was 0-30) in ) calculaThe hypothesis that pulse-echo technique is capable of detecting multiple bubbles simultaneously has been confirmed. It can be seen from Nevertheless, the tested range was limited and the results can be quite different for different combinations of bubble diameter, wavelength, and TDX beam diameter. The simple consideration regarding these three parameters, which has been presented in this paper, could be improved upon, especially by analysing the sound diffraction behind bubbles and the reflection from bubble vertices positioned there in more detail. An improved understanding would allow for choosing more fitting a combination and thus improve the performance. Finally, it should be noted that the uncertainty in determining the pulse-echo measurement volume limits the application of this technique since bubble number density cannot be measured with high accuracy.With that being said, the pulse-echo technique can resolve each bubble individually and by combining it with methods from ,18,21 it


Conventional techniques for the noninvasive measurement of brain activity involve critical limitations in spatial or temporal resolution. Here, we propose the method for noninvasive brain function measurement with high spatiotemporal resolution using optical signals. We verified that diffused near-infrared light penetrating through the upper jaw and into the skull, which we term as optoencephalography (OEG), leads to the detection of dynamic brain signals that vary concurrently with the electrophysiological neural activity. We measured the OEG signals following the stimulation of the median nerve in common marmosets. The OEG signal response was tightly coupled with the electrophysiological response represented by the somatosensory evoked potential (SSEP). The OEG measurement is also shown to offer rather clear discrimination of brain signals. The development of noninvasive techniques to allow the measurement of brain activity is imperative for revealing how the human brain functions. Conventional techniques for noninvasive measurement of brain activity such as functional magnetic resonance imaging (fMRI), near-infrared spectroscopy (NIRS), magnetoencephalography (MEG), and electroencephalography (EEG), are burdened by critical limitations in spatial or temporal resolution . In ordeIn this study, three healthy common marmosets  were assessed. The marmosets were placed in a regular day-night cycle and had free access to food and water. This study was approved by the Ethics Committee for Experimental Animals of Hiroshima University. The marmosets were treated according to the guidelines stipulated by the Institutional Animal Care and Use Committee. The animals were diverted to other studies after the end of the study.2) and heart rate by a pulse oximeter during the OEG or SSEP measurements. An electrical stimulation was applied to the median nerve of the left wrist using 1.5 mm long needle electrodes. The electric current stimulation consisted of a monophasic square wave pulse (100 μs in duration) applied just above the motor threshold to elicit a slight but visible twitch of the thumb every 1.7 s.To induce a rapid inhalation anesthesia, a concentration of 2.5% of isoflurane  (3 l/min air) for about 5 min. Then, the concentration of isoflurane was reduced and maintained at 1.0% for the continuation of the experiment. We monitored blood oxygen saturation level , e.g. at the same position as the photo-sensor in the OEG measurement. The reference and ground electrodes were placed at the left and right earlobes, respectively. EEG recordings were taken using a DC amplifier with a low-pass filter at 500 Hz and sampled with a 16 bit A/D converter, similar to that used in the OEG recording. The average of 300 EEG signals was calculated to resolve the SSEP. We measured the OEG signals at four points surrounding the position  in order to evaluate the spatial resolution of OEG. The positions for OEG measurement were: vertex ; 14 mm right from vertex ; 7 mm right and 7 mm anterior from vertex ; 7 mm right and 7 mm posterior from vertex  in addition to  as shown in The marmoset’s head was shaved. During the recording sessions, the marmoset was placed in a wooden restraining chair. For OEG recording, an LED  emitting 850 nm near-infrared light was fixed on the palate in the mouth. The LED was embedded in polyethylene resin, shaped in the form of a mouth-guard, and fitted onto the palate of the upper jaw, as shown in  signals –13; the t-test shows that the OEG amplitudes of the negative and positive peaks measured at the four points: , ,  and  shown in The OEG response measured at , which is 7 mm to the right of the skull vertex, is presented in Our results demonstrate that the OEG signal response is tightly coupled to the electrophysiological response, following a sensory stimulation of the peripheral nerve. The high cross-correlation coefficient of 0.72 between the OEG and SSEP indicates a strong relationship between the OEG signal and the electrophysiological neural activity in the brain. Our findings in this study revolutionize the measurement of brain dynamic function, which has been difficult to achieve using conventional methods such as NIRS, fMRI, MEG and EEG. These conventional methods are constrained by limitations in temporal or spatial resolution. The signal for neural activity measured by NIRS or fMRI is based on the hemodynamic response, and therefore, the attainable temporal resolution is in the range of a few seconds. The measurement with EEG/MEG has a temporal resolution in the order of milliseconds; however, the problem of estimating the current sources in EEG/MEG recordings is fundamentally difficult and without solution to date . The stuIn this study, we proposed the noninvasive method to measure the brain signals using diffused near-infrared light penetrating the head from upper jaw to scalp, which is denoted as OEG. In order to verify the validity of OEG, we observed OEG response following the somatosensory stimulation in common marmosets. The results show that OEG signal response is tightly coupled with the electrophysiological response represented by the SSEP. We also confirmed that the OEG measurement offer rather clear discrimination of brain signals.


When choices are made freely, they might emerge from pre-existing neural activity. However, whether neurons in the prefrontal cortex (PF) show this anticipatory effect and, if so, in which part of the process they are involved is still debated. To answer this question, we studied PF activity in monkeys while they performed a strategy task. In this task when the stimulus changed from the previous trial, the monkeys had to shift their response to one of two spatial goals, excluding the one that had been previously selected. Under this free-choice condition, the prestimulus activity of the same neurons that are involved in decision and motor processes predicted future choices. These neurons developed the same goal preferences during the prestimulus presentation as they did later in the decision phase. In contrast, the same effect was not observed in motor-only neurons and it was present but weaker in decision-only neurons. Overall, our results suggest that the PF neuronal activity predicts upcoming actions mainly through the decision-making network that integrate in time decision and motor task aspects. Decision-making has been traditionally studied using experimental paradigms in which the correct choice is determined by a set of instructions. However, little attention has been paid to how decisions are made when subjects are free to decide when to act or which choice to make. In the latter situation of free choice, most experiments have focused on cases in which the options that are provided are neither correct nor incorrect but have different associated values  performed a strategy task  and were approved by the National Institute of Mental Health (NIMH) Animal Care and Use Committee (IACUC). Details on the experimental procedures have been described in Genovesio et al.  or to choose one of the other two goal locations  when the stimulus changed Figure . BecauseUnrewarded trials were followed by a second-chance trial, keeping the distribution of the reward rates of each goal comparable and independent of any preference by the monkeys. In the second-chance trial, the monkeys were required to select the goal that remained after eliminating the most recent ones. In all cases, the reward consisted of a 0.1-ml drop of fluid.In an aseptic surgical procedure and using isoflurane anesthesia (1 to 3%), we performed a 27 × 36-mm craniotomy over the right frontal lobe in each monkey. Then, we implanted several titanium bone screws into the surrounding bone, to which we attached a recording chamber and a head-restraint device with methacrylate acrylic cement. Postoperative analgesia was given for 3–5 days.The monkeys’ eye position recorded and monitored with an infrared oculometer  at 500 or 1000 Hz. Single-unit potentials were isolated with quartz-insulated platinum-iridium electrodes , advanced into the cortex by a 16-electrode microdrive with independent control of each electrode . The signal was amplified and discriminated using a multispike detector  or a multichannel acquisition processor . With the latter, neuronal waveforms were always resorted with the Offline Sorter (Plexon). We used CORTEXn = 887/1456). In this subset, we identified decision neurons and motor neurons. The decision neurons were defined as the neurons that were spatial goal-selective  in the IS1 (early instruction stimulus period) period of the free-choice trials . The motor neurons were defined as the neurons encoding the goal location in the reaction and movement time . Bias activity was studied in the period between 0 and 200 ms before stimulus presentation (prestimulus period). We used this temporal window, because it is the period just before the presentation of the stimulus. In all cases, only correct trials were considered for analyses.From the initial dataset on 1456 neurons in the PF  between preferred and nonpreferred goals conditions was calculated using a nonoverlapping window of 100 ms. Only the time intervals in which the neural activity was significantly different for at least three bins are reported. Different windows sizes led to equivalent results (data not shown). The preferred and nonpreferred goals for each neuron corresponded to the goal that was associated with the maximum average activity and the average of the two remaining ones, respectively.The average firing rate of the neural population was plotted using the mean of the individual neural responses, calculated with a window of 50 ms and a sliding window of 5 ms to smooth the curves. The statistical significance  in locations at two depths per penetration. After approximately 10 days, the animal was deeply anesthetized and perfused with formaldehyde-containing fixative. The brains were later sectioned in the coronal plane and Nissl-stained for cytoarchitectonic analysis  with future goal location  as a factor. We identified 143 of 887 (16%) neurons modulated by goal location during the prestimulus period and 145 neurons (16%) modulated during the RMT period with 42 neurons belonging to the two groups , those that were involved during motor selection but not during decision making (motor-only neurons) and those that were involved in both decision making and motor selection (decision and motor neurons). Henceforth, the change-shift trials are referred to as free-choice trials, because in these cases, the monkeys were free to choose between two goals without knowing which goal would be rewarded. The decision neurons were defined as those that encoded the future goal location in the first 80–400 ms of the IS  whereas the motor neurons are those that encoded it during the RMT period. The prestimulus period corresponded to the time during which the monkeys were first informed on the two potential goals during the free-choice trials. To identify both group of neurons, we performed a one-way ANOVA  before presentation of the stimulus. The activity of these neurons was also significant for 400 ms after the disappearance of the IS (from 200 to 600 ms after IS offset). On the contrary, the activity between preferred and nonpreferred goals of motor-only neurons was significantly different 200 ms after the appearance of IS but not before . Thus, we can rule out the possibility that the differences in the prestimulus activity between the groups could be accounted by differences in the degree of selectivity.Next, we examined whether the population of decision-only neurons showed a prestimulus neural response bias by comparing their activity for choices toward the preferred and nonpreferred goal locations before presentation of the IS. Top panel of Figure An example of a decision and motor neuron that was selective for the left goal in the free-choice trials is shown in Figure n = 1 to n = 101 for decision-only neurons; from n = 1 to n = 103 for motor-only neurons; from n = 1 to n = 42 for decision and motor neurons). The prediction exceeded chance values (33%) for decision-only and decision and motor neurons, increasing in both cases with the number of neurons that were used together. Chance value was 33% because in the prestimulus period, before IS presentation, all three targets were potential goals. On the contrary, the prediction remained at chance level for the motor-only neurons, independently of the number of neurons used for prediction. Importantly, the decision and motor neurons showed a much greater proportion of correctly predicted trials compared with the decision-only neurons. Moreover, the prediction from the prestimulus activity of decision and motor neurons peaked at ~55%, well above chance and close to the maximum percentage of trials that could be predicted (66%) considering that before the presentation of the stimulus the potential choices were three. These results show a high predictive power of the future choice of the prestimulus activity of decision and motor neurons. Moreover, the prediction is notably higher than that provided by the decision-only neurons.To quantify how reliably the prestimulus activity of each group of neurons predicted the final goal choice, we used a classification algorithm with neuron-dropping analysis  when all neurons of the group were pooled. We differentiated motor and decision activity based on the period of the analysis, notwithstanding the fact that other functions, such as attention to target and motor vs. abstract goal coding, could not be dissociated. Our central finding is that a preference for the same target emerged in these neurons before presentation of the stimulus, indicating that the same future choice is encoded already in the pre-existing activity. Moreover, the neural activity bias emerged 900 ms, but not earlier, before presentation of the stimulus, suggesting that the neural response bias originated only after the beginning of the trial, when the monkeys were engaged in the new trial. However, they did not yet commit to any decision as shown by the good performance in the repeat-stay trials that imposed a forced choice (see Figure 2 in Genovesio et al., To achieve a high level of accuracy in the strategy task the monkeys needed to perform several cognitive operations in addition to a free choice. First, they needed to maintain in memory the previous IS and chosen goal to be able to select the correct goal in the trial. Second, they needed to decide to either stay or switch to a different response based on the comparison between IS in the previous and current trial. Last and only in the free-choice trials they needed to choose one of two targets. While the other cognitive operations were examined by our previous articles (Genovesio et al., Many studies have examined the function of PF in decision-making, most of which have focused on tasks in which the correct response depends on the comparison between sensorial events using disparate sensory systems and domains, demonstrating how PF cells participate in decision-making (Kim and Shadlen, Several neurophysiological studies have failed to observe an anticipatory response bias in PF neurons when monkeys perform perceptual discrimination tasks, even when the psychological judgments were difficult (Kim and Shadlen, Conversely, using value-based free-choice decisions, a recent neurophysiological study reported anticipatory activity of neurons in the PFdl that was predictive of future choice (Maoz et al., Unlike in earlier studies, our task has the advantage of not requiring any comparison between alternatives to determine the correct goal location, as in the perceptual tasks, or any evaluation and comparison of the values of the alternatives, as in value-based decision tasks. Under these new conditions, we found that neurons involved in goal coding from the decision to the motor phase, in the PF showed prestimulus activity that was highly predictive of future decisions. Importantly the decision neurons’ activity could not depend on differences in visual responses because all three targets were always presented. Thus, our results indicate that neurons that exhibit a bias in the prestimulus period are not necessarily dissociated from those that are involved in decision formation, as proposed (Maoz et al., In earlier studies (Genovesio et al., In conclusion, the pre-existing activity of neurons in the PF contributes to the decision process in free-choice conditions but we cannot rule out the contribution of other areas as the source of the bias. Further, our study has examined the prefrontal contribution of the PFdl and PFdm to free choice at the single-cell level, showing that under no external constraints or instructions, the pre-existing state of the decision and motor PF neurons that appear to bridge in time the decision and motor phases Fuster,  has a siAG performed the experiment, EM analyzed the data and AG and EM wrote the article.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.


Great expectations are connected with application of indirect fetal electrocardiography (FECG), especially for home telemonitoring of pregnancy. Evaluation of fetal heart rate (FHR) variability, when determined from FECG, uses the same criteria as for FHR signal acquired classically—through ultrasound Doppler method (US). Therefore, the equivalence of those two methods has to be confirmed, both in terms of recognizing classical FHR patterns: baseline, accelerations/decelerations (A/D), long-term variability (LTV), as well as evaluating the FHR variability with beat-to-beat accuracy—short-term variability (STV). The research material consisted of recordings collected from 60 patients in physiological and complicated pregnancy. The FHR signals of at least 30 min duration were acquired dually, using two systems for fetal and maternal monitoring, based on US and FECG methods. Recordings were retrospectively divided into normal (41) and abnormal (19) fetal outcome. The complex process of data synchronization and validation was performed. Obtained low level of the signal loss (4.5% for US and 1.8% for FECG method) enabled to perform both direct comparison of FHR signals, as well as indirect one—by using clinically relevant parameters. Direct comparison showed that there is no measurement bias between the acquisition methods, whereas the mean absolute difference, important for both visual and computer-aided signal analysis, was equal to 1.2 bpm. Such low differences do not affect the visual assessment of the FHR signal. However, in the indirect comparison the inconsistencies of several percent were noted. This mainly affects the acceleration (7.8%) and particularly deceleration (54%) patterns. In the signals acquired using the electrocardiography the obtained STV and LTV indices have shown significant overestimation by 10 and 50% respectively. It also turned out, that ability of clinical parameters to distinguish between normal and abnormal groups do not depend on the acquisition method. The obtained results prove that the abdominal FECG, considered as an alternative to the ultrasound approach, does not change the interpretation of the FHR signal, which was confirmed during both visual assessment and automated analysis. Fetal heart activity is a primary source of information which enables assessment of the fetal state during pregnancy and at labor. This information is obtained mainly through analysis of the fetal heart rate (FHR) signal being formed from the instantaneous values calculated according to the formula: FHR [bpm] = 60000/T [ms]. The FHR values are expressed in beats per minute, and T is the time interval between two consecutive fetal heart beats that comprises one complete cardiac cycle. Together with additional signals describing the uterine contractile activity and fetal movement profile, the FHR signal constitutes the cardiotocographic record. Acquisition of these additional signals is quite simple, but measurement of the fetal heart rate has been always a challenge. Already in 1960s the fetal electrocardiogram was recorded for the first time by means of electrode attached to fetal head. The quality of such recorded direct fetal electrocardiogram (FECG) is usually very good, and thus it enables, using a quite simple processing method, determination of the beat-to-beat intervals with very high accuracy. However, the invasive approach and application limited to the labor only caused that direct method did not found wide application in clinical practice.As a result of further research and development the noninvasive ultrasound (US) method has become a standard approach since early 1970s, as it can be used both during pregnancy and labor. At present, all bedside fetal monitors intended to use in clinical conditions are based on the pulsed Doppler ultrasound technique, with measurement transducer attached to maternal abdomen. Principle of operation relies on internal processing of the envelope of the US beam reflected from moving parts of fetal hearts—valves or walls, to find the episodes corresponding to consecutive heart beats. However, a complex structure and varying content of the US signal, usually caused by relocation of the fetal heart in relation to a transducer during monitoring session, make a determination of the beat-to-beat interval very difficult . The files from the KOMPOREL System provide the FHR_E signal being determined on a basis of fetal electrocardiogram recorded from the abdominal wall of the mother. The fetal electrocardiogram is recorded by using four electrodes placed on the maternal abdomen. The crucial step in extraction of the FECG from the abdominal signal is a suppression of maternal electrocardiogram while preserving the fetal QRS complexes  , determined for the corresponding (applying the time shift) FHR_U and FHR_E values. To improve the performance of synchronization function it was necessary to further reduce the influence of random interferences appearing in the FHR signals, as well as sudden value changes resulting from the measurement errors or potential acceleration and deceleration episodes. Hence, the segments with sudden changes in the FHR signal were excluded from the function determination, if the absolute difference between a given value and the preceding one was higher than 10 bpm , in respect to the signals synchronized after the first stage. If at the beginning or end of a given signal any interference associated with the start or end of the monitoring session occurred, they were also removed in the trimming process. Trimming to the full minutes in turn, results from the fact that the analysis of the instantaneous FHR variability is always carried out within a 1-min signal segments. Finally, as a result of the synchronization procedure some signal pairs could be shortened by as much as 4 min. After the second stage of synchronization the common part of the analyzed signals is trimmed to the largest whole number of the minutes .We assumed that the minimum length of synchronized signals (constituting the pair) subjected to further analysis should be 10 min. According to that criterion only one recording was rejected, and 66 recordings were left.The next processing step consisted of verifying the signal pairs in terms of their quality, measured both by a size and nature of the signal loss episodes. Episodes of signal loss are preliminarily detected by the monitoring systems used, and represented by zero values in the FHR signal. For the purpose of this work also the potential erroneous FHR values, as not meeting the adopted criteria, were marked as signal loss episodes, using the dedicated developed program. Signal segments were considered to be signal loss if they did not meet the van Geijn modified criterion : the recording duration, signal loss level, mean value of the differences between the corresponding instantaneous FHR values (MD), standard deviation (SD), mean absolute difference (MAD), as well as the summary statistics for the entire research material. The difference between the pairs of corresponding instantaneous values of FHR_U and FHR_E was expressed dually: as the heart beats per minute (bpm) as well as in milliseconds. The second representation is obtained by conversion of the FHR values into intervals between successive heart beats, according to the hyperbolic transformation with the 60,000 factor.As equally important it is assumed the comparison of the signals in a format commonly used in automated analysis of the low variability FHR signal components  of the differences between the corresponding parameters obtained in the FHR_U and FHR_E signals was examined.As shown in the literature . Created according to the described procedure the FHR_U and FHR_E signals in the form of time event series, provided the basis values for determination of the instantaneous variability indices. These indices, widely acclaimed in the literature  of the differences between the values of the indices obtained for each signal pair was also examined.While processing a given segment, if percentage of valid values, relevant for a given index (according to its definition), was less than 20%, it was assumed that the index value was undetermined for that minute. Such cases are the result of the signal loss episodes in the analyzed signals. In a series of minute values calculated for a given signal, they are defined as a 1-min loss of the given index value and marked with the value of −1. The index average value for a given signal is calculated from all 1-min values, excluding those marked as undetermined. Additionally, a non-linear parameter of instantaneous FHR variability was proposed, in a form of the regularity measure—the sample entropy index (SampEn)   signal was represented by the feature set comprising: 15 parameters determined by the MONAKO System, 10 indices describing the instantaneous FHR variability and SampEn entropy measure. The differences between the values of these features obtained in two groups  were expressed by the mean percentage difference (MPD) for both groups—where the normal outcome group was taken as reference. The statistical significance of the difference between the mean values of each feature obtained for two groups was assessed using Student's The indirect comparison of FHR_U and FHR_E signals, as for predicting the fetal outcome, was based on the capability to classify the FHR signals from a given acquisition methods into normal and abnormal analyzing the determined clinical FHR parameters.SD = 10.9 min). The recordings were characterized by low signal loss . It enabled the metrological assessment of the inconsistency between the two acquisition methods. Comparison at that stage was performed for each individual recording and the summary of descriptive statistics for entire research material is presented in Table In the computer-aided system, the automated analysis aimed at determination of clinically important FHR patterns is carried out using the FHR values averaged over 2.5 s. It makes the comparison between FHR_E and FHR_U signals represented by such averaged values especially important. Averaging processes caused a slight decrease of the signal loss in both types of signals, to the values: 4.3% in US, and 1.4% in FECG  for individual parameters describing quantitatively the FHR signal, which have been determined for signals from both methods, are presented in Table Indirect comparison of the FHR_U and FHR_E signals was performed on the basis of the variability indices defined for signal represented as time event series—the heart beats. Summary of the results  for the selected 11 parameters describing the FHR signal variability is presented in Table With regard to such large inconsistencies it has to be decided which of the two methods may be considered as providing the FHR variability description being closer to the true one. The answer is not obvious, because in this work no reference signal was acquired simultaneously with two analyzed methods. Such gold standard can be provided by previously mentioned the direct fetal electrocardiography, where the pure FECG is acquired from the fetal head. In the previous studies where the FHR signal from ultrasound method was compared with the reference one, it has been shown that ultrasound method underestimates the short-term variability on a level between 20 and 40% in reference to direct fetal electrocardiography. A similar trend can be seen in Table The signal database has been divided into two groups: normal and abnormal, according to the established fetal outcome criteria. The description of two signal groups is shown in Table As above, no statistically significant differences were noted for all the indices describing both the short-term and long-term FHR variability. Decrease of most of the long-term variability indices was noted in abnormal groups (MPD ranged from −20 to −9%) for both FHR_U Table  and FHR_The paper proposes an extended process of comparing two different methods of fetal heart rate monitoring. It takes into account the issues associated with comparing different biomedical signals—the unsatisfying usability of the results obtained from direct signal comparison. High reliability of the comparison results can only be ensured by using the clinically significant parameters determined for signals acquired by both methods being analyzed . On the other hand, the mean absolute difference measured between the methods, being important for both visual and computer-aided signal analysis, was equal to 1.2 bpm. When relating to typical FHR level of about 140 bpm, the inconsistency takes the value of about 0.9%. These results are similar to those obtained in Cohen et al. . Subjects read approved consent form and gave written informed consent to participate in the study.JJ, JW, and AM designed the study approach and experiments. KH and AM described the research background in the introduction section. KH and JJ collected the research material. TK and RM provided the signal synchronization procedures. JJ, JW, and MJ were responsible for analysis and interpretation of data. TK and JJ performed statistics. JW wrote the manuscript with contributions from JJ, KH, RM, and MJ. All authors read and approved the final manuscript.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. The reviewer HA and handling Editor declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.


The use of Willis covered stent (WCS) for intracranial aneurysms has increased based on the promising results of previous studies about its safety and effectiveness. With the accumulation of cases, reports about peri-procedural complications are emerging. In our department, 25 patients were treated with WCS during December 2015 to March 2017. We here reported an unexpected technical complication occurred in the treatment with the WCS for a blood blister-like aneurysm (BBA). During the procedure, the distal end of the stents detached from the dilating balloon partially or as a whole. This was attributed to the tortuosity of the access route and the extracorporeal gas exhaust maneuver. Then we applied a half-dilating technique to retrieve the detached stent. The procedures were detailed in this report and the possible reasons and approaches to avoid it were explored. Intracranial blood blister-like aneurysm (BBA) is a type of aneurysm that lacks both the intima and media, and tends to rupture. It remains a demanding task to find a safe and effective approach to eliminating this lesion because of the fragility of artery wall –3. NowadA 52-year-old female with intermittent headache and dizziness was admitted into our department. Computed tomographic angiography showed an aneurysm located at ICA as later verified by the digital subtraction angiography (DSA). The shape and location of the aneurysm indicated the diagnosis of a BBA at C6 segment  of ICA Figure A.Five days before the procedure, dual antiplatelet therapy (aspirin 100 mg qd and clopidogrel 75 mg qd) was administered. The endovascular procedure was performed under general anesthesia and the right femoral artery was canalized. We adopted a tri-axial system to provide adequate support. That is to place an 8 F guiding catheter  in the C1 segment, and a XT-27 inside the Navien so that the Navien can be carry distally to the aneurysm, thus facilitating the following deployment of the WCS. However, because of the Simmons-style ICA  and the tortuosity of the petrous segment, the Navien could only be accessed no distal to the C4 segment. Though not satisfying, we proceed the procedure without further introduce the Navien to the supraclinoidal segment. The XT-27 was withdrawn and we used an Echelon-10 and 200-cm synchro-14 to access the M2 segment and then a 300-cm Synchro-14 exchanged the 200-cm microwire. We then chose a WCS measured 3.0 mm × 10.0 mm in size and navigated it over the microwire and bridged the aneurysm neck under roadmap guidance. Before dilation of the balloon, a control DSA was performed to confirm the position, yet we found that the distal end of the stent was already detached from the balloon  was administered before procedure. Routine procedure (described previously) was operated, with a type II ICA, the Navien could access to the C5 segment easily, we then navigated a WCS over the microwire under roadmap guidance. When the stent was sent out from Navien, there was no stent between two markers, and we were not sure where the stent was Figure C. We retCompared with other types of AN, BBA is more dangerous due to their fragile vessel wall and the high-risk to rupture. Numerous treatment methods have been proposed: microsurgical clipping or wrapping, coiling assisted with balloons or stents, and flow diverters. The current literatures have not reached a consensus on an optimal approach for treating this lesion. Though not as frequently reported, WCS is a favored option for BBA in our center considering its ability to reach instant elimination of the aneurysm and durability in follow-up .Here, we reported a complication which we have encountered when BBA was treated with WCS. We believe that three reasons might account for this complication, namely, failed to access the Navien distal to the aneurysm neck in tortuous access route, exhausting the gas extracorporeally, and adjusting the position of the stent repeatedly in the fear of cover the ophthalmic artery (OA) and posterior communicating artery (PcomA). All these three factors augmented the friction between the stent and access route, thus leading to premature detachment. The Navien catheter is relative smooth and flexible, advancing the Navien distally to the aneurysmal neck guaranteed robust support for the stent system and lowered the damage to the vessel caused by the stent navigation, this was true especially in tortuous access route. Exhausting the gas intracorporeally will eliminate an extra loosening of the stent attachment to the balloon. To better detect any dislocation of the distal end of the exchanging wires, we would navigate the WCS to the intracranial portion of ICA in the following operations before gas exhaustion. At last, due to the location of BBA, the aneurysm is distal to the siphon curve and adjacent to OA and PcomA. This special location makes the choice of the stent length difficult. Since a longer stent might have difficulties passing through the siphon curve and cover the orifices of OA and PcomA. A shorter stent may easily across the curve; however, it entails much effort to position the stent properly as to cover the neck of aneurysm without endoleaks. This repeated maneuver might lead to premature detachment. We have not come across such a complication in our earlier Jostent cases since Jostent coronary stent was mainly used to treat lesions proximal to the C5 segment of ICA and rarely been used for classic BBA located in supraclinoidal region. The Simmons-style ICA tortuosity increases the access difficulty of the stent, leaving too much friction and twisting of the device, which ultimately contributes to the detachment.There are some experiences that should be learnt from these two cases. First, with a tortuous access route, especially when we encounter the Simmons-2-style ICA, we should navigate the Navien distally to the aneurysm neck. Second, intracorporeal gas exhaustion is favored since extracorporeal exhaustion would predispose the stent in a state prone to detach along the access route. Third, try not to repeatedly repositioning the stent in the supraclinoidal segment. In the end, when the stent is partially detached, we can apply the half-dilating technique to retrieve the stent.Special cautions should be taken in the face of a Simons-style ICA in the treatment of BBA with a WCS. The tortuosity of the ICA may increase the risk of stent detachment from the delivery wire. To avoid this procedure-related complication, it is feasible to exhaust the gas intracorporeally after navigate the WCS to the intracranial portion of ICA, choose a shorter stent and navigate the Navien distal to the aneurysm. When this complication occurred, the stent can be safely retrieved using the half-dilating technique.Written informed consent was obtained from the patient for the publication of this case report.YuxiangZ and YupengZ: collected the data, drafted the manuscript, and are assistant performer of the procedures; these two authors are co-first author. FL: collecting the data. CJ: chief performer of procedures and conceived the manuscript.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.


Simultaneous bilateral mid-clavicle fracture with unilateral dislocation of the acromioclavicular (AC) joint is an extremely rare injury combination.Herein, we report a case of polytrauma in a 42 years old female following a road traffic accident.The radiographs showed the fractures in bilateral middle third of the clavicle and AC joint dislocation of left shoulder.The patient was treated with a 5-hole locking hook plate to stabilize the left AC joint and a shortly reconstruction plate to fix the left clavicle. Moreover, another 6-hole truncated anatomic reconstruction plate was used to fix the fracture of the right clavicle.At the 1-year follow-up, the patient had excellent range of motion and functional outcomes.It is important to achieve stability and aim for excellence in terms of full shoulder function in this rare combination injury. However, a combined injury involving a fracture of the middle third of the clavicle and dislocation of the acromioclavicular (AC) joint is quite uncommon. Herein, we report a case of a female driver with simultaneous bilateral mid-clavicle fractures and unilateral dislocation of the AC joint. The surgical treatment used to manage the injury is described along with a discussion of the key learning points.2The study was approved by the ethics committees of the participating hospitals and institutes, and in accordance with the principles stated in the Declaration of Helsinki, and written informed consent was obtained from the patient.A 42-year-old, left-hand-dominant female presented in the emergency department after being involved in a high-velocity road traffic crash. The patient was hemodynamically stabilized in the emergency department. Initial assessment revealed that she had contusion and swelling over the anterior aspect of the chest that extended up to the shoulders. At admission, the patient was taking shallow breaths and presented with pain during breathing, which was labored. The neurologic status and vascular status of the bilateral upper extremity were normal. Palpation revealed a palpable bony defect at the left acromion. A computed tomography scan of the thorax revealed a bilateral hemopneumothorax. The radiographs showed fractures in the bilateral middle third of the clavicle and AC joint dislocation in the left shoulder Fig. . Given t3–3 The only way to prevent malunion in a dislocated midshaft clavicle fracture is with either open reduction internal fixation (ORIF) or a percutaneous procedure. In our case, ORIF was chosen for the left shoulder, and surgical treatment was applied for both type III clavicle fractures. In 2009, Yeh et al reported 1 case with this combination injury. A precontoured plate was used to fix the clavicle. To achieve stability of the clavicle to the acromion and coracoid, a semitendinosus allograft was used to reconstruct the AC and CC ligaments. This was the first report in which ORIF was used for fixation of a clavicle fracture with ipsilateral AC and CC ligament reconstruction. In the present case, we applied a locking hook plate in this rare combination injury. A single implant contoured to stabilize the fractures and AC joint dislocation would have likely provided an ideal construct. However, there was no clavicle hook plate long enough to cover two-thirds of the clavicle length in our inventory. Therefore, we had to cut-off a reconstruction plate and fix the midshaft clavicle fracture and AC joint together with a hook plate. It is unclear whether a stress riser effect will occur between the 2 fixations. At the last follow-up, we found an excellent functional outcome of this fixation and satisfactory progress of the union. To the best of our knowledge, this is the only case in which this particular method has been employed in the management of the described combination injury. Nevertheless, continuous follow-up and biomechanics analysis are needed to support the clinical results and to validate the technique.At present, early AC joint fixations are gradually being accepted by many surgeons, especially for complete AC joint injuries  that involve a high-energy mechanism that results in significant instability of the AC joint. The common methods used to stabilize the AC joint include the Weaver-Dunn procedure, hook plate stabilization, screw stabilization, and anatomic reconstruction of the CC ligaments.In this rare case, which involved simultaneous bilateral midshaft clavicle fractures and unilateral AC joint dislocation, it was important to achieve stability and aim for excellence in terms of full shoulder function. The radiographs and type of injury should be carefully reviewed before treatment. This case also shows that applying surgical treatment to provide a rigid fixation and facilitate good range of movement early and in the long term can result in a good functional outcome.


Phase segregation of membranal components, such as proteins, lipids, and cholesterols, leads to the formation of aggregates or domains that are rich in specific constituents. This process is important in the interaction of the cell with its surroundings and in determining the cell's behavior and fate. Motivated by published experiments on curvature-modulated phase separation in lipid membranes, we formulate a mathematical model aiming at studying the spatial ordering of composition in a two-component biomembrane that is subjected to a prescribed (imposed) geometry. Based on this model, we identified key nondimensional quantities that govern the biomembrane response and performed numerical simulations to quantitatively explore their influence. We reproduce published experimental observations and extend them to surfaces with geometric features (imposed geometry) and lipid phases beyond those used in the experiments. In addition, we demonstrate the possibility for curvature-modulated phase separation above the critical temperature and propose a systematic procedure to determine which mechanism, the difference in bending stiffness or difference in spontaneous curvatures of the two phases, dominates the coupling between shape and composition. The biological lipid bilayer membrane, or in short “biomembrane,” is a fundamental building block of the cell. It forms the barrier that separates the interior of the cell from its surroundings but is also responsible for almost all interaction of the cell with its environment, including transport, adhesion, regulation, transduction, and signaling –5. The dThe fluidity of the biomembrane combined with its spatial heterogeneity brings about a unique coupling between shape (geometry) and composition. For example, lipid phases that possess high bending stiffness highly favor regions with small (magnitude) curvature . Also, tIn the last two decades, much effort has been invested into understanding the consequences of the coupling between shape and composition in biomembranes. Theoretical models have generalized uniform composition models –27 to acμm. In order to decouple the main membrane from the underlying substrate a double membrane system was used: first, a supported membrane of uniform composition was deposited on the substrate. Then, the “main” membrane, a giant unilamellar vesicle (GUV), was introduced on top. Parthasarathy et al. showed that beyond a critical temperature, the spatial organization of lipid phases can be directed by gradients of membrane curvature, provided that these gradients are large enough.In a recent work, Parthasarathy et al.  designedIn the current paper we analyze this type of experiment by means of a mathematical model combined with numerical simulations. The main goal is to reproduce the experimental observations mentioned above but also to generalize them and motivate new experiments. Accordingly, the structure of the paper is as follows: A. Above, the first term is the (Helfrich) bending energy  describes the mole fraction of the second component, which we also refer to as local composition or concentration. A few comments are in order: (i) functional  The specific mixing energy, f, combines the aggregation enthalpy and the entropy of mixing. A simple model that is often adopted for modeling the mixing energy is the so-called “gas lattice” or “regular solution” model, which takes the form , and γ = 10−19 [J]  , 54 implMotivated by the experiments of Parthasarathy et al. , we consmb . In the experiments of Parthasarathy et al.   , 54, whiWe formulated a simple mathematical model to study the spatial ordering of composition in a two-component biomembrane that is subjected to prescribed (imposed) geometry. The mathematical model does not account for possible anisotropy of the membrane constituents or for possible interaction between lipids in the two leaflets of the bilayer membrane. In addition, the numerical scheme, which follows the steepest descent method, leads to metastable equilibrium configurations associated with local minima of the free energy. We note, however, that applying the numerical scheme to slightly different initial conditions or to a larger domain of solution did not change the essence (topology) of the solution. Based on this model, we identified key nondimensional quantities that govern the biomembrane response and performed numerical simulations to quantitatively study their influence. Our numerical results show that the geometry-driven ordering of the biomembrane composition is largely governed by the difference between the nondimensional bending stiffness and spontaneous curvatures of each phase, while the magnitude of this phenomenon is proportional to the ratio between the bending energy and the  interaction energy of the phases. Roughly speaking, energy considerations favor configurations in which the phase that is stiffer and has smaller spontaneous curvature is located at regions having smaller curvature. The numerical simulations reproduced the experimental observation of Parthasarathy et al. , who fouAn important advantage of a mathematical model is that it enables studying the behavior at various settings with minimal effort and resources, before entering the lab. The agreement of our model results with experimental observations strengthens our confidence in the model and numerical scheme and opens the door to examining new and different conditions than those used in the original experiments. For example, we have demonstrated that, if the surface geometry is properly designed, phase separation can occur above the critical temperature. Such curvature-induced phase separation above the critical temperature awaits experimental examination. Also, we propose a systematic procedure to determine which mechanism, the difference in bending stiffness or difference in spontaneous curvatures of the two phases, dominates the coupling between shape and composition. The procedure is based on the observation that the mechanism associated with the difference in bending stiffness depends on the magnitude of the surface curvature but indifferent to the sign (direction) of the curvature. On the contrary, the mechanism related to the spontaneous curvatures strongly depends on both magnitude and sign (direction) of the surface curvature. The consequences of these differences have been demonstrated by a set of simulations.Movies showing the evolution in time for the simulations shown in Figure 2.