Here we describe a bench-top cryostat system to control the temperature of liquid ethane in a cryo-plunge apparatus designed for biological specimen preparation for electron cryomi-croscopy. It comprises a foam insulated Dewar containing a copper cryostat cup, whose temperature is controlled via an active feedback system to within 0.1 K. The device can easily be incorporated into existing manual and semi-automatic cryo-plunge instruments that are not equipped with cryogenic temperature control. Over the course of normal use, we find that using a cryostat is convenient, fast, and does not require special mixtures of cryogens like ethane/propane. This simple cryostat improves the reliability and reproducibility of biological specimen preparation for electron cryomicroscopy. IElectron cryomicroscopy (cryo-EM) depends on the ability to freeze water quickly enough to ensure it enters an amorphous solid phase.The most commonly used cryogen for freezing is liquid ethane, for the following reasons: 1. the melting point (90.4 K) is slightly above the boiling point of liquid nitrogen, 2. the heat capacity 68.5 J/mol K) is similar to water (74.5 J/mol K), and 3. the boiling point is 184 K, giving a large range of temperature before the liquid loses thermal contact with a surface by boiling, thus avoiding calefaction and the Leidenfrost effect. J/mol K Still, ethane has several drawbacks, including its flammability, its potential to cause burns if it contacts exposed tissue, and its melting point being above that of liquid nitrogen. While the first two hazards are easily mitigated by careful handling and safe protocols, the latter leads to reduced reproducibility and reliability in the specimen preparation process. It is desirable to keep the ethane temperature close to its melting point as this ensures proper vitrification of the specimen and prevents the formation of crystalline ice.One way to avoid some of these drawbacks is to use cryogens other than ethane, but these too have limitations. Propane  can also be used but has the disadvantage that in its solid form, it sublimes in vacuum at a lower rate than ethane and this may affect the amount of residual material left on the specimen.To avoid these problems while still allowing the use of a cheap and relatively innocuous cryogen like ethane, some commercial freeze-plunge apparatus like the Leica EM GP and the EMS-002 have built-in, proprietary temperature controllers for their ethane cups with varying degrees of temperature stability. Still, there are a vast number of custom made manual plungers and semi-automated instruments without temperature control which would benefit from having a robust cryostat that eliminates temperature as a variable in the specimen freezing process. This includes the original plungers designed by Dubochet and colleagues at European Molecular Biology Laboratory (EMBL),IIThe overall design of the cryostat system is shown in μm thick adhesion layer) and a final layer of gold (0.5 μm thick surface layer), to prevent oxidation, reduce the emissivity of the surface, and ensure the durability and easy cleaning of the cup. The sensor and heater connections are attached with a shielded cable to a small control box, which is used to both set and monitor the temperature of the cryostat.To measure the temperature of the ethane cup, a calibrated platinum resistor is located within the sidewall of the cup and is attached to the control electronics using a 4-wire probe configuration to improve the accuracy of the measurement . The heaC1, C2, C3 in The overall design of the control unit is diagrammed in The most important factor in achieving the level of temperature stability demonstrated below was the design of the cooling arms . IdeallyIIICooling the system is achieved by filling the outer container ring with liquid nitrogen, covering it with the lid, and waiting for the ethane to reach the desired temperature. This process can be sped up by repeatedly topping up the ethane cup and outer ring with nitrogen during cooling. A standard procedure for the use of the instrument is provided in the To test the temperature stability, the cryostat was cooled as described, filled with ethane, and the feedback controller was set to 93.0 K, which is the typical operating temperature for freezing grids. A calibrated K-type thermocouple probe was taken from liquid nitrogen at 77.4 K and placed in the centre of the liquid ethane. The temperature was recorded for 10 min and is shown in To ensure that the system is effective and practical for routine use, we froze numerous types of specimen >10), including pure water and aqueous solutions of protein complexes, DNA, RNA, and viruses on multiple types of specimen supports0, includFinally, we note that occasionally, a thin layer of opaque material collects on the surface of the liquid ethane during use. These are contaminants  which can end up on the surface of the frozen specimen and interfere with imaging. The precise control of the ethane temperature, afforded by this device, allows one to detect the presence of these contaminants and remove them. Without temperature control, the solid contaminants can easily be confused with frozen ethane, making them difficult to detect and eliminate.IVPrecisely controlling the freezing temperature eliminates one variable from the cryo-EM specimen preparation process, thus reducing the difficulty and improving the reproducibility of making high-quality specimens for high-resolution imaging. Further, it obviates the need for mixtures of ethane and propane or repeated manual heating of the cryogen during cryo-EM specimen vitrification. The cryostat design delineated herein uses simple yet robust principles of feedback control and can be adapted to the design of cryostats in other applications.See the Supp Info


Zero velocity update (ZUPT) plays an important role in pedestrian navigation algorithms with the premise that the zero velocity interval (ZVI) should be detected accurately and effectively. A novel adaptive ZVI detection algorithm based on a smoothed pseudo Wigner–Ville distribution to remove multiple frequencies intelligently (SPWVD-RMFI) is proposed in this paper. The novel algorithm adopts the SPWVD-RMFI method to extract the pedestrian gait frequency and to calculate the optimal ZVI detection threshold in real time by establishing the function relationships between the thresholds and the gait frequency; then, the adaptive adjustment of thresholds with gait frequency is realized and improves the ZVI detection precision. To put it into practice, a ZVI detection experiment is carried out; the result shows that compared with the traditional fixed threshold ZVI detection method, the adaptive ZVI detection algorithm can effectively reduce the false and missed detection rate of ZVI; this indicates that the novel algorithm has high detection precision and good robustness. Furthermore, pedestrian trajectory positioning experiments at different walking speeds are carried out to evaluate the influence of the novel algorithm on positioning precision. The results show that the ZVI detected by the adaptive ZVI detection algorithm for pedestrian trajectory calculation can achieve better performance. Pedestrian navigation, having received more and more attention from researchers in recent years, is an important branch in the field of navigation. PNS can help personnel in missions to identify their positions in real time and to get in touch with the command center; thus the safety of the emergency rescue personnel can be greatly guaranteed in an unknown environment. In addition, in places such as an airport, theatre, underground parking, other large public places and modern cities with tall buildings, it is necessary for pedestrians to identify their positions and find targets.At present, technologies suitable for pedestrian navigation can be divided into positioning technology based on the Global Navigation Satellite System (GNSS), positioning technology based on the radio frequency (RF) signal, as well as positioning technology based on self-contained sensors. The first kind is relatively mature, but the positioning accuracy is affected in indoor environments or outdoor environments with tall buildings and trees. The PNS based on the RF signal During pedestrian’s walking process, there is a period  is defined as north-east-down, which is consistent with the local geographic coordinate system. In general, the motion range of the pedestrian is relatively small, so the real-time position and trajectory will be shown in the tangential frame in this paper. After collecting the IMU output data, the angular rate can be used to update the attitude matrix and calculate the attitude angle. On this basis, transforming the specific force measured in the body coordinate system (b-frame) to the navigation coordinate frame and removing the harmful acceleration, then the speed information can be obtained by integrating the acceleration once, and the position information can be obtained by integrating the acceleration again. The basic equations of the strapdown inertial navigation system (SINS) can be expressed as follows:n-frame and b-frame, b-frame to the n-frame, b-frame with respect to the n-frame; n-frame with respect to the Earth frame; and The strapdown inertial navigation algorithm of PNS is similar to the traditional strapdown inertial navigation algorithm. The navigation calculation process mainly includes attitude update, velocity update and position update. The navigation coordinate system  [The analysis in m (STFT)  and Wignm (STFT) , can obtm (STFT) . The SPWBecause the sensor output is discrete rather than continuous, the continuous time signal y axis gyroscope output data during the walking process, the time domain waveform of the data is shown in y axis gyroscope output is shown in y axis gyroscope output.Collecting a group of y axis gyroscope output. y axis gyroscope output. The color enclosing lines represent the signal amplitude at the corresponding time and frequency, and the same color enclosing lines represent the distribution of the frequency with the same signal amplitude. It is very clear that the time-frequency spectrum contains multi-peak spectral lines and that the maximum signal amplitude appears within the range of 1.3–1.55 Hz. Hence, if directly extracting the ridge line of the spectrum to obtain the time-frequency information, all of the multiple frequency constituents are interference items, which will make it difficult to identify the gait frequency. In addition, Furthermore, the SPWVD was used to extract the time-frequency information of the y axis gyroscope output. Among those frequency ranges, the frequency doubling has the highest energy intensity, and the gait frequency has the second highest energy intensity. In addition, multi-peaks may appear in all of the multiple frequency ranges. Therefore, the pedestrian gait frequency (1)y axis gyroscope output.Using the SPWVD to extract the time-frequency spectral line of the (2)Extract the frequency (3)Extract the frequency (4)Analyze other time-frequency spectral lines in (1) according to Steps (2)–(3); then, the gait frequency In order to accurately identify the pedestrian gait frequency and effectively filter the multiple frequency constituents, this paper puts forward a time-frequency information extraction method based on SPWVD-RMFI, whose principle diagram is shown in According to the above description, the principle of the time-frequency extraction method based on SPWVD-RMFI can be shown by the flow chart in During the walking process, the SPWVD-RMFI method proposed in this paper can extract the gait frequency correctly, which provides the foundation for the thresholds’ selection in the adaptive ZVI detection algorithm.On the basis of the gait frequency obtained by the SPWVD-RMFI method in x axis, y axis and z axis at time Define According to the fact that the sensor output in the ZVI is approximate to a constant, the ZVI in the human gait can be extracted by setting thresholds to Equations (10) and (11). The detail is shown in the following equation:When the judgment conditions in Equation (12) are fulfilled at the same time, we consider the pedestrian’s walking speed at The amount of experiments on different gait frequencies have been done to obtain the relationships between the thresholds  and a fast speed (116 steps/min); then, with the traditional fixed threshold method, the ZVI in the pedestrian gait was detected. The upper part of Meanwhile, adopting the adaptive ZVI detection algorithm to detect the ZVI in the pedestrian gait, the results are shown in In order to further compare the ZVI detection performance between the adaptive ZVI detection algorithm and the traditional fixed threshold method, the experimenter walked 200 steps  at the speeds of 80 steps/min, 100 steps/min and 120 steps/min, respectively. The data in Therefore, the design and implementation of the adaptive ZVI detection algorithm enhances the accuracy of ZVI detection at different walking speeds, which further improves the positioning effect of PNS and makes it have better robustness and stronger practical application.Furthermore, pedestrian trajectory positioning experiments at different walking speeds were carried out to assess the influence of the novel adaptive ZVI detection algorithm on positioning accuracy.z axis has a better effect on sensing the foot movement and that the amplitude of the acceleration changes greatly; the gyroscope in the y axis has an obvious perception of foot rotation, and the amplitude of the angular rate changes greatly. In addition, it can also be found from The pedestrian trajectory positioning experiment was carried out on a 49 m-wide and 13.9 m-long rectangular route on campus. Facing north, the experimenter started and walked a loop along the route at “slow-normal-fast-slow-normal-fast-slow” speed alternately and finally returned to the start point. The total walking distance was 125.8 m, and the total walking time was 119.6 s. The raw data output by the accelerometers and gyroscopes during the walking process are shown in y axis gyroscope output, showing that the amplitude and the cycle of the angular rate change with the walking speed, which matches the “slow-normal-fast-slow-normal-fast-slow” speed changing characteristic. The middle part of By adopting the adaptive ZVI detection algorithm to analyze the IMU output during the walking process, the detection results of the gait frequency and ZVI are provided in Then, using the ZUPT-aided pedestrian navigation algorithm to calculate the pedestrian trajectory. The results are shown in We also conducted the pedestrian trajectory positioning experiment on a longer path, as shown in This paper designs a novel adaptive ZVI detection algorithm based on SPWVD-RMFI for the PNS with self-contained sensors. The novel algorithm can extract the pedestrian’s gait frequency during walking in real time. With the establishment of the function relationships between ZVI detection thresholds and gait frequency, the problem of setting the thresholds adaptively for ZVI detection at different walking speeds is solved, which realizes the accurate detection of ZVI. Compared with the traditional fixed threshold method, the novel algorithm has better robustness and higher detection precision of ZVI. At the same time, the results of ZVI detection contrast experiments and pedestrian trajectory positioning experiments at different walking speeds show that the novel algorithm can effectively suppress the false and missed detections existing in the traditional fixed threshold method. Meanwhile, the ZVI detected by the adaptive ZVI detection algorithm for pedestrian trajectory calculation has better performance. In addition, the SPWVD-RMFI algorithm presented in this paper can also be applied to the motion frequency detection of human health monitoring and the step length estimation of PNS based on the pedestrian dead reckoning algorithm.In a future study, we will pay close attention to the problem of heading correction for PNS. By adopting the adaptive ZVI detection algorithm proposed in this paper for ZUPT and combing the heading correction algorithm, the positioning accuracy of the PNS can be further improved.


Due to a number of methodological advantages and theoretical considerations, more and more studies in clinical psychology research employ the Experience Sampling Method (ESM) as a data collection technique. Despite this growing interest, the absence of methodological guidelines related to the use of ESM has resulted in a large heterogeneity of designs while the potential effects of the design itself on the response behavior of the participants remain unknown. The objectives of this systematic review are to investigate the associations between the design characteristics and the data quality and feasibility of studies relying on ESM in severe psychiatric disorders.We will search for all published studies using ambulatory assessment with patients suffering from major depressive disorder, bipolar disorder, and psychotic disorder or individuals at high risk for these disorders. Electronic database searches will be performed in PubMed and Web of Science with no restriction on the publication date. Two reviewers will independently screen original studies in a title/abstract phase and a full-text phase based on the inclusion criteria. The information related to the design and sample characteristics, data quality, and feasibility will be extracted. We will provide results in terms of a descriptive synthesis, and when applicable, a meta-analysis of the findings will be conducted.Our results will attempt to highlight how the feasibility and data quality of ambulatory assessment might be related to the methodological characteristics of the study designs in severe psychiatric disorders. We will discuss these associations in different subsamples if sufficient data are available and will examine limitations in the reporting of the methods of ambulatory studies in the current literature.CRD42017060322) and is available in full on the University of York website (http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42017060322).The protocol for this systematic review was registered on PROSPERO (PROSPERO 2017:The online version of this article (10.1186/s13643-018-0673-1) contains supplementary material, which is available to authorized users. Several reasons can explain the growing interest of clinical research in ambulatory assessment methods. Patients are generally poor in providing accurate, global, retrospective reflections of real-life experiences and behaviors, which is especially problematic for depressed patients who suffer from cognitive impairment  and for Despite the rapid increase of the use of momentary assessment methods in clinical psychology and psychiatric research, methodological challenges related to the use of such methods remain. In particular, as this method repeatedly prompts individuals to rate their current affective and cognitive state in the context of their daily life, it is plausible that the repetition of self-evaluations induces reactivity . A number of studies have reported reactive effects to the repeated assessments in several populations including healthy participants , 16 and Our objective is to investigate protocol- and subject-related factors that could undermine the feasibility of ambulatory studies and the quality of the data collected through this methodological framework in psychotic disorder (PD), major depressive disorder (MDD), bipolar disorder (BD), and high-risk individuals for these disorders (HR).This protocol is based on the PRISMA-P  guidelines . For traA systematic literature search will be performed without publication time limit in PubMed and Web of Science. Observational as well as randomized controlled studies will be included. Case studies, case reports, protocols, study designs, and systematic reviews will not be considered. The search strategy was designed to include relevant terms regarding ambulatory and momentary assessments  as well as terms related to the clinical diagnosis of the participants under study . The search strategy will use either MeSH or keyword heading. A concept plan was built with the identified keywords and descriptors to run the search [see Additional file Only studies using ESM/EMA designs in PD, MDD, BD, and HR will be included in this systematic review. If available within the included studies, data from non-psychopathological/healthy control groups (HC) will be considered and will serve as a reference group. Ambulatory studies involving only a single daily assessment will be excluded as this time sampling is not representative of the repeated momentary assessment that defines ESM research. To determine the eligibility of the original studies, two researchers (HV and AR) will independently conduct the screening of the studies in the title/abstract and full-text phases based on the inclusion and exclusion criteria. The screening results will be compared in order to identify any discrepancies. In case of a disagreement, a third researcher (IMG) will be consulted. We will use the PRISMA flow diagram to report quantitative and qualitative information on every phase of the selection process.When available, data will be extracted for the following items: (i) general study characteristics ; (ii) sample characteristics ; (iii) ambulatory design characteristics ; and (iv) the attrition rate  and the compliance rate  of the included studies. When needed, the corresponding authors of the original studies will be contacted for further information. Data from the included studies will be extracted and stored in a customized spreadsheet structured according to the items mentioned above and that will be provided as part of the supplementary materials in the upcoming systematic review.The current systematic review does not investigate the main outcomes of the studies that will be included. As such, the conventional assessment of methodological quality is not directly applicable. Instead, the quality of the reporting of the attrition and compliance rates in the included studies will be assessed independently by HV and AR. The scale and the scoring developed to perform this assessment will be derived from the four-point item of the Grades of Recommendation, Assessment, Development, and Evaluation Working Group  to fit tStudies providing sufficient data regarding the main outcomes  will be analyzed. If data are not amendable to a statistical analysis, a qualitative synthesis of the main outcomes under study will be conducted. If a sufficient amount of commensurable data is available, a quantitative synthesis  will be performed.pij denotes the proportion of completed evaluations for the jth participant in the ith study and ni the group size). We expect either xi denotes the total number of self-evaluations collected and mi the theoretical maximal number of self-evaluations allowed by the design).For attrition, we will analyze the reported/calculated proportions. For compliance, there is in principle a proportion  per participant, but this information is unlikely to be available. Instead, we will analyze the mean proportions  2015 checklist: recommended items to address in a systematic review protocol. (DOC 55 kb)Additional file 2:Concept plan of the search strategy. (DOCX 12 kb)


As a sedentary lifestyle leads to numerous health problems, it is important to keep constant motivation for a more active lifestyle. A large majority of the worldwide population, such as office workers, long journey vehicle drivers and wheelchair users, spends several hours every day in sedentary activities. The postures that sedentary lifestyle users assume during daily activities hide valuable information that can reveal their wellness and general health condition. Aiming at mining such underlying information, we developed a cushion-based system to assess their activity levels and recognize the activity from the information hidden in sitting postures. By placing the smart cushion on the chair, we can monitor users’ postures and body swings, using the sensors deployed in the cushion. Specifically, we construct a body posture analysis model to recognize sitting behaviors. In addition, we provided a smart cushion that effectively combine pressure and inertial sensors. Finally, we propose a method to assess the activity levels based on the evaluation of the activity assessment index (AAI) in time sliding windows. Activity level assessment can be used to provide statistical results in a defined period and deliver recommendation exercise to the users. For practical implications and actual significance of results, we selected wheelchair users among the participants to our experiments. Features in terms of standard deviation and approximate entropy were compared to recognize the activities and activity levels. The results showed that, using the novel designed smart cushion and the standard deviation features, we are able to achieve an accuracy of (>89%) for activity recognition and (>98%) for activity level recognition. Since sedentary behavior may cause diverse and severe health and wellness problems, adequate moderate or vigorous activity can reduce the incidence of chronic diseases, non-communicable disease and obesity. A large majority of worldwide population, such as office workers, long journey vehicle drivers, and wheelchair users spends several hours every day in sedentary activities. Many of our daily life tasks such as desk work, watching TV, eating, or commuting to work, lead us to engage in prolonged sitting activities. Therefore, monitoring sitting physical activity and assessing physical activity level is important, and can better instruct the user to engage in an active lifestyle.In the context of Body Area Networks (BANs) , multi sTo investigate the activity level of people with sedentary lifestyle, we developed a smart cushion that is able to monitor sitting postures non invasively. Activity can be recognized and activity levels can be quantified so to provide users with reminders to exercise or take a break and therefore to minimize the health risk as well as to give the users timely necessary interventions.a novel Body Posture Analysis Model (BPAM), proposed to analyze the sitting behavior;a novel smart cushion, with an integrated embedded unit that better combines pressure and inertial sensors;a method of activity level assessment, proposed to recognize activities and activity levels.Our aim is to develop an effective method to achieve high accuracy for continuous activity level assessment for long-term sitting users. The main contributions of the paper are the following:The remainder of the paper is organized as follows: Posture/activity recognition detection has been a hot topic in many research areas, such as pervasive and mobile computing, context-aware computing, and ambient assisted living. The information hidden behind the posture/activity is also very meaningful to reflect the user’s health status. As pressure sensor based smart cushion is unobtrusive, several related works adopted it to recognize physical activity , to measMany studies on activity level assessment are based on accelerometers placed on the user body or use internal sensors of the smartphone. Other studies fuse heterogeneous sensor data, such as motion data from accelerometers and gyroscopes with physiological data such as electrocardiography (ECG), and electromyography (EMG). We classify the related literature in two main approaches: single sensor-based methods and multi sensor fusion methods.activity effective index is used to analyze exercise performance based on pattern recognition in the activity effective analysis stage.Liu et al.  presenteGrillon et al.  proposedDuring sitting conditions, the trunk, pelvis and thigh are mostly determinant of the posture. Mork et al.  investigAs cushion based posture recognition system is noninvasive and easy to implement, many researchers choose this technology to recognize the postures/activities. There exist two main production technologies of smart cushions for motion detection: the first one is based on a pressure sensor array such as e-textile, whereas the second one relies on the use of fewer individual sensors deployed on the seat or backrest. Compared with using sensor arrays, recent research focused on using fewer, independent sensors with advantage of low cost and easier marketing promotion.Yu et al.  proposedTo better summarize the related work on cushion based systems, in Smart cushion based systems are noninvasive and can uncover valuable knowledge from the postures. To the best of our knowledge, a smart cushion with an integrated unit to better fuse accelerometer and pressure sensors signal has never been proposed before. In the following, we will discuss our novel smart cushion and the analysis method adopted in our activity level assessment system.In the following paragraphs, we describe the body posture analysis model of sitting behavior, explain our novel smart cushion and the deployment schema of the sensors on a real chair.x axis, left-right as the y axis, and up-down as the z axis. The x axis reflects the body swing from anterior-posterior direction, and the y axis reflects the body swing from medial-lateral direction. The variation of rotation angles velocity can better provide the extent of body swing.Based on former studies ,23,24,25Two types of sensors are used in our cushion: six pressure sensors and a 9-axis inertial measurement unit. The deployment of the sensors on the cushion is shown in it is one integration unit that better combine the pressure sensors and accelerometer;it is easy to deploy, since all the sensors were deployed on the cushion seat;it is noninvasive, with the facility to monitor the sitting postures and activities.Compared with the previous research on smart cushion design that use pressure sensors and accelerometers ,28,33 asWith respect to our former research ,35, we dThe displacement of the Center of Pressure (CoP) can assess postural stability in the field of biomechanics . The CoPO, and each As in And then the CoP value for the two axis can be calculated as follows:MPU9250 is a 9-DoF IMU , placed The circuit board of the smart cushion is shown Micro Controller Unit (MCU), to process the sensor data using Arduino Pro Mini ;Bluetooth communication unit, to send the processed results to remote devices ;Vibration Motor, controlled by the MCU, is used to alarm the users;Power supply circuit, to provide the power to the circuit board.On the left-top of the circuit board is located the control circuit unit, that is composed of the following components:Using the smart cushion described in the former paragraph, we can assess activity levels of users sitting on the chair. The system architecture is shown in t, we can get the raw data vector Using the smart cushion, we are able to collect the time series of sampled data. Instance vectors are generated from the pressure sensors and IMU. In order to capture small movements of body, data was collected at a frequency of 10 Hz. After the wave filtering period, at the time Using the raw data collected as described in Standard deviation is a measure that is used to quantify the amount of variation or dispersion of a set of data values. A low standard deviation indicates that the data points tend to be close to the mean  of the set, while a high standard deviation indicates that the data points are spread out over a wider range of values. Using Matlab, we can easily calculate the standard deviation value. The feature vector can be represented as y Pincus  and it im an integer representing the length of compared run of data, we form a sequence of m-dimensional vectors i, r , then N can be calculated as r is 0.2 multiplied by the standard deviation of the data samples in a time slide window; it is called tolerance threshold for accepting similar patterns between the neighboring segments , all of them are in healthy status and with no limb injury. They can stand a little, but most of the time they need a wheelchair to facilitate their moving demands. Their BMI is in the range of , whose distribution in our experiment sample is shown in During the experiment, they were free to choose the time period for the test session and they were asked to perform common activities on wheelchair among (1) Reading a book; (2) Desk working at a computer; (3) Having a conversation (in peace status); (4) Swing left-right or front-back; (5) Doing physical exercise such as lifting a weight. On average, experiment sessions lasted about 2 h and each participant had to perform 6 sessions over the two weeks. All the experiment sessions have been video recorded so to manually label the samples of each performed activity with one of the three defined activity levels.In order to test our designed cushion and system, we analyzed the data using WEKA data mining toolbox . A 10-fop-dimensional vector also known as a feature vector. Each node of the tree represents a decision ; at each node, J48 chooses the feature  of the data that most effectively splits its set of samples into distinct subsets according to the normalized information gain (NIG). In particular, the algorithm chooses the feature with the highest NIG to generate the decision node. The main parameters used to tune the classifier generation are the pruning confidence (C = 0.25) and the minimum number of instances per leaf (M = 2).J48 is a specific decision tree implementation of the well known C4.5 algorithm using the concept of information entropy. The classifier model is generated by a training procedure that uses a set of pre-classified samples. Each sample is a Using the experiment protocol described in It has been shown that small window size is effective to detect physical activity on devices with reduced resources . Howeverp) and the recall (r) of the test. p is the number of correct positive results divided by the number of all positive results, and r is the number of correct positive results divided by the number of positive results. F-measure can be interpreted as a weighted average of the precision and recall, where F-measure reaches its best value at 1 and worst at 0. Here we examine the F-measure value for the recognition of each kind of activity; results are reported in Referring to previous literature as shown in x-axis represents the number of samples. The y-axis represents the As the time slide window is set at 30 s and the sampling frequency is set to 10 Hz, each time slide window contains 300 raw data, with 50% overlap. To give an exemplification, the plots in As shown in The recognition results for each activity and activity level using 10-fold cross validation are depicted in As shown in As clearly shown in The recognition results achieved using only the pressure sensors unit are shown in Recognition results obtained using the novel designed cushion are shown in In As shown in As shown in Activity recognition and level assessment of people with sedentary lifestyle is very useful and can promote physical exercise and lead to more active life. In this paper, we proposed a method of activity classification and activity level assessment using a novel designed smart cushion. The cushion combines the pressure sensors and IMU better than previous systems. It is suitable for monitoring the sitting behavior in contexts such as workplace, car, or on the wheelchairs and can be easily implemented with low-cost embedded devices. Experiments on wheelchair users have been carried out; activity recognition and activity level assessment have been performed.Future works will be devoted to recognizing more kinds of sitting activity and to design a mechanism for a finer grained activity level assessment, also we will recruit more subjects and collect more data in order to provider a robust, reliable results. Furthermore, we will include the monitoring of other body parts such as upper and lower limb in order to provide a total body activity analysis model. Finally, we plan to investigate the integration of physiological sensor data ,48 to ge


Cardiac resynchronization therapy (CRT) is an effective treatment for heart failure (HF) patients with an electrical substrate pathology causing ventricular dyssynchrony. However 40–50% of patients do not respond to treatment. Cardiac modeling of the electrophysiology, electromechanics, and hemodynamics of the heart has been used to study mechanisms behind HF pathology and CRT response. Recently, multi-scale dyssynchronous HF models have been used to study optimal device settings and optimal lead locations, investigate the underlying cardiac pathophysiology, as well as investigate emerging technologies proposed to treat cardiac dyssynchrony. However the breadth of patient and experimental data required to create and parameterize these models and the computational resources required currently limits the use of these models to small patient numbers. In the future, once these technical challenges are overcome, biophysically based models of the heart have the potential to become a clinical tool to aid in the diagnosis and treatment of HF. Heart failure (HF) is a complex and varied disease which results from structural or functional abnormalities impairing the ability of the heart to pump blood and deliver sufficient oxygen to meet the body’s metabolic needs. Pathological remodeling occurs with the progression of HF and refers to the macroscale changes in the mass and shape of the heart as well as the microscale changes in the myocyte cellular structure and ionic channel distribution and density which detrimentally affect cardiac function over time. Conceptually “reverse remodeling” is the reversal of this progressive deterioration, and is indicated with surrogate markers such as a reduction in ventricular volume and mass, as well as improvements in the contractile function of the heart. Reverse remodeling has been shown to be correlated with better therapeutic outcomes for patients .Large clinical trials  have found cardiac resynchronization therapy (CRT) to be an effective treatment which possibly promotes reverse remodeling for patients with drug refractory mild to severe HF with prolonged QRS duration –4. ProloMulticenter studies have shown that CRT reduces mortality and morbidity and reduces HF hospitalizations . ClinicaThe goal of CRT is to stop or reverse the progression of HF by resynchronizing the electrical activation and mechanical contraction of the ventricles of the heart leading to a functional improvement in the pumping of blood throughout the circulatory system. Computer models can be used to simulate the electrical activity on the heart from the cellular level through to the tissue level (electrophysiology models), giving rise to contraction of the ventricles , as well as the pumping of the blood throughout the cardiac system (circulatory models).A schematic of how these models relate to each other is shown in Fig. The first electromechanical model investigating LBBB and CRT was based on a generic idealized shape of the heart . Though Myofiber orientation plays an important role in electrical and mechanical properties of cardiac tissue. The electrical activation in the heart spreads two- to sevenfold faster along the fiber rather than transverse to the fiber direction –23. FurtA large number of studies of heart biomechanics , 25–32 hCurrently, in vivo DT-MRI has been performed on healthy volunteers’ scans , 45 and The importance of scar in response to CRT has been consistently observed in clinical studies, where pacing within scar regions has a detrimental effect on the response to CRT . In addiIn the clinical setting, scar regions are typically segmented from contrast-enhanced cardiac MRI using signal intensity thresholding techniques. Typically, the ventricular wall is manually or automatically delineated and the signal intensity within the wall is used to define regions of scar. The most widely used methods are the full-width-half-max  and stanDifferent scar segmentation methods yield differences in scar size, shape, and distribution , which cAn outline of typical workflow for generating the anatomical models used in electrophysiology and electromechanical cardiac simulations is shown in Fig. Computer models need to reflect the changes in the electrical activation pattern that HF or CRT induces. In the typical clinical setting, electrical dyssynchrony in the heart is measured using 12-lead electrocardiograms (ECG). The duration and morphology of the QRS from the 12-lead ECG are used as guidelines for patient selection for CRT. However, the limitation of this widely used clinical tool is that the small number of leads recording at a distance from the heart may not fully capture the electrical activation of the heart. In computer models, the QRS duration is often used as a surrogate for time taken for the electrical activation to pass through the ventricles to parameterize the conduction velocity , 57–59.A more comprehensive picture of the electrical activation across the torso can be achieved with non-invasive body surface potential mapping (BSPM). BSPM captures many more ECGs across the torso via a multi-electrode vest . Though the diagnostic value of BSPM can be larger than that of 12-lead ECG , 61, theComputer models also need to reflect the functional changes in the heart due to LBBB and CRT response. Non-invasive imaging (Cine MRI or echocardiography) can capture the deformation of the heart throughout the cardiac cycle. Clinical measures such as LV volume transient , end-diastolic volume, end-systolic volume, ejection fraction , LV mass, and LV motion dyssynchrony indices can be derived from these images. Wall motion measurements from tagged MRI can be used to validate deformations predicted by the model , 64.Pressure measurements can be both invasive  or non-invasive . The pressure and/or volume transients are used to adapt the geometry parameters (in the circulatory models –66) and In the section “Modeling Geometry,” we described a typical workflow to generate geometrical models of the heart based on patient-specific anatomy. Such patient-specific anatomical models may be combined with electrophysiological models to simulate activation sequences and study a patient’s electrical response to CRT. To accurately simulate a patient’s activation sequence, model parameters must be fitted to electrical measurements, such as ECG, EAM, and BSPM, and validated. A typical workflow for electrophysiology personalization is shown in Fig. The monodomain and bidomain models belong to the class of multi-scale models of cardiac electrophysiology. Both models describe electrical activity at the cellular scale, where action potentials are generated, and at the tissue scale, where action potentials propagate from one cell to another. While the Monodomain model only describes propagation in the intracellular space, the Bidomain model also includes the extracellular domain. The Bidomain model is the more complete electrophysiology model of the two and as such, also more computationally expensive. Thus, most CRT studies employ the Monodomain model , 58, 67.Although the monodomain model is computationally cheaper than the bidomain model, solving the monodomain model still requires significant computational effort to resolve the steep wave-front of activation. To overcome this limitation, the Eikonal model has also been used in CRT modeling studies  to simulWith a similar goal, cellular automaton models  have alsA type of surface source model called the Equivalent Dipole Layer model, which computes body surface potentials from the transmembrane potential on the myocardial surface (source) based on the Bidomain formulation , 75, hasAt the organ scale, the cardiac bioelectric behavior is controlled by a cardiac conduction system. In the ventricles, this system is typically referred to as the Purkinje system (PS), and is composed of the bundle of His, the left and right bundle branches, and an extensive Purkinje network, which connects to the myocardium at the Purkinje-ventricular junctions. Propagation in the PS is two to three times faster than in the myocardium, allowing fast distribution of impulses over the endocardium and ensuring ventricular synchrony. Thus, when modeling the activation sequence at the organ scale, it is important to include the PS properties into the model, as it significantly affects the activation pattern in the heart.In CRT models of realistic ventricular anatomy, the PS has been modeled as a tree of one-dimensional elements coupled to the myocardium , 68 or aA similar approach was used to investigate the role of electrical conduction in the PS during CRT pacing in failing hearts . MotivatComputer models have been used to study the effect of CRT on electrical activation in the presence of the ECG characteristic of LBBB , which cElectrophysiology simulations have also been used to optimize lead location, AVD, and VVD during CRT. These models offer the opportunity to carry out non-invasive, automatic optimization of CRT in silico. Briefly, the approach consists of simulating electrical activation in a realistic BiV anatomy for different AVD and VVD as well as several different lead locations and minimizing the error between the obtained activation sequences for each case against a simulated physiological case to determine which combination of AVD, VVD, and lead location yields the best acute response to CRT –73, 81. Although computer models have been useful to simulate complex electrophysiological properties during CRT, tuning these models to accurately simulate a patient’s ventricular electrophysiology is challenging due to the high number of parameters involved. Therefore, Sanchez et al.  investigThe ECGSIM approach was used by van Huysduynen et al. . ECGSIM Dyssynchrony in the electrical activation of the heart naturally leads to mechanical dyssynchrony in the heart. However, clinical studies have shown that resolving the electrical dyssynchrony does not necessarily improve the mechanical dyssynchrony –85. For To model the substantial deformation that the heart undergoes throughout the cardiac cycle, three components are required: a constitutive law for passive material properties of the myocardium, an active contraction model to represent active tension generation along myofibers, and a coupling method between the electrophysiology simulation and the mechanics simulation.Passive material properties of the myocardium can be modeled using anisotropic , hyperelastic (or viscoelastic) constitutive equations –89, or m2+ signal that activates the sarcomeres, causing tension generation and contraction of the myocyte, which at the organ scale translates into pumping of blood in the heart. However, the mechanical contraction of heart can also effect the electrophysiology of the cardiac cells through mechano-electric feedback (MEF) [The electrical activity throughout the myocardium leads to the mechanical contraction and relaxation of the heart through excitation-contraction coupling (ECC) . On a ceck (MEF) , such asck (MEF) , 95 to cphenomenological coupling [weakly coupled models [strongly coupled models which take into account the MEF [Active tension generated along myofibers as a consequence of cellular excitation during systole is included in the mechanics model as an additional tension component in the fiber direction. There are three ways to model ECC in electromechanics models. The majority of electromechanical models of the heart have focused on coupling , 96 by md models , 98 by m the MEF , 100.weakly coupled models, due to the large computational costs of implementing strongly coupled electromechanical models. In personalized models, parameters defining the active tension transient are fitted to match available clinical measurements for cardiac deformation during systole such as systolic pressure, volume transients, or cardiac motion from cine-MRI. The simulated mechanical deformation of the heart models can then be further analyzed to determine mechanical and hemodynamic response outcomes.To date, computer models investigating CRT have done so with phenomenological and Most of the cardiac models studying LBBB and CRT response have neglected the longer-terms effect of pathological remodeling and reverse remodeling associated with the two states. Incorporation of growth models allows for simulations of the dynamic anatomical changes in the heart with the progression of LBBB or CRT response. In , the effElectromechanical models of the failing heart have been used to investigate optimizing the acute CRT response. One strategy for optimizing CRT is to maximize the acute hemodynamic response (AHR), given as the maximal rate of systolic left ventricular pressure rise , 104. HoIn recent studies, patient-specific biomechanical models developed from extensive and rich clinical data were used to predict the acute hemodynamic effects of pacing protocols , 30, 105The location of the LV pacing lead has been shown to have an effect on CRT response , 109, anOptimizing the device settings (AVD/VVD) has been shown to improve the acute functional response, such as AHR and EF, to CRT in the clinical setting –117. In In addition to using models to optimize CRT response to existing treatment methods, computer models of the heart have also been used to evaluate emerging technologies for delivering pacing to the heart . ConventElectromechanical models looking at optimizing the AV delay settings are ventricular models of the heart, neglecting the atria , 105. InMost published electromechanical models predicting CRT response have used the AHR as an outcome measure. Clinical studies have shown poor reproducibility of AHR due to biological variability, especially when only measured once . In 131131, it wThe predictability of AHR with regards to long-term therapeutic response is still controversial, with some studies finding no correlation to chronic remodeling   and otheVentricular models have tended to focus on the simulation of a single beat with boundary conditions being represented by Windkessel models. Contraction models connected to the circulatory models , 137 havThe multi-scale approach of three-dimensional computational electromechanics models offers a highly detailed simulation of microscopic and macroscopic phenomena. However, clinical translation is limited by the large computational efforts required to solve the model, especially when dealing with electromechanical coupling. High computational costs also restrict the simulation to cardiac chambers and often the simulation of a single beat, even though ventricular filling from the pulmonary and systemic venous systems through the atria and resistance to ejection through the aorta and pulmonary artery are likely to play a role in CRT response and optimization.An alternative model strategy is to discard or significantly reduce the representation of the patient anatomy and employ a zero-dimensional or reduced dimensional approach. This dimensionality reduction allows for much faster simulations , therefore allowing additional components to be included in the model, such as the systemic and the pulmonary circulation, and to simulate the circulatory system as a closed loop over multiple beats –141.The increased speed of these simulations does have limitations. Lumped-parameter models, together with the loss of spatial information, require additional parameters for the circulatory system that need to be estimated. This issue has been partially addressed by Arts et al. with the CircAdapt model . Figure Despite its high degree of flexibility, the original CircAdapt model is unable to account for intraventricular interaction, which plays an important role in HF and CRT, as the pump function of one ventricle is directly affected by the function of the other –145. TheIn a further refinement to provide information about local deformation, the TriSeg model was further extended in the MultiPatch model . The thrThe CircAdapt model and its extensions described so far simulate macroscopic adaptation of cardiac chambers, with a limited representation of microscopic dynamics. When dealing with HF and CRT, the understanding of microscopic compensatory mechanisms may be important. The modular structure of CircAdapt makes it relatively easy to couple it with models for microscopic electrical activation and sarcomere contraction . By coupIn summary, the CircAdapt model constitutes a valuable alternative to computationally intense three-dimensional models. Its modular structure makes CircAdapt easy to couple with more detailed frameworks for the dynamics of interest needed to address a specific clinical problem. The TriSeg and the MultiPatch model as extensions of CircAdapt partially overcome the lack of local information about electrical activation and mechanical deformation in ventricular walls, making these frameworks more suitable for LBBB and CRT simulations. The efficient simulations offered by CircAdapt also lead to a fast clinical translation compared to three-dimensional models for cardiac electromechanics. In future work, the coupling of these two modeling frameworks could prove invaluable in modeling changes in LBBB and reverse remodeling due to CRT in HF patients.In this review, we have discussed cardiac computer models used to investigate cardiac dysfunction, especially focusing on LBBB and CRT. Electrophysiology, electromechanical, and circulatory models have been used to identify the optimal pacing location and intracardiac timings to improve response to CRT, investigate the cardiac substrate  to provide insight into the pathologies in the heart that cause the electrical and mechanical dyssynchrony in LBBB and the response due to CRT, as well as to study new technologies such as multisite pacing or endocardial LV pacing.The electromechanical models discussed in this review require extensive clinical information, oftentimes including invasive measurements. Future work requires the development of pipelines that allow for the autogeneration of models and parameters from non-invasive data, as well as methods to reduce the computational costs or improvements in the parallel scalability of the simulations.Patient-specific models for CRT are often very complex with many free parameters. At the same time the large patient variability in the CRT patient populations motivates personalizing model parameters to each individual patient. However, efficiently and uniquely constraining model parameters remains a significant challenge in model creation. The inability to uniquely constrain parameters using available clinical data will in some cases limit the predictive ability of the model. However, in biological systems, not all parameters will have equal impact on all model predictions , allowinThis is especially true in light of the heterogeneous patient population within a standard CRT cohort, where questions remain unanswered regarding the accuracy and reliability of model predictions. The uncertainties inherent in the models due to reliability and robustness of data measurements (such as AHR) and modeling assumptions need to be addressed upfront when presenting biophysical models of the heart to clinicians. Computational modeling offer an additional tool to make clinical decisions; however, diagnostic and treatment decisions based on model simulations need to be made with the full knowledge of the errors and confidence in the models.The current state of the computational modeling of LBBB and CRT patients rely on expertise in image processing, numerical analysis, mesh generation, and cardiac electrophysiology, mechanics and circulatory response which presents another barrier to clinical translation. The development of user-friendly tools that allow the non-expert model to model the electrical, functional, and anatomical response of the patient to CRT within a clinically useful timeframe remains a challenge for the community. The development of these tools requires close collaboration and feedback from clinical stakeholders.To date, clinical translation of biophysical tools to model dyssynchrony and CRT response remain out of reach with current frameworks for creating and parameterizing patient-specific models requiring (1) substantial amount of information and (2) large amount of computational resources to simulate a single heartbeat. In addition, the robustness and accuracy of the measurements as well as the resulting model simulations/predictions need to be demonstrated.Once these challenges have been met, dyssynchronous heart models can be used to: examine interventions in-silico; aid in clinical decisions of disease prognosis and prospective treatment plans; predict the long-term response to CRT for further classification of patients who would/would not benefit from CRT, thus reducing the need for unnecessary procedures impacting the health of patients; as well as provide a testing ground for emerging technologies.


It has been suggested that a transition between a pelycosaurian-grade synapsid dominated fauna of the Cisuralian (early Permian) and the therapsid dominated fauna of the Guadalupian (middle Permian) was accompanied by, and possibly driven by, a mass extinction dubbed Olson’s Extinction. However, this interpretation of the record has recently been criticised as being a result of inappropriate time-binning strategies: calculating species richness within international stages or substages combines extinctions occurring throughout the late Kungurian stage into a single event. To address this criticism, I examine the best record available for the time of the extinction, the tetrapod-bearing formations of Texas, at a finer stratigraphic scale than those previously employed. Species richness is calculated using four different time-binning schemes: the traditional Land Vertebrate Faunachrons (LVFs); a re-definition of the LVFs using constrained cluster analysis; individual formations treated as time bins; and a stochastic approach assigning specimens to half-million-year bins. Diversity is calculated at the genus and species level, both with and without subsampling, and extinction rates are also inferred. Under all time-binning schemes, both at the genus and species level, a substantial drop in diversity occurs during the Redtankian LVF. Extinction rates are raised above background rates throughout this time, but the biggest peak occurs in the Choza Formation (uppermost Redtankian), coinciding with the disappearance from the fossil record of several of amphibian clades. This study, carried out at a finer stratigraphic scale than previous examinations, indicates that Olson’s Extinction is not an artefact of the method used to bin data by time in previous analyses. A faunal turnover of tetrapods has long been recognised between the Cisuralian and Guadalupian . The former is characterised by a diverse array of amphibians, pelycosaurian-grade synapsids (particularly carnivorous sphenacodontids and herbivorous edaphosaurids), and captorhinids, whereas the latter is dominated by therapsid synapsids, with increased diversity of parareptiles and amphibian diversity substantially reduced . These fThe possibility of a mass extinction accompanying this transition was first suggested by The hypothesis of Sahney & Benton has been criticised as being based on family-level data that was not corrected for sampling heterogeneity . NeverthDespite this, the theory of Olson’s Extinction has been criticised in other ways. Further criticism of Olson’s Extinction was put forward by Macroleter, previously only known from the Middle Permian of Russia, caused Second, It is not the purpose of this paper to argue against these two criticisms of The “best section” of tetrapods in the Cisuralian is doubtless that of Texas, which represents a reasonably continuous sequence from the late Carboniferous until the end of the Cisuralian . A detaihttp://fossilworks.org) on October 2017, were the principal sources, but were supplemented by observation of specimens in museum collections and also by data sent from some museums . Specimens of uncertain provenance were not included. The data was examined at both species and genus level. While it has often been the preference to examine data at the species-level, Data on the number of specimens of tetrapod species in each time bin was assembled from a variety of sources. The primary literature and the paleobiology database, downloaded from the fossilworks website : the biostratigraphic bins based on the first and last appearances of key tetrapod genera . As thesThe second binning scheme used represents a redefinition of the land vertebrate faunochrons using a clustering approach. CONISS is a constrained clustering analysis, which groups stratigraphic sections into hierarchical clusters based on the taxonomic distances between, while maintaining the order of the stratigraphic sequence . The taxThe third binning scheme simply treats each formation as a time bin. The lithostratigraphy was devised by The fourth and final binning scheme uses a stochastic approach, in an attempt to address the time averaging that occurs when coarse time bins covering several million years are employed. The ages of the top and bottom of each formation were used as maximum and minimum bounds on the ages of each specimen known from within that formation. The period of time under study was split into half-million-year time bins, and each specimen was assigned at random to one of the bins between its maximum and minimum age brackets. One hundred such datasets were generated, and the analyses of diversity and extinction rate were applied to all 100. Such stochastic methods have been shown to provide more accurate estimates of standing diversity than binning approaches, even when the origination and extinction are biased towards coinciding with the boundaries of bins .For all four binning schemes, the absolute ages were derived from http://bio.mq.edu.au/j˜alroy/SQS.html). The stochastic binning method allows the implementation of the more precise and accurate methods of calculating extinction rates using the gap fillers method  estimates were calculated using two methods. The first is a taxic diversity estimate, a simple count of the number of species observed in each time bin without sampling correction. The second employs shareholder quorum subsampling SQS; , which ss method . Since ts method  to incres method . This waWhen clustering the formations using CONISS, a number of changes are made to the boundaries of the LVFs . The LitIt is worth clarifying here that this analysis is not intended to cast doubt on the LVFs as originally defined; rather, they represent a biostratigraphic scheme more specific to the Texas section. The changes to the Coyotean LVF are most likely due to this being primarily defined by taxa from the well sampled early Cisuralian localities in New Mexico , which aRaw, uncorrected species and genus-level diversity estimates indicate a substantial fall in diversity between the Redtankian and Littlecrotonian, based on all four time-binning schemes . The finWhen the data are binned by the Land Vertebrate Faunachrons , subsampling by SQS supports the Littlecrotonian as the time of lowest diversity  and 4. TThe higher-resolution-binning schemes both indicate the drop in subsampled diversity occurs throughout the Redtankain  and 6. TThree peaks in extinction rate are identified at the both at the genus and species level: at the top of the Belle Plains, Arroyo and Choza formations (the latter being the largest) . During Peaks in origination rates at the species level are observed at the bottom of the Arroyo and the San Angelo formations . The forHaving argued against an extinction of tetrapods across the Kungurian/Roadian boundary (due to the inappropriate time-binning strategies used in other diversity studies and the disagreement over the age of the San Angelo and Chickasha formations), All diversity estimates presented here support a decrease in species and genus richness between the Redtankian and Littlecrotonian. The diversity estimates at finer stratigraphic scales support the observations of Does this period of elevated extinction rates and declining diversity constitute a mass extinction? It is worth noting at this point that mass extinctions appearing in the fossil record as prolonged declines is an issue that has a long history of discussion in the published literature, going back to the work of Ophiacodon, and the abundant record of Varanosaurus, represented in the Arroyo Formation by the species V. acutirostris , was discounted as representing a taxon of uncertain assignment. However, almost three decades of study, both anatomical and cladistic, support the ophiacodontid affinity of Varanosaurus (Edaphosaurus is known from the Arroyo formation (E. pogonias), but it still represents one of the most abundant herbivores in this fauna  and palaeotemperate localities . Eryopidormation . Crucialormation . Eryopidormation . The Triormation . Both arormation . The ChoThere has not been much work on the environmental context surrounding this event, but the extended period of extinction has been suggested to coincide with substantial climatic changes recorded in the Texas sequence. The sediments of the Vale Formation record a transition from an environment dominated by large perennial streams to one of braided channels, with indications that flow was interrupted by substantial periods of drying . The ChoNo matter what time-binning scheme is employed, no matter whether the data is examined at the species or genus level, and no matter whether the data is corrected for sampling or not, a substantial mass extinction event is observed in tetrapods during the Redtankian Land Vertebrate Fanuachron. Throughout the Redtankian, extinction rates were raised substantially above background levels, rising to a peak in the uppermost Choza Formation. Tetrapod diversity declines throughout this period, and by the end of the Redtankian, species richness is less than a quarter of that observed at the start.10.7717/peerj.4767/supp-1Data S1Number of specimens of each species in each formation.Click here for additional data file.10.7717/peerj.4767/supp-2Data S2Number of specimens of each genus in each formation.Click here for additional data file.10.7717/peerj.4767/supp-3Data S3R script giving the function to calculate extinction rates using the gap fillers method, along with instructions for use.Click here for additional data file.


Fully integrated monitoring systems have shown promise in improving confidence in composite materials while reducing lifecycle costs. A distributed optical fibre sensor is embedded in a fibre reinforced composite laminate, to give three sensing regions at different levels through-the-thickness of the plate. This study follows the resin infusion process during fabrication of the composite, monitoring the development of strain in-situ and in real time, and to gain better understanding of the resin rheology during curing. Piezoelectric wafer active sensors and electrical strain gauges are bonded to the plate after fabrication. This is followed by progressive loading/unloading cycles of mechanical four point bending. The strain values obtained from the optical fibre are in good agreement with strain data collected by surface mounted strain gauges, while the sensing regions clearly indicate the development of compressive, neutral, and tensile strain. Acoustic emission event detection suggests the formation of matrix (resin) cracks, with measured damage event amplitudes in agreement with values reported in published literature on the subject. The Felicity ratio for each subsequent loading cycle is calculated to track the progression of damage in the material. The methodology developed here can be used to follow the full life cycle of a composite structure, from manufacture to end-of-life. Fibre reinforced polymer (FRP) composites are known to be stronger, more corrosion resistant, and more lightweight than traditional metals and metal alloys. Improvements in the achievable properties and manufacturing techniques has led to an increase in their use in critically loaded structural applications. However, with new techniques comes uncertainty of the parameters involved. It is not uncommon to find voids, dry and resin rich regions, and other imperfections in finished composite parts. Defects and damage can often be imparted during fabrication. These and the inherent nature of the process can lead to residual strains in the finished product, which may affect the overall performance. Non-destructive inspection/evaluation (NDI/E) techniques are often employed for the detection, localisation, and quantification of flaws and damage. Widely researched methods include the use of X-rays , ultrasoThis paper presents an experimental study where a distributed optical fibre sensor is embedded and used to follow the full manufacturing process of a composite laminate, providing valuable information related to the rheology of the system and captures the magnitude of residual strains. During mechanical four point bending, distributed strain and acoustic emissions are monitored to be able to detect the initiation and monitor the progress of damage in the structure as the maximum load is increased. The use of these ‘smart sensors’ has proven to be effective and reliable in the authors’ and others’ previous work when applied to the SHM of composite materials. Similar experimental observations are made in this work, thus validating that it is scientifically sound and has relevance in this research field.Introduced in the late 80s to early 90s, fibre Bragg grating (FBG) sensors are the most common optical fibre sensor in SHM applications ,21. FBGsA distributed optical fibre sensor (DOFS) is a single optical fibre, sensitive at multiple points along its length ; thus, iAcoustic emission (AE) is an SHM technique which uses piezoelectric sensors as receivers of elastic waves, generated by microstructural damage, as they propagate through the material. A network of three or more sensors can be used to determine the damage source location and estimate the severity and type of damage. The use of AE for early damage detection in composites is well established , with thWhen a homogeneous, isotropic specimen is loaded incrementally, a phenomenon known as the ‘Kaiser Effect’ is observed; AE signals are only emitted in subsequent loadings when the previous maximum load is exceeded. In composite materials, a similar effect is observed; this is known as the Felicity effect . In compDuring subsequent loadings of a component, a reduction in the Felicity ratio generally tends to be observed. Observation of the load at which AE events start to occur during a mechanical loading test can, therefore, reveal information about the load-time history of a component, providing the material properties are known.A composite laminate (400 mm × 200 mm) was manufactured by vacuum assisted resin infusion moulding of six plies of carbon fibre fabric—5-harness satin weave, supplied by Cytec Solvay Group —with an epoxy resin system . For more information about the manufacturing process, the reader is referred to —were bonAfter manufacture, quasi-static four point bending was conducted on the plate (trimmed to 385 mm × 145 mm) using an adaptation of the ASTM standard D7264: ‘Flexural properties of polymer matrix composite materials’ on an Instron 5969 testing machine fitted with a 10 kN load cell . Though During each loading, the surface strain on the top and bottom surfaces of the panel was measured by uniaxial strain gauges. Four piezoelectric wafer active sensors (PWAS) acted as receivers of AE during loading were bonded on the top of the plate a. FigureResin infusion was carried out at room temperature, using a vacuum to draw the resin through the fibres. During this process, the strain in the optical fibre can be attributed only to mechanical strain. During the curing process, thermocouples were used to follow the change in temperature, while the DOFS measures the total strain, which comprises two components: mechanical strain and thermal strain. The temperature influences greatly the total strain in the panel, thus concealing the mechanical strain that results from the curing process; so, using data obtained from a short length of optical fibre, sensitive only to changes in temperature, it was possible to offset the total strain to give the value of mechanical strain. When plotted against temperature, taken as an average from the three thermocouples, the effect of each stage of the curing cycle on the mechanical strain experienced by different regions of the laminate becomes clear . During A small peak is visible in each measurement region, increasing in amplitude from 400 s to 1600 s. On first glance it may appear that this is a concentration of stress caused by the presence of local damage in the structure which occurred during loading. A more plausible possibility is that this peak is caused by yarn crimp within the fabric plies above and below the embedded optical fibre sensor. With this in mind, the possible nesting characteristics of the fabric plies above and below the optical fibre were investigated. If analysis of the recorded acoustic emission signals was constrained to the distribution of amplitude, as many researchers have done in the past, the AE signals recorded would suggest the formation of matrix cracks. The general trend for AE hit amplitudes is to increase as the strain is increased, demonstrating the development of damage in the structure. Particularly high amplitude hits in the range 90–100 dB, which researchers ,35,44,46This work has shown the ability to combine two different types of sensors for structural health monitoring of composite structures. Distributed strain monitoring during fabrication can provide valuable information about the resin rheology in addition to mechanical properties of a part prior to the completion of its manufacture. Once it goes into service, the embedded optical fibre can continuously monitor applied strains that could determine its performance. The undulating geometry of strain data recorded by the optical fibre sensor is a result of crimp in the yarns which make up the layers of fabric above and below the optical fibre sensing regions. These small peaks are accentuated as the strain is increased—an observation which should be taken into account when this technique is used in service.The use of AE monitoring has shown promise in the early distinction and quantification of damage mechanisms in composite materials. The Felicity effect can be used to determine the time-load history of a component. When combined with historical strain data, this information can be particularly beneficial in informing the design of structures based on the distribution and concentration of strains. The importance of taking into account multiple features in each AE signal to be able to distinguish between different damage mechanisms has been highlighted in this work. In addition, the material/sensor system should not be neglected in the interpretation of the results. To use acoustic emission monitoring in-service, it is important to consider the effect of extraneous noise on the system and to define carefully an appropriate threshold. It is possible to use the PWAS to calculate an AE source location based on the time of arrival of signals to different sensors. Repetition of damage in the same or different locations can, therefore, be distinguished and correlated against any residual strains observed along the length of the embedded optical fibre. In near future work, AE data will be validated by sectioning and optical microscopy as well as by conventional non-destructive testing (NDT) techniques.


Non-compressible torso hemorrhage (NCTH) remains a significant cause of morbidity and mortality in the field of trauma and emergency medicine. In recent times, there has been a resurgence in the adoption of Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA) for patients who present with NCTH. Like all medical procedures, there are benefits and risks associated with the REBOA technique. However, in the case of REBOA, these complications are not unanimously agreed upon with varying viewpoints and studies. This article aims to review the current knowledge surrounding the complications of the REBOA technique at each step of its application. Non-compressible torso hemorrhage (NCTH) is a major cause of morbidity and mortality in the trauma setting . The difp = 0.120) [REBOA shows promise in improving the outcomes for patients with NCTH in comparison to RT. In a recent prospective study, there was no significant difference in overall mortality between patients undergoing RT and those undergoing REBOA for NCTH  . However= 0.120) .Considering the increasing number of cases treated using the REBOA technique, the aim of this paper is to review complications of REBOA at each stage of the procedure using a combination of literature review and clinical experience. PubMed online searches were used including search words such as REBOA, resuscitation, hemorrhage, and shock. We also highlight key areas for further investigation and research.Complications of REBOA are numerous and can be caused by the insertion of the intra-aortic balloon occlusion catheter and femoral artery sheath. The major complications of REBOA catheter insertion are vessel injuries , embolization, air emboli, and peripheral ischemia .The greatest limitation to REBOA is the ischemia caused by total aortic occlusion . ProlongThe severe ischemic complication of the lower extremities can be associated with sheath placement for REBOA, and the use of large-sized sheaths for REBOA can be a critical risk factor for lower extremity ischemia .As blood flow is inversely proportional to the vessel cross-sectional area, it is acceptable that large-sized sheaths may decrease blood flow to the extremities . Some exREBOA has been used routinely in endovascular management of abdominal aortic aneurysms (EVAR) via large diameter sheaths, typically 12–14 Fr or larger. The development of balloon catheters deliverable via 7 Fr sheaths have led to new enthusiasm for the technique for trauma patients. However, the evidence for its efficacy is limited .Although these complications are related to sheath insertion and are not specific to REBOA, it is important for surgeons performing REBOA to be aware of these potential access site consequences and address them at time of sheath removal to avoid limb-threatening vascular complications . MoreoveAn additional challenge of REBOA is the need for rapid and accurate placement. This technique can provide total occlusion of the aorta either just above the diaphragm (zone I), to control intra-abdominal bleeding, or above the aorto-iliac bifurcation (zone III), to control bleeding in the pelvis or proximal extremities , 18.Animal studies suggest that zone I REBOA is survivable for 60 min and zone III for 90 min. However, the Norii registry study shows that zone I occlusion for 45 min was uniformly lethal and there were only two survivors after 90 min of REBOA occlusion in the Inoue registry study. Once the REBOA catheter is inflated, the time to obtain definitive control of bleeding is limited and the need is absolute .Balloon inflation is an integral part of the procedure and must be executed carefully. The balloon should be inflated until the blood pressure is augmented and contralateral femoral pulse is stopped, approximately 8 mL for zone I or 3 mL for zone III .It is crucial that the practitioner performing REBOA is aware of the complications related to the inflation level and duration of the inflation in this step of the procedure. The physician should be careful to not over-inflate the balloon, as an over-inflation will rupture the balloon or the blood vessel . A systeAnother complication that must be avoided is the profound ischemia related to a long-term occlusion. Animal data suggests that prolonged occlusion of the aorta is associated with ischemia-reperfusion injury and potentially an increased risk of death . The proReinforcing the idea that the duration of the occlusion must be minimal, Saito N et al. reported that the time from inflation to deflation of the aortic balloon in 24-h survivors was shorter than in non-survivors. It was suspected that reperfusion injuries caused by systemic ischemia would lead to death. In experiments with swine, Morrison et al. reported that a longer aortic inflation time increased the release of interleukin-6, incidence of adult respiratory distress syndrome, and use of vasopressors [In an attempt to minimize distal ischemia and extend the duration of use of REBOA, studies have led to the development of partial REBOA (pREBOA), whereby the balloon is deflated slightly, allowing a degree of flow beyond the balloon . SeveralAlthough the REBOA technique continues to be studied, some studies demonstrate that a partial approach maintained normal physiology better than the complete one, minimized the systemic impact of distal organ ischemia, and reduced hemodynamic instability, allowing the potential for longer periods of intervention .During balloon occlusion, specific complications can occur such as accessing the wrong vascular tree, misplacement of the wire or balloon within the arterial system, the creation of dissection flaps or other arterial injury, retroperitoneal hemorrhage, the development of lactic acidosis and organ dysfunction, and the development of clots which may lead to limb ischemia .REBOA placement in some countries currently requires large arterial sheaths such as 7 to 14 Fr in the common femoral artery. It has been reported that these large sheaths may be associated with severe complications, including lower extremity ischemia and amputations. These complications may be related to the near occlusive diameter of these large sheaths, the length of time they remain in the artery, the location of insertion, and potential damage that can be caused during the insertion.These problems related to the management of REBOA has led physicians to hypothesize that one of the causes associated with the rate of complications could be the diameter of the sheaths. A prospective observational study by Walter L. et al. proposed that the use of new low-profile devices could decrease vascular complications associated with REBOA .A retrospective review of patients receiving REBOA through a 7 Fr sheath for refractory traumatic hemorrhagic shock performed from January 2014 to June 2015 at five tertiary-care hospitals in Japan reported that 7 Fr introducer device for REBOA may be a safe and effective alternative to large-bore sheaths and may remain in place during the post-procedure resuscitative phase without sequelae. The main benefits of a 7 Fr system include tolerance of a prolonged indwelling sheath time and the ability to remove the sheath successfully with only manual compression [REBOA balloon deflation and subsequent reperfusion is an integral stage in the procedure and can lead to potential cardiovascular complications. Previously, clinical guidelines have recommended the controlled deflation of the balloon to minimize sudden physiologic derangements. However, a study conducted on use of REBOA in 13 patients with pelvic fractures found six patients experienced hemodynamic shock upon balloon deflation. Of these six patients, three were resuscitated, one recovered after reinflation of the balloon, and the remaining two died from the shock . This isn = 24), two patients experienced lower limb ischemia following sheath removal, both of which required amputation below the knee. This is resultant from the prolonged systemic ischemia [After completion of the procedure and deflation of the balloon, both the REBOA balloon catheter (and wire if used) may be removed and various techniques may be employed to remove the device, ensuring there is no clot in the sheath or distal extremity of the sheath. The sheath can then be removed through a surgical longitudinal incision through the groin, exposing both distal and proximal areas to the sheath, before adequate closure of the artery . In a 5-The exact indications for REBOA remain uncertain . Future The use of endovascular aortic occlusion is an adjunct for resuscitation in patients with severe hemorrhage. In the setting of traumatic arrest from hemorrhage below the diaphragm, RT with cross-clamp may be used instead of REBOA for the purpose of aortic occlusion. In patients with physiologic decompensation, the advantage of REBOA is the ability to place the catheter at the intended level of occlusion, monitor the intra-aortic pressure with high-fidelity (if using the ER-REBOA catheter), and rapidly inflate the balloon prior to arrest is less invasive and committal than a RT. In the setting of severe pelvic hemorrhage, traditional control with pelvic packing and/or internal iliac ligation can be augmented by REBOA placed prior to these measures as a bridge to hemostasis. The benefits of using REBOA are largely based on the nature of it being a less invasive procedure and being able to intervene earlier in the downward spiral of exsanguinating hemorrhage: REBOA offers immediate, early temporization of hemorrhage prior to cardiovascular collapse. Consequences of early temporization may include decreased blood product transfusions with their inherent risks and sequela, less stress on cardiac function, decreased secondary brain injury for those with significant TBI, and the chance for survival beyond the ED. Significant research including the role of partial REBOA will help refine its use for a wide variety of clinical scenarios.REBOA is an emergent and increasingly accepted technique used as a less invasive alternative for controlling bleeding in patients with NTCH. However, for this procedure to be used in widespread practice, a better understanding of the potential complications that can arise in all stages must be well recognized. Complications can arise in arterial access, balloon positioning, inflation, during occlusion, deflation, and removal of the sheath. Comprehensive investigation and studies conducted into each of these stages of REBOA can allow identification of specific complications and adequate measures to be taken to avoid these complications and reduce potential morbidity and mortality associated with REBOA.


Recently, the multiphase method was proposed to estimate cohort effects after removing the effects of age and period in age-period contingency table data. Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver and is strongly associated with cirrhosis, due to both alcohol and viral etiologies. In epidemiology, age-period-cohort (APC) model can be used to describe (or predict) the secular trend in HCC mortality.The confidence interval (CI) of the weighted estimates was found to be relatively narrow (compared to unweighted estimates). Moreover, for males, the mortality trend reverses itself during 2006–2010 was found from an increasing trend into a slightly deceasing trend. For females, the increasing trend reverses  itself during 2001–2005.The weighted estimation of the regression model is recommended for the multiphase method in estimating the cohort effects in age-period contingency table data.The regression model can be modified through the weighted average estimate of the effects with narrower CI of each cohort.After isolating the residuals during the median polish phase, the final phase is to estimate the magnitude of the cohort effects using the regression model of these residuals on the cohort category with the weight equal to the occupied proportion according to the number of death of HCC in each cohort. Evaluating disease and mortality patterns over time has become popular in understanding the utility of disease etiology in public health. However, the trend assessment of age-specific mortality presented inconsistent patterns between age groups. Birth cohort analyses are valuable in predicting future increases (or decreases) of diseases under the same pattern among birth cohorts. In epidemiology, one popular interpretation on the relationship between age, period, and cohort (APC) variables is that age and period interact to create unique generational experiences. Age effects are correlated with the outcome at various ages, such as deaths caused by cancer. Simultaneously, period effects influenced all ages over time. Birth cohort effects presented changes across groups with the same birth year who had the same outcome during the same period. Disease mortality is not only influenced by birth cohort effects but also affected by age and period. For example, if a person born in 1980  is highly at risk of dying due to cardiovascular disease during his/her lifetime, it will take at least 30 years  for him/her to die during adulthood  at the beginning of 2010. Therefore, the conceptualization of cohort effects was proposed based on the interaction between age and period . HoweverRecently, the multiphase method was proposed by Keys and Li  and provThe median polish was developed to describe data in a two-way contingency table  and remoHepatocellular carcinoma (HCC) is the most common primary malignancy of the liver and is strongly associated with cirrhosis, due to both alcohol and viral etiologies . Of all In this study, we investigated the longitudinal trends of HCC mortality data from the Vital Statistics as our demonstration. We evaluated the HCC mortality to identify the effects of age, period, and cohort and examined whether these effects varied by gender. This study aimed to use weighted average method to modify the multiphase method, in order to estimate the cohort effect. We also illustrated how to estimate the cohort effect using the multiphase method and compared the results to those estimated by proposed weighted average method.Figures Among the birth cohorts, men born in 1936 exhibited the highest risk of HCC mortality Table , respectijkƐ) were close to zero.In this study, we limited our APC analysis of the median polish procedure to estimating cohort effects and 95% CIs of the HCC mortality. Based on this analysis, it appears that the residual errors  and facilitate prediction that are grossly missing. If we directly observe the long-term trends of HCC mortalities from 1976 to 2010 in Taiwan Figure , no one From a clinical viewpoint, hepatitis B virus (HBV) infection is an important health issue worldwide with high morbidity, approximately 2 billion people infected and 350 million suffering from chronic HBV infection . The HBVThis study investigated trend of cohort effect through applying median polish procedure. The weighted estimates for modification of the regression model of these residuals then allow a weighted average estimate on the effect with narrower CI of each cohort. The results are reported in the form of cohort effects using the 1946 cohort, because these categories present the fewest changes in HCC mortality rates with cohort influence removed.In most modeling methods (such as linear or nonlinear regression models), one of the common assumptions is that each real value of data provides equal information to estimate the parameters in a model which was undertaken. It means that the standard deviation of the error term is the constant underlying predictor variables. Based on our literature reviews, the assumption does not hold in modeling to empirically estimate the parameters. When we use weighted regression, the unknown parameters are estimated, a less weight is given for the less precise data points and more weights are given for the precise data points. The advantage is that weighted procedure can reduce the standard deviation of the estimator. However, the drawback of the weighted regression method is almost unknown in empirical practice. Because the exact weight is almost unknown, the estimated weight can be used to estimate the parameters. Moreover, experience shows that the weighting due to estimation does not change much and often does not affect regression analysis or its interpretation . TheoretSeveral potential limitations of our study should be noted. First, we can only infer about the etiologies of the changes observed. The HCC mortality based on age, period, and cohort effects are re-amenable for an APC model. However, the presence of set assumptions for the median polish that we used should be noted in the present study. Second, APC analysis can be used extensively in the epidemiology field in populations of developing or recently developed countries, where long-running cohort studies are limited. Third, we do not have information from the aggregated format datasets to adjust confounders, such as comorbidities or lifestyle, in the APC model. Further studies using individual data is needed to solve this limitation. Fourth, we use the number of deaths due to HCC as the weight to modify the regression procedure in the multiphase method. Because the exact weight is almost unknown, the use of various weights may cause minor inflation among estimated cohort effects. Lastly, circumstances in which various APC estimation methods to address the non-identifiable problem may occur . MeanwhIn conclusion, the weighted estimation to modify the regression model then allows a weighted average effect with narrower CI of each cohort. In summary, the weighted estimation of the regression model is recommended for multiphase method to estimate the cohort effects in age-period contingency table data.To illustrate the calculations, we used the HCC mortality data from 1976 to 2010 for men and women in Taiwan, which were obtained from individual health records of the Ministry of Health and Welfare (MOHW). HCC mortality was classified based on the International Classification of Disease (ICD) Code 150. The mortality data were available for 10 five-year age groups , 7 five–year time periods , and 16 birth cohorts . In Table ith age group and the jth period group be denoted by ijλ The APC model is as follows:μ, the age effects by iα, the period effects by jβ, and the cohort effects by Kγ. The following constraints are used:Let the mortality rate of the ijλ) is established using the log-additive effect as a constant term plus age, period effect, and multiplicative interaction term, which can be regarded as a fully saturated model that includes systematic and unsystematic components (random error). The systematic component contains cohort effect. After isolating the residuals from the median polish phase, the final phase is to estimate the magnitude of cohort effects through regression of these residuals (kƐ) on the cohort category The multiphase method includes three-phase processes that concretized the estimation of the cohort effect as a partial interaction in age-period contingency table data , 9. The kƐ is established using a vector of cohort effects (kγ) and error terms (ijkƐ), where ijkƐ represented the error terms unmeasured as i age, j period, and k cohort categories.The e– to the rate each age and period group. Then, take the ratio of log-additive rate without and with cohort effects for each cohort. If the rate ratio of the cohort is close to one, then it is determined as the referent birth cohort. The referent birth cohort can be determined based on the slight variation of its rate after removing the influencing factors.According to the cohort-specific mortality by age that calculated as removed and unremoved cohort influence to decide reference categories. Reference categories of cohort had a minimum difference in cohort-specific mortality between with and without cohort influence. After subtracting residuals form contingency data, we can use the residual to calculate the log-additive rate (without cohort effect) with multiplying factor kW denote the weight of the kth cohort category:For birth cohorts with members that achieved the cohort, let i age and j period of data provides equal information  for the estimation of cohort effects in a model while the weighting factor is generally unknown. Empirically, the equally weighted assumption is usually violated while modeling to estimate the cohort effect. The empirical weighting factor most widely used is the number of death [However, the common assumption is that each cohort across of death . Each ofTo check model fitness and furthermore we plot deviance residuals which from the null model, the age model, the age-period model, and then to the APC model (under the proposed weighted method) progressively .