Peak Of Waveform Research Articles

Waveform Analysis To Identify Biomechanical Relationships and Differences Between Softball Pitchers With and Without Pain.

Softball pitchers accrue high rates of injury. Research suggests certain mechanics at discrete pitch events are related with pain. Here, we examine relationships between peak throwing shoulder kinetics and trunk/pelvis kinematics and compare trunk/pelvis kinematics between pitchers who were healthy and those currently experiencing pain. (1) Peak shoulder kinetics would be positively related to greater trunk and pelvis flexion, lateral flexion, and rotation; and (2) pitchers in pain would exhibit greater trunk and pelvis flexion, lateral flexion, and rotation during the pitch than those who were pain-free. Cross-sectional study. A total of 42 high school pitchers (height, 1.71 ± 0.06 m; weight, 75.0 ± 15.9 kg; age, 16 ± 2 years) were separated into 2 groups based on presence or absence of pain. Peak kinetic data from 3 pitches per pitcher were averaged and used as dependent variables. Kinematic data were averaged across 3 trials, and time normalized to 101 datapoints between foot contact and follow-through of the pitch. Statistical parametric mapping regressions were used to assess the relationships between peak shoulder kinetics and waveform of trunk and pelvis kinematics. Pelvic lateral tilt significantly predicted peak throwing shoulder superior (P = 0.05) and lateral (P = 0.04) force. Pelvis rotation predicted peak superior force (P = 0.02). Waveform analyses revealed no waveform differences between healthy pitchers and those currently experiencing pain. Peak shoulder kinetic variables are related with pelvic positioning during the pitch; however, trunk and pelvis kinematics do not differ according to presence of pain. Pitchers in pain do not adopt specific trunk and pelvic alterations during the pitch, potentially concealing the effects of pain from visual identification. Coaches and clinicians need to discuss health status with pitchers versus relying on visual observations to understand pain and injury risk.

Assessing Transducer Parameters for Accurate Medium Sound Speed Estimation and Image Reconstruction.

The influence of the transducer lens on image reconstruction is often overlooked. Lenses usually exhibit a lower sound speed than soft biological tissues. In academic research, the exact lens sound speed and thickness are typically unknown. Here, we present a simple and nondestructive method to characterize the lens sound speed and thickness as well as the time to peak of the round-trip ultrasound waveform, another key parameter for optimal image reconstruction. We applied our method to three transducers with center frequencies of 2.5, 7.5, and 15 MHz. We estimated the three parameters with an element-by-element transmission sequence that records internal reflections within the lens. We validated the retrieved parameters using an autofocusing approach that estimates sound speed in water. We show that the combination of our parameters estimation method with two-layer ray tracing outperforms standard image reconstruction. For all transducers, we successfully improved the accuracy of medium sound speed estimation, spatial resolution, and contrast. The proposed method is simple and robust and provides an accurate estimation of the transducer lens parameters and the time to peak of the ultrasound waveform, which leads to improved ultrasound image quality.

Investigation of Type A Aortic Dissection Using Computational Modelling.

Aortic dissection is a catastrophic failure of the endothelial wall that could lead to malperfusion or rupture. Computational modelling tools may help detect arterial damage. Technological advancements have led to more sophisticated forms of modelling being made available to low-grade computers. These devices can create 3D models with clinical data, where the clinical blood pressure waveforms' model can be used to form boundary conditions for assessing hemodynamic parameters, modelling blood flow propagation along the aorta to predict the development of cardiovascular disease. This study presents patient-specific data for a rare case of severe Type A aortic dissection. CT scan images were taken nine months apart, consisting of the artery both before and after dissection. The results for the pre-dissection CT showed that the pressure waveform at the ascending aorta was higher, and the systolic pressure was lagging at the descending aorta. For the post-dissection analysis, we observed the same outcome; however, the amplitude for the waveform (systolic pressure) at the ascending aorta increased in the false lumen by 25% compared to the true lumen by 3%. Also, the waveform peak (systolic) was leading by 0.01 s. The hemodynamic parameter of wall shear stress (WSS) predicted the aneurysm's existence at the ascending aorta, as well as potential aortic dissection. The high WSS contours were located at the tear location at the peak blood flow of 0.14 s, which shows the potential of this tool for earlier diagnosis of aortic dissection.

Transverse cracking signal characterization in CFRP laminates using modal acoustic emission and digital image correlation techniques

The process of formation and subsequent propagation of transverse cracks in 90° plies of carbon-fiber laminated composites was studied using modal acoustic emission approach and digital image correlation techniques. The results from modal acoustic emission approach, which included a newly developed processing tool for acoustic emission waveforms, provided information for identification and subsequent characterization or localization of signals originating from transverse cracking by analysis of the separated flexural and extensional Lamb wave modes in terms of their modal parameters. The digital image correlation method served as a verification tool of the acoustic emission data outputs in the terms of activity of significant localized events originating from the formation of the transverse crack in the 90oply. This made it possible to specify more locally the accompanying activity belonging to the formation or propagation of the magistral transverse crack. The manuscript also presents results related to the evolution of flexural/extensional wave modal parameters as the function of loading force for both [0/0/0/90]S and [90/0/0/0]S panels. It can be concluded that the detection of transverse cracks requires the need for applying a more complex acoustic emission data analysis methodology, while the standard parametric analysis, including the waveform peak frequency, is not sufficient. The presented methodology may serve as a basis for development of robust analysis tool capable of detecting the investigated phenomena.

Adaptive design of experiments to fit surrogate Gaussian process regression models allows fast sensitivity analysis of the input waveform for patient-specific 3D CFD models of liver radioembolization

Background and objectivePatient-specific 3D computational fluid dynamics (CFD) models are increasingly being used to understand and predict transarterial radioembolization procedures used for hepatocellular carcinoma treatment. While sensitivity analyses of these CFD models can help to determine the most impactful input parameters, such analyses are computationally costly. Therefore, we aim to use surrogate modelling to allow relatively cheap sensitivity analysis. As an example, we compute Sobol's sensitivity indices for three input waveform shape parameters. MethodsWe extracted three characteristic shape parameters from our input mass flow rate waveform (peak systolic mass flow rate, heart rate, systolic duration) and defined our 3D input parameter space by varying these parameters within 75 %-125 % of their nominal values. To fit our surrogate model with a minimal number of costly CFD simulations, we developed an adaptive design of experiments (ADOE) algorithm. The ADOE uses 100 Latin hypercube sampled points in 3D input space to define the initial design of experiments (DOE). Subsequently, we re-sample input space with 10,000 Latin Hypercube sampled points and cheaply estimate the outputs using the surrogate model. In each of 27 equivolume bins which divide our input space, we determine the most uncertain prediction of the 10,000 points, compute the true outputs using CFD, and add these points to the DOE. For each ADOE iteration, we calculate Sobol's sensitivity indices, and we continue to add batches of 27 samples to the DOE until the Sobol indices have stabilized. ResultsWe tested our ADOE algorithm on the Ishigami function and showed that we can reliably obtain Sobol's indices with an absolute error <0.1. Applying ADOE to our waveform sensitivity problem, we found that the first-order sensitivity indices were 0.0550, 0.0191 and 0.407 for the peak systolic mass flow rate, heart rate, and the systolic duration, respectively. ConclusionsAlthough the current study was an illustrative case, the ADOE allows reliable sensitivity analysis with a limited number of complex model evaluations, and performs well even when the optimal DOE size is a priori unknown. This enables us to identify the highest-impact input parameters of our model, and other novel, costly models in the future.

Additional Factor X Enhances Emicizumab-Driven Coagulation Function in Patients with Hemophilia A and Hemophilia A Mice.

Bypassing agents are used for breakthrough bleedings in patients with hemophilia A with inhibitor (PwHAwI) receiving emicizumab prophylaxis. Previous study demonstrated a weak binding affinity between emicizumab and factor (F)X (K d; 1.85 μM), and that this value was much greater than the plasma FX concentration (∼130 nM). We speculated that increased FX levels could enhance coagulation potential in emicizumab-treated patients with hemophilia A (PwHA). To investigate the relationship between FX concentrations and emicizumab-driven coagulation. Plasma FX (up to 1,040 nM) and emicizumab (50 µg/mL) were added to FVIII-deficient plasmas, and plasma-derived FX (520 nM) or recombinant (r)FVIIa (2.2 µg/mL) was added to plasmas from three emicizumab-treated PwHAwI. The adjusted maximum coagulation velocity (Ad|min1|) by clot waveform analysis and peak thrombin (PeakTh) by thrombin generation assay in them were evaluated. Emicizumab (3.0 mg/kg), human (h)FIX (100 IU/kg), and various doses of hFX (100-500 IU/kg) were intravenously administered to HA mice. Clotting time/clot formation time (CT/CFT) were assessed using rotational thromboelastometry, and blood loss was estimated by a tail-clip assay. The addition of FX to FVIII-deficient plasma with emicizumab increased Ad|min1| and PeakTh. The coagulation parameters in emicizumab-treated PwHAwI spiked with additional FX remained within the normal range as well as the additional rFVIIa. In animal models, hFX injection shortened the CT and CT + CFT. The shorter CT and CT + CFT, and the lower blood loss were evident after 200 or 500 IU/kg hFX administration, and those indices were comparable to those in wild-type mice. Supplementation with FX may improve emicizumab-driven hemostasis in PwHA.

Site-Specific Ground-Motion Waveform Generation Using a Conditional Generative Adversarial Network and Generalized Inversion Technique

ABSTRACT Accurate ground-motion simulations are essential for seismic hazard assessments and engineering practices. Herein, we propose a novel method combining conditional generative adversarial networks (cGANs) and the generalized inversion technique (GIT) to generate site-specific and variability-controlled strong-motion seismograms. The cGANs calculate synthetic seismogram without amplitude scales. The GIT is to separate the source, path, and site characteristics from the Fourier amplitude spectrum (FAS) of the observed seismograms. This method is applied to plate boundary earthquakes off the Pacific coast of Tohoku, Japan. It successfully generates a set of strong-motion seismograms at a given magnitude, distance, and observation station. The output waveforms reproduce the P and S waves as well as coda waves. We validate the method through a quantitative comparison with observed seismograms in terms of both time-domain duration and frequency-domain amplitude characteristics, using metrics of peak ground acceleration (PGA), peak ground velocity, FASs, response spectra, and waveform duration time. The validation results show that the variation in the PGA of the observed seismograms and the synthetic seismograms has a standard deviation of 0.643, and the duration of the seismograms has a standard deviation of 0.346, comparable to the standard deviations seen in the previous studies. Our approach offers high accuracy in stochastic finite-source modeling for a period of 1 s or shorter. The two features of the method, site-specificity and variability control, can contribute to further improvements in seismic hazard assessment by incorporating empirical information based on observed seismograms.

Neural signatures of indirect pathway activity during subthalamic stimulation in Parkinson’s disease

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) produces an electrophysiological signature called evoked resonant neural activity (ERNA); a high-frequency oscillation that has been linked to treatment efficacy. However, the single-neuron and synaptic bases of ERNA are unsubstantiated. This study proposes that ERNA is a subcortical neuronal circuit signature of DBS-mediated engagement of the basal ganglia indirect pathway network. In people with Parkinson’s disease, we: (i) showed that each peak of the ERNA waveform is associated with temporally-locked neuronal inhibition in the STN; (ii) characterized the temporal dynamics of ERNA; (iii) identified a putative mesocircuit architecture, embedded with empirically-derived synaptic dynamics, that is necessary for the emergence of ERNA in silico; (iv) localized ERNA to the dorsal STN in electrophysiological and normative anatomical space; (v) used patient-wise hotspot locations to assess spatial relevance of ERNA with respect to DBS outcome; and (vi) characterized the local fiber activation profile associated with the derived group-level ERNA hotspot.

Detection of biomagnetic signals from induced pluripotent stem cell-derived cardiomyocytes using deep learning with simulation data

The detection of spontaneous magnetic signals can be used for the non-invasive electrophysiological evaluation of induced pluripotent stem cell-derived cardiomyocytes (iPS-CMs). We report that deep learning with a dataset that combines magnetic signals estimated using numerical simulation and actual noise data is effective in the detection of weak biomagnetic signals. To verify the feasibility of this method, we measured artificially generated magnetic signals that mimic cellular magnetic fields using a superconducting quantum interference device and attempted peak detection using a long short-term memory network. We correctly detected 80.0% of the peaks and the method achieved superior detection performance compared with conventional methods. Next, we attempted peak detection for magnetic signals measured from mouse iPS-CMs. The number of detected peaks was consistent with the spontaneous beats counted using microscopic observation and the average peak waveform achieved good similarity with the prediction. We also observed the synchronization of peak positions between simultaneously measured field potentials and magnetic signals. Furthermore, the magnetic measurements of cell samples treated with isoproterenol showed potential for the detection of chronotropic effects. These results suggest that the proposed method is effective and has potential application in the safety assessment of regenerative medicine and drug screening.

Analysis of pulse-wave propagation characteristics in abdominal aortic sclerosis disease

In this work, a bidirectional fluid‒structure coupling finite element analysis model of the abdominal aorta was established, with the various vascular elastic modulus as the main parameters for atherosclerosis, taking into consideration blood's dynamic viscosity and compressibility. Pressure and velocity pulse-wave propagation were investigated through the application of a full-coupling analysis algorithm. The effect of atherosclerosis degree on the propagation characteristics of pulse waves in the bifurcated abdominal aorta was quantitatively analyzed. Arterial bifurcation can cause substantial attenuation on the peak of pressure pulse waveform and an increase in wave velocity during the cardiac cycle. The elastic modulus and bifurcation properties of the arterial wall directly affected the peak value and wave propagation velocity of the pressure pulse wave. The preliminary results of this work will be crucial in guiding the evolution of the pressure pulse wave and the initial diagnosis of atherosclerotic disease through the waveform.

A novel identification method of microseismic events based on empirical mode decomposition and artificial neural network features

Microseismic technology has been widely used in geological hazard monitoring. However, the effective identification and classification of microseismic events in mines have always been a challenge in hazard monitoring. In this paper, a new method combining the empirical mode decomposition (EMD) algorithm and artificial neural network is proposed for the classification and identification of microseismic waveforms. This is the first study to explore such a model in the microseismic monitoring of coal mines. The data for this study were collected from a coal mine in northern China. A total of 2768 microseismic events and 2435 non-microseismic events were manually selected from a large amount of data. Firstly, the microseismic waveform reconstruction was performed using the 4th to 8th Intrinsic Mode Function (IMF) obtained by the EMD algorithm. Secondly, the peak factor, clearance factor, impulse factor, kurtosis, skewness, and waveform factor of each reconstructed microseismic waveform were used as features. Subsequently, the convolutional neural network (CNN) was used to classify microseismic events. Among them, data from 3600 microseismic events were used as the training set, and data from 1603 microseismic events were used as the test set. Finally, the original waveform data were used as input and compared with the classification results processed with the EMD algorithm. The classification methods of the BP neural network and Radial Basis Function (RBF) neural network were used for verification. The results of the processed features showed a significant increase in accuracy. The classification accuracy of CNN, BP neural network, and RBF neural network are 97.37%, 91.99%, and 94.23%, respectively. The results show that the utilization of the feature processing technique and CNN algorithm in this study demonstrates superior efficacy in microseismic event classification, which can be used in practice.

Characteristics of blood flow velocity in the radial artery and finger capillaries using magnetoplethysmogram and photoplethysmogram

The Hall element and optical sensor, which can detect the magnetic field change caused by the minute fluctuations of the permanent magnet according to the periodic movement of the radial artery and the light absorption and reflection intensity according to the change in wrist blood flow, respectively, are used as key elements in digital healthcare devices. The pulse waves of the radial artery inside the wrist were measured and analyzed using a clip-type pulsimeter, magnetoplethysmogram (MPG). The pulse wave, which is the change in blood flow obtained by photoplethysmogram (PPG), was measured on the dorsal side of the wrist or the fingers simultaneously with MPG. The ABFV (artery blood flow velocity) is a few ten cm/s as DH (distance between MPG and PPG) divided by ΔT(a) which is the time difference between the first peaks of MPG and PPG waveforms on the dorsal side of the wrist. The PBFV (peripheral blood flow velocity) is a few mm/s as LH (hand length) divided by ΔT(p), which is the time difference between the first peak of MPG waveform and the third peak PPG waveform on the finger. For four subjects of 20s, SPWV was approximately 0.98∼1.19 m/s, ABFV in the radial artery was approximately 0.40∼0.44 m/s, and finger capillary PBFV was approximately 6.3∼8.6 cm/s. These results show reasonable values similar to the blood velocity of many blood vessels flowing through the human body.

Spherical shock waveform reconstruction by heterodyne interferometry.

The indirect measurement of shock waveforms by acousto-optic sensing requires a method to reconstruct the field from the projected data. Under the assumption of spherical symmetry, one approach is to reconstruct the field by the Abel inversion integral transform. When the acousto-optic sensing modality measures the change in optical phase difference time derivative, as for a heterodyne Mach-Zehnder interferometer, e.g., a laser Doppler vibrometer, the reconstructed field is the fluctuating refractive index time derivative. A technique is derived that reconstructs the fluctuating index directly by assuming plane wave propagation local to a probe beam. With synthetic data, this approach is compared to the Abel inversion integral transform and then applied to experimental data of laser-induced shockwaves. Time waveforms are reconstructed with greater accuracy except for the tail of the waveform that maps spatially to positions near a virtual origin. Furthermore, direct reconstruction of the fluctuating index field eliminates the required time integration and results in more accurate shock waveform peak values, rise times, and positive phase duration.

Revisiting the Chicken Auditory Brainstem Response: Frequency Specificity, Threshold Sensitivity, and Cross Species Comparison.

The auditory brainstem response (ABR) is important for both clinical and basic auditory research. It is a non-invasive measure of hearing function with millisecond-level precision. The ABR can not only measure the synchrony, speed, and efficacy of auditory physiology but also detect different modalities of hearing pathology and hearing loss. ABRs are easily acquired in vertebrate animal models like reptiles, birds, and mammals, and complement existing molecular, developmental, and systems-level research. One such model system is the chicken; an excellent animal for studying auditory development, structure, and function. However, the ABR for chickens was last reported nearly 4 decades ago. The current study examines how decades of ABR characterization in other animal species support findings from the chicken ABR. We replicated and expanded on previous research using 43 chicken hatchlings 1- and 2-day post-hatch. We report that click-evoked chicken ABRs presented with a peak waveform morphology, amplitude, and latency like previous avian studies. Tone-evoked ABRs were found for frequencies from 250 to 4000 Hertz (Hz) and exhibited a range of best sensitivity between 750 and 2000 Hz. Objective click-evoked and tone-evoked ABR thresholds were comparable to subjective thresholds. With these revisited measurements, the chicken ABR still proves to be an excellent example of precocious avian development that complements decades of molecular, neuronal, and systems-level research in the same model organism.

Central systolic blood pressure as a risk for the accelerated progression of arterial stiffness

Abstract In the arterial tree, the systolic blood pressure (SBP) exhibits a pressure gradient from central to peripheral and is higher in the periphery because of pressure wave reflection. However, this gradient is attenuated with the elevation of central SBP (cSBP) in case with abnormal pressure wave reflection in arterial tree. It remains unclear whether increase of the cSBP might be an independent risk for the accelerated progression of arterial stiffness. Using the latent growth curve model (LGCM) analysis, this prospective observational study was conducted to examine whether elevation of the cSBP might be an independent risk for the accelerated progression of arterial stiffness in middle-aged Japanese men.In this 9-year prospective observational study, 3862 middle-aged Japanese men (42 ± 9 years old) without cerebrocardiovascular disease at the study baseline underwent annual measurements of the brachial-ankle pulse wave velocity (baPWV), and cSBP, estimated by radial pressure wave analysis as the second peak of radial pressure wave form (SBP2). During the follow-up period (6.4 ± 2.5), significant increases of baPWV and SBP2 were observed in all subjects. Analysis using the LGCM confirmed that the SBP2, a maker of cSBP (B=0.260, P &amp;lt; 0.001) was significant determinants of the slope of annual changes of baPWV during the study period. Our finding suggests that elevated cSBP is an independent risk for the accelerated progression of arterial stiffness in middle-aged Japanese men.

Hardware-in-the-loop testing of grid-tied PMSG-based wind power generation system with optimum PI parameters

The regulators based on PI control law continue to be the key elements in many of the industrial systems for their control. Likewise, the wind power generation systems (WPGSs) also make extensive use of PI regulators in their control schemes. The enhanced performance of these WPGS depends on proper selection of the PI regulator parameters. This paper deals with the control of a grid-tied permanent magnet synchronous generator (PMSG)-based WPGS wherein, a new attempt has been depicted to apply the most optimum design of the involved PI regulator parameters for the proposed WPGS based on standard performance indices making use of four popular optimization algorithms namely genetic algorithm (GA), cultural algorithm (CA), particle swarm optimization (PSO) and artificial bee colony (ABC). An informative discussion has also been presented which would be useful for practicing engineers/researchers to select flexibly and reasonably the PI regulators parameters meant for the control of the proposed WPGS. A detailed simulation model developed in MATLAB/Simulink has been used to analyze the performance of the proposed PMSG-based WPGS employed with the most optimum values of PI regulator parameters. The performances of WPGS have been compared while the most optimum PI regulator parameters have been included in the control system, and also when incorporating the PI regulator parameters in WPGS control designed via classical d-partition technique. The results obtained under gradually changing wind speed profile show the improvement in the performance of WPGS in terms of peak overshoot, time response and waveform oscillations. The experimental validation of the control performances have been carried out by way of real-time hardware-in-the-loop (HIL) testing making use of Typhoon HIL402 emulator and TMS320F28335 digital signal controller. The obtained real time HIL results are in close agreement to the results obtained in simulations using MATLAB/Simulink. A deviation of less than 4% was observed in the percentage overshoot/undershoot of the PMSG speed and DC link voltage determined through simulation and experimental means under various wind speed conditions.

Multi-transfer learning techniques for detecting auditory brainstem response

The assessment of the well-being of the peripheral auditory nerve system in individuals experiencing hearing impairment is conducted through auditory brainstem response (ABR) testing. Audiologists assess and document the results of the ABR test. They interpret the findings and assign labels to them using reference-based markers like peak latency, waveform morphology, amplitude, and other relevant factors. Inaccurate assessment of ABR tests may lead to incorrect judgments regarding the integrity of the auditory nerve system; therefore, proper Hearing Loss (HL) diagnosis and analysis are essential. In order to identify and assess ABR automation while decreasing the possibility of human error, machine learning methods, notably deep learning, may be an appropriate option. To address these issues, this study proposed deep-learning models using the transfer-learning (TL) approach to extract features from ABR testing and diagnose HL using support vector machines (SVM). Pre-trained convolutional neural network (CNN) architectures like AlexNet, DenseNet, GoogleNet, InceptionResNetV2, InceptionV3, MobileNetV2, NASNetMobile, ResNet18, ResNet50, ResNet101, ShuffleNet, and SqueezeNet are used to extract features from the collected ABR reported images dataset in the proposed model. It has been decided to use six measures accuracy, precision, recall, geometric mean (GM), standard deviation (SD), and area under the ROC curve to measure the effectiveness of the proposed model. According to experimental findings, the ShuffleNet and ResNet50 models' TL is effective for ABR to diagnosis HL using an SVM classifier, with a high accuracy rate of 95% when using the 5-fold cross-validation method.

Cognitive control subprocess deficits and compensatory modulation mechanisms in patients with frontal lobe injury revealed by EEG markers: a basic study to guide brain stimulation

BackgroundFrontal lobe injury (FLI) is related to cognitive control impairments, but the influences of FLI on the internal subprocesses of cognitive control remain unclear.AimsWe sought to identify specific biomarkers for...

Coagulant potentials of emicizumab in the plasmas from infant and toddler patients with hemophilia A.

Emicizumab significantly reduces bleedings in patients with hemophilia A (PwHA). A clinical study (HAVEN 7; NCT04431726) for PwHA aged less than or equal to 12months is ongoing, but emicizumab-driven coagulation potential in PwHA in early childhood remains to be clarified. To investigate the in vitro or in vivo coagulation potential of emicizumab in plasmas obtained from infant and toddler PwHA. Twenty-seven plasma samples from 14 infant/toddler PwHA (aged 0-42months, median 19months) who received emicizumab (n=9), factor (F)VIII products (n=8), or no treatment (n=10) were obtained. FVIII activity in FVIII-treated plasmas was cancelled by the addition of anti-FVIII monoclonal antibody (mAb). Emicizumab-treated plasmas (in vivo) and emicizumab-spiked plasmas (in vitro) were analyzed. Emicizumab-untreated plasma or emicizumab-treated plasma supplemented with two anti-emicizumab mAbs were used as references. Adjusted maximum coagulation velocity (Ad|min1|) by clot waveform analysis and peak thrombin (Peak-Th) by thrombin generation assay was assessed. Ad|min1| values in 24 samples were improved by the presence of emicizumab. Values did not improve in the three remaining samples (aged 1, 23, and 31months). Although the presence of emicizumab showed an age-dependent increase in Peak-Th in 20 samples, this increase was not observed in seven samples (aged 0, 1, 1, 2, 8, 19, and 36months). Emicizumab-dependent increases in both Ad|min1| and Peak-Th were shown in 18 samples, and increases in either parameter were shown in eight samples. One sample (from patient aged 1month) showed no increase in both, however. Emicizumab could improve coagulant potential in plasmas from infant/toddler patients with hemophilia A.

Attitude control of quadrotor UAV based on fuzzy PID control under small disturbance

This paper proposes a attitude control method based on fuzzy control. Firstly, the basic model of quadrotor UAV is constructed, then the fuzzy PID controller based on fuzzy control strategy is introduced, and finally the simulation comparison experiments under PID control and fuzzy PID control are conducted. The experimental results show that the parameters of each link in the PID control method are easy to set, but the overshoot amount is large and the adjustment time is long; The simulation model of fuzzy PID control is relatively complex, and it is difficult to reach the predetermined expectation and difficult to accurately control. However, the output of overshoot, short regulation time and the waveform peak are small. In terms of anti-interference, fuzzy PID is more adaptive than PID control.