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The goals and approaches to fluid therapy vary through different stages of resuscitation. This pilot study was designed to test the safety and feasibility of a fluid therapy protocol for the second or optimisation stage of resuscitation in patients with predicted severe acute pancreatitis (SAP).Spontaneously breathing patients with predicted SAP were admitted after initial resuscitation and studied over a 24-h period in a tertiary hospital ward. Objective clinical assessment (OCA; heart rate, mean arterial pressure, urine output, and haematocrit) was done at 0, 4, 8, 12, 18-20, and 24 h. All patients had mini-fluid challenge (MFC; 250 ml intravenous normal saline within 10 min) at 0 h and repeated at 4 and 8 h if OCA score ≥2. Patients who were fluid responsive (10% change in stroke volume after MFC) received 5-10 ml/kg/h, otherwise 1-3 ml/kg/h until the next time point. Passive leg raising test (PLRT) was done at each time point and compared with OCA for assessing volume status and predicting fluid responsiveness.This fluid therapy protocol based on OCA, MFC, and PLRT and designed for the second stage of resuscitation was safe and feasible in spontaneously breathing predicted SAP patients. The PLRT was superior to OCA (at 0 and 8 h) for predicting fluid responsiveness and guiding fluid therapy.This pilot study found that a protocol for intravenous fluid therapy specifically for the second stage of resuscitation in patients with predicted SAP was safe, feasible, and warrants further investigation.

Photoacoustic/ultrasound endoscopic imaging is regarded as an effective method to achieve accurate detection of intestinal disease by offering both the functional and structural information, simultaneously. Compared to the conventional endoscopy with single transducer and laser spot for signal detection and optical excitation, photoacoustic/ultrasound endoscopic probe using circular array transducer and ring-shaped laser beam avoids the instability brought by the mechanical scanning point-to-point, offering the dual-modality imaging with high accuracy and efficiency. Meanwhile, considering the complex morphological environments of intestinal tracts in clinics, developing the probe having sufficient wide imaging distance range is especially important. In this work, we develop a compact circular photoacoustic/ultrasonic endoscopic probe, using the group of fiber, lens and home-made axicon, to generate relatively concentrated ring-shaped laser beam for 360° excitation with high efficiency. Furthermore, the laser ring size can be tuned conveniently by changing the fiber-lens distance to ensure the potential applicability of the probe in various and complex morphological environments of intestines. Phantom experimental results demonstrate imaging distance range wide enough to cover from 12 mm to 30 mm. In addition, the accessibility of the photoacoustic signals of molecular probes in ex vivo experiments at the tissue depth of 7 mm using excitation energy of 5 mJ has also been demonstrated, showing a high optical excitation efficiency of the probe.

Objective: Traditional endoscopic ultrasonography (EUS), which uses one-dimensional (1-D) curvilinear or radial/circular transducers, cannot achieve dynamic elevational focusing, and the slice thickness is not sufficient. The purpose of this study was to design and fabricate a 1.5-dimensional (1.5-D) circular array transducer to achieve dynamic elevational focusing in EUS in vivo . Methods : An 84 × 5 element 1.5-D circular array transducer was successfully developed and characterized in this study. It was fabricated with PZT-5H 1-3 composite that attained a high-electromechanical coupling factor and low-acoustic impedance. The acoustic field distribution was measured with different transmission modes to validate the 1.5-D elevational beam focusing capability. The imaging performance of the 84 × 5 element 1.5-D circular array transducer was evaluated by two wire phantoms, an agar-based cyst phantom, an ex vivo swine pancreas, and an in vivo rhesus macaque rectum based on multifocal ray-line imaging method with five-row elevational beam steering. Results : It was demonstrated that the transducer exhibited a central frequency of 6.47 MHz with an average bandwidth of 50%, a two-way insertion loss of 23 dB, and crosstalk of Conclusion : Dynamic elevational focusing and the enhancement of the slice thickness in EUS were obtained with a 1.5-D circular array transducer. Significance : This study promotes the development of multirow and two-dimensional array EUS probes for a more precise clinical diagnosis and treatment.

Background Acute pancreatitis (AP) is a common digestive disease with increased incidence globally but without internationally licenced pharmacological therapy. Moderately severe and severe acute pancreatitis (MSAP/SAP) contributes predominately for its morbidities and mortality and has been managed in West China Hospital for decades using the traditional Chinese medicinal formula chaiqin chengqi decoction (CQCQD). The current study tests whether the early administration of CQCQD will result in improved clinical outcomes in predicted MSAP/SAP patients. Methods This is a single-centre, randomised, controlled, double-blind pragmatic clinical trial. AP patients aged 18–75 admitted within 72 h of onset will be assessed at admission for enrolment. We excluded the predicted mild acute pancreatitis (Harmless Acute Pancreatitis Score > 2 at admission) and severe organ failure (Sequential Organ Failure Assessment [SOFA] score of respiratory, cardiovascular, or renal systems > 3) at admission. Eligible patients will be randomly allocated on a 1:1 basis to CQCQD or placebo control administration based on conventional therapy. The administration of CQCQD and placebo is guided by the Acute Gastrointestinal Injury grade-based algorithm. The primary outcome measure will be the duration of respiratory failure (SOFA score of respiratory system ≥ 2) within 28 days after onset. Secondary outcome measures include occurrence of new-onset any organ failure (SOFA score of respiratory, cardiovascular, or renal system ≥ 2) and new-onset persistent organ failure (organ failure lasts > 48 h), dynamic surrogate biochemical markers and clinical severity scores, gut-centred treatment modalities, local complications status, intensive care need and duration, surgical interventions, mortality, and length of hospital stay. Follow-up will be scheduled on 6, 12, and 26 weeks after enrolment to assess AP recurrence, local complications, the requirement for surgical interventions, all-cause mortality, and patient-reported outcomes. Discussion The results of this study will provide high-quality evidence to appraise the efficacy of CQCQD for the early management of AP patients. Trial registration Chictr.org.cn Registry (ChiCTR2000034325). Registered on 2 July, 2020.

Atherosclerotic cardiovascular disease is a major cause of human disability and mortality. Our previous study demonstrated the safety and efficacy of sonodynamic therapy (SDT) on atherosclerotic plaques. However, traditional single-element therapeutic transducer has single acoustic field, and positioning therapeutic and imaging transducers in the same position is difficult during ultrasound imaging-guided SDT. Continuously changing the position of transducers to intervene lesions in different positions is required, increasing the difficulty of treatment. Thus, an SDT device with precise theranostics is required. Therefore, we designed and fabricated a "concentric ultrasound transducer for theranostics" (CUST-T), comprising a central 8-MHz linear array transducer for ultrasound imaging, and a peripheral 1-MHz hollow two-dimensional (2-D) planar array transducer for generating phased-array focused ultrasound (PAFUS). The CUST-T exhibited high imaging resolution at a distance of up to 20 mm from the transducer and could generate a personalized complex PAFUS acoustic field to match various lesions. In vitro biomedical results showed that PAFUS-SDT induced RAW264.7-derived foam cell apoptosis leading to a targeting field apoptotic rate 4.36-6.24 times that of the nontargeting field and the significant apoptotic region was consistent with the PAFUS acoustic field. In vivo, PAFUS-SDT guided by ultrasound imaging significantly increased the lumen area ( ) and collagen level ( ), whereas the wall thickness ( ) and lipid content ( ) of rabbit femoral artery were reduced. In conclusion, CUST-T provided image guidance sufficient for accurate SDT for atherosclerotic plaques in peripheral arteries and could be applied in clinical practice.

Yanqiu He,1,* Cheng Hu,1,* Shiyu Liu,1 Mingjie Xu,1 Ge Liang,2 Dan Du,3 Tingting Liu,1 Fei Cai,1 Zhiyao Chen,1 Qingyuan Tan,1 Lihui Deng,1 Qing Xia1 1Pancreatitis Centre, Department and Laboratory of Integrated Traditional Chinese and Western Medicine, West China Hospital, Sichuan University, Chengdu, People’s Republic of China; 2Laboratory of Clinical Proteomics and Metabolomics, Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, People’s Republic of China; 3Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lihui Deng, Pancreatitis Centre, Department and Laboratory of Integrated Traditional Chinese and Western Medicine, West China Hospital, Sichuan University, Chengdu, People’s Republic of China, Email denglihui@scu.edu.cnBackground: Acute pancreatitis (AP) is an inflammatory disorder of the exocrine pancreas without specific treatment. Shenmai injection (SMI) was reported to eliminate the severity of experimental AP. This study aimed to explore the mechanisms underlying the synergistic protective effects of SMI on AP based on network pharmacology and experimental validation.Methods: Network pharmacology analysis and molecular docking based on identified components were performed to construct the potential therapeutic targets and pathways. The principal components of SMI were detected via ultra-high-performance liquid chromatography-coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS). Effect of SMI and the identified components on cellular injury and IL6/STAT3 signaling was assessed on mouse pancreatic acinar cell line 266– 6 cells. Finally, 4% sodium taurocholate (NaT) was used to induce AP model to assess the effects of SMI in treating AP and validate the potential molecular mechanisms.Results: By searching the TCMSP and ETCM databases, 119 candidate components of SMI were obtained. UHPLC-QTOF/MS analysis successfully determined the representative components of SMI: ginsenoside Rb1, ginsenoside Rg1, ginsenoside Re, and ophiopogonin D. Fifteen hub targets and eight related pathways were obtained to establish the main pharmacology network. Subnetwork analysis and molecular docking indicated that the effects of these four main SMI components were mostly related to the interleukin (IL) 6/STAT3 pathway. In vitro, SMI, ginsenoside Rb1, ginsenoside Rg1, ginsenoside Re, and ophiopogonin D increased the cell viability of NaT-stimulated mouse pancreatic acinar 266– 6 cells and decreased IL6 and STAT3 expression. In vivo, 10 mL/kg SMI significantly alleviated the pancreatic histopathological changes and the expression of IL6 and STAT3 in the AP mice.Conclusion: This study demonstrated SMI may exert anti-inflammatory effects against AP by suppressing IL6/STAT3 activation, thus providing a basis for its potential use in clinical practice and further study in treating AP.Keywords: acute pancreatitis, Shenmai injection, network pharmacology, molecular docking, IL6/STAT3 signaling pathway

Underdamped feature and hysteresis existing in electromagnetic scanning micro-mirrors (EMSMs) often lead to oscillation and undesired positioning error of deflection angle. In this paper, a model-based robust scheme is proposed for the angle tuning of mirror plate of the EMSM. To build a proper model for describing the behavior of EMSM, which is also convenient for the design of tuning strategy, a data-driven model composed of linear dynamic submodel as well as hysteresis submodel is developed. In the data-driven model, the deflection mechanism is described by a linear dynamic submodel while the hysteresis in EMSM is depicted by a nonsmooth hysteresis basis function submodel. Then, in order to compensate for the internal oscillation caused by both underdamping factor and hysteresis, a pseudo-feedforward oscillation compensator (PFOC) not relying on the inverse model is proposed. Then, the design procedure of the angle tuning strategy with the PFOC is presented. Afterward, the robust design of the angle tuning scheme is also studied to overcome the effect of compensation residual. Subsequently, the proposed scheme is applied to the angle tuning of EMSM.

In this article, a pressure sensor data-driven optimization by using extremum seeking (ES) technique is applied to optimize the combustion phase in a diesel engine. In particular, a cost function is constructed for the ES optimization with the in-cylinder maximum temperature $\hat{T}_{\text{max}_n}$ , which is an indication of NOx emission performance, and the thermal efficiency $\eta _n$ as tradeoff considerations. The data-driven nature lies in the fact that $\hat{T}_{\text{max}_n}$ is estimated from the in-cylinder pressure measurement within each engine cycle by assuming the in-cylinder process to be a quasi-steady state process, which is, then, compensated with the model-free ES optimization. It is noted that the approach developed in this article does not require the use of real NOx sensor data, which could otherwise jeopardize the ES optimization practically due to the unignorable and hard-to-predict gas transportation delay. Therefore, it is argued that this article actually delivers an alternative soft sensor solution to real NOx sensors for engine optimization purpose. The effectiveness of the proposed method is demonstrated on a single-cylinder diesel engine test bench with the help of steady-state engine tests. The method can be extended to data-driven optimization applications that also utilizes physical sensors with measurement delay.

In this article, a precision positioning control approach of a linear exhaust gas recirculation valve (LEGRV) system using online optimization technique is proposed. As both dynamics and nonlinear factors, including hysteretic features, are inherent in LEGRV systems, the modeling of system is not an easy process. In order to avoid the complex obstacle of modeling, in this method, a simplified model, for e.g., linear or linearized dynamic model, is developed to approximate the essential motion feature of pintle position of the linear valve. For compensating the effect of model uncertainty caused by unmodeled nonlinear and dynamic factors, a model error compensator (MEC) is introduced. Then, an online optimizing positioning control (OPC) scheme is applied to the control of pintle position of valve. In this control scheme, the estimated gradient of MEC with respect to control variable is also included in the control strategy to suppress the influence of model uncertainty. Considering the effect of nonsmoothness of hysteresis inherent in the system, a nonsmooth optimization-search method based on the technique of generalized gradient is proposed. Afterward, the stability analysis of the OPC+MEC system is presented. Finally, the experimental results to evaluate the performance of proposed control method are presented.

Worldwide research and development programs aim to reduce harmful emissions from transportation vehicles. Soft sensors have shown great potentials to reduce cost and improve onboard diagnosis for vehicle emission control. In this work, two sets of soft sensors are proposed to predict the emissions and exhaust heat flux of a gasoline engine. Extensive steady-state measurement points over the entire engine operating conditions are collected for model training and validation, and the locally linear model tree learning method is adopted. The CO, NOx, hydrocarbon, exhaust temperature, and exhaust heat flux are estimated by the soft sensors under steady-state conditions. Training of CO, exhaust temperature, and exhaust heat flux models has achieved high model accuracy over the entire engine map. Local models are developed for NOx and HC emissions to improve model performance at different engine operating speed/load conditions, especially in the low emission zone. Model validation has shown correlation coefficients ranging 0.983 ∼ 0.999

Early prediction of persistent organ failure (POF) is crucial for patients with acute pancreatitis (AP). Growth differentiation factor 15 (GDF15), also known as macrophage inhibitory cytokine 1 (MIC-1), is associated with inflammatory responses. We investigated changes in plasma GDF15 and assessed its predictive value in AP.The study included 290 consecutive patients with AP admitted within 36 h after symptoms onset. Clinical data obtained during hospitalization were collected. Plasma GDF15 levels were determined using enzyme-linked immunosorbent assays. The predictive value of GDF15 for POF was analyzed.There were 105 mild, 111 moderately severe, and 74 severe AP patients. Plasma GDF15 peak level were measured on admission, and significantly declined on the 3rd and 7th day. Admission GDF15 predicted POF and mortality with areas under the curve (AUC) of 0.847 (95% confidence interval [CI] 0.798-0.895) and 0.934 (95% CI 0.887-0.980), respectively. Admission GDF15, Bedside Index of Severity in Acute Pancreatitis, and hematocrit were independent factors for POF by univariate and multivariate logistic regression, and the nomogram built on these variables showed good performance (optimism-corrected c-statistic = 0.921). The combined predictive model increased the POF accuracy with an AUC 0.925 (95% CI 0.894-0.956), a net reclassification improvement of 0.3024 (95% CI: 0.1482-0.4565, P 0.001), and an integrated discrimination index of 0.11 (95% CI 0.0497-0.1703; P 0.001).Plasma GDF15 measured within 48 h of symptom onset could help predict POF and mortality in AP patients.

Preamble detection is an important yet challenging task for underwater acoustic communications. The received preamble is distorted by unknown multipath propagation, severe Doppler scaling effect, various noise, and external interference in underwater scenarios. In this letter, we propose a cyclic feature detector using a Zadoff–Chu sequence by exploiting its cyclic features. The Doppler scale information is carried by these cyclic features. The proposed detector can bypass the requirement of channel information and is robust to carrier frequency offset. Moreover, it can deal with noise uncertainty and impulsive interference. Simulation and experimental results show that the proposed detector significantly outperforms the state of the art in detection performance.

Essentially, the performance improvement of automotive systems is a multi-objective optimization problem [1–4] due to the challenges in both operation management and control. The interconnected dynamics inside the automotive system normally requires precise tuning and coordination of accessible system inputs. In the past, such optimization problems have been approximately solved through expensive calibration procedures or an off-line local model-based approaches where either a regressive model or a first-principle model is used. The model-based optimization provides the advantage of finding the optimal model parameters to allow the model to be used to predict the real system behavior reasonably [5]. However, other than the model complexities, there are practically two issues facing the integrity of these models: modeling uncertainty due to inaccurate parameter values and/or unmodeled dynamics, and locally effective range around operating points. As a result, the optimum solutions extracted from the model-based approach could be subject to failure of expected performance [6].

Endoscopic ultrasound (EUS), an interventional imaging technology, utilizes a circular array to delineate the cross-sectional morphology of internal organs through the gastrointestinal (GI) track. However, the performance of conventional EUS transducers has scope for improvement because of the ordinary piezoelectric parameters of Pb(Zr, Ti) $\text{O}_{{3}}$ (PZT) bulk ceramic as well as its inferior mechanical flexibility which can cause material cracks during the circular shaping process. To achieve both prominent imaging capabilities and high device reliability, a 128-element 6.8-MHz circular array transducer is developed using a Pb(Mg $_{\text {1/3}}$ Nb $_{\text {2/3}}$ ) $\text{O}_{{3}}$ -PbTiO3 (PMN-PT) 1–3 composite with a coefficient of high electromechanical coupling ( ${k}_{{\text {t}}} \sim 0.78$ ) and good mechanical flexibility. The characterization results exhibit a large average bandwidth of 58%, a high average sensitivity of 100 mVpp, and a crosstalk of less than −37 dB near the center frequency. Imaging performance of the PMN-PT composite-based array transducer is evaluated by a wire phantom, an anechoic cyst phantom, and an ex-vivo swine intestine. This work demonstrates the superior performance of the crucial ultrasonic device based on an advanced PMN-PT composite material and may lead to the development of next-generation biomedical ultrasonic devices for clinical diagnosis and treatment.

Extremum seeking (ES) is a model-free optimization method that has been successfully applied to the automotive engine calibration. However, the slow convergence speed of ES algorithms presents a concern for the online application of this approach to engine optimization where time constraint is critical. In this paper, a model-guided ES architecture is proposed and is showcased with fuel injection optimization for a diesel engine at different operating points. In particular, by integrating a computable engine model into the ES scheme and monitoring the operation point online, the optimal combustion phase under the current operating point can be estimated and this estimation serves as the initialization of the online optimization, resulting in significantly shortened convergence time of ES. The effectiveness of the model-guided ES scheme is validated in the fuel injection optimization design, where the injection timing is controlled to achieve the best compromise between the diesel engine thermal efficiency and the in-cylinder peak pressure rise rate, with both experiments and simulation results presented.

In this paper, a multi-step-ahead predictive control approach for dynamic systems with preceded backlash-like hysteresis based on nonsmooth nonlinear programming is proposed. In this approach, a nonsmooth multi-step-ahead predictive model is developed for long-range prediction of the controlled dynamic systems with preceded backlash-like hysteresis. Then, the predictive control strategy is treated as a problem of on-line nonsmooth nonlinear programming. Subsequently, the stability of the nonsmooth predictive control system is analyzed and the corresponding stability condition is derived. Afterward, a numerical example and a simulation based on a mechanical servo system are presented, respectively.

This paper presents an identification approach for electromagnetic micro-mirrors using data-driven model with hysteresis. Usually, linear models are applied to modeling of electromagnetic micro-mirrors. However, from the experimental results, it can find that hysteresis phenomenon exists in the electromagnetic micro-mirror. Thus, it is not proper for using the linear model for modeling of electromagnetic micro-mirror. In this paper, a data-driven model with hysteresis is proposed for modeling the performance of electromagnetic micro-mirrors. In this model, a linear dynamic submodel is employed to model the deflection mechanism, whilst a dynamic hysteresis submodel is used to describe the hysteresis phenomenon in the electromagnetic actuating mechanism of the micro-mirror. One of the challenges of identification for electromagnetic micro-mirror is the electromagnetic torque cannot be measured directly. For handling this problem, a so-called predictive identification algorithm is applied to parameter estimation of the model. The effect of random noise on the identification is also considered. Then, the paper also presents the experimental results of modeling an electromagnetic micro-mirror.

In this paper, a modeling method for electromagnetically-actuated micro-mirror using measured input and output data is presented. For the description of the behavior of micro-mirror, a Hammerstein model involved with hysteresis is proposed. In the Hammerstein model, the deflection mechanism is depicted by a linear dynamic model while the electromagnetic hysteresis is described by a modified Prandtl-Ishlinskii model. Subsequently, a recursive identification algorithm is applied for parameter estimation of the model. Then, the experimental results of modeling an electromagnetic micro-mirror are presented.

This paper presents a new extremum seeking control (ESC) that is able to handle a class of unknown actuator hysteresis in the form of the Bouc-Wen Model with unknown parameters. By inserting high frequency dither signals to the actuator, the main result shows that the output of the overall system, which consists of the dynamic plant, the ESC block, and the actuator with hysteresis, can still achieve semi-global practical asymptotic stability provided that the frequency and the amplitude of the dither signals are selected appropriately. Simulation results support the theoretic findings.

This work demonstrates the application of the extremum seeking method for model calibration. A nonlinear, first-principle engine model is simplified for implementation in real-time control. A semi-empirical correlation is used for estimation of the wall heat transfer in the simplified engine model. The heat transfer coefficient is tuned using the extremum seeking approach to minimize the error between measurement and modeled cylinder pressure. Engine steady state measurement results are used for the demonstration and validation of the proposed technique.

Exhaust Gas Recirculation (EGR) is common on most modern diesel engines resulting in significant reduction of NOx emissions. Heavy EGR application is an enabling technique for the advanced combustion modes operating in the low temperature combustion (LTC) regime, wherein simultaneous NOx and soot emission reduction can be attained. The primary effect of EGR is the dilution of the intake charge following the displacement of fresh air by the combustion products. However, the correlation between EGR and its effectiveness is non-linear due to the lean burn nature of boosted diesel engines. This correlation is further complicated when oxygenated fuels are used for combustion in the LTC mode. In this work, the intake oxygen concentration [O2]int is selected as a representative of EGR and its effectiveness in emission abatement is shown using an array of experimental results. An EGR characterization model is developed to quantify the dynamic interaction between [O2]int and engine operating variables, namely the intake boost, exhaust gas recirculation (EGR) amount, the fueling quantity and the fuel type. The model is validated on the research engine platform in steady state and transient tests. Finally, the control of EGR effectiveness is experimentally demonstrated to achieve ultra-low NOx emissions at different engine operating points.

The position control of an Electronic Throttle Body (ETB) is challenging due to its nonlinear characteristics of input and output relation. In this work, the control of ETB is first accomplished by applying a data-driven optimization method-Extremum Seeking (ES). Experimental results are presented to demonstrate the effectiveness of the ES control approach.

A model of Wiener structure is presented in this work to represent the characteristics of an electronic throttle body. The proposed model consists of a linear submodel, which is used to capture the electric motor dynamics of the throttle body, and a nonlinear submodel, which is used to represent the nonlinearities in friction and spring torques. The relationship between the proposed model and the physics based model is analyzed. Model parameter identification and validation are demonstrated using open-loop measurement data.