Study on a Kind of Simulation Training System of Photoelectric Theodolite

A kind of system of target simulation training of photoelectric theodolite is presented. On the basis of the experiment duties, almost 40 operation courses are set according to five modules, which are equipment operation, parameter testing, maintaining, troubleshooting and task flow. Modeling strategy of several kinds of aircraft track is studied and set. The modeling and controlling of the key parts of photoelectric theodolite are achieved with the software of UG and Unity3D. Then the fault waveform of the equipment failure is completed by the soft LabVIEW. With the software Eduis, the multimedia of the operation courses are done. Then scientific and reasonable assessment model is studied and set to evaluate the operation of the trainees. Finally, with the examples of the trainees exams and troops using, it shows the system of target simulation training of photoelectric theodolite meets the requirements

Study on a Kind of Simulation Training System of Photoelectric Theodolite

A kind of system of target simulation training of photoelectric theodolite is presented. On the basis of the experiment duties, almost 40 operation courses are set according to five modules, which are equipment operation, parameter testing, maintaining, troubleshooting and task flow. Modeling strategy of several kinds of aircraft track is studied and set. The modeling and controlling of the key parts of photoelectric theodolite are achieved with the software of UG and Unity3D. Then the fault waveform of the equipment failure is completed by the soft LabVIEW. With the software Eduis, the multimedia of the operation courses are done. Then scientific and reasonable assessment model is studied and set to evaluate the operation of the trainees. Finally, with the examples of the trainees exams and troops using, it shows the system of target simulation training of photoelectric theodolite meets the requirements

Research on Broadband Matching Method for Capacitive Micromachined Ultrasonic Transducers Based on PDMS/TiO2 Particles

The study of impedance matching between a transducer and its working medium is an important part of acoustic transducer design. The traditional quarter wavelength matching (Q-matching) scheme is not suitable for broadband capacitive micromachined ultrasonic transducers. To mitigate this issue, a 0–3 composite broadband matching layer based on polydimethylsiloxane (PDMS) substrate/TiO2 particles is designed to achieve electrical insulation and efficient acoustic energy transfer of underwater capacitive micromachined ultrasonic transducer (CMUT) devices. In this work, the coherent potential approximation model is used to analyze the properties of 0–3 composite materials. Samples are prepared for performance testing to determine the proportion of TiO2 particles that enable the 0–3 composite materials to have the same longitudinal acoustic impedance as water. The CMUT device is packaged by a spin coating and pouring process, and its performance tests are carried out. The experimental results show that the central frequency of the transducer remains at 1.74 MHz, the −6 dB fractional bandwidth increases from 97.3% to 100.3%, the 3 dB directional main beam width increases from 8.3° to 10.3°, the side lobes decrease significantly, and the device has good reception sensitivity. These values imply that the 0–3 composite material has good matching performance, and this matching scheme has the advantages of high efficiency and wide bandwidth. This broadband matching method endows CMUTs with great advantages in underwater detection systems, and it facilitates underwater ultrasonic imaging of CMUT

Deep learning for detecting cerebral aneurysms with CT angiography

Background: Cerebral aneurysm detection is a challenging task. Deep learning may become a supportive tool for more accurate interpretation. Purpose: To develop a highly sensitive deep learning-based algorithm that assists in the detection of cerebral aneurysms on CT angiography images. Materials and Methods: Head CT angiography images were retrospectively retrieved from two hospital databases acquired across four different scanners between January 2015 and June 2019. The data were divided into training and validation sets; 400 additional independent CT angiograms acquired between July and December 2019 were used for external validation. A deep learning-based algorithm was constructed and assessed. Both internal and external validation were performed. Jackknife alternative free-response receiver operating characteristic analysis was performed. Results: A total of 1068 patients (mean age, 57 years 6 11 [standard deviation]; 660 women) were evaluated for a total of 1068 CT angiograms encompassing 1337 cerebral aneurysms. Of these, 534 CT angiograms (688 aneurysms) were assigned to the training set, and the remaining 534 CT angiograms (649 aneurysms) constituted the validation set. The sensitivity of the proposed algorithm for detecting cerebral aneurysms was 97.5% (633 of 649; 95% CI: 96.0, 98.6). Moreover, eight new aneurysms that had been overlooked in the initial reports were detected (1.2%, eight of 649). With the aid of the algorithm, the overall performance of radiologists in terms of area under the weighted alternative free-response receiver operating characteristic curve was higher by 0.01 (95% CI: 0.00, 0.03). Conclusion: The proposed deep learning algorithm assisted radiologists in detecting cerebral aneurysms on CT angiography images, resulting in a higher detection rate

A Bayesian reanalysis of the Standard versus Accelerated Initiation of Renal-Replacement Therapy in Acute Kidney Injury (STARRT-AKI) trial

Background Timing of initiation of kidney-replacement therapy (KRT) in critically ill patients remains controversial. The Standard versus Accelerated Initiation of Renal-Replacement Therapy in Acute Kidney Injury (STARRT-AKI) trial compared two strategies of KRT initiation (accelerated versus standard) in critically ill patients with acute kidney injury and found neutral results for 90-day all-cause mortality. Probabilistic exploration of the trial endpoints may enable greater understanding of the trial findings. We aimed to perform a reanalysis using a Bayesian framework. Methods We performed a secondary analysis of all 2927 patients randomized in multi-national STARRT-AKI trial, performed at 168 centers in 15 countries. The primary endpoint, 90-day all-cause mortality, was evaluated using hierarchical Bayesian logistic regression. A spectrum of priors includes optimistic, neutral, and pessimistic priors, along with priors informed from earlier clinical trials. Secondary endpoints (KRT-free days and hospital-free days) were assessed using zero–one inflated beta regression. Results The posterior probability of benefit comparing an accelerated versus a standard KRT initiation strategy for the primary endpoint suggested no important difference, regardless of the prior used (absolute difference of 0.13% [95% credible interval [CrI] − 3.30%; 3.40%], − 0.39% [95% CrI − 3.46%; 3.00%], and 0.64% [95% CrI − 2.53%; 3.88%] for neutral, optimistic, and pessimistic priors, respectively). There was a very low probability that the effect size was equal or larger than a consensus-defined minimal clinically important difference. Patients allocated to the accelerated strategy had a lower number of KRT-free days (median absolute difference of − 3.55 days [95% CrI − 6.38; − 0.48]), with a probability that the accelerated strategy was associated with more KRT-free days of 0.008. Hospital-free days were similar between strategies, with the accelerated strategy having a median absolute difference of 0.48 more hospital-free days (95% CrI − 1.87; 2.72) compared with the standard strategy and the probability that the accelerated strategy had more hospital-free days was 0.66. Conclusions In a Bayesian reanalysis of the STARRT-AKI trial, we found very low probability that an accelerated strategy has clinically important benefits compared with the standard strategy. Patients receiving the accelerated strategy probably have fewer days alive and KRT-free. These findings do not support the adoption of an accelerated strategy of KRT initiation

Regional Practice Variation and Outcomes in the Standard Versus Accelerated Initiation of Renal Replacement Therapy in Acute Kidney Injury (STARRT-AKI) Trial: A Post Hoc Secondary Analysis.

ObjectivesAmong patients with severe acute kidney injury (AKI) admitted to the ICU in high-income countries, regional practice variations for fluid balance (FB) management, timing, and choice of renal replacement therapy (RRT) modality may be significant.DesignSecondary post hoc analysis of the STandard vs. Accelerated initiation of Renal Replacement Therapy in Acute Kidney Injury (STARRT-AKI) trial (ClinicalTrials.gov number NCT02568722).SettingOne hundred-fifty-three ICUs in 13 countries.PatientsAltogether 2693 critically ill patients with AKI, of whom 994 were North American, 1143 European, and 556 from Australia and New Zealand (ANZ).InterventionsNone.Measurements and main resultsTotal mean FB to a maximum of 14 days was +7199 mL in North America, +5641 mL in Europe, and +2211 mL in ANZ (p p p p p p p p = 0.007).ConclusionsAmong STARRT-AKI trial centers, significant regional practice variation exists regarding FB, timing of initiation of RRT, and initial use of continuous RRT. After adjustment, such practice variation was associated with lower ICU and hospital stay and 90-day mortality among ANZ patients compared with other regions