Experimental Study and Numerical Study on Shear Bearing Capacity of Shear Key Joints of Reinforced Concrete Open-Web Sandwich Plates

The shear key in the reinforced concrete open-web sandwich plate (RCOSP) is a block joint that connects with the top chord and the bottom chord. In order to understand the failure mode of the shear key and verify the accuracy of the current algorithm, a total of 9 test pieces are prepared and classified 3 groups were assigned longitudinal reinforcement (LR) ratios of 0.49%, 0.82%, and 1.24%, respectively. The horizontal concentrated static loading under simple support condition is carried out. The test results show that the shear key is horizontally cut and the concrete is pulled apart or crushed along the direction of chord width at the shear key-chords area; the strain level of the concrete and stirrup of the shear key is lower averagely; the development of the horizontal displacement and the strain of the longitudinal bars of the test pieces goes through elastic, elastoplastic, and plastic stages; the ultimate load of the test pieces has almost no relationship with the reinforcement ratio of shear key but is controlled by the degree of crack development in the area where shear key connects with the chords. To avoid the current algorithm overestimating the shear capacity of shear key, the restricted condition of shear section is proposed. The finite element analysis (FEA) further verifies that the restricted condition of shear section proposed in this paper is reasonable and necessary.

TWO-LEAD JOINT DETECTION ALGORITHM OF QRS COMPLEXES IN ECG SIGNAL

Objective: The detection of QRS complexes is an important part of computer-aided analysis of electrocardiogram (ECG). However, most of the existing detection algorithms are mainly for single-lead ECG signals, which requires high quality of signal. If the signal quality decreases suddenly due to some interference, then the current algorithm is easy to cause misjudgment or missed detection. To improve the detection ability of QRS complexes under sudden interference, we study the QRS complexes information on multiple leads in-depth, and propose a two-lead joint detection algorithm of QRS complexes. Methods: Firstly, the suspected QRS complexes are screened on the main lead. For the suspected QRS complexes with low confidence and the complexes that may be missed, further accurate detection and joint judgment shall be carried out at the corresponding position of the auxiliary lead. At the same time, the adaptive threshold adjustment algorithm and backtracking mechanism are used to modify the detection results. Results: The proposed detection algorithm is validated using 48 ECG records of the MIT-BIH arrhythmia database, and achieves average detection accuracy of 99.71%, sensitivity of 99.88% and positive predictivity of 99.81%. Conclusion: The proposed algorithm has high accuracy, which can effectively deal with the sudden interference of ECG signal. Meanwhile, the algorithm requires small amount of computation, and can be embedded into hardware for real-time detection.

Practical Wisdom, Rules, and the Patient-Doctor Conversation

One of the aspirations of today’s standard algorithm for clinical decision making is to avoid physician paternalism. This chapter argues that this aspiration is in tension with what often actually happens at the bedside. The chapter suggests further that what actually happens may be preferable to the rigorous exclusion of paternalism. The current algorithm for bedside decision making has had the effect of limiting the scope for the exercise of the physician’s practical wisdom. Although the physician’s exercise of practical wisdom can verge on paternalism, it can also help patient and physician jointly arrive at the best decision, all things considered. Such an exercise of practical wisdom is what many patients expect and what excellent clinical practice requires. The chapter explores the tension between these competing claims on physician conduct in the care of patients.

Rapid and Accurate Data Processing for Silver Nanoparticle Oxidation in Nano-Impact Electrochemistry

In recent years, nano-impact electrochemistry (NIE) has attracted widespread attention as a new electroanalytical approach for the analysis and characterization of single nanoparticles in solution. The accurate analysis of the large volume of the experimental data is of great significance in improving the reliability of this method. Unfortunately, the commonly used data analysis approaches, mainly based on manual processing, are often time-consuming and subjective. Herein, we propose a spike detection algorithm for automatically processing the data from the direct oxidation of sliver nanoparticles (AgNPs) in NIE experiments, including baseline extraction, spike identification and spike area integration. The resulting size distribution of AgNPs is found to agree very well with that from transmission electron microscopy (TEM), showing that the current algorithm is promising for automated analysis of NIE data with high efficiency and accuracy.

Research on 1/0, 0/0, 0^0 and Complete Theorem of 1/0-1/0=0/0-0^0

It is known that 0 cannot be taken as a denominator which not only leads to 1/0, 0/0, and 0^0 as meaningless but also compels many functions to appear discontinuous while numerous existing formulas would be subjected to restrictions. More importantly, the research on mathematics is also restricted to a certain extent in terms of their direction. Therefore, it is of great significance to endow 0 as a denominator in perfecting the current algorithm to solve a series of problem in the mathematics field that has been persistently present for a long time, to fill in many research gaps that have been neglected, as well as to elevate mathematical research to a higher level.

Can we detect fibrofatty band in patients with bowel obstruction on CT scan?

Fibrofatty bands are composed of adipose tissue and connective tissue and can tangle around the bowel and caused intestinal obstruction. Currently, there is a lack of radiological teaching or guidance on how to identify fibro-fatty band in patients with bowel obstruction. The true incidence of fibrofatty band induced bowel obstruction is likely to have been overlooked. We present a case series of patients with fibrofatty bands with different features and aim to highlight key radiological findings that may help in the radiological diagnosis. We advocate that these features should be incorporated into the current algorithm for radiologist when assessing scan images of patients with intestinal obstruction.

Improvements to the use of the Trajectory-Adaptive Multilevel Sampling algorithm for the study of rare events

The Trajectory-Adaptive Multilevel Sampling (TAMS) is a promising method to determine probabilities of noise-induced transition in multi-stable high-dimensional dynamical systems. In this paper, we focus on two improvements of the current algorithm related to (i) the choice of the target set and (ii) the formulation of the score function. In particular, we use confidence ellipsoids determined from linearised dynamics in the choice of the target set. Furthermore, we define a score function based on empirical transition paths computed at relatively high noise levels. The suggested new TAMS method is applied to two typical problems illustrating the benefits of the modifications.

An Integrated Scheduling Algorithm for Multi-Device-Processes with the Strategy of Exchanging Adjacent Parallel Processes of The Same Device

The current integrated scheduling algorithm ignores the influence of the pre-process on the post-process when solving the multi-device-process integrated scheduling problem, which leads to the problem of poor tightness between serial processes and low parallelism between parallel processes. This paper points out that there is no restriction of scheduling sequence between adjacent parallel processes on the same processing device, and the scheduling sequence between parallel processes on the same device can be flexibly processed to optimize the scheduling results, on the basis of the current algorithm scheduling scheme, this paper proposes the application of multi-device adjacent parallel process interchange strategy and multi-device adjacent parallel process interchange adjustment strategy, which avoid the influence of the pre-process on the post-process, improves the compactness of the serial process and the parallelism of the parallel process, and optimizes the scheduling results.

Deep Learning approach to LHCb Calorimeter reconstruction using a Cellular Automaton

The optimization of reconstruction algorithms has become a key aspect in LHCb as it is currently undergoing a major upgrade that will considerably increase the data processing rate. Aiming to accelerate the second most time consuming reconstruction process of the trigger, we propose an alternative reconstruction algorithm for the Electromagnetic Calorimeter of LHCb. Together with the use of deep learning techniques and the understanding of the current algorithm, our proposal decomposes the reconstruction process into small parts that benefit the generalized learning of small neural network architectures and simplifies the training dataset. This approach takes as input the full simulation data of the calorimeter and outputs a list of reconstructed clusters in a nearly constant time without any dependency in the event complexity.

Non-Contact Heart Rate Detection When Face Information Is Missing during Online Learning

Research shows that physiological signals can provide objective data support for the analysis of human emotions. At present, non-contact heart rate data have been employed in the research of medicine, intelligent transportation, smart education, etc. However, it is hard to detect heart rate data using non-contact traditional methods during head rotation, especially when face information is missing in scenarios such as online teaching/learning. Traditional remote photoplethysmography (rPPG) methods require a static, full frontal face within a fixed distance for heart rate detection. These strict requirements make it impractical to measure heart rate data in real-world scenarios, as a lot of videos only partially record the subjects’ face information, such as profile, too small distance, and wearing a mask. The current algorithm aims to solve the problem of head deflections between 30 degrees and 45 degrees by employing a symmetry substitution method, which can replace the undetected region of interest (ROI) with the detectable one. When face information is partially missing, our algorithm uses face–eye location to determine ROI. The results show that the method in this paper can solve certain practical problems related to heart rate detection, with a root mean square error (RMSE) under 7.64 bpm.