Spectrum preprocessing is an essential component in the near‐infrared (NIR) calibration. However, it has mostly been configured arbitrarily in the literature and calibration applications. In this paper, a systematic evaluation framework was proposed to quantify the effect of preprocessing, where repeated cross‐validation and evaluation are involved. As many as 108 preprocessing schemes were gathered from the literature and were tested on 26 different NIR calibration problems. Using the evaluation framework, appropriate schemes can be found for several datasets, reducing the root mean square error of prediction (RMSEP) by 50%–60% compared with using the raw spectrum. However, the influence of preprocessing is highly data‐dependent, and no universal solution could be found. Taking the effectiveness and correlation into consideration, Savitzky‐Golay (SG), SG1D, and SG1D + vector normalization (VN)(/standard normal variate [SNV]) are worth testing first. Nevertheless, the heterogeneity at both the dataset level and sample level demonstrated the necessity of a complete evaluation. Our scripts are available at https://github.com/jiaoyiping630/spectrum-preprocessing.

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Background Although right ventricular ( RV ) volume was significantly decreased in symptomatic patients with repaired tetralogy of Fallot ( rTOF ) after pulmonary valve replacement ( PVR ), RV size was still enlarged along with RV dysfunction. Methods and Results A prospective case‐control study was conducted in a tertiary hospital; 81 asymptomatic repaired tetralogy of Fallot patients with moderate or severe pulmonary regurgitation were enrolled. The enrolled cohort was divided into 2 groups: PVR group (n=41) and medication group (n=40). Cardiac magnetic resonance, transthoracic echocardiography, and electrocardiography were scheduled after recruitment and 6 months after PVR or recruitment. Adverse events were recorded during follow‐up. Three deaths, 1 heart transplantation, 3 PVR s, and 2 symptomatic heart failures in medication group and 1 redo PVR in the PVR group were observed during follow‐up. Compared with the medication group, the PVR group had significantly lower adverse events rate ( P =0.023; odds ratio, 0.086; 95% CI, 0.010–0.716), and RV function was significantly improved ( P <0.05). Binary logistic regression analysis identified preoperative RV end‐systolic volume index (10‐mL/m 2 increment, P =0.009; odds ratio, 0.64; 95% CI, 0.457–0.893) was an independent predictor of normalization of RV size after PVR . A preoperative RV end‐systolic volume index cut‐off value of 120 mL/m 2 (area under curve, 0.819; sensitivity, 90.3%; specificity, 70%) was analyzed by receiver operating characteristic curves for normalized RV size after PVR . Conclusions PVR in asymptomatic repaired tetralogy of Fallot patients is appropriate and effective in reducing right ventricular size and preserving right ventricular function. The recommended criterion of RV end‐systolic volume index for PVR is 120 mL/m 2 .

In networks-on-chip (NoC) designs, delay variations and crosstalk noise have become a serious issue with the continuously shrinking geometry of semiconductor devices and the increasing switching speed. The crosstalk between adjacent lines causes data dependent signal delay and noise, thus finally makes the communication channel unreliable. The crosstalk problem can be mitigated by wide spacing of serial lines, however, the wider spacing of serial lines will reduce the number of the lines, thus reduce the data throughput. In this paper, we propose a multi-path routing scheme to maximize the data throughput by utilizing multiple paths for concurrent data transmission. For the proposed multi-path routing scheme, we consider two transport models: the multi-path full bitbank transport model and the multi-path half bitbank transport model. Through theoretical analysis, we show that the proposed multi-path scheme achieves significant improvement in data throughput under both transport models.

With large-scale development of distributed generation (DG) and its potential role in microgrids, the microgrid cluster (MGC) becomes a useful control model to assist the integration of DG. Considering that microgrids in a MGC, power dispatch optimization in a MGC is difficult to achieve. In this paper, a hybrid interactive communication optimization solution (HICOS) is suggested based on flexible communication, which could be used to solve plug-in or plug-out operation states of microgrids in MGC power dispatch optimization. HICOS consists of a hierarchical architecture: the upper layer uses distributed control among multiple microgrids, with no central controller for the MGC, and the lower layer uses a central controller for each microgrid. Based on flexible communication links among microgrids, the optimal iterative information are exchanged among microgrids, thus HICOS would gradually converge to the global optimal solution. While some microgrids plug-in or plug-out, communication links will be changed, so as to unsuccessfully reach optimal solution. Differing from changeless communication links in traditional communication networks, HICOS redefines the topology of flexible communication links to meet the requirement to reach the global optimal solutions. Simulation studies show that HICOS could effectively reach the global optimal dispatch solution with non-MGC center. Especially, facing to microgrids plug-in or plug-out states, HICOS would also reach the global optimal solution based on refined communication link topology.