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Background: Stereo-vision-based three-dimensional coordinates measurement technology has been widely applied in the military or civil fields. There are two problems that need to be solved. The first problem is that each camera’s internal parameters and the two cameras' external parameters need to be calibrated. To increase the measurement range, usually, the turntable is used with the stereo vision system together. The second problem is the calibration of the turntable. Objective: The aim of the study is to construct and calibrate a stereo-vision-based coordinates measurement system via a two-axis turntable. Methods: Considering that the internal parameters of each camera do not change during the measurement process and the complicated optimization process of one-step self-calibration, a two-step stereo vision calibration method is proposed. In the first step, we calibrate the internal parameters of each camera through a specially designed planar target with circular points. In the second step, on the basis of the calibrated results of the internal parameters, the two cameras' external parameters are calibrated through a simple target which could be distributed in the measurement volume. For the calibration of the two-axis turntable, we calibrated the rotation axes of the turntable and the coordinates of points in the 3D space could be measured considering the non-orthogonality of the axes. Results: Some experiments are provided to examine the calibration methods we proposed. They are the plane target measurement experiments; the standard ball center coordinates measurement experiments and target pose measurement experiments. Experiment results demonstrate the superiority of the calibration method we proposed. Conclusion: We studied the calibration methods of the stereo-vision-based coordinates measurement system via a two-axis turntable. The experimental results show the measurement accuracy of our system is less than 0.1mm.

Appropriate embryo-uterine interactions are essential for implantation. Besides oocyte abnormalities, implantation failure is a major contributor to early pregnancy loss. Previously, we demonstrated that two members of the Iroquois homeobox transcription factor family, IRX3 and IRX5, exhibited distinct and dynamic expression profiles in the developing ovary to promote oocyte and follicle survival. Elimination of each gene independently caused subfertility, but with different breeding pattern outcomes. Irx3 KO (Irx3LacZ/LacZ) females produced fewer pups throughout their reproductive lifespan which could only be partially explained by poor oocyte quality. Thus, we hypothesized that IRX3 is also expressed in the uterus where it acts to support pregnancy. To test this hypothesis, we harvested pregnant uteri from control and Irx3 KO females to evaluate IRX3 expression profiles and the integrity of embryo implantation sites. Our results indicate that IRX3 is expressed in the endometrial stromal cells at day 4 of pregnancy (D4) with peak expression at D5–D6, and then greatly diminishes by D7. Further, studies showed that while embryos were able to attach to the uterus, implantation sites in Irx3 KO pregnant mice exhibited impaired vascularization and abnormal expression of decidualization markers. Finally, we also observed an impaired response of the Irx3 KO uteri to an artificial deciduogenic stimulus, indicating a critical role of this factor in regulating the decidualization program. Together, these data established that IRX3 promotes female fertility via at least two different mechanisms: (1) promoting competent oocytes and (2) facilitating functional embryo–uterine interactions during implantation.

Objective: To improve the delivery efficiency of spot scanning proton therapy by simultaneously reducing the number of spots and energy layers using the reweighted $l_1$ regularization method. Approach: We formulated the proton treatment planning problem as a convex optimization problem with a cost function consisting of a dosimetric plan quality term plus a weighted $l_1$ regularization term. We iteratively solved this problem and adaptively updated the regularization weights to promote the sparsity of both the spots and energy layers. The proposed algorithm was tested on four head-and-neck patients, and its performance, in terms of reducing the number of spots and energy layers, was compared with existing standard $l_1$ and group $l_2$ regularization methods. We also compared the effectiveness of the three methods ($l_1$, group $l_2$, and reweighted $l_1$) at improving plan delivery efficiency without compromising dosimetric plan quality by constructing each of their Pareto surfaces charting the trade-off between plan delivery and plan quality. Main results: The reweighted $l_1$ regularization method reduced the number of spots and layers by an average of 40% and 35%, respectively, with an insignificant cost to dosimetric plan quality. From the Pareto surfaces, it is clear that reweighted $l_1$ provided a better trade-off between plan delivery efficiency and dosimetric plan quality than standard $l_1$ or group $l_2$ regularization, requiring the lowest cost to quality to achieve any given level of delivery efficiency. Significance: Reweighted $l_1$ regularization is a powerful method for simultaneously promoting the sparsity of spots and energy layers at a small cost to dosimetric plan quality. This sparsity reduces the time required for spot scanning and energy layer switching, thereby improving the delivery efficiency of proton plans., Comment: 27 pages, 7 figures

Yanxia Huang,1,2,* Jiatong Lin,1,3,* Weimin Yi,1,2,* Qinghua Liu,1,4 Linhui Cao,1,2 Yongcong Yan,1,4 Anqi Fu,5 Tingxuan Huang,5 Yingcheng Lyu,1,3 Qihui Huang,1,2 Jie Wang1,4 1Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People’s Republic of China; 2Department of Traditional Chinese Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People’s Republic of China; 3Department of Thoracic Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People’s Republic of China; 4Department of Hepatobiliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People’s Republic of China; 5Sun Yat-Sen University Zhongshan School of Medicine, Guangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jie WangDepartment of Hepatobiliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Yanjiang West Road 107#, Guangzhou 510120, People’s Republic of ChinaEmail jiewsysu@163.comQihui HuangDepartment of Traditional Chinese Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Yanjiang West Road 107#, Guangzhou 510120, People’s Republic of ChinaEmail hqhui84181833@sina.comBackground: Gastric cancer was still one of the commonly diagnosed cancer types and the third-most common cause of cancer-related death in the world. Gentiopicroside, which is extracted from the Gentianella acuta, is commonly used in both traditional treatment and modern clinical care; therefore, its anticancer effects have been attracted more attention. However, the systematic analysis of action mechanism of Gentiopicroside on gastric cancer (GC) has not yet been carried out.Aim: A network pharmacology-based strategy combined with molecular docking studies and in vitro validation was employed to investigate potential targets and molecular mechanism of Gentiopicroside against GC.Materials and Methods: Potential targets of Gentiopicroside, as well as related genes of GC, were acquired from public databases. Potential targets, and signaling pathways were determined through bioinformatic analysis, including protein–protein interaction (PPI), the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, molecular docking and cell experiments were performed to further verify the above findings.Results: Our findings revealed that the anticancer activity of Gentiopicroside potentially involves 53 putative identified target genes. In addition, GO, KEGG, and network analyses revealed that these targets were associated with cell proliferation, metabolic process, and other physiological processes. Furthermore, we have proved that critical compound affected the expression of CCND1, CCNE1, p-AKT and p-P38 at protein levels. These findings provide an overview of the anticancer action of Gentiopicroside from a network perspective; meanwhile, it might also set an example for future studies of other materials used in traditional Chinese medicine (TCM).Conclusion: This study comprehensively illuminated the potential targets and molecular mechanism of Gentiopicroside against GC. It also provided a promising approach to uncover the scientific basis and therapeutic mechanism of TCM treating for disease.Keywords: Gentiopicroside, gastric cancer, mechanism, network pharmacology, molecular docking

Industrial Control Systems (ICS) are evolving with advances in new technology. The addition of wireless sensors and actuators and new control techniques means that engineering practices from communication systems are being integrated into those used for control systems. The two are engineered in very different ways. Neither engineering approach is capable of accounting for the subtle interactions and interdependence that occur when the two are combined. This paper describes our first steps to bridge this gap, and push the boundaries of both computer communication system and control system design. We present The Separator testbed, a Cyber-Physical testbed enabling our search for a suitable way to engineer systems that combine both computer networks and control systems., 6 pages, 4 figures

Periodic event-triggered control (PETC) is a version of event-triggered control (ETC) that only requires to measure the plant output periodically instead of continuously. In this work, we present a construction of timing models for these PETC implementations to capture the dynamics of the traffic they generate. In the construction, we employ a two-step approach. We first partition the state space into a finite number of regions. Then in each region, the event-triggering behavior is analyzed with the help of LMIs. The state transitions among different regions result from computing the reachable state set starting from each region within the computed event time intervals.

Energy constraint long-range wireless sensor/ actuator based solutions are theoretically the perfect choice to support the next generation of city-scale cyber-physical systems. Traditional systems adopt periodic control which increases network congestion and actuations while burdens the energy consumption. Recent control theory studies overcome these problems by introducing aperiodic strategies, such as event trigger control. In spite of the potential savings, these strategies assume actuator continuous listening while ignoring the sensing energy costs. In this paper, we fill this gap, by enabling sensing and actuator listening duty-cycling and proposing two innovative MAC protocols for three decentralized event trigger control approaches. A laboratory experimental testbed, which emulates a smart water network, was modelled and extended to evaluate the impact of system parameters and the performance of each approach. Experimental results reveal the predominance of the decentralized event-triggered control against the classic periodic control either in terms of communication or actuation by promising significant system lifetime extension.

From the perspective of the limited energy in wireless visual sensor networks, based on the lifting wavelet transform method run in the elimination mode and SPECK coding by skipping some high-frequency sub-bands, an energy effective image compression coding method is proposed according to the adaptive requirement of the image quality and energy consumption. The experiments show that the method has a good effect on energy conservation, which is more obvious in the image transmission at low bit rate.