Clean relaying aided cognitive radio under the coexistence constraint

We consider the interference-mitigation based cognitive radio where the primary and secondary users can coexist at the same time and frequency bands, under the constraint that the rate of the primary user (PU) must remain the same with a single-user decoder. To meet such a coexistence constraint, the relaying from the secondary user (SU) can help the PU's transmission under the interference from the SU. However, the relayed signal in the known dirty paper coding (DPC) based scheme is interfered by the SU's signal, and is not "clean". In this paper, under the half-duplex constraints, we propose two new transmission schemes aided by the clean relaying from the SU's transmitter and receiver without interference from the SU. We name them as the clean transmitter relaying (CT) and clean transmitter-receiver relaying (CTR) aided cognitive radio, respectively. The rate and multiplexing gain performances of CT and CTR in fading channels with various availabilities of the channel state information at the transmitters (CSIT) are studied. Our CT generalizes the celebrated DPC based scheme proposed previously. With full CSIT, the multiplexing gain of the CTR is proved to be better (or no less) than that of the previous DPC based schemes. This is because the silent period for decoding the PU's messages for the DPC may not be necessary in the CTR. With only the statistics of CSIT, we further prove that the CTR outperforms the rate performance of the previous scheme in fast Rayleigh fading channels. The numerical examples also show that in a large class of channels, the proposed CT and CTR provide significant rate gains over the previous scheme with small complexity penalties.Comment: 30 page

Detecting Slow Wave Sleep Using a Single EEG Signal Channel

Background: In addition to the cost and complexity of processing multiple signal channels, manual sleep staging is also tedious, time consuming, and error-prone. The aim of this paper is to propose an automatic slow wave sleep (SWS) detection method that uses only one channel of the electroencephalography (EEG) signal. New Method: The proposed approach distinguishes itself from previous automatic sleep staging methods by using three specially designed feature groups. The first feature group characterizes the waveform pattern of the EEG signal. The remaining two feature groups are developed to resolve the difficulties caused by interpersonal EEG signal differences. Results and comparison with existing methods: The proposed approach was tested with 1,003 subjects, and the SWS detection results show kappa coefficient at 0.66, an accuracy level of 0.973, a sensitivity score of 0.644 and a positive predictive value of 0.709. By excluding sleep apnea patients and persons whose age is older than 55, the SWS detection results improved to kappa coefficient, 0.76; accuracy, 0.963; sensitivity, 0.758; and positive predictive value, 0.812. Conclusions: With newly developed signal features, this study proposed and tested a single-channel EEG-based SWS detection method. The effectiveness of the proposed approach was demonstrated by applying it to detect the SWS of 1003 subjects. Our test results show that a low SWS ratio and sleep apnea can degrade the performance of SWS detection. The results also show that a large and accurately staged sleep dataset is of great importance when developing automatic sleep staging methods

CCN2 Enhances Resistance to Cisplatin-Mediating Cell Apoptosis in Human Osteosarcoma

Osteosarcoma (OS) is the most common form of malignant bone tumor and is an aggressive malignant neoplasm exhibiting osteoblastic differentiation. Cisplatin is one of the most efficacious antitumor drugs for osteosarcoma patients. However, treatment failures are common due to the development of chemoresistance. CCN2 (also known as CTGF), is a secreted protein that binds to integrins, modulates the invasive behavior of certain human cancer cells. However, the effect of CCN2 in cisplatin-mediated chemotherapy is still unknown. Here, we found that CCN2 was upregulated in human osteosarcoma cells after treatment with cisplatin. Moreover, overexpression of CCN2 increased the resistance to cisplatin-mediated cell apoptosis. In contrast, reduction of CCN2 by CCN2 shRNA promoted the chemotherapeutic effect of cisplatin. We also found that CCN2 provided resistance to cisplatin-induced apoptosis through upregulation of Bcl-xL and survivin. Knockdown of Bcl-xL or survivin removed the CCN2-mediated resistance to apoptosis induced by cisplatin. On the other hand, CCN2 also promoted FAK, MEK, and ERK survival signaling pathways to enhance tumor survival during cisplatin treatment. In a mouse xenograft model, overexpression of CCN2 promoted resistance to cisplatin. However, knockdown of CCN2 increased the therapeutic effect of cisplatin. Therefore, our data suggest that CCN2 might be a critical oncogene of human osteosarcoma for cisplatin-resistance and supported osteosarcoma cell growth in vivo and in vitro

Peritoneal metastatic adenocarcinoma possibly due to a gastric duplication cyst: a case report and literature review

BACKGROUND: Gastric duplication cysts are rare congenital abnormalities, and malignant transformation of these duplications is also thought to be rare. CASE PRESENTATION: During a routine health checkup, a 28-year-old man underwent abdominal sonography followed by computed tomography (CT) with contrast agent, which revealed a cystic lesion with no enhancement. Laparoscopic surgery showed a 10 × 10 cm cyst adhering to the gastric corpus. However, attempts to remove the lesion en bloc were unsuccessful, and the ruptured cyst had contaminated the peritoneal cavity. Gastric duplication was diagnosed from microscopic examination of the cyst. Seven months later, the patient suffered a progressive increase in ascites, and repeated cytological analysis showed small nests of adenocarcinoma cells, with primary lesion unknown. Diagnostic laparoscopy showed multiple white nodules scattered over the surface of the liver, greater omentum, and peritoneum. Biopsy of the omental nodules confirmed adenocarcinoma, while carcinomatosis was diagnosed in the peritoneum. CONCLUSIONS: Clinical presentation and chronological developments indicated that the malignancy probably originated from the gastric duplication cyst. This case highlights the importance of accurate preoperative diagnosis and optimal surgical management for gastric duplication as well as considering the potential existence of malignant transformation during surgical evaluation of adult patients with gastric duplication cysts

Beating the Clauser-Horne-Shimony-Holt and the Svetlichny games with Optimal States

We study the relation between the maximal violation of Svetlichny's inequality and the mixedness of quantum states and obtain the optimal state (i.e., maximally nonlocal mixed states, or MNMS, for each value of linear entropy) to beat the Clauser-Horne-Shimony-Holt and the Svetlichny games. For the two-qubit and three-qubit MNMS, we showed that these states are also the most tolerant state against white noise, and thus serve as valuable quantum resources for such games. In particular, the quantum prediction of the MNMS decreases as the linear entropy increases, and then ceases to be nonlocal when the linear entropy reaches the critical points ${2}/{3}$ and ${9}/{14}$ for the two- and three-qubit cases, respectively. The MNMS are related to classical errors in experimental preparation of maximally entangled states.Comment: 7 pages, 3 figures; minor changes; accepted in Physical Review

Optimal estimation and control for lossy network: stability, convergence, and performance

In this paper, we study the problems of optimal estimation and control, i.e., the linear quadratic Gaussian (LQG) control, for systems with packet losses but without acknowledgment. Such acknowledgment is a signal sent by the actuator to inform the estimator of the incidence of control packet losses. For such system, which is usually called as a user datagram protocol (UDP)-like system, the optimal estimation is nonlinear and its calculation is time-consuming, making its corresponding optimal LQG problem complicated. We first propose two conditions: 1) the sensor has some computation abilities; and 2) the control command, exerted to the plant, is known to the sensor. For a UDP-like system satisfying these two conditions, we derive the optimal estimation. By constructing the finite and infinite product probability measure spaces for the estimation error covariances (EEC), we give the stability condition for the expected EEC, and show the existence of a measurable function to which the EEC converges in distribution, and propose some practical methods to evaluate the estimation performance. Finally, the LQG controllers are derived, and the conditions for the mean square stability of the closed-loop system are established

Design and frequency analysis of continuous finite-time-convergent differentiator

In this paper, a continuous finite-time-convergent differentiator is presented based on a strong Lyapunov function. The continuous differentiator can reduce chattering phenomenon sufficiently than normal sliding mode differentiator, and the outputs of signal tracking and derivative estimation are all smooth. Frequency analysis is applied to compare the continuous differentiator with sliding mode differentiator. The beauties of the continuous finite-time-convergent differentiator include its simplicity, restraining noises sufficiently, and avoiding the chattering phenomenon