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Sonic hedgehog acts as a key mitogen to drive cell proliferation and as a morphogen to direct cell differentiation during embryonic development and adult tissue maintenance by controlling the activities of its transcriptional effectors Glis. We previously reported that RNF220 controls the nuclear translocation and subcellular localization of Glis by promoting their K63-linked polyubiquitination, through which it fine tunes Shh/Gli gradients during ventral spinal cord patterning. RNF220 also epigenetically regulates Shh signaling by targeting epifactor EED in cerebellar development. Here, we continued to study the molecular events underlying RNF220-mediated Shh regulation in the cytoplasm. The results showed that HDAC6 is required for RNF220-induced Gli accumulation in the cytoskeletal fraction and inclusion in aggresomes. In the cytoplasm, Glis polyubiquitinated by RNF220 are prone to interact with p62 and destined for autophagy-mediated degradation. Additionally, we showed that RNF220 inhibits the processing of Gli2 and Gli3 both in vitro and in vivo. Collectively, our studies shed new light on Shh signaling regulation.

Sonic hedgehog (Shh) signaling is essential for the proliferation of cerebellar granule neuron progenitors (CGNPs), and its misregulation is linked to various disorders, including cerebellar cancer medulloblastoma (MB). During vertebrate neural development, RNF220, a ubiquitin E3 ligase, is involved in spinal cord patterning by modulating the subcellular location of glioma-associated oncogene homologs (Glis) through ubiquitination. RNF220 is also required for full activation of Shh signaling during cerebellum development in an epigenetic manner through targeting embryonic ectoderm development. ZC4H2 was reported to be involved in spinal cord patterning by acting as an RNF220 stabilizer. Here, we provided evidence to show that ZC4H2 is also required for full activation of Shh signaling in CGNP and MB progression by stabilizing RNF220. In addition, we found that the ubiquitin E3 ligase RING finger LIM domain-binding protein (RLIM) is responsible for ZC4H2 stabilization via direct ubiquitination, through which RNF220 is also thus stabilized. RLIM is a direct target of Shh signaling and is also required for full activation of Shh signaling in CGNP and MB cell proliferation. We further provided clinical evidence to show that the RLIM‒ZC4H2‒RNF220 cascade is involved in Shh-group MB progression. Disease-causative human RLIM and ZC4H2 mutations affect their interaction and regulation. Therefore, our study sheds light on the regulation of Shh signaling during cerebellar development and MB progression and provides insights into neural disorders caused by RLIM or ZC4H2 mutations.

To enable high speed and reliable transmission for non-line-of-sight scenarios in 60GHz millimeter-wave wireless personal area networks, a novel relaying-assisted network model with asymmetrical transceiver architecture is considered. Based on the asymmetrical transceiver architectures, we propose a new analog and digital hybrid beamforming protocol, in which relay is capable of both phase and amplitude modification, while user terminals are only enable to shifter phases. The proposed protocol targets to reduce computational complexity and cost, and to increase precision for beamforming without a priori knowledge of channel state information or relying on high antenna configurations. Through numerical simulations, we confirm that the proposed solution shows the system performances on channel gain, coverage probability and spectral efficiency, surpassing analogonly beamforming without increasing algorithm complexity.

Data collection is a basic application of wireless sensor networks, where every sensor node collects data and then forwards data to the Sink node through a multi-hop path. In traditional TDMA scheduling, sensors consume extra energy because of the state transitions which occur numerous times in a TDMA frame. And the longer the length of a TDMA frame, the longer duration of a data collection and the larger of time latency. For the problem mentioned above, Slot Reuse Continuous Link Scheduling problem is proposed in this paper, and then formalized into a cross-layer optimization problem involving the network, medium access control, and physical layers with the objective of maximizing the energy efficiency. We transform the problem into two sub-problems: constructing a data collection tree; joint power control and link scheduling for the data collection tree. Based on an existing data collection tree, we propose an algorithm for allocating a continuous slot and transmission power on every link. Simulation results show that the proposed algorithm can shorten the duration of a data collection process, reduce the number of state transitions and energy consumption, improve network energy efficiency when compared with other existing data collection strategies.

We present optimization algorithm for relay (RLY) selection and, source (SRC) and RLY power allocations in a cooperative multicast millimeter-wave (mmWave) system with non-line-of-sight (non-LoS) sensing. We show that there is a significant benefit to the system outage performance by allocating powers for the SRC and the RLYs selected from the candidates availing of line-of-sight (LoS) paths. Specifically, we consider the joint optimization of RLY selection, and, SRC and RLY power allocations to minimize the largest outage probability among all the common-multicast group (co-MGroup) users. The joint optimization problem is non-convex and the complexity of finding the optimal solution is extremely high. Using the dual-step iterative optimization (DIO) algorithm, the joint problem is decomposed into a non-convex RLY selection, and, a convex SRC and RLY power allocation problem. By exploiting the search method and the Lagrange multipliers algorithm, we present efficient algorithms that yield the optimal solutions for both RLY selection (non-convex) and, SRC and RLY power allocation problems. The simulation results indicate significant improvements both on outage probability and power consumption performances over the traditional two-stage multicasting.

In this work, we consider outage performance for a 5G wireless cellular network consisting of multiple cooperative multicast groups (MGroups) under kinds of fading channels, which allows users adhering to different MGroups can be served simultaneously. Based on the law of total probability theory, we first propose a new analytical approach to derive a new probability density equality lemma, which can be used to upper bound average outage probability of multiple MGroups (MMGroups) systems with interference-aware spectrum sharing transmissions in the case that interference channel state information (CSI) is known. After then, based on the proposed probability density equality lemma, we also analyze average outage probability upper bound under kinds of fading channels with inter-MGroup interferences. The simulated results reveal that the derived upper bounds indeed provide upper bounds over the average outage probability of MMGroups systems operated on kinds of fading channels, and these bounds become tight when interferences decrease or outage thresholds drop.

Shore-hoisting motor in the daily work will produce a large number of vibration signal data,in order to analyze the correlation among the data and discover the fault and potential safety hazard of the motor, the data are discretized first, and then Apriori algorithm are used to mine the strong association rules among the data. The results show that the relationship between day 1 and day 16 is the most closely related, which can guide the staff to analyze the work of these two days of motor to find and solve the problem of fault and safety.

Web page content extraction is a fundamental step in the application of data mining which supplies pure data source with little noise. The original web page with fully embedded with contentirrelevant information such as JavaScript and advertisements is mixed with noise. The purity of the data makes a difference in application. Consequently, a web information extraction model based on statistical and positional relationship between the title and content is proposed in this paper. The exact localization of title will promote the precision of content extraction and inversely the accurate extracted content will have a positive feedback to ensure the right title is extracted. First and foremost, each text node is compared to the content selected from the tag of title to get the score of similarity. We can get the final score of each separate node by summing up its node attribute score. The node with the highest score will be regarded as the accurate title at present. According to the position of title, we narrow the scope of main content which is distributed after the title. With the help of statistical information of the web page we then traverse the DOM tree to obtain the content contained in the node with maximal weight. Experimental results prove that the algorithm is much better than that of previous extraction rules and applicable to extract main content from web pages.