Computing Offloading Based on TD3 Algorithm in Cache-Assisted Vehicular NOMA-MEC Networks.

In this paper, in order to reduce the energy consumption and time of data transmission, the non-orthogonal multiple access (NOMA) and mobile edge caching technologies are jointly considered in mobile edge computing (MEC) networks. As for the cache-assisted vehicular NOMA-MEC networks, a problem of minimizing the energy consumed by vehicles (mobile devices, MDs) is formulated under time and resource constraints, which jointly optimize the computing resource allocation, subchannel selection, device association, offloading and caching decisions. To solve the formulated problem, we develop an effective joint computation offloading and task-caching algorithm based on the twin-delayed deep deterministic policy gradient (TD3) algorithm. Such a TD3-based offloading (TD3O) algorithm includes a designed action transformation (AT) algorithm used for transforming continuous action space into a discrete one. In addition, to solve the formulated problem in a non-iterative manner, an effective heuristic algorithm (HA) is also designed. As for the designed algorithms, we provide some detailed analyses of computation complexity and convergence, and give some meaningful insights through simulation. Simulation results show that the TD3O algorithm could achieve lower local energy consumption than several benchmark algorithms, and HA could achieve lower consumption than the completely offloading algorithm and local execution algorithm.

Sensor Management Method of Giving Priority to Confirmed Identified Targets.

The optimization objective function of sensor management for target identification is commonly established based on information theory indicators such as information gain, discrimination, discrimination gain, and quadratic entropy, which can control the sensors to reduce the overall uncertainty of all targets to be identified but ignores the speed of target being confirmed as identified. Therefore, inspired by the maximum posterior criterion of target identification and the target identification confirmation mechanism, we study a sensor management method that preferentially allocates resources to identifiable targets. Firstly, in the distributed target identification framework based on Bayesian theory, an improved identification probability prediction method that provides feedback the global identification results to local classifiers is proposed, which can improve the accuracy of identification probability prediction. Secondly, an effective sensor management function based on information entropy and expected confidence level is proposed to optimize the identification uncertainty itself rather than its variation, which can increase the priority of targets that satisfy the desired confidence level. In the end, the sensor management for target identification is modeled as a sensor allocation problem, and the optimization objective function based on the effective function is constructed, which can improve the target identification speed. The experimental results show that the correct identification rate of the proposed method is comparable to the methods based on information gain, discrimination, discrimination gain, and quadratic entropy in different scenarios, but the average time to confirm the identification is the shortest.

CAAGP: Rethinking channel attention with adaptive global pooling for liver tumor segmentation.

Channel attention, a channel-wise method often used in computer vision tasks, including liver tumor segmentation tasks, is able to model the channel relationship to augment the representation ability of feature maps. Channel attention could adaptively generate channel-wise responses using global pooling, which aggregates spatial information roughly. Actually, global pooling may introduce the loss of fine information, which is vital for segmentation tasks. Hence, we rethink the problem and propose the channel attention with adaptive global pooling(short for CAAGP), which preserves spatial and fine-grained information for liver tumor segmentation tasks when channel attention is generated. The model consists of three main parts, including improved self-attention, adaptive global pooling and responses generation modules. Self-attention achieves excellent performance in the computing of the spatial attention, while introducing serious calculation and memory burdens. In order to remedy these burdens, we improve self-attention and consider aggregating spatial information from x and y directions respectively. Extensive experiments have been conducted to verify the effectiveness of our proposed method. Our CAAGP outperforms other attention mechanisms significantly in liver tumor segmentation, especially for tumors with small size.

miR-200c/PAI-2 promotes the progression of triple negative breast cancer via M1/M2 polarization induction of macrophage.

PURPOSE: To investigate the effect of miR-200c/PAI-2 on macrophage polarization into M2-type TAMs in TNBC. METHODS AND MATERIALS: PAI-2 expression in MDA-MB-231con, MDA-MB-231miR-200ab and MDA-MB-231miR-200c breast cancer cells was evaluated by RT-PCR and immunofluorescence (IF), while the expression of the TAM marker F4/80 and the M2-type TAM marker CD206 in MDA-MB-231con, MDA-MB-231miR-200c and MDA-MB-231miR-200c/siPAI-2 mouse lung metastatic tumor tissues was examined with immunohistochemistry (IHC). The effects of RAW264.7 cells on MDA-MB-231con, MDA-MB-231miR-200c and MDA-MB-231miR-200c/siPAI-2 were examined by transwell co-culture. CD206 expression in RAW264.7 cells were confirmed by immunostaining. The level of PAI-2 and IL-10 in the co-culture supernatants were assessed using ELISA. RESULTS: 1. RT-PCR and IF analysis showed that PAI-2 was upregulated in MDA-MB-231miR-200c cells. 2. IHC assays analysis showed that the numbers of F4/80 and CD206 positive cells were increased in MDA-MB-231miR-200c tumor tissues, while in MDA-MB-231miR-200c/siPAI-2 tumor tissues were decreased. 3. Transwell co-culture assays analysis showed that MDA-MB-231miR-200c cells significantly promoted the cell migration ability compared with the control group, while knockdown PAI-2 significantly inhibited the cell migration ability (P < 0.05). 4. Transwell co-culture and immunostaining assays analysis showed that overexpression miR-200c in MDA-MB-231 cell line increased the CD206 expression in RAW264.7 cells, while knockdown PAI-2 decreased. 5. ELISA assays analysis showed that miR-200c-mediated MDA-MB-231 cells significantly increased the secretion of PAI-2 and IL-10, while decreased the secretion of PAI-2 and IL-10 in MDA-MB-231 miR-200c/siPAI-2 cells. CONCLUSIONS: miR-200c promotes the malignant progressions of TNBC by PAI-2 upregulation and M2 phenotype macrophages polarization.

Robust Beamforming Design for Secure V2X Downlink System with Wireless Information and Power Transfer under a Nonlinear Energy Harvesting Model.

Vehicle to everything (V2X) has been deemed a promising technology due to its potential to achieve traffic safety and efficiency. This paper considers a V2X downlink system with a simultaneous wireless information and power transfer (SWIPT) system where the base station not only conveys data and energy to two types of wireless vehicular receivers, such as one hybrid power-splitting vehicular receiver, and multiple energy vehicular receivers, but also prevents information from being intercepted by the potential eavesdroppers (idle energy vehicular receivers). Both the base station and the energy vehicular receivers are equipped with multiple antennas, whereas the information vehicular receiver is equipped with a single antenna. In particular, the imperfect channel state information (CSI) and the practical nonlinear energy harvesting (EH) model are taken into account. The non-convex optimization problem is formulated to maximize the minimum harvested energy power among the energy vehicular receivers satisfying the lowest harvested energy power threshold at the information vehicular receiver and secure vehicular communication requirements. In light of the intractability of the optimization problem, the semidefinite relaxation (SDR) technique and variable substitutions are applied, and the optimal solution is proven to be tight. A number of results demonstrate that the proposed robust secure beamforming scheme has better performance than other schemes.

Connexin43 and AMPK Have Essential Role in Resistance to Oxidative Stress Induced Necrosis.

Reactive oxygen species (ROS) induced oxidative stress leads to cell damage and neurological disorders in astrocytes. The gap junction protein connexin43 (Cx43) could form intercellular channels in astrocytes and the expression of Cx43 plays an important role in protecting the cells from damage. In the present study, we investigated the contribution of Cx43 to astrocytic necrosis induced by the ROS hydrogen peroxide (H2O2) and the mechanism by which AMPK was involved in this process. Fluorescence microscopy, flow cytometry, and western blot were used quantitatively and qualitatively to determine the cell apoptosis, necrosis, and protein expression. Lack of Cx43 expression or blockage of Cx43 channels resulted in increased H2O2-induced astrocytic necrosis, supporting a cell protective effect of functional Cx43 channels. Our data suggest that AMPK is important for Cx43-mediated ROS resistance. Inhibition of AMPK activation results in reduction of necrosis and ROS production. Taken together, our findings suggest that the role of Cx43 in response to H2O2 stress is dependent on the activation of AMPK signaling pathways and regulates ROS production and cell necrosis.

Helicobacter pylori infection associated with type 2 diabetic nephropathy in patients with dyspeptic symptoms.

AIMS: The aim of this conventional case-control study was to investigate the prevalence and relationship between Helicobacter pylori infection in type 2 diabetes mellitus (DM) and diabetic nephropathy (DN). METHODS: A total of 241 type 2 DM patients and 69 non-diabetic subjects with dyspeptic symptoms were enrolled in the study. Gastroduodenal lesions were observed by gastrointestinal endoscopy and the presence of H. pylori was identified by rapid urease test and serum IgG antibodies to H. pylori. According to the urinary albumin excretion rate (UAE), patients were classified into diabetes mellitus group (DM group, with UAE <30 mg/24h); diabetic nephropathy group 1 (DN group 1, with UAE 30 mg/24 h to <300 mg/24 h); and diabetic nephropathy group 2 (DN group 2 ≥ 300 mg/24 h). The 69 non-diabetic subjects were used as control group. The serum levels of inflammatory factors such as tumor necrosis factor-α (TNF-α) and interleukin (IL)-8 were determined using ELISA. RESULTS: The prevalence of H. pylori infection in DN group 1 and DN group 2 was 45/72 (62.5%) and 34/53 (64.15%), respectively, which was significantly higher than in control [28/65 (43.1%)] and DM groups [42.9% (27/63)]. No significant differences of H. pylori prevalence were detected between DN groups as well as DM and control groups. Interestingly, in both DN groups, higher levels of IL-8, TNF-α and urinary albumin excretion rate were found in H. pylori positive subjects. CONCLUSIONS: Diabetic nephropathy patients are more susceptible to H. pylori infection. Our data support an association between H. pylori infection and diabetic nephropathy.