Search

Video surveillance in intelligent transportation systems (ITS) is in the rapid growth stage, where video analytics is a potential technology to improve the safety of the Internet of Autonomous Vehicles (IoAV). However, massive video data transmission and computation-intensive video analytics bring an overwhelming burden for vehicular networks. Moreover, owing to the unstable network connection, the video data are not always reliable, which makes data sharing lack of security and scalability in IoAV. In this work, we first propose a video analytics framework, where the multi-access edge computing (MEC) and blockchain technologies are integrated into IoAV to optimize the transaction throughput of the blockchain system as well as reducing the latency of the MEC system. Furthermore, based on deep reinforcement learning, the joint optimization problem is modeled as a Markov decision process (MDP), and the asynchronous advantage actor-critic (A3C) algorithm is adopted to solve this problem. Simulation results demonstrate that our approach can fast converge and significantly improve the performance of blockchain-enabled IoAV with MEC.

In intelligent transportation systems (ITS), the vehicular ad-hoc network (VANET) is an enabling technology that can provide information exchange services among connected and autonomous vehicles (CAVs). Video streaming over VANETs is a potential application to ensure the safety of drivers and passengers and improve infotainment services. However, owing to the dynamic network topology, video transmission in VANETs is very challenging in terms of latency, reliability, and security. Therefore, a comprehensive summary of the state-of-art video streaming over VANETs is surveyed in this work. Firstly, related works and background knowledge are introduced. Then, a systematic survey on resource allocation (RA) scheme for video streaming in VANETs is provided, and some prevailing and feasible optimization tools are elaborated. Furthermore, enabling technologies of video streaming over VANETs are summarized with a special focus on the integration of video communication, caching, and computing. Finally, we give some challenges and future research directions.

Remote user authentication schemes provide a system to verify the legitimacy of remote users’ authentication request over insecure communication channel. In last years, many authentication schemes using password and smart card have been proposed. However, password might be revealed or forgotten and smart card might be shared, lost or stolen. In contrast, the biometrics, such as face, fingerprint or iris, have no such weakness. With the trend of mobile payment, more and more applications of mobile payment use biometrics to replace password and smart card. In this paper, we propose a biometric-based remote authentication scheme substituting biometric and mobile device bounded by user for password and smart card. This scheme is more convenient, suitable and securer than the schemes using smart cards on mobile payment environment.

Space-air-ground Internet of vehicle networks is a promising network paradigm to support diverse vehicular services. Exploiting the unique advantages of spatial, aerial, and terrestrial network segments, the quality of service (QoS) of different services can be met by smart access network selection. However, the integrated network inevitably has to face many challenges, such as dynamic network topology, heterogeneous resources, and long propagation latency, which can seriously degrade the QoS performance. In order to provide QoS guarantee to vehicles, we propose a novel architecture called QoS-guaranteed access assistance (QA2) serve vehicles with access assistance. To be specific, a virtualized layer is established in the network, which contains the logical resources of ground network infrastructures. Using that layer, Access Assistants are flexibly deployed at a dynamic set of ground infrastructures, and then help vehicles to acquire network services with satisfied QoS requirements. Furthermore, to accommodate temporal-spatial-varying network demands of vehicles, QA2 adopts a cost-effective deployment scheme, which updates the locations of Assistants based on the real-time traffic flow with the minimum operation cost. The evaluation results demonstrate the effectiveness of QA2, which increases request success rate by more than 50%. The results also prove that the cost-effective deployment scheme can efficiently adapt to the change of traffic flow, and achieve a good balance between QoS guarantee and cost saving. The operation cost is saved by more than 25%, and the QoS performance is improved by more than 22%.

Although information-centric networking (ICN) can boost the performance of sensor data delivery in wireless sensor networks (WSNs), its energy efficiency may be significantly impaired due to the receiver-driven request-response transmission model. ICN sensors have to keep long-time active mode to wait for the requests that may arrive at any time, resulting nontrivial energy waste for energy-constrained WSNs. An intuitive method to conserve energy is to schedule partial nodes to fall asleep, but at the cost of extra data fetching delay. In this work, we investigate multi-hop cooperative caching for green WSN over receiver-driven ICNs. By leveraging regional caches, not only can the energy be saved, but also the data fetching delay can be reduced. We formulate those two cooperation gains and capture the trade-off between energy saving and delay reduction. Based on the optimal trade-off, we present a solution of scoped multi-hop cooperative caching and elaborate a green cooperation policy for each sensor to determine its operation scope and conduct a proper cooperation decision. Our simulation results show that our proposed multi-hop cooperative caching can save more than 91.0% energy and achieve 28.9% delay reduction than the basic ICWSN, and also reduce 60.2% energy consumption than the existing cooperative caching schemes.

Optical tweezers are a powerful tool for exploring physical properties of particles in various environments through analysis of their dynamics in a trapping potential. Analysis of the trapped parti...

Generally, automatic diagnosis of the presence of metastases in lymph nodes has therapeutic implications for breast cancer patients. Detection and classification of breast cancer metastases have high clinical relevance, especially in whole-slide images of histological lymph node sections. Fast early detection leads to huge improvement of patient’s survival rate. However, currently pathologists mainly detect the metastases with microscopic assessments. This diagnosis procedure is extremely laborious and prone to inevitable missed diagnoses. Therefore, automated, accurate patient-level classification would hold great promise to reduce the pathologist’s workload while also reduce the subjectivity of diagnosis. In this paper, we provide a novel deep regional metastases segmentation (DRMS) framework for the patient-level lymph node status classification. First, a deep segmentation network (DSNet) is proposed to detect the regional metastases in patch-level. Then, we adopt the density-based spatial clustering of applications with noise (DBSCAN) to predict the whole metastases from individual slides. Finally, we determine patient-level pN-stages by aggregating each individual slide-level prediction. In combination with the above techniques, the framework can make better use of the multi-grained information in histological lymph node section of whole-slice images. Experiments on large-scale clinical datasets (e.g., CAMELYON17) demonstrate that our method delivers advanced performance and provides consistent and accurate metastasis detection in clinical trials.

It remains unclear whether laparoscopic conversation to open gastrectomy causes higher morbidity and has an adverse effect on the long-term survival outcomes of patients with gastric cancer. This study was designed to evaluate the impact of the conversion on short and long-term outcomes of patients with locally advanced gastric cancer (AGC). We retrospectively investigated 871 patients who initially underwent laparoscopic gastrectomy (LG) for pathologically confirmed diagnosis of AGC between February 2009 and April 2018. The patients were grouped as the conversion (CONV) group and completed laparoscopic (LAP) group. The 1:2 propensity score matching was performed to reduce the effect of bias due to the imbalanced baseline features between the two groups. Multivariate analyses were performed to identify risk factors for conversion and poor survival. After propensity-score matching, 168 patients (56 in the CONV group and 112 in the LAP group) were studied. The CONV group was associated with significantly longer operation time (252.4 vs. 216.7 min, P < 0.001) and greater estimated blood loss (234.8 vs. 171.2 ml, P < 0.001) as compared with the LAP group. The time to first flatus (3.8 vs. 3.3 days, P = 0.043), time to start a liquid diet (4.1 vs. 3.5 days, P = 0.021), and postoperative hospital stay (8.7 vs. 7.6 days, P = 0.020) were significantly longer in the CONV group than that in the LAP group. The overall complication rate did not differ significantly between the CONV group and the LAP group (16.1% vs. 12.5%, P = 0.692). Both 5-year overall survival (OS) and 5-year disease-free survival (DFS) did not differ significantly between the CONV group and the LAP group (P = 0.805, P = 0.945, respectively). Multivariate analysis showed that lymphovascular invasion and stage III were independent prognostic factors for poor OS and DFS, whereas conversion was not. The conversion from laparoscopic to open gastrectomy had no negative impact on morbidity and long-term survival outcomes for patients with locally AGC.

Background and Purpose The present study aimed to compare the efficacy and tolerability of different blood pressure (BP)-lowering strategies.Methods Randomized controlled trials that compared various antihypertensive treatments and stroke outcomes were included. Eligible trials were categorized into three scenarios: single or combination antihypertensive agents against placebos; single or combination agents against other agents; and different BP-lowering targets. The primary efficacy outcome was the risk reduction pertaining to strokes. The tolerability outcome was the withdrawal of drugs, owing to drug-related side effects (PROSPERO registration number CRD42018118454 [20/12/2018]).Results The present study included 93 trials (average follow-up duration, 3.3 years). In the pairwise analysis, angiotensin-converting enzyme inhibitors (ACEis) and beta-blockers (BBs) were inferior to calcium channel blockers (CCBs) (odds ratio [OR], 1.123; 95% confidence interval [CI], 1.008 to 1.252) (OR, 1.261; 95% CI, 1.116 to 1.425) for stroke prevention, BB was inferior to angiotensin II receptor blockers (ARB) (OR, 1.361; 95% CI, 1.142 to 1.622), and diuretics were superior to ACEi (OR, 0.871; 95% CI, 0.771 to 0.984). The combination of ACEi+CCB was superior to ACEi+diuretic (OR, 0.892; 95% CI, 0.823 to 0.966). The network meta-analysis confirmed that diuretics were superior to BB (OR, 1.34; 95% CI, 1.11 to 1.58), ACEi+diuretic (OR, 1.47; 95% CI, 1.02 to 2.08), BB+CCB (OR, 2.05; 95% CI, 1.05 to 3.79), and renin inhibitors (OR, 1.87; 95% CI, 1.25 to 2.75) for stroke prevention. Regarding the tolerability profile, the pairwise analysis revealed that ACEi was inferior to CCB and less tolerable, compared to the other treatments.Conclusions Monotherapy using diuretics, CCB, or ARB, and their combinations could be employed as first-line treatments for stroke prevention in terms of efficacy and tolerability.

Vehicular named data networking (VNDN) has the data-centric and in-network caching advantages that are in line with the requirements of multi-hop content retrieval in vehicular ad hoc networks (VANETs). Some current restrictive forwarding strategies utilize single-path forwarding to mitigate the Interest broadcast storm in VNDN. However, these strategies do not provide any reliable mechanism for Interest and Data forwarding to address the problem of low performance caused by the dynamic and unreliable VANETs communication environment. In this paper, we propose a packet forwarding strategy based on optimal and backup (PFOB) for VNDN. For Interest, PFOB establishes a single-path forwarding with high reliability and reachability by increasing the signal strength and node-degree criterion and retransmission mechanism. For Data, PFOB provides a reliable multi-path backup forwarding mechanism without additional network overhead. Simulation results show that PFOB can effectively improve the Interest satisfaction ratio, reduce the number of application retransmissions, and reduce the Interest satisfaction delay compared to the current strategies.

Object detection for autonomous driving is a huge challenge in the cross-domain adaptation scenario, especially for the time- and resource-consuming task. Distributed deep learning (DDL) has demonstrated a considerably good balance between efficiency and computation complexity. However, the reliability of DDL is low. Moreover, the cost of training data and model is not priced well. In this article, a novel blockchain-enabled model sharing approach is proposed to improve the performance of object detection with cross-domain adaptation for autonomous driving systems. Based on the blockchain and mobile-edge computing (MEC) technology, a domain-adaptive you-only-look-once (YOLOv2) model is trained across nodes, which can reduce significantly the domain discrepancy for different object categories. Furthermore, smart contracts are developed to perform data storage and model sharing tasks efficiently. The reliability of model sharing is ensured with blockchain consensus. We evaluate the proposed method under public data sets. The simulation results demonstrate that the efficiency and reliability of the proposed approach are better than the reference model.

Background Glucocorticoid (GC) is the first-line therapy in acute attacks of multiple sclerosis (MS), but its efficacy is individually variable and may be associated with glucocorticoid receptor (GR) gene. Objective To establish the association between GR gene sequence and clinical GC sensitivity in Chinese MS patients. And to investigate the expression differences of serum GRα and FK506 binding protein 5 (FKBP5) in GC responders and non-responders. Materials and methods Coding exons 2–9 of the GR gene from 97 MS patients were sequenced. We performed ELISA to detect serum GRα and FKBP5 before the GC impulse therapy in patients with different GC sensitivities (according to the EDSS changes before and after the GC medication). Results Seven new mutations were located in exon 2, but the presence or absence of mutations was not associated with the response to GC therapy (P = 0.416). The GC-sensitive patients had higher GRα (P = 0.011) but lower FKBP5 (P = 0.025) levels in the serum. Conclusions The GR mutations detected in our study were not associated with the response to GC in Chinese MS patients. Higher GRα and lower FKBP5 levels in the serum might predict the response to GC, which may provide potential therapeutic target for GC-resistant patients with acute MS attack.

MicroRNA-155 is over-expressed in many human cancers, but researches on its association with malignant oesophageal squamous cell carcinoma (ESCC) are limited. The aim of the present study was to evaluate the potential value of

Named Data Networking (NDN) has the advantages of content-based, location-independent and in-network caching. These characteristics are naturally suitable for highly dynamic Vehicular Ad hoc Networks (VANETs), so VNDN has become a promising network architecture. However, achieving effective and reliable multi-hop content retrieval is still a major challenge in VNDN where network parameters change frequently and the channel reliability is poor. In this paper, we propose a protocol based on prediction and network coding for content retrieval in vehicular named data networking (PreNCCR). In order to adapt to the dynamic and random packet loss characteristics of VANETs and restrict flooding, a prediction-based opportunistic routing in which the priority of candidate forwarder is determined through prediction mechanism is proposed. On this basis, a network coding-based packet forwarding strategy is proposed in which the available network capacity are effectively utilized. The evaluation results show that under moderate network configuration parameters, compared with VNDN-geo, CCVN, and SelNC protocols, PreNCCR can not only achieve 33.8% ~ 99.8% higher request satisfaction ratio, 46.6% ~ 65.1% lower delay, but also can reduce the consumption of Interest and Data by 32.6% ~ 80.7%, 52.3% ~ 60.1%.

Sensor nodes in wireless body-area networks are expected to use compressed sensing (CS) for ultralow-power consumption. For signal recovery in CS systems, compared with the software implementation, the hardware processor has superiority on power, real-time ability, and so on. Although orthogonal matching pursuit (OMP) is conventionally selected in hardware implementations, its low recovery performance is still a problem. We propose to use the subspace pursuit (SP) algorithm that can achieve higher recovery performance with less iteration to implement the hardware processor. First, a new SP by a square-root-free method and a computation reuse scheme are proposed to reduce the SP’s complexity. Then, the fully paralleled architectures and elaborate pipelines are proposed to improve the processing throughput. Finally, we give an FPGA implementation prototype. Simulations compared with OMP show that the traditional SP can improve more than 8 dB on recovery performance or it can reduce more than 31% sampling paths in sensor nodes. These benefits are kept by our proposed SP because our improvement does not modify the algorithmic nature. Nevertheless, the significant complexity reduction is achieved by our proposal. The proposed SP processor can recover ECG signals with 28.2 dB and achieve the processing throughput of 44.4 K vectors/s.

BACKGROUND: Benign prostatic hyperplasia (BPH) is a common micturition disorder in middle-aged and elderly males, and it is one of the most common urology-related diseases worldwide. However, standard therapeutic drugs (α1-receptor blockers + 5α reductase inhibitors) do not provide anti-inflammatory or anti-infective effects. The Phellodendron Bawei tablet is a proprietary Chinese medicine with anti-inflammatory and anti-infective effects. Here, we analyzed whether the combination of standard therapeutic drugs and Phellodendron Bawei tablets has more advantages than placebo with standard management in improving the lower urinary tract symptoms (LUTs), sleep quality, sexual function, and medication compliance in patients with BPH. METHODS: This study was a prospective, double-blind, single-center, 6-month clinical trial in patients with BPH. Male patients, 45–75 years old, a history of moderate-to-severe BPH/LUTs for more than 6 months, moderate-to-severe LUTs [International Prostate Symptom Score (IPSS) ≥8], maximum urine flow rate (Qmax) of 30 mL. All patients were randomly divided into two cohorts at baseline. The standard management (SM) group was treated with tamsulosin + finasteride + placebo, while the experimental group was treated with tamsulosin + finasteride + Phellodendron Bawei tablets. The clinical indicators were as follows: Age, body mass index (BMI), blood prostate-specific antigen (PSA), PV, Qmax, IPSS; IPSS voiding subscore (IPSS-V), IPSS storage subscore (IPSS-S), and IPSS quality of life (IPSS-QOL)], five-item version of the International Index of Erectile Function (IEFF-5) score, Athens Insomnia Scale (AIS) score, and the Medication Adherence Questionnaire (MAQ). And adverse drug reactions were observed. Student’s t-test was used to analyze results. RESULTS: We randomly divided 120 patients into two groups, with 60 patients in each group, and a total of 105 patients completed the study. IPSS-S (P=0.027) and AIS scores (P

Named Data Networking (NDN) presents strong bandwidth benefits on edge networks because its in-network caching design is probably fit for popularity and locality. However, separate NDN edge regions cannot be efficiently connected over IP backbone world, slowing down the deployment of NDN edges. Due to the difference of stateful NDN and stateless IP in forwarding principles, the coexistence of two protocols is difficult and challenging in the network layer. In this paper, we propose iGate, an NDN gateway design for tunneling over IP world, to bridge two kinds of protocols in the same layer. iGate translates protocols between stateful NDN and stateless IP by two temporary tables. It considers many factors about gateway efficiency, like table tunning, minimal NDN integration, TCP/UDP alternatives. We evaluate the performance of iGate with a real implementation on Linux and the results show that it can achieve more than 85.03% translation efficiency and less than 29% protocol conversion delay compared with IP VPN which uses the typical tunneling technology over IP network. Our work presents a practical and highly-efficient solution to assemble NDN edges into IP world, and can be applied to other similar Information-Centric Networking (ICN) designs.

Background: Optic neuritis (ON) is an important clinical manifestation of neuromyelitis optic spectrum disease (NMOSD). Myelin oligodendrocyte glycoprotein (MOG) antibody-related and aquaporin 4 (AQP4) antibody-related ON show different disease patterns. The aim of this study was to explore the differences in structure and function of the visual pathway in patients with ON associated with MOG and AQP4 antibodies.Methods: In this prospective study, we recruited 52 subjects at Beijing Tiantan Hospital, including 11 with MOG Ig+ ON (MOG-ON), 13 with AQP4 Ig+ ON (AQP4-ON), and 28 healthy controls (HCs). Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) of optic radiation (OR), primary visual cortex volume (V1), brain volume, and visual acuity (VA) were compared among groups. A multiple linear regression was used to explore associations between VA and predicted factors. In addition, we used optical coherence tomography (OCT) to examine thickness of the peripapillary retinal nerve fiber layer (pRNFL) and retinal ganglion cell complex (GCC) in a separate cohort consisting of 15 patients with ON (8 MOG-ON and 7 AQP4-ON) and 28 HCs.Results: Diffusion tensor imaging showed that the FA of OR was lower than controls in patients with AQP4-ON (p = 0.001) but not those with MOG-ON (p = 0.329) and was significantly different between the latter two groups (p = 0.005), while V1 was similar in patients with MOG-ON and AQP4-ON (p = 0.122), but was lower than controls in AQP4-ON (p = 0.002) but not those with MOG-ON (p = 0.210). The VA outcomes were better in MOG-ON than AQP4-ON, and linear regression analysis revealed that VA in MOG-ON and AQP4-ON was both predicted by the FA of OR (standard β = −0.467 and −0.521, p = 0.036 and 0.034). Both patients of MOG-ON and AQP4-ON showed neuroaxonal damage in the form of pRNFL and GCC thinning but showed no statistically significant difference (p = 0.556, 0.817).Conclusion: The structural integrity of OR in patients with MOG-ON, which is different from the imaging manifestations of AQP4-ON, may be a reason for the better visual outcomes of patients with MOG-ON.

Background To perform a prospective, randomized, single center study to investigate the efficacy of combined use of curcumin, an anti-inflammatory agent, with the best standard management (BSM, tamsulosin and finasteride) in benign prostatic hyperplasia (BPH) patients. Methods One hundred and twenty-two consecutive patients were randomized to receive tamsulosin 0.2 mg, finasteride 5 mg, and curcumin 2,250 mg once a day (curcumin + BSM group, n=61) versus tamsulosin 0.2 mg, finasteride 5 mg, and placebo (BSM group, n=61) for 6 months. The safety of treatments and their efficacy on improving waist circumference (WC), periprostatic fat thickness (PPFT), lower urinary tract symptoms (LUTS), and sexual function were assessed at baseline and month 6. Results One hundred and sixteen patients completed the whole procedure (116/122, 95.1%). There were significant improvements in prostate volume (PV), maximum flow rate (Qmax), the International Prostate Symptom Score (IPSS), IPSS-voiding subscore (IPSS-V), IPSS-storage subscore (IPSS-S), and quality of life (QoL) from baseline after treatment in both groups. Additionally, both WC and PPFT decreased significantly after treatments than those at baseline in the curcumin + BSM group. Also, WC and PPFT in the curcumin + BSM group were significantly lower than those in the BSM group. In addition, IPSS-S, QoL score, and the 5-item version of the International Index of Erectile Function (IIEF-5) in the curcumin + BSM group improved significantly compared with those in the BSM group. Conclusions We conclude that curcumin combined with tamsulosin and finasteride has more beneficial effects in reducing PPFT, protecting erectile function, improving urinary retention symptoms, and QoL scores in BPH patients compared to tamsulosin and finasteride alone. Trial registration Chinese Clinical Trial Registry ChiCTR2100043800.

ICN names data rather than hosts and then directly relays packets according to data names. This fundamental shift in naming from host-dependent to host-independent enables ICN to cache data for future service in its network. Therefore, ICN acts as not only a tunnel to transmit data but also a temporary cache of data, which inevitably confronts data attacks. In this article, for the first time, we investigate caching security from a system recovery perspective, and find that ICN attacked by typical caching attacks can be eventually recovered to the normal state if in-network security on data is provided. However, it may cause concern about the recovery time. To address this concern, we introduce a lightweight solution to shorten the recovery period of ICN by constructing and managing trusted zones with Dual Tunnels among Routers in a Penalty-Feedback Way (Duty). The feasibility and effectiveness of our design are verified by the experimental evaluations on real topology. Our work indicates a new perspective in the cache security of ICN and addresses some future work.

Information-centric networking (ICN) names contents instead of end-nodes and enables in-network caching to reuse those named packets, thus improving the efficiency of content delivery. On-path caching is an inherent feature in ICN, which caches contents along the path from providers to consumers, while off-path caching is not directly supported and its maintenance normally requires non-trivial overhead. In this paper, we propose a lightweight regional cache collaboration approach, called OpenCache, to sharing popular cached data among small-range caches with least cache information exchanges, especially for hierarchical-named ICN. Different from other available solutions, OpenCache enables collaborators to exchange aggregated hierarchical names (i.e., prefixes), instead of data structures summarized from separated and specific data names, to fundamentally reduce the collaborating cost of communication and maintenance. In addition, our approach exploits forwarding information base (FIB) to selectively relay Interest packets to nearby collaborative routers for low-cost data retrieval. Theoretical analyses and extensive experiments have been conducted to evaluate our scheme and the results show that OpenCache can reduce packet latency in retrieving data by about 38% compared to original ICN while its additional collaborating overhead is only around 15% of other schemes. Our approach explores the feasibility of lightweight collaboration with aggregation of hierarchical names.

Existing communication protocols for mobile ad hoc networks (MANETs) mis-fit flying ad hoc networks (FANETs) due to their exclusive design challenges on the typical long communication distance and high mobility degree of nodes. To tackle them, we introduce a hybrid omnidirectional and multi-beam directional antenna structure for gradient-elastic control-data separation. Based on dual antennas, we further propose a novel communication strategy, which combines location prediction with target tracing, to catch and trace communication targets by adaptively exchanging heartbeat locations for stable data transmission. The performance evaluation shows that our proposal achieves 35.8% increase in data link robustness.

To examine and compare fully-automated and manually measured corneal nerve fiber parameters in type 2 diabetes mellitus (T2DM) patients with and without diabetic peripheral neuropathy (DPN).A total of 128 T2DM subjects and 24 healthy controls underwent neuropathy assessment and bilateral corneal confocal microscopy (CCM). Five representative nerve fiber images were selected for each participant and analyzed manually and with fully-automated software. Corneal nerve fiber length (CNFL), branch density (CNBD), and fiber density (CNFD) were examined.Manual and full-automated methods for the whole cohort were significantly positive correlated for CNFL, CNBD and CNFD (r = 0.818, 0.845, 0.457, all P 0.001). Analysis of agreement between the two measurements using Bland-Altman method showed a bias of 2.05 mm/mmThis study demonstrated strong correlations between manual and fully-automated CNFL and CNBD, but not CNFD. Fully-automated corneal nerve fiber parameter quantification may be a fast, objective way to detect DPN.

Vehicular named data networking (VNDN) is a networking architecture candidate to support various kinds of content-oriented applications in high dynamic topology environment. Its inherent in-network caching facilitates content delivery and the communication efficiency in the vehicular network. However, during the process of data delivery, fast and varying vehicle mobility changes the position of relay routers, which makes data packet delivered through the reverse path difficult. Furthermore, frequent link disruption and packet retransmission lead to the increase of network load and the decrease of user QoE. To address these problems, we propose a cluster-based cooperative caching approach with mobility prediction (COMP) in VNDN. The main idea of COMP is to establish communication among vehicles with similar mobility pattern to mitigate the impact of vehicle mobility, as the link between nodes with a similar pattern is relatively stable and reliable. Specifically, we design a clustering algorithm to group vehicles with similar mobility pattern via mobility prediction and present a cooperative caching to construct intra-cluster and inter-cluster communication over the vehicle clusters. To increase the cache resource utilization and the diversity of the cached data, we classify the cached data into the most popular data and the less popular data based on request frequency, and furthermore, the corresponding cache placement and transmission schemes are proposed. The evaluation results show that most of the vehicles (>95%) can acquire feasible and efficient data delivery via COMP, and COMP significantly improves network performance and user QoE.

Objective: To evaluate the efficacy and safety of MK-801 and its effect on lesion volume in rat models of acute brain injury. Data Sources: Key terms were “stroke”, “brain diseases”, “brain injuries”, “brain hemorrhage, traumatic”, “acute brain injury”, “dizocilpine maleate”, “dizocilpine”, “MK-801”, “MK801”, “rat”, “rats”, “rattus” and “murine”. PubMed, Cochrane library, EMBASE, the China National Knowledge Infrastructure, WanFang database, the VIP Journal Integration Platform (VJIP) and SinoMed databases were searched from their inception dates to March 2018. Data Selection: Studies were selected if they reported the effects of MK-801 in experimental acute brain injury. Two investigators independently conducted literature screening, data extraction, and methodological quality assessments. Outcome Measures: The primary outcomes included lesion volume and brain edema. The secondary outcomes included behavioral assessments with the Bederson neurological grading system and the water maze test 24 hours after brain injury. Results: A total of 52 studies with 2530 samples were included in the systematic review. Seventeen of these studies had a high methodological quality. Overall, the lesion volume (34 studies, n = 966, MD = −58.31, 95% CI: −66.55 to −50.07; P < 0.00001) and degree of cerebral edema (5 studies, n = 75, MD = −1.21, 95% CI: −1.50 to −0.91; P < 0.00001) were significantly decreased in the MK-801 group compared with the control group. MK-801 improved spatial cognition assessed with the water maze test (2 studies, n = 60, MD = −10.88, 95% CI: −20.75 to −1.00; P = 0.03) and neurological function 24 hours after brain injury (11 studies, n = 335, MD = −1.04, 95% CI: −1.47 to −0.60; P < 0.00001). Subgroup analysis suggested an association of reduction in lesion volume with various injury models (34 studies, n = 966, MD = −58.31, 95% CI: −66.55 to −50.07; P = 0.004). Further network analysis showed that 0–1 mg/kg MK-801 may be the optimal dose for treatment in the middle cerebral artery occlusion animal model. Conclusion: MK-801 effectively reduces brain lesion volume and the degree of cerebral edema in rat models of experimental acute brain injury, providing a good neuroprotective effect. Additionally, MK-801 has a good safety profile, and its mechanism of action is well known. Thus, MK-801 may be suitable for future clinical trials and applications.

Scalable and hierarchical naming on contents enables the flexibility of named data networking of things towards globally massive data and applications. However, the side effects of frequent packet fragmentation across layers and thus non-trivial traffic overhead are unavoidable due to scalable and unlimited-length names. In this letter, a local name translation (LAT) is proposed to translate long names into short ones to establish succinct local communication, while preserving the advantages of scalable naming for global uses. With over 30% bandwidth reduction and 40% storage saving, the succinctness and effectiveness of the LAT are verified through model analyses and evaluation results.

Purpose: Polycystic ovary syndrome (PCOS) is considered as one of the most common endocrine disorder with heterogeneity. There are also reports that liver receptor homolog 1 [LRH-1 or nuclear receptor subfamily 5 group A member 2 (NR5A2)] plays an important role in the reproductive system. But up to now, there are no reports related to the link with PCOS and LRH-1. In this study, we aimed to detect the LRH-1 expression in the ovarian granulosa cell of PCOS patients and explore the potential relationship between LRH-1 and PCOS. Methods: 146 follicular fluid sample were collected in this study, including 72 from PCOS patients and 74 from control patients who underwent intracytoplasmic sperm injection (ICSI) or in vitro fertilization-embryo transfer (IVF-ET). The ovarian granulosa cells were extracted from the patient's follicular fluid by magnetic-activated cell sorting (MACS) method, and the real-time quantitative PCR (qRT-PCR) was used to measure the expression of LRH-1 in ovarian granulosa cells. Then we analyzed the correlation between the expression level of LRH-1 and the clinical characteristics of patient by using Pearson Correlation analysis. Results: The expression of LRH-1 was significantly higher in PCOS patients ovarian granulosa cells than that in the control patients [vs(1.38±0.47)vs(1.03±0.32), t=5.327, pConclusions: Compared with the control group, we found that LRH-1 was highly expressed in the ovarian granulosa cells of PCOS patients. Our study has revealed the relationship between the LRH-1 expression and PCOS, which suggested that LRH-1 may play an important role in ovulation disorders. While this finding provided new ideas for the study of the pathogenesis, it also provided a theoretical basis for the clinical diagnosis and treatment for PCOS.

In intelligent transportation systems (ITS), video analytics is a potential technology to enhance the safety of the Internet of Vehicles (IoV). However, massive video data transmission and computation-intensive video analytics bring an overwhelming burden for IoV. Furthermore, due to the unstable network connection, the video data are not always reliable, which makes data sharing lack of security and scalability in IoV. In this paper, for video analytics applications, the multi-access edge computing (MEC) and blockchain technologies are integrated into IoV to optimize the transaction throughput as well as reducing the latency of the MEC system. Furthermore, the joint optimization problem is formulated as a Markov decision process (MDP), and the asynchronous advantage actor-critic (A3C) algorithm is adopted to solve this problem. Simulation results show that the proposed approach can fast converge and signifcantly improve the performance of blockchain-enabled IoV with MEC.

Background: In neuromyelitis optica spectrum disorders (NMOSDs), inflammation is not the sole driver of accumulation of disability; neurodegeneration is another important pathological process. We aim to explore different patterns of cortical atrophy and ventricular enlargement in NMOSD. Methods: We retrospectively analyzed a cohort of 230 subjects, comprising 55 healthy controls (HCs), 85 multiple sclerosis (MS), and 90 NMOSD patients from Tianjin Medical University General Hospital and Beijing Tiantan Hospital. Different compartments of the brain (total gray, cortex, subcortex gray, and ventricle volume) were evaluated with the FreeSurfer. Multiple linear regressions were adopted to explore associations between cortex volume and predict factors. Results: Compared with HCs, NMOSD, and MS displayed an enlarged lateral and third ventricle (p < 0.001), whereas expansion of the fourth ventricle was observed in MS rather than NMOSD (p = 0.321). MS and NMOSD patients exhibited cortical thinning in comparison with HCs. However, pronounced cortical atrophy were only significant in pre-cuneus, parahippocampal, and lateral occipital lobe between MS and NMOSD. Patients with NMOSD had decreased local gyrification index in orbitofrontal and pre-cuneus lobe, and reduced pial surface area. Linear regression analysis revealed cortex volume were predicated by advanced age (standardized β = -0.404, p = 0.001) as well as prolonged disease history (standardized β = -0.311, p = 0.006). Conclusion: NMOSD exhibited global cortex atrophy with enlarged lateral and third ventricles. Moreover, cortex volume is associated with age and disease duration.

Inflammation plays a major role in the development of myocardial ischemia-reperfusion (IR) injury. Recombinant human brain natriuretic peptide (rhBNP), a man-made version of a peptide that is elevated in heart failure, exhibits anti-inflammatory effects in various tissues. However, its role in myocardial IR injury remains unclear. In this study, we demonstrate that treatment with rhBNP provided protection for mice against myocardial IR injury as manifested by reduced infarct size and well-preserved myocardial, attenuated inflammatory infiltration and CD4+ T cell proliferation function, and inhibited expression of proinflammatory related genes. Furthermore, mechanistic studies revealed that rhBNP inhibited Jurkat T proliferation by promoting PI3K/AKT/mTOR phosphorylation. Collectively, our data suggest that the administration of rhBNP during IR injury could expand our understanding of the cardioprotective effects of rhBNP.

Personally identifiable information (PII) is widely used for many aspects such as network privacy leak detection, network forensics, and user portraits. Internet service providers (ISPs) and administrators are usually concerned with whether PII has been extracted during the network transmission process. However, most studies have focused on the extractions occurring on the client side and server side. This study proposes a static tainting extraction approach that automatically extracts PII from large-scale network traffic without requiring any manual work and feedback on the ISP-level network traffic. The proposed approach does not deploy any additional applications on the client side. The information flow graph is drawn via a tainting process that involves two steps: inter-domain routing and intra-domain infection that contains a constraint function (CF) to limit the “over-tainting. Compared with the existing semantic-based approach that uses network traffic from the ISP, the proposed approach performs better, with 92.37% precision and 94.04% recall. Furthermore, three methods that reduce the computing time and the memory overhead are presented herein. The number of rounds is reduced to 0.0883%, and the execution time overhead is reduced to 0.0153% of the original approach.

Objective Deep venous thrombosis (DVT) is a severe complication in longitudinally extensive transverse myelitis (LETM) patients. It may interfere with LETM treatment and delay the recovery of the spinal dysfunction. However, there is less data about the prevalence and risk factors of DVT in patients with LETM. We analyzed data retrospectively to ascertain the prevalence of DVT and the clinical risk factors for DVT. Methods Clinical data on 255 LETM patients were collected from medical records. All patients were performed color Doppler ultrasound(US) to screen DVT in both lower extremities when admitted. Clinical characteristics of LETM patients with DVT were compared with those without DVT using corresponding statistical methods. Multivariate logistic regression was performed to identify risk factors related to DVT. Results DVT were found in 11.8% patients with LETM. Univariate analysis showed that age, muscle force and elevated baseline D-dimer were risk factors for DVT. After multivariate logistic regression, age, dyslipidemia, segments of lesions, and elevated baseline D-dimer remained significant independent risk factors. Conclusions DVT is common in patients with LETM and related to patient’s age, dyslipidemia, segments of lesions, and elevated baseline D-dimer. Early recognition of DVT and thrombosis prophylaxis are appropriate in patients with LETM.

It is widely common that mobile applications collect non-critical personally identifiable information (PII) from users’ devices to the cloud by application service providers (ASPs) in a positive manner to provide precise and recommending services. Meanwhile, Internet service providers (ISPs) or local network providers also have strong requirements to collect PIIs for finer-grained traffic control and security services. However, it is a challenge to locate PIIs accurately in the massive data of network traffic just like looking a needle in a haystack. In this paper, we address this challenge by presenting an efficient and light-weight approach, namely TPII, which can locate and track PIIs from the HTTP layer rebuilt from raw network traffics. This approach only collects three features from HTTP fields as users’ behaviors and then establishes a tree-based decision model to dig PIIs efficiently and accurately. Without any priori knowledge, TPII can identify any types of PIIs from any mobile applications, which has a broad vision of applications. We evaluate the proposed approach on a real dataset collected from a campus network with more than 13k users. The experimental results show that the precision and recall of TPII are 91.72% and 94.51% respectively and a parallel implementation of TPII can achieve 213 million records digging and labelling within one hour, reaching near to support 1Gbps wire-speed inspection in practice. Our approach provides network service providers a practical way to collect PIIs for better services.

Obstructive sleep apnea (OSA) is associated with increased levels of systemic inflammatory markers, increased arterial stiffness, and endothelial dysfunction, which may lead to increased cardiovascular risk. We aimed to quantify the effects of continuous positive airway pressure (CPAP) on cardiovascular biomarkers and to establish predictors of response to CPAP. We searched PubMed and the Cochrane Library from inception to May 31, 2017. Randomized controlled trials (RCTs) assessing the efficacy of CPAP on high-sensitivity C-reactive protein (hs-CRP), interleukin 6 (IL-6), tumor necrosis factor- alpha (TNF-α), augmentation index (AIx), pulse wave velocity (PWV), and flow-mediated dilatation (FMD) in patients with OSA were selected by consensus. We included 15 RCTs comprising 1090 patients in the meta-analysis. The pooled standard mean difference (SMD) of effect of CPAP on hs-CRP was − 0.64 (95% confidence interval (CI) − 1.19 to − 0.09; P = 0.02). CPAP was associated with a reduction in AIx of 1.53% (95% CI, 0.80 to 2.26%; P

Underwater images suffer degradation from light propagates through water. The degradation by light propagation not only affects the quality of underwater images but limits the ability of object detection. In this paper, we propose a color correction method by cycle-consistent adversarial networks (CycleGAN) for an improvement of underwater object detection. The proposed CycleGAN is implemented with a polynomial loss function including adversarial loss, cycle-consistency loss, and structural similarity index measure (SSIM) loss. Thereby, underwater images are generated as output images including the content and structure of the input images. Simulation results show that our method achieves an improved 7% mean average precision in underwater object detection, compared with a conventional method.

Perceptual video coding (PVC) can provide a lower bitrate with the same visual quality compared with traditional H.265/high efficiency video coding (HEVC). In this work, a novel H.265/HEVC-compliant PVC framework is proposed based on the video saliency model. Firstly, both an effective and efficient spatiotemporal saliency model is used to generate a video saliency map. Secondly, a perceptual coding scheme is developed based on the saliency map. A saliency-based quantization control algorithm is proposed to reduce the bitrate. Finally, the simulation results demonstrate that the proposed perceptual coding scheme shows its superiority in objective and subjective tests, achieving up to a 9.46% bitrate reduction with negligible subjective and objective quality loss. The advantage of the proposed method is the high quality adapted for a high-definition video application.

In Named Data Networking (NDN), Pending Interest Table (PIT) is proposed to record the forwarding information of interest packets forwarded but not responded. Each incoming interest packet or data packet needs to be queried and processed in PIT, and the overhead would rise as the scale of PIT increases. Therefore, PIT is required to have a very high processing speed. To effectively improve the forwarding efficiency of PIT in NDN, a new architecture of the PIT using a hot table to achieve prefix grading is designed and implemented. The concept of “prefix value” is proposed to determine the value of a prefix carrying the information content of an interest packet, and to store and prioritize the prefix information with a higher value. The results of the comparison experiment show that the architecture of the PIT with a hot table can significantly improve processing speed of the PIT and accelerate forwarding efficiency of the NDN node.

In this paper, we propose a proposal based method for saliency detection. Our method separates the salient proposals out by assigning them a novel attention mechanism, semantic attention (SeA). The attention are established based on the observation that regions with high attention should have similarly semantic concepts with salient objects. The SeA takes the high-level semantic features from Faster Region-based Convolutional Neural Network (Faster R-CNN) to assist the proposal selection in images with complex background. We select the salient proposals according to their semantic attention probabilities. Quantitative and qualitative experiments on four datasets demonstrate that the proposed algorithm performs favorably against the state-of-the-art methods.

Chinese natural language analysis is an important interface between humans and computers. During the analysis, unstructured natural languages were usually input, while a generating structured query language is needed for computer understanding. The paper proposes a method for natural language analysis in some restricted modes based on domain knowledge database, lexical analysis and syntactic analysis. In our approach, a semantic dependency tree is treated as an intermediate language, and semantic dependency analysis model and grammar recognition were used to re-present the input sentence as a structural sentence. An experiment system has been developed based on traffic information database. The experiment results and examples demonstrate that our method can effectively understand various common natural query statements with good usability in restricted situations.

Wind-induced vibration (WIV) and power extraction performances of a circular cylinder with symmetrically installed fin-shaped rods (FSR) were experimentally and numerically investigated under different coverages. The FSR coverage which is expressed as an angle (α) is measured from the upstream edge to the downstream edge of the rod. The effect of FSR installation angle (θ) which is the angle from the stagnation point of cylinder to the upstream edge of the rod was also considered in this work. The FSR cylinder is exposed in uniform wind and allowed to vibrate in cross-flow direction. The output electric power is realized by piezoelectric patch. It is found that, for most cases, the output power of FSR cylinder increases monotonously with the rise of α for a given wind velocity (U). In addition, the tendency of output voltage varies with the wind velocity is highly similar to that of output power. The maximum values of output voltage and power are 19.70 V and 1.90 mW can be obtained when α= 20° (θ= 60°). The WIV responses of FSR cylinder show that the amplitudes of FSR cylinder increase with the rise of α for low installation angle (θ= 0°, 30°) and the maximum amplitudes exceed 2D (D: diameter of circular cylinder) can be observed for α= 40°/50° (θ= 30°) and α= 20° (θ= 60°). The reduced frequency of cylinder for θ= 0° and 30° does not sensitive to the coverage (α). It is worth noting that multiple frequencies can be captured for high coverage. Due to the boundary layer separating point moves in downstream direction with the increase of U and α, the vortex pattern switches from 2S to 2P.

Building a reliable and efficient network layer for large-volume content delivery over satellite is extremely challenging due to space circumstances of unreliable connectivity, long propagation delay and high dynamics. In this paper, we address those challenges in satellite networking and propose an information-centric data retrieval scheme to provide disruption-tolerant, low-delay and highly efficient content delivery. Our design, namely Coding-enabled Adaptive-Pull (CAP) scheme, is rooted in the concept of information-centric networking, transferring named contents rather than maintaining unreliable end-to-end connections in space. CAP retrieves data in one-to-many request-response model and adaptively adjusts the retrieval expectation according to network states. Meanwhile, the data retrieval scheme embeds with fountain-style erasure coding over its named packets for reliable transmission to reduce the needs of packet retransmission and utilizes in-network caching to tolerate possible link disruption. Evaluation results show that our scheme reduces delivery delay in most cases of unreliable links by nearly 82% and 75% compared with IP and NDN, respectively, and by 72% compared to delay-tolerant networking technique in a space-oriented scenario, with outstanding performance in tolerating delays and disruptions.

Constructed-response items are commonly used in educational and psychological testing, and the answers to those items are typically scored by human raters. In the current rater monitoring processes, validity scoring is used to ensure that the scores assigned by raters do not deviate severely from the standards of rating quality. In this article, an adaptive rater monitoring approach that may potentially improve the efficiency of current rater monitoring practice is proposed. Based on the Rasch partial credit model and known development in multidimensional computerized adaptive testing, two essay selection methods—namely, the D-optimal method and the Single Fisher information method—are proposed. These two methods intend to select the most appropriate essays based on what is already known about a rater’s performance. Simulation studies, using a simulated essay bank and a cloned real essay bank, show that the proposed adaptive rater monitoring methods can recover rater parameters with much fewer essay questions. Future challenges and potential solutions are discussed in the end.

Background Previous findings of the association between socioeconomic deprivation and mortality after ischemic stroke are inconsistent. There is a lack of data on the association with combined low education, occupational class, and income. We assessed the associations of three indicators with mortality. Methods We examined data from the China National Stroke Registry, recording all stroke patients occurred between September 2007 and August 2008. Baseline socioeconomic deprivation was measured using low levels of education at Results In a 12-month follow-up 1640 patients died. After adjustment for age, sex, cardiovascular risk factors, severity of stroke, and prehospital medications, odds ratio for mortality in patients with low education was 1.25 (95%CI 1.05–1.48), manual laboring 1.37 (1.09–1.72), and low income 1.19 (1.03–1.37). Further adjustment for acute care and medications in and after hospital made no substantial changes in these odds ratios, except a marginal significant odds ratio for low income (1.15, 0.99–1.33). The odds ratio for low income was 1.27 (1.01–1.60) within patients with high education. Compared with no socioeconomic deprivation, the odds ratio in patients with socioeconomic deprivation determined by any one indicator was 1.33 (1.11–1.59), by any two indicators 1.36 (1.10–1.69), and by all three indicators 1.56 (1.23–1.97). Conclusions There are significant inequalities in survival after ischemic stroke in China in terms of social and material forms of deprivation. General socioeconomic improvement, targeting groups at high risk of mortality is likely to reduce inequality in survival after stroke.

In this work, a high efficiency coding unit (CU) size decision algorithm is proposed for high efficiency video coding (HEVC) inter coding. The CU splitting or non-splitting is modeled as a binary classification problem based on probability graphical model (PGM). This method incorporates two sub-methods: CU size termination decision and CU size skip decision. This method focuses on the trade-off between encoding efficiency and encoding complexity, and it has a good performance. Particularly in the high resolution application, simulation results demonstrate that the proposed algorithm can reduce encoding time by 53.62%-57.54%, while the increased BD-rate are only 1.27%-1.65%, compared to the HEVC software model.

Zedoary turmeric oil, a plant extract currently in clinical use, may provide potent pharmacological actions such as liver injury. In the previous study, to improve the in vivo absorption of ZTO and produce a high oral bioavailability, chitosan was employed to prepare sustained-release microspheres containing ZTO. In this study, a portability liver cancer model of rats was established successfully to compare the pharmacodynamic of ZTO microspheres and injection. In vitro results showed that microspheres had almost uniformly spherical shapes and were well dispersed by a relatively dynamic stable system. In vivo, compared with the control group, all ZTO microspheres groups resulted in growing inhibition of walker-256 cells transplanted solid tumor and the obvious controlled tumor size. At the same dose, ZTO microspheres suggested a better effect. The data showed that three doses of ZTO microspheres could prolong the average survival time considerably. None of the severe signs such as the pimelosis, fibrotic changes and fibrous septum were detected in the histopathology study.

Background During acute attacks of neuromyelitis optica spectrum disorder (NMOSD), intravenous immunoglobulin (IVIG) maybe useful building on experience treating autoimmune disorders. Methods We conducted a retrospective study of several treatment modes for NMOSD attacks at Beijing Tiantan Hospital and Tianjin Medical University General Hospital. Clinical outcomes were defined as the short-term remission status. The good (GR), moderate (MR) or poor remission (PR) was respectively defined to triple-grade based on percentage change of initial and follow-up Expanded Disability Status Scale (EDSS) scores. Results A total of 243 attacks was analyzed in 198 patients from 2014 to 2019. Treatment groups included 153 attacks given high-dose intravenous steroids (HD-S), 14 given IVIG, 69 episodes of IVIG plus HD-S and 7 treated with plasma exchange. The proportion of patients with better outcomes were significantly lower in IVIG alone group than HD-S alone group (p = 0.004). However, sequential treatments for IVIG and HD-S yielded a higher likelihood of clinical improvement in severe attacks with EDSS ≥ 6.5 (OR = 5.85, p = 0.007). Conclusion These results did not support IVIG-alone therapy as a first-line option for acute NMOSD. However, adding HD-S to IVIG therapy was superior to HD-S alone for patients with high-onset EDSS.

Anti-N-methyl-d-aspartate receptor encephalitis (NMDARe) can coexist with myelin oligodendrocyte glycoprotein antibody (MOG-ab) disease. To characterize MOG-ab disease during NMDARe, we analyzed all the patients with MOG-ab disease and NMDARe from our hospital from December 2018 to December 2019 and data from a systematical review of previously published reports. Details of the patients identified were summarized and literature was reviewed. Four of thirty (14.2%) patients with anti-NMDARe had overlapping MOG-ab disease in our department. Analyze together with previously reported cases. Thirty-two NMDARe patients had overlapping MOG-ab disease. The onset age ranged from 3 to 48 years. Twenty-four patients (74%) developed abnormal behavior or cognitive dysfunction during the episodes of anti-NMDARe. None of these patients had tumors. 84% (27/32) patients received high doses of steroids as first-line immunotherapy and 28% (9/32) received mycophenolate mofetil (MMF) to prevent relapse. Twenty-six of twenty-seven (96%) had a good outcome. Steroids are the most common first-line immunotherapies in NMDARe overlapping MOG-ab disease. Most of the NMDARe patients overlapping MOG-ab disease have a good prognosis.