A Secure Ciphertext Retrieval Scheme against Insider KGAs for Mobile Devices in Cloud Storage

With the advent of cloud computing, data privacy has become one of critical security issues and attracted much attention as more and more mobile devices are relying on the services in cloud. To protect data privacy, users usually encrypt their sensitive data before uploading to cloud servers, which renders the data utilization to be difficult. The ciphertext retrieval is able to realize utilization over encrypted data and searchable public key encryption is an effective way in the construction of encrypted data retrieval. However, the previous related works have not paid much attention to the design of ciphertext retrieval schemes that are secure against inside keyword-guessing attacks (KGAs). In this paper, we first construct a new architecture to resist inside KGAs. Moreover we present an efficient ciphertext retrieval instance with a designated tester (dCRKS) based on the architecture. This instance is secure under the inside KGAs. Finally, security analysis and efficiency comparison show that the proposal is effective for the retrieval of encrypted data in cloud computing

DQN-based resource allocation for NOMA-MEC-aided multi-source data stream

Abstract This paper investigates a non-orthogonal multiple access (NOMA)-aided mobile edge computing (MEC) network with multiple sources and one computing access point (CAP), in which NOMA technology is applied to transmit multi-source data streams to CAP for computing. To measure the performance of the considered NOMA-aided MEC network, we first design the system cost as a linear weighting function of energy consumption and delay under the NOMA-aided MEC network. Moreover, we propose a deep Q network (DQN)-based offloading strategy to minimize the system cost by jointly optimizing the offloading ratio and transmission power allocation. Finally, we design experiments to demonstrate the effectiveness of the proposed strategy. Specifically, the designed strategy can decrease the system cost by about 15% compared with local computing when the number of sources is 5

Structural characteristics and exploration fields in passive continental margin basins of Central Atlantic

The petroleum resources of the passive continental margin basins in the Central Atlantic are rich, but the insufficient knowledge of basin structural characteristics and accumulation conditions in the area restricts the exploration of deepwater oil and gas. Based on the integral analysis of seismic, drilling, gravity anomalies and magnetic anomalies data, the basin structural characteristics and hydrocarbon accumulation conditions in deepwater area of the passive continental margin basins of the Central Atlantic are studied and the exploration fields are predicted with the Senegal and Scotia basins as key anatomical objects. It can be concluded that the passive continental margin basins of the Central Atlantic have experienced three evolution stages: the rift period, the transition period and the drift period, with corresponding development of three tectonic layers: the rift layer, the depression layer and the continental margin layer, and the basin structures are controlled by transform faults and basement properties. From Triassic to Early Jurassic rift period, a series of horst-graben structures were formed, and the sediments were mainly continental ones such as rivers, lakes and deltas. From Middle to Late Jurassic transition period, the marginal ridge or submarine uplift zone were developed due to the activity of transform faults, and a landward high terrain limited environment was formed due to the stretch, thinning and subsidence of the Paleozoic weak basement, providing a favorable condition for the development of source rocks in the depression layer. During Cretaceous drift period, platform margin reef and delta-slope floor fan reservoirs were developed. Both the deepwater slope floor fan in the Scotia Basin and the platform margin reef in the Senegal Basin have great exploration potential

Intelligent computing for WPT–MEC-aided multi-source data stream

Abstract Due to its low latency and energy consumption, edge computing technology is essential in processing multi-source data streams from intelligent devices. This article investigates a mobile edge computing network aided by wireless power transfer (WPT) for multi-source data streams, where the wireless channel parameters and the characteristic of the data stream are varied. Moreover, we consider a practical communication scenario, where the devices with limited battery capacity cannot support the executing and transmitting of computational data streams under a given latency. Thus, WPT technology is adopted for this considered network to enable the devices to harvest energy from the power beacon. In further, by considering the device’s energy consumption and latency constraints, we propose an optimization problem under energy constraints. To solve this problem, we design a customized particle swarm optimization-based algorithm, which aims at minimizing the latency of the device processing computational data stream by jointly optimizing the charging and offloading strategies. Furthermore, simulation results illustrate that the proposed method outperforms other benchmark schemes in minimizing latency, which shows the proposed method’s superiority in processing the multi-source data stream

Intelligent resource allocation scheme for cloud-edge-end framework aided multi-source data stream

Abstract To support multi-source data stream generated from Internet of Things devices, edge computing emerges as a promising computing pattern with low latency and high bandwidth compared to cloud computing. To enhance the performance of edge computing within limited communication and computation resources, we study a cloud-edge-end computing architecture, where one cloud server and multiple computational access points can collaboratively process the compute-intensive data streams that come from multiple sources. Moreover, a multi-source environment is considered, in which the wireless channel and the characteristic of the data stream are time-varying. To adapt to the dynamic network environment, we first formulate the optimization problem as a markov decision process and then decompose it into a data stream offloading ratio assignment sub-problem and a resource allocation sub-problem. Meanwhile, in order to reduce the action space, we further design a novel approach that combines the proximal policy optimization (PPO) scheme with convex optimization, where the PPO is used for the data stream offloading assignment, while the convex optimization is employed for the resource allocation. The simulated outcomes in this work can help the development of the application of the multi-source data stream

Enrichment of Hydrogen from a Hydrogen/Propylene Gas Mixture Using ZIF-8/Water-Glycol Slurry

In this work, zeolitic imidazolate framework-8 (ZIF-8), a subclass of metal organic frameworks (MOFs), was dispersed in a water-glycol solution to form a porous slurry. Using this porous slurry, a tail gas mixture containing hydrogen/propylene was separated. Experiments were performed to investigate the effects of using only the solid ZIF-8 material, a ZIF-8/water slurry, a ZIF-8/glycol slurry, or a ZIF-8/water-glycol slurry on the selectivity of the separation. The experimental results show that the slurry made from ZIF-8/water-glycol (20%) achieves good gas separation. The respective influences of the solid content, initial pressure, and temperature on the separation performance were also investigated in detail. We found that lower temperature, a ZIF-8 mass fraction of 20 wt %, and a higher operation pressure are suitable for the recovering of hydrogen from a H2/C3H6 mixture. The selectivity of C3H6 over H2 reaches 128 at 680 kPa initial pressure. The slurries were completely reusable for at least three cycles. The structure of the ZIF-8 material was not altered after repeated separation, meaning the material can likely be reused more than three times on an industrial scale

Microbial Community Structure Diversity in the Dewatered Sludge from 4 Different Waste Water Treatment Plants used for CSRB in Colder Season

Compacted Sludge Reducing Barrier (CSRB) was tested to be a feasible barrier for Acid Mine Drainage (AMD) from tailings in case the ground water contamination. Because of its double function (encapsuling and reducing), the microbial community structure diversity in the sludge played a key role. In this paper, we researched the correlation between heavy metals and microbial structure diversity in the dewatered sludge from 4 different sewage treatment process plants in Lanzhou city, a developing area of northwest China, in the colder season. The results indicated that the microbial community structure diversity differed and were unique among the different sewage plants; their correlation with heavy metals was also unique independently

Acanthopanax senticosus Harms improves Parkinson's disease by regulating gut microbial structure and metabolic disorders

Parkinson's disease (PD) is the second most common neurodegenerative disease, with an increasing prevalence as the population ages, posing a serious threat to human health, but the pathogenesis remains uncertain. Acanthopanax senticosus (Rupr. et Maxim.) Harms (ASH) (aqueous ethanol extract), a Chinese herbal medicine, provides obvious and noticeable therapeutic effects on PD. To further investigate the ASH's mechanism of action in treating PD, the structural and functional gut microbiota, as well as intestinal metabolite before and after ASH intervention in the PD mice model, were examined utilizing metagenomics and fecal metabolomics analysis. α-syn transgenic mice were randomly divided into a model and ASH groups, with C57BL/6 mice as a control. The ASH group was gavaged with ASH (45.5 mg/kg/d for 20d). The time of pole climbing and autonomous activity were used to assess motor ability. The gut microbiota's structure, composition, and function were evaluated using Illumina sequencing. Fecal metabolites were identified using UHPLC-MS/MS to construct intestinal metabolites. The findings of this experiment demonstrate that ASH may reduce the climbing time of PD model mice while increasing the number of autonomous movements. The results of metagenomics analysis revealed that ASH could up-regulated Firmicutes and down-regulated Actinobacteria at the phylum level, while Clostridium was up-regulated and Akkermansia was down-regulated at the genus level; it could also recall 49 species from the phylum Firmicutes, Actinobacteria, and Tenericutes. Simultaneously, metabolomics analysis revealed that alpha-Linolenic acid metabolism might be a key metabolic pathway for ASH to impact in PD. Furthermore, metagenomics function analysis and metabolic pathway enrichment analysis revealed that ASH might influence unsaturated fatty acid synthesis and purine metabolism pathways. These metabolic pathways are connected to ALA, Palmitic acid, Adenine, and 16 species of Firmicutes, Actinobacteria, and Tenericutes. Finally, these results indicate that ASH may alleviate the movement disorder of the PD model, which may be connected to the regulation of gut microbiota structure and function as well as the modulation of metabolic disorders by ASH