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The development of offshore wind farms has experienced rapid growth during the past decade. In particular, China has the highest number of installations worldwide, but some challenges exist for further development. Consequently, some researchers suggest combining wave energy with offshore wind energy. To fully implement this plan, a comprehensive resource assessment of combined offshore wind and wave energy systems is needed. Investigations of the parameters, such as the spatial and temporal distribution of wind and wave energy, aggregate resource reserves, available technical potential, and total capacity factor, are vital for designing the required wind turbines and wave energy converters. To assist scientific development and governmental decision making, this paper aims to evaluate offshore wind and wave energy resources from a technological perspective. The results show that theoretical offshore wind and wave energy resources are abundant in China's ocean territory, with a potential of approximately 3 TW. Technically, of the three most popular offshore wind turbines, i.e., 6, 8, and 10 MW, 10 MW is overall the most suitable in China. However, of the three wave energy converters, i.e., 120, 250, and 750 kW, 120 kW is the best candidate for Liaoning Province, and 750 kW is the most suitable for the remainder of its region. Overall, the total annual energy production is approximately 7000 TWh. [ABSTRACT FROM AUTHOR]

While functional MRI (fMRI) studies have mainly focused on gray matter, recent studies have consistently found that blood-oxygenation-level-dependent (BOLD) signals can be reliably detected in white matter, and functional connectivity (FC) has been organized into distributed networks in white matter. Nevertheless, it remains unclear whether this white matter FC reflects underlying electrophysiological synchronization. To address this question, we employ intracranial stereotactic-electroencephalography (SEEG) and resting-state fMRI data from a group of 16 patients with drug-resistant epilepsy. We find that BOLD FC is correlated with SEEG FC in white matter, and this result is consistent across a wide range of frequency bands for each participant. By including diffusion spectrum imaging data, we also find that white matter FC from both SEEG and fMRI are correlated with white matter structural connectivity, suggesting that anatomical fiber tracts underlie the functional synchronization in white matter. These results provide evidence for the electrophysiological and structural basis of white matter BOLD FC, which could be a potential biomarker for psychiatric and neurological disorders. Whether connectivity in white matter detected by functional MRI relates to underlying electrophysiological synchronization is unclear. Here, the authors show that blood-oxygenation-level-dependent (BOLD) functional connectivity and intracranial stereotactic-electroencephalography (SEEG) connectivity are correlated across a wide range of frequency bands. [ABSTRACT FROM AUTHOR]

The widely application of positioning technology has made collecting the movement of people feasible for knowledge-based decision. Data in its original form often contain sensitive attributes and publishing such data will leak individuals' privacy. Especially, a privacy threat occurs when an attacker can link a record to a specific individual based on some known partial information. Therefore, maintaining privacy in the published data is a critical problem. To prevent record linkage, attribute linkage, and similarity attacks based on the background knowledge of trajectory data, we propose a data privacy preservation with enhanced l-diversity. First, we determine those critical spatial-temporal sequences which are more likely to cause privacy leakage. Then, we perturb these sequences by adding or deleting some spatial-temporal points while ensuring the published data satisfy our ( L , α , β )-privacy, an enhanced privacy model from l-diversity. Our experiments on both synthetic and real-life datasets suggest that our proposed scheme can achieve better privacy while still ensuring high utility, compared with existing privacy preservation schemes on trajectory. [ABSTRACT FROM AUTHOR]

To evaluate the surgical outcomes of total anomalous pulmonary venous drainage focusing on survival, postoperative and pulmonary venous obstruction. Further investigate the role of primary sutureless technique in patients with preoperative pulmonary venous obstruction. Consecutive patients underwent total anomalous pulmonary venous drainage repair in our institution during Jan 2000 to Dec 2019 were enrolled into this retrospective analysis. Since 2016, sutureless repair was regularly applied in patients with preoperative pulmonary venous obstruction. All patients with preoperative pulmonary venous obstruction referred before 2016 had underwent traditional repair. A total of 95 patients were included. During follow-up time of 85 months, main endpoints were documented in 21 patients, including 9 (9.5%) early deaths, 3 (2.3%) late deaths and 9 (9.5%) postoperative pulmonary venous obstructions. Preoperative pulmonary venous obstruction was presented in 26 (27.4%) patients with more emergent surgery (14/26 vs 3/69, P < 0.001) was required. Main endpoints occurred more in patients with preoperative pulmonary venous obstruction (4/26 vs 5/69, P = 0.004). Patients experienced sutureless technique had a lower incidence of postoperative PVO at follow-up (0/11 versus 4/11, P = 0.045). Outcomes of surgical repair for total anomalous venous drainage are satisfactory. However, preoperative pulmonary venous obstruction may be accompanying unfavorable early deaths and postoperative pulmonary venous obstruction. Propensity matching analysis showed that sutureless technique was benefit for postoperative pulmonary venous obstruction without longer cardiopulmonary bypass and aortic cross-clamp time. [ABSTRACT FROM AUTHOR]

As a special kind of application of wireless sensor networks, body sensor networks (BSNs) have broad application perspectives in health caring. Big data acquired from BSNs usually contain sensitive information, such as physical condition, location information, and so on, which is compulsory to be appropriately protected. However, previous methods overlooked the privacy protection issue, leading to privacy violation. In this paper, a differential privacy protection scheme for sensitive big data in BSNs is proposed. A tree structure is constructed to reduce errors and provide long range queries. Haar Wavelet transformation method is applied to convert histogram into a complete binary tree. At last, to verify the advantages of our scheme, several experiments are conducted to show the outperformed results. Experimental results demonstrate that the tree structure greatly reduces the calculation overheads which preserves differential privacy for users. [ABSTRACT FROM AUTHOR]

Lung ischemia-reperfusion injury (LIRI) is still an unsolved medical issue, which negatively affects the prognosis of many lung diseases. The aim of this study is to determine the effects of RvD1 on LIRI and the potential mechanisms involved. The results revealed that the levels of complement, immunoglobulin, cytokines, sICAM-1, MPO, MDA, CINC-1, MCP-1, ANXA-1, TLR4, NF-κBp65, apoptosis index, and pulmonary permeability index were increased, whereas the levels of SOD, GSH-PX activity, and oxygenation index were decreased in rats with LIRI. Except for ANXA-1, these responses induced by LIRI were significantly inhibited by RvD1 treatment. In addition, LIRI-induced structure damages of lung tissues were also alleviated by RvD1 as shown by H&E staining and transmission electron microscopy. The results suggest that RvD1 may play an important role in protection of LIRI via inhibition of complement, immunoglobulin, and neutrophil activation; down-regulation of TLR4/NF-κB; and the expression of a variety of inflammatory factors. [ABSTRACT FROM AUTHOR]

In Body Area Networks (BANs), big data collected by wearable sensors usually contain sensitive information, which is compulsory to be appropriately protected. Previous methods neglected privacy protection issue, leading to privacy exposure. In this paper, a differential privacy protection scheme for big data in body sensor network is developed. Compared with previous methods, this scheme will provide privacy protection with higher availability and reliability. We introduce the concept of dynamic noise thresholds, which makes our scheme more suitable to process big data. Experimental results demonstrate that, even when the attacker has full background knowledge, the proposed scheme can still provide enough interference to big sensitive data so as to preserve the privacy. [ABSTRACT FROM AUTHOR]

As a special kind of attack, node capture attack in wireless sensor networks destroys the confidentiality and integrity of network traffic by physically capturing sensor nodes and extracting the cryptographic keys for eavesdropping the communications. However, previous researches pay little attention to the attacking efficiency, which leads to big attacking times and long execution time. In this paper, we propose a graph-based method for modeling the node capture attack on random key pre-distribution scheme. A full graph is constructed to specialize the compromising relationships between nodes and paths, and then the way of evaluating the destructiveness is introduced. The full graph attack (FGA) is designed to ensure the maximum destructiveness of each captured node so as to reduce the attacking times and shorten the execution time, simultaneously. To promote the performance of FGA in attacking efficiency, two optimal attacking algorithms, namely opti-graph attack (OGA) and path covering attack (PCA), are developed. Simulation results show that FGA, OGA and PCA reduce 38, 10 and 51 % attacking times, and enhance 39, 11 and 40 % attacking efficiency than traditional node capture attack methods. Moreover, they save 39, 11 and 50 % energy in compromising the networks. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are composed of a large number of tiny sensor nodes that are self-organized through wireless communication. It aims to perceive, collect, and process information from network coverage areas. The open nature of WSNs makes them easily exposed to a variety of attacks and brings many security challenges. Furthermore, because of the limited resources, some nodes may refuse to forward packets by dropping them to save their resources such as battery, cache, and bandwidth. To resist the attacks from these selfish nodes and to punish them, we propose a fuzzy-based dynamic trust model in this paper. The model uses fuzzy sets combining with grey theory to evaluate every node's trust credibility based on direct trust and indirect trust relationship. Only those with higher trust values can be chosen to forward packets. Those untrustworthy nodes with lower trust values will be detected and excluded from the trust list. Thus, our proposal also produces an incentive to compel the selfish nodes to wellbehave again to participate in the WSN again. Additionally, we introduce the time slice scheme to guarantee a reliable node possess enough time to enjoy its services, which can solve the problem that a suddenly interrupted link causes a significant decrease of the trust value. Simulation results show that our dynamic trust model can not only demonstrate the effectiveness in detecting selfish nodes, but also possess better performance even if the bursty traffic exists. [ABSTRACT FROM AUTHOR]

This study aims to determine the effect of Lipoxin (LX)A on myocardial ischemia reperfusion injury (MIRI) in rats and the related molecular mechanisms. Male SD rats were divided into six groups. The sham operation groups (groups C1, C2) were injected with 2 ml/kg normal saline before and after coronary artery threading, respectively. The MIRI group (groups I/R1, I/R2) were injected with normal saline before and after MIRI, respectively. The LXA groups (groups LX1, LX2) were injected with LXA before and after MIRI treatment, respectively. The hematoxylin-eosin staining and ultrastructural changes of cardiac muscle were observed. The serum levels of interleukin (IL)-1β, IL-6, IL-10, tumor necrosis factor (TNF) α and cardiac troponin I (cTnI) were measured before open-chest operation and at the end of the experiment. The mRNA and protein levels of GRP-78 and caspase-12 were determined in each group. The myocardial cell apoptosis, myeloperoxidase (MPO), superoxide dismutase (SOD), and malondialdehyde (MDA) contents were detected. The mRNA and protein levels of GRP-78 and caspase-12, the apoptosis, the serum IL-1β, IL-6, IL-10, TNF-α, and cTnI concentrations, MPO, SOD, MDA contents were significantly increased in groups I/R1, I/R2, LX1, and LX2 compared with those in groups C1 and C2 ( P < 0.05). The mRNA and protein expression levels of GRP-78 and caspase-12 in groups LX1 and LX2 were lower than those in groups I/R1 and I/R2. Compared with group I/R1 and I/R2, the myocardial neutrophil infiltration and ultrastructure damage were significantly less in groups LX1 and LX2. GRP-78 and IL-10 are expressed both extracellularly and intracellularly, but are mainly expressed in the cytoplasms. In the absence of MIRI, LXA has no detectable effect on GRP-78 and caspase-12 expression. Before and after MIRI, application of LXA significantly inhibits neutrophil activation, and attenuates myocardial inflammatory injury and oxidative stress. LXA downregulates the mRNA and protein expression of GRP-78 and caspase-12. LXA could play a role in myocardial protection via a mechanism related to downregulation of GRP-78 and caspase-12, and inhibition of apoptosis. [ABSTRACT FROM AUTHOR]

In the node compromise attack, the adversary physically captures nodes and extracts the cryptographic keys from the memories, which destroys the security, reliability and confidentiality of the networks. Due to the dynamical network topology, designing an efficient node compromise attack algorithm is challenging, because it is difficult to model the attack or to enhance the attacking efficiency. In this paper, a general algorithm for modeling the node compromise attack in VANET is proposed, which promotes the attacking efficiency by destroying the network backbone. The backbone is constructed using the connected dominating set of the network, which has relevant to the intermeeting time between the vehicles. Then two attacking algorithms are proposed based on the general model, which destroy the network in a centralized and distributed version while maximizing the destructiveness. Simulations are conducted to show the advantages of our scheme. Simulation results reveal that our scheme enhances the attacking efficiency in different mobility models and different applications, which is suitable for modeling the node compromise attack in VANET. At last, discussions are presented to the illustrate the influences of the characteristics to the attacking efficiency with respect to vehicle speed, communication range and key sharing probability. [ABSTRACT FROM AUTHOR]

In the node capture attack, the adversary intelligently captures nodes and extracts the cryptographic keys from their memories to destroy the security, reliability and confidentiality of the wireless sensor networks. However, it suffers from low attacking efficiency and high resource expenditure. In this paper, we approach this attack from an adversarial view and develop a matrix-based method to model the process of the node capture attack. We establish a matrix to indicate the compromising relationship between the nodes and the paths. We propose a Matrix-based node capture attack Algorithm (MA in short), which can maximize the destructiveness while consuming the minimum resource expenditure. We conduct several experiments to show the performance of MA. Experimental results manifest that MA can reduce the attacking round, shorten the execution time, enhance the attacking efficiency and conserve the energy cost. [ABSTRACT FROM AUTHOR]

Body sensor networks (BSNs) enable the pervasive, long-term, and real-time monitoring in any environment and without restriction of activity. Security and privacy are extremely critical issues of BSNs, as sensitive information is transmitted through the wireless network. This paper proposes a novel sensitive data aggregation scheme based on data hiding for BSNs, namely SDAS. SDAS adopts the packet combination based on the sensitive data aggregation tree built in each BSN to reduce the transmission energy consumption by eliminating transmitted redundancy. After lossless compression, the compressed sensitive data are embedded into various ordinary data in the combined packet by using a lightweight data hiding algorithm to prevent the disclosure of the sensitive data and avoid arousing the attention of attackers. Extensive analysis demonstrates that our proposed scheme can ensure a high level of security and privacy of the sensitive data without affecting the ordinary data quality, while delivering low power consumption. [ABSTRACT FROM AUTHOR]

During normal translation, the binding of a release factor to one of the three stop codons (UGA, UAA or UAG) results in the termination of protein synthesis. However, modification of the initial uridine to a pseudouridine (Ψ) allows efficient recognition and read-through of these stop codons by a transfer RNA (tRNA), although it requires the formation of two normally forbidden purine-purine base pairs. Here we determined the crystal structure at 3.1 Å resolution of the 30S ribosomal subunit in complex with the anticodon stem loop of tRNASer bound to the ΨAG stop codon in the A site. The ΨA base pair at the first position is accompanied by the formation of purine-purine base pairs at the second and third positions of the codon, which show an unusual Watson-Crick/Hoogsteen geometry. The structure shows a previously unsuspected ability of the ribosomal decoding centre to accommodate non-canonical base pairs. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are widely deployed to collect data in military and civilian applications today. Due to the open nature of a WSN, it is relatively easy for an adversary to eavesdrop and trace packets in order to capture the receiver. Therefore, location privacy, particularly the location privacy of the sink node, requires ultimate protection because of its critical position in WSNs. In this paper, we propose a sink location privacy protection scheme by injecting fake packets, but every real packet is still routed along its shortest path. The fake packets are routed to some random destinations and some fake sinks in order to provide the path diversity. It is difficult for an attacker to distinguish the real packets from the fake packets. Thus, the chance of finding the real sink by packet-tracing attack is reduced. Privacy analysis shows that the sink location privacy can be protected better with higher successful probability. We examine the packet travel delay, safe time, and energy consumption by both mathematical analysis and simulations. [ABSTRACT FROM AUTHOR]

A Wireless Sensor Network (WSNs) fault-tolerant protocol is proposed in this paper. By setting up a robust cluster topology, the fault-tolerant algorithm can search any faulty node in the path and revise the path furthermore. Once the cluster head fails, it will be substituted by other alternative cluster heads with the lowest cost, and the path will be re-established. Experiments show that this algorithm can not only locate the faulty nodes in the path accurately, shield the influence of the error node in clusters, but also reduce the retransmission times of relevant data caused by error node. Therefore, the proposed algorithm is effective and sufficient enough to resist malicious attack and node losses. In energy consumption aspect, compared with others, the proposed algorithm has a more advantage in energy conservation. [ABSTRACT FROM AUTHOR]

In pervasive computing environments, users can get services anytime and anywhere, but the ubiquity and mobility of the environments bring new security challenges. The user and the service provider do not know each other in advance, they should mutually authenticate each other. The service provider prefers to authenticate the user based on his identity while the user tends to stay anonymous. Privacy and security are two important but seemingly contradictory objectives. As a result, a user prefers not to expose any sensitive information to the service provider such as his physical location, ID and so on when being authenticated. In this paper, a highly flexible mutual authentication and key establishment protocol scheme based on biometric encryption and Diffie-Hellman key exchange to secure interactions between a user and a service provider is proposed. Not only can a user’s anonymous authentication be achieved, but also the public key cryptography operations can be reduced by adopting this scheme. Different access control policies for different services are enabled by using biometric encryption technique. The correctness of the proposed authentication and key establishment protocol is formally verified based on SVO logic. [ABSTRACT FROM AUTHOR]

Abstract  : This study concerns the cognitive process of mathematical problem posing, conceptualized in three stages: understanding the task, constructing the problem, and expressing the problem. We used the eye tracker and think-aloud methods to deeply explore students’ behavior in these three stages of problem posing, especially focusing on investigating the influence of task situation format and mathematical maturity on students’ thinking. The study was conducted using a 2 × 2 mixed design: task situation format (with or without specific numerical information) × subject category (master’s students or sixth graders). Regarding the task situation format, students’ performance on tasks with numbers was found to be significantly better than that on tasks without numbers, which was reflected in the metrics of how well they understood the task and the complexity and clarity of the posed problems. In particular, students spent more fixation duration on understanding and processing the information in tasks without numbers; they had a longer fixation duration on parts involving presenting uncertain numerical information; in addition, the task situation format with or without numbers had an effect on students’ selection and processing of information related to the numbers, elements, and relationships rather than information regarding the context presented in the task. Regarding the subject category, we found that mathematical maturity did not predict the quantity of problems posed on either type of task. There was no significant main group difference found in the eye-movement metrics. [ABSTRACT FROM AUTHOR]