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Many studies have shown that clustered Wireless Sensor Networks (WSNs) have a better performance in terms of the balance of energy and lifetime. However, due to the harsh environment and open communication, the clustered WSNs are easy to be attacked. The selective forwarding attack is one of the most difficult attacks to be detected. When a malicious sensor node launches the selective forwarding attacks, it drops part of or all the data packets it received. In this paper, we propose a Noise-Based Density Peaks Clustering (NB-DPC) algorithm for detecting selective forwarding attacks. It can detect selective forwarding attacks by clustering the Cumulative Forwarding Rates ( CFRs ) of all sensor nodes. The NB-DPC algorithm has been improved by defining noise points specifically for identifying malicious behavior and deleting the unnecessary steps in Density Peaks Clustering (DPC) for faster detection speed. The NB-DPC has a low Missed Detection Rate (MDR) and False Detection Rate (FDR) of below 1% according to the simulation results.

In the event-driven wireless sensor networks (EWSNs), the event of interests occurs irregularly and at random in the network. Then, sensor nodes near the event sense the event and send out data packets of the event. Next, router nodes (RNs) forward those packets to the sink node (SN) by multi-hop communications. Compromised RNs would become malicious and launch selective forwarding attacks by dropping part of or all the packets from other nodes. On the other hand, a harsh environment makes the channel poor, so the routing nodes under a harsh environment have low packet forwarding rates because they sometimes have to give up forwarding the current packets after many tries to forward them due to poor channel. If the malicious nodes’ forwarding rates become close to those of nodes under a harsh environment, the schemes based on packet forwarding rates for detecting selective forwarding attack may fail because they cannot differentiate the low data packet forwarding rates resulting from the malicious behaviors or harsh environment. To solve this problem, we provide a combined scheme for detecting selective forwarding attack in wireless sensor networks (WSNs) under harsh environments. This scheme employs a data clustering algorithm (DCA) to screen the malicious nodes out by clustering their cumulative forwarding rates (CFRs) and designs a voting decision method to protect the nodes under a harsh environment from being judged as malicious nodes. The simulation results show that our scheme has a low false detection rate (FDR) of 1% and a low missed detection rate (MDR) of 5% respectively with negligible energy consumption in WSNs under a local variable harsh environment.

Perinatal exposure to nicotine produces ventilatory and chemoreflex deficits in neonatal mammals. Medullary 5-HT neurons are putative central chemoreceptors that innervate respiratory nuclei and promote ventilation, receive cholinergic input and express nicotinic acetylcholine receptors (nAChRs). Perforated patch clamp recordings were made from cultured 5-HT neurons dissociated from the medullary raphé of 0–3 day old ePet-EYFP mice. The effect of exposure to low (6 mg kg(−1)day(−1)) or high (60 mg kg(−1)day(−1)) doses of nicotine in utero (prenatal), in culture (postnatal), or both and the effect of acute nicotine exposure (10 μM), were examined on baseline firing rate (FR at 5% CO(2), pH = 7.4) and the change in FR with acidosis (9% CO(2), pH 7.2) in young (12– 21 days in vitro, DIV) and older (≥ 22 DIV) acidosis stimulated 5-HT neurons. Nicotine exposed neurons exhibited ~67% of the response to acidosis recorded in neurons given vehicle (p=0.005), with older neurons exposed to high dose prenatal and postnatal nicotine, exhibiting only 28% of that recorded in the vehicle neurons (p

Deployed in a harsh or hostile environment and running in an unattended state, wireless sensor networks (WSNs) are vulnerable to many attacks. The selective forwarding attack is one most difficult to be detected, and trust-based detection methods often fail especially under the poor wireless channels. Based on nodes’ cumulative forwarding rates ( CFRs ) and cumulative transmission rates ( CTRs ), we propose a clustering scheme in clustered WSNs to divide the nodes into three types: malicious, suspicious, and regular nodes. To defend selective forwarding attacks of malicious nodes, our scheme isolates them from the network. For suspicious nodes, our scheme uses the non-cooperative game with incomplete information to force them to promote forwarding rates. In the game, the reward and punishment mechanism reduces the attackers’ expected revenues and trust values. And the suspicious nodes, screened out by our clustering method, will be forced to forward packets to elude our detecting scheme. The Nash equilibrium of the game between regular nodes and suspicious nodes is proved to exist here. Simulation results show that our scheme can promote network throughput largely, and our dynamic-time behavior monitoring scheme can gain a longer network lifetime than that of the full-time behavior monitoring scheme.

Background: Vector control has been a key strategy in malaria prevention and elimination for decades. However, insecticide resistance is becoming a serious threat to vector control. Anopheles sinensis is one of the important transmission vectors for malaria in Guizhou Province, China. However, little is known on insecticide resistance status and related mechanism. In this study, the diversity and frequency of the major insecticide resistance associated genes such as voltage-gated sodium channel (vgsc) and acetylcholinesterase-1 ( ace-1 ) genes that encoded the target proteins of Pyrethroids and OPs were investigated in field populations.Methods: Adult mosquitoes were collected from 12 sampling sites across Guizhou by lamp trapping. Female An. sinensis were identified by morphological and molecular identification. Genomic DNA was extracted to amplify vgsc and ace-1 gene fragments. PCR products were sequenced bi-directly. Mutations of vgsc gene at locus 1014 and that of ace-1 at locus 119 were analyzed using MEGA 7.1 software, and the frequencies of mutations were calculated respectively.Results: 5 kdr mutation alleles at the locus 1014 of vgsc gene as a result of three amino acid replacements ( namely 1014F/C/S) in 548 samples of 12 An. sinensis populations. The total frequency of kdr mutation alleles was 27.4%, of which the TTT/C (F) allele had a highest mutation frequency of 22.5%. The top three mutation genotypes were from XiShui, TongZhi and DeJiang populations collected in north Guizhou. There were three alleles at locus 119 in ace-1 gene with 49.47% of GGC/G, 0.17% of GGT/G and 50.36% of AGC/S. The 100% frequency of mutation genotypes (GS, SS) was found in CeHeng, LuoDian and SanDu populations gathered in southwest Guizhou.Conclusion: A diverse genetic mutations of vgsc and ace-1 genes are found in An. sinensis in Guizhou. There are a significant geographical heterogeneities of allele frequency among different populations in Guizhou. A high frequency of kdr mutation (>44 %) in north Guizhou. The 119S mutation of ace-1 gene is present at a high frequency in most An. sinensis populations in Guizhou, especially in the previously highly endemic malaria regions. These findings suggest continued monitoring of the genotypic diversity of insecticides resistance genes may assist to formulate a region-customized resistance management strategies.

The key pre-distribution schemes in wireless sensor networks (WSNs) have attracted researchers’ attentions recently in some applications. These researches of key pre-distribution focus on the balance among security, energy overhead and network resilience, because of the low computing ability, small storage and limited energy of nodes in WSNs. In this paper, a key pre-distribution scheme based on sub-regions is proposed for multi-hop wireless sensor networks. The significant contribution of this scheme is that both the least number of polynomials stored in one sensor node and the least number of nodes storing the same polynomial can be determined such that any two neighbor nodes can communicate securely. The sub-regions are formed by diffusing hop-by-hop without any node’s location information, and every node has at least one common polynomial with its neighbors to generate the session key between them. Even if k (k

Security is critical to any networks, including WSNs. The packets are transmitted hop by hop in WSNs over a broadcasting medium, which makes them vulnerable. So, data encryption should be employed. Due to the resource-limited nodes in WSNs, the producing, distribution, and management of keys, needful for encryption, become challenging research issues. Among them, key distribution is the most complicated because of nodes’ random deployment and poor memory space. In this paper, a novel key distribution scheme of bivariate symmetric polynomials based on sub-region is proposed for distributed WSNs. With reasonable division of sub-regions, the process of keys distribution goes on without nodes’ location information. It is extremely different from location-based or grid-based key distribution schemes. More obvious advantage is that the number of polynomials stored in each node is much less than E–G scheme and poly&&q-composite scheme. The simulation result shows our scheme far outperforms the poly&&q-composite scheme with much less energy overhead.

6LoWPAN, which realizes the seamless connection between the IP control network and wireless sensor network. Therefore, we propose a fast scheme of wireless sensor networks access to IPv6 in this paper based on 6LowPAN. Through the design of software and hardware, the network can fast access IPv6. The multi-node, large-scale wireless sensor network and IP wired network are seamlessly connected and data exchange can be realized. That can meet the application requirements of sensor network point-to-point, data exchange, and command issuing among different networks.

Reliable transmission and long lifetime are our main goals for wireless body sensor networks (WBSNs). Due to the mobility of the human body, the network topology often changes, and the problem of node connection interruption is inevitable. To solve the problem, the Relay Selection and Interruption Processing (RSIP) scheme is proposed in this paper. It established a function of the residual energy and the historical transmission success rate of each node to select the relay node forwarding data to implement dynamic routing transmission. Also, an interrupt processing algorithm in RSIP is used to deal with the connection interruption problem storing data, delaying forwarding data, dropping data when timeout, and finding more reliable relay nodes. The simulation results show that the RSIP scheme extends the lifetime by approximately 12.4%, 20.8%, and 35.5% compared with the CLDO scheme, the JRP scheme, and the EERP scheme respectively, as well as it has higher throughput rate than these three schemes under non-bad situations.

In Sybil attack, a single faulty entity illegitimately claims multiple identities to gather more packets, which is extremely detrimental to network performance. This paper proposes an enhanced RSSI-based detection scheme with an innovative detection framework, including suspicious node screening phase and Sybil node verification phase. Introducing reputation module and adaptive threshold, malicious nodes are figured and marked by monitoring node promptly, which is essential to guarantee the reliability of detection nodes. In the collaborative work, monitoring node screens out the suspicious Sybil nodes firstly, and then selects two high reputation nodes for every suspicious node as detection nodes to carry out the verification of Sybil nodes. Theoretical analysis and simulation results show that our scheme achieves fast locating ability and high detection accuracy with low energy consumption.

With the popularity of wireless sensor networks (WSNs), it is high time to solve the tough problem of isolated nodes. To avoid isolated clusters effectively, we proposed Diffusion Clustering Routing Protocol (DCRP). In this scheme, clusters are diffusing outward from the base station (BS) hop by hop. BS and the one-depth sensor nodes form the first cluster and then new cluster heads (CHs) are selected from the member nodes of existing clusters. Moreover, the optimal CHs equation (1) consist of three factors of the number of neighbor nodes, depth and residual energy. DCRP realizes the communication between neighbour CHs without the help of relay nodes and makes energy consumption equilibrate among CHs during data transmission, prolonging the lifespan of WSNs with low transmission delay. Table 1 shows that DCRP extends the lifespan of WSNs by 65%, 16% and 10% respectively compared with DEBR, EEUC and MOCH.

CYP4B1 belongs to the mammalian CYP4 enzyme family and is predominantly expressed in the lungs of humans. It is responsible for the oxidative metabolism of a wide range of endogenous compounds and xenobiotics. In this study, using data from The Cancer Genome Atlas (TCGA) project and the Gene Expression Omnibus (GEO) database, a secondary analysis was performed to explore the expression profile of CYP4B1, as well as its prognostic value in patients with lung adenocarcinoma (LUAD). Based on the obtained results, a significantly decreased CYP4B1 expression was discovered in patients with LUAD when compared with their normal counterparts (pp = 0.0041), history of pharmaceutical (p = 0.0127) and radiation (p = 0.0340) therapy, mutations in KRAS/EGFR/ALK (p = 0.0239), and living status of dead (p = 0.0026). Survival analysis indicated that the low CYP4B1 expression was an independent prognostic indicator of shorter survival in terms of overall survival (OS) and recurrence-free survival (RFS) in patients with LUAD. The copy number alterations (CNAs) and sites of cg23440155 and cg23414387 hypermethylation might contribute to the decreased CYP4B1 expression. Gene set enrichment analysis (GSEA) suggested that CYP4B1 might act as an oncogene in LUAD by preventing biological metabolism pathways of exogenous and endogenous compounds and enhancing DNA replication and cell cycle activities. In conclusion, CYP4B1 expression may serve as a valuable independent prognostic biomarker and a potential therapeutic target in patients with LUAD.

Many key management schemes have been proposed to ensure the security of communication in wireless sensor networks, which aims to balance the contradictory relationship among energy overhead and network’s resilience. In this paper, a novel key-distributed scheme based on sub-regions division is proposed for distributed wireless sensor networks. Firstly, using the characteristics that the signals are in the form of a circle to transmit, we can form many sub-regions with a circular boundary. Secondly, a certain amount of bivariate symmetric polynomials will be distributed to nodes by sub-region. Finally, we choose the hash function value which is generated by all the common bivariate symmetric polynomials of the two communication nodes as the session keys. It ensures any two adjacent nodes can communicate securely. The simulation results show that our scheme can reduce the average energy consumption by about 27.6%–60.1% compared with traditional scheme and the invulnerability of our scheme is better.

Mobile wireless sensor network (MWSN) has the features of self-organization, multiple-hop and limited energy resources. It is vulnerable to a wide set of security attacks, including those targeting the routing protocol functionality. In this paper, the existing security problems and solutions in MWSN are summarized, and then a trust management system based on neighbor monitoring is proposed. In the trust management system, the trust value is calculated by the neighbor monitoring mechanism, and the direct trust value and the indirect trust value are combined to establish the distributed trust model to detect the malicious nodes. The consistency check algorithm is capable of defending against the attacks on the trust model. In addition, because of the limited energy of the sensor nodes, the energy-balanced algorithm is introduced to prolong the lifespan of MWSN. The residual energy and energy density are considered in the routing decision. Finally, the simulation experiments show that the proposed algorithm can detect the malicious nodes effectively and achieve the energy-balanced goal to prolong the lifespan of MWSN.

Lhermitte-Duclos disease (LDD) is a rare, non-cancerous entity characterized by enlarged, abnormally developed cerebellar folia containing dysplastic cells. Symptomatic LDD is commonly observed in adults (adult-onset LDD, aLDD) as an isolated condition or associated with Cowden's disease (CD). The present study aimed to investigate the magnetic resonance imaging (MRI) characteristics and the underlying pathological findings in 7 cases of aLDD, with emphasis on the association with CD and the need for active cancer surveillance once the diagnosis of LDD is confirmed. The MRI findings along with the clinical and histopathological data collected from 7 patients with aLDD were retrospectively reviewed. The diagnosis of CD was based on a range of clinical characteristics, according to the International Cowden Consortium Criteria. A thorough review of the published data was conducted and our results indicated that all 7 cases shared similar MRI characteristics, whether the aLDD was sporadic (2 cases) or associated with CD (5 cases), including a highly typical non-enhancing striated MRI appearance of thickened folia, consisting of alternating bands on T1- and T2-weighted images. On gross examination, the involved cerebellar folia were distorted and enlarged, whereas the histopathological examination revealed that the molecular layer was widened and occupied by abnormal ganglion cells. Moreover, a reduction in the number or absence of the Purkinje cells and hypertrophy of the granular cell layer were observed. Our findings were consistent with the diagnosis of LDD. Variable levels of vacuolization of the white matter and the molecular layer were observed in all the cases. Notably, CD34 immunohistochemical analysis revealed the presence of angiogenesis within the lesions. aLDD associated with CD exhibited no pathological or immunohistochemical characteristics that were distinct from those of isolated aLDD. Of the 7 cases of aLDD, 5 presented with symptoms suggestive of CD, which is a syndrome associated with a high risk of multiple benign and malignant neoplasms. In conclusion, aLDD exhibits characteristic MRI and histopathological findings and displays a strong association with CD. Therefore, we recommend that the MRI diagnosis of aLDD triggers active cancer surveillance and preventive care.

The security problems of wireless sensor networks (WSN) have attracted people’s wide attention. In this paper, after we have summarized the existing security problems and solutions in WSN, we find that the insider attack to WSN is hard to solve. Insider attack is different from outsider attack, because it can’t be solved by the traditional encryption and message authentication. Therefore, a reliable secure routing protocol should be proposed in order to defense the insider attack. In this paper, we focus on insider selective forwarding attack. The existing detection mechanisms, such as watchdog, multipath retreat, neighbor-based monitoring and so on, have both advantages and disadvantages. According to their characteristics, we proposed a secure routing protocol based on monitor node and trust mechanism. The reputation value is made up with packet forwarding rate and node’s residual energy. So this detection and routing mechanism is universal because it can take account of both the safety and lifetime of network. Finally, we use OPNET simulation to verify the performance of our algorithm.

A wireless sensor network (WSN) faces a number of outsider and insider attacks, and it is difficult to detect and defend against insider attacks. In particular, an insider selective-forwarding attack, in which the attackers select some of the received packets to drop, most threatens a WSN. Compared to a distributed WSN, a cluster-based WSN will suffer more losses, even the whole network’s destruction, if the cluster head is attacked. In this paper, a scheme solving the above issues is proposed with three types of nodes, the Cluster Head (CH), the Inspector Node (IN) and Member Nodes (MNs). The IN monitors the CH’s transmission to protect the cluster against a selective-forwarding attack; the CH forwards packets from MNs and other CHs, and randomly checks the IN to ascertain if it works properly; and the MNs send the gathered data packets to the CH and evaluate the behaviors of the CH and IN based on their own reputation mechanism. The novelty of our scheme is that in order to take both the safety and the lifespan of a network into consideration, the composite reputation value (CRV) including forwarding rate, detecting malicious nodes, and surplus energy of the node is utilized to select CH and IN under the new suggested network arrangement, and the use of a node’s surplus energy can balance the energy consumption of a node, thereby prolonging the network lifespan. Theoretical analysis and simulation results indicate that the proposed scheme can detect the malicious node accurately and efficiently, so the false alarm rate is lowered by 25.7% compared with Watchdog and the network lifespan is prolonged by 54.84% compared with LEACH (Low Energy Adaptive Clustering Hierarchy).

Beijing IR Free-Electron laser facility has been under upgrade in several aspects. For system modification, a new undulator beam line parallel to the old one that permits BFEL to simultaneously operate at two different wavelengths and a beam line to produce coherent synchrotron radiation and Compton back-scattering soft X-ray are being added. Optical beam pipe from undulator output to the experiment rooms is under fabrication. For improvement of the stability of operation, much work had been done to reduce the fluctuations of the electron beam parameters and the time jitter of the RF pulses. For extension of wavelength of operation, Au plated copper mirrors with axial out-coupling hole were used instead of the original multi-layer dielectric mirrors. For improving the laser performance, a new 31/2 cavity RF gun is pending installation, and a self-adaptive, feed-forward control system for beam loading compensation of the microwave electron gun to avoid longitudinal emittance blow-up has been successfully tested. Separate, independent RF power feeds of the RF gun and linac section will be implemented to facilitate the optimization of the operating conditions. (C) 1998 Elsevier Science B.V. All rights reserved.

To balance energy load is a key point in wireless sensor networks (WSNs). LEACH, a popular energy-efficient protocol in WSN, manages the operation of network based on clustering algorithm. Since all of the nodes have the same probability to become cluster heads, it can not be used in heterogeneous WSNs (HWSNs). Several other methods, such as SEP, DEEC and EDFM have been proposed in literatures. In this paper we propose a new protocol, Fixed Zone Clustering Protocol (FZCP), which is also based on clustering, but it is different from above protocols. In our protocol the zones of clusters are determined in advanced and cluster heads are elected based on residual energy and expected energy cost. Each cluster has only one cluster head. Simulations show that FZCP can put off the dead time of first node by about 11%, 38% and 156% compared with EDFM, SEP and LEACH.

Analysis of network traffic has shown that traffic data exhibits high degree of self-similarity at different time scale. The feature of self-similarity indicates that there exists a predictive structure of the network traffic. In this paper, an improved finite-impulse-response neural network which utilizes momentum-modified temporal back-propagation algorithm is proposed for traffic prediction. Then the prediction results are used for dynamic buffer allocation to reduce packet loss in queuing systems. Simulation results show that the FIR neural network has good ability for traffic prediction, and the dynamic buffer allocation scheme based on traffic prediction with FIR neural network can effectively reduce packet loss rate.

In wireless sensor network (WSN), the total energy is restricted, how to make good use of the limited energy resource is a very important aspect in the research of WSN. In this paper, a more reasonable energy consumption model is proposed: Optimal Energy Consumption Model (OECM). Under the new model of energy consumption, different network parameters can obtain different optimal clusters. It is different from LEACH algorithm which has the same clusters for any WSNs if the number of node is a constant. The simulation results show that the optimal number of cluster heads is not only related with the number of the nodes n, but also with the radius of the network R, packet length L and circuit energy dissipation.

In this paper, a new heterogeneous wireless sensor networks (HWSNs) model with energy heterogeneity and computational heterogeneity is proposed. Energy dissipation structure and optimal cluster head number function in HWSNs are obtained based on mathematics model, providing the guidance for designing energy efficient clustering routing protocols. Besides, we propose a new energy efficient routing mechanism named EDFM, the cluster head election algorithm in EDFM is based on energy dissipation forecast method which considers the residual energy and energy consumption rate in all nodes. Simulation results show that EDFM balances energy consumption better than conventional routing protocols, and prolongs the lifetime of networks obviously.

A novel buffer management algorithm named dynamic neural sharing (DNS) is suggested in this paper. It is based on the back propagation learning algorithm (BPA). Simulations show that it can reduce the packet loss in self-similar traffic patterns, and a trade-off between packet loss and fairness can be realized well than those traditional algorithms such as complete partitioning (CP), complete sharing (CS) and static partial sharing (SPS).

Along with the abundance of traffic types and increase of requirements to QoS, the way to allot the limited resources becomes more and more important. This article analyzes the problem of bandwidth allocation for video traffic according to three traffic models and puts forward corresponding calculation methods. The results of simulation demonstrate that under the condition of fixed buffer size, the method based on the log-normal-FARIMA model provides much smaller loss rate.

A 48-year-old woman was admitted with a 3-year history of intermittent dizziness and unstable gait. Cranial MRI demonstrated a laminated lesion of T2 hyperintensity and T1 hypointensity involving the left cerebellar hemisphere, which appeared enlarged (figure, A–C). Secondary hydrocephalus and Chiari I malformation were observed. Because the striated appearance on MRI was characteristic of Lhermitte-Duclos disease,1 presurgical diagnosis was made. Total resection of this lesion was performed, and histopathologic evaluation confirmed the diagnosis (figure, D). Follow-up neuroradiologic studies revealed no recurrence. However, recent ultrasonography showed multiple nodules in the patient’s right breast, which was predictive of a confident clinical diagnosis of Cowden disease.2