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On the basis of the study of the analog electronic circuit theory, a component-level health quantitative assessment model based on support vector machine algorithm was proposed in this paper. This paper divided the health condition of analog electronic circuits into health status, sub-health status and failure status, then the particle swarm optimization (PSO) was applied on the optimization of support vector optimization parameters. In the end, this paper builds the component-level health quantitative assessment model based on support vector machine algorithm.

Markov random field (MRF) has been widely used in SAR image segmentation because of the advantage of directly modeling the posterior distribution and suppresses the speckle on the influence of the segmentation result. However, when the real SAR images are nonstationary images, the unsupervised segmentation results by MRF can be poor. The recent proposed triplet Markov field (TMF) model is well appropriate for nonstationary SAR image processing due to the introduction of an auxiliary field which reflects the nonstationarity. In addition, on account of the texture features of SAR image, a fusion image segmentation method is proposed by fusing the gray level image and texture feature image. The effectiveness of the proposed method in this paper is demonstrated by a synthesis SAR image and the real SAR images segmentation experiments, and it is better than the state-of-art methods.

In electronic confrontation, Synthetic Aperture Radar (SAR) is vulnerable to different types of electronic jamming. The research on SAR jamming image quality assessment can provide the prerequisite for SAR jamming and anti-jamming technology, which is an urgent problem that researchers need to solve. Traditional SAR image quality assessment metrics analyze statistical error between the reference image and the jamming image only in the pixel domain; therefore, they cannot reflect the visual perceptual property of SAR jamming images effectively. In this demo, we develop a SAR image quality assessment system based on human visual perception for the application of aircraft electromagnetic countermeasures simulation platform. The internet of things and cloud computing techniques of big data are applied to our system. In the demonstration, we will present the assessment result interface of the SAR image quality assessment system.

The jointly quantitative analysis of multi-sensor gait data for the best gait-classification performance has been a challenging endeavor in wireless body area networks (WBANs)-based gait telemonitoring applications. In this study, based on the joint sparsity of data, we proposed an advanced hybrid technique of distributed compressed sensing (DCS) and joint sparse representation classification (JSRC) for multi-sensor gait classification. Firstly, the DCS technique is utilized to simultaneously compress multi-sensor gait data for capturing spatio-temporal correlation information about gait while the energy efficiency of the sensors is available. Then, the jointly compressed gait data are directly used to develop a novel neighboring sample-based JSRC model by defining the sparse representation coefficients-inducing criterion (SRCC), in order to yield the best classification performance as well as a lower computational time cost. The multi-sensor gait data were selected from an open wearable action recognition database (WARD) to validate the feasibility of our proposed method. The results showed that when the comparison ratio and the number of neighboring samples are selected as 70% and 40%, respectively, the best accuracy (95%) can be reached while the lowest computational time spends only 60 ms. Moreover, the best accuracy and the computational time can increase by 5% and decrease by 40 ms, respectively, when compared with the traditional JSRC techniques. Our proposed hybrid technique can take advantage of the joint sparsity of data for jointly processing multi-sensor gait data, which greatly contributes to the best gait-classification performance. This has great potential for energy-efficient telemonitoring of multi-sensor gait.

A simple and sensitive cyclodextrin-micellar electrokinetic capillary chromatography (CD-MEKC) method with UV detection was developed and validated for the determination of vancomycin (VCM) in serum. The separation was achieved in 14 min at 25 °C with a fused-silica capillary column of 40.2 cm × 75 μm i.d. (effective length 30.2 cm) and a run buffer containing 25 mM borate buffer with 50 mM sodium dodecylsulfonate (SDS) (pH 9.5) and 2% sulfobutyl-β-cyclodextrin (sulfobutyl-β-CD). Under optimal conditions for biological samples, good separations with high efficiency and short analysis time were achieved. Several parameters affecting the drug separation from biological matrices were studied, including buffer types, concentrations, and pHs. The methods were validated over the range of 0.9998–99.98 µg/mL. Calibration curves of VCM also showed good linearity (r2 > 0.999). Intra- and interday precisions (relative standard deviation, RSD) were less than 5.80% and 7.38%, and lower limit of quantification (LLOQ) were lower than 1.0 μg/mL. The mean recoveries ranged between 84.03% and 91.69%. The method was successfully applied for monitoring VCM concentrations in serum of patients with peritoneal dialysis-associated peritonitis (PDAP). The assay should be applicable to pharmacokinetic studies and routine therapeutic drug monitoring of this drug in serum.

Background Malignant intraventricular meningiomas are quite rare and may spread along the craniospinal axis or extraneurally. However, simultaneous cerebrospinal dissemination and distal extraneural metastasis has seldom been reported. Case presentation A 51-year-old woman presented with recurrent anaplastic meningioma in the trigone of right lateral ventricle over a 1.5-year period. Suggested radiotherapy was refused after each operation. The patient showed a local relapse and dissemination around the previous tumoral cavity and along the spinal canal during the last recurrence. Left pulmonary metastasis was also found. She died despite multiple lesion resections. Conclusions Malignant intraventricular meningiomas are an uncommon subset of intracranial meningiomas, and have a great potential for intraneural and extraneural metastasis. Systemic investigation for metastasis is required after surgery, especially for those without adjuvant therapies.

Sir, The incidence of postoperative epidural hematoma (EDH) is less than 2 % and most EDHs occur in the supratentorial compartment and produce clinical symptoms within the first 3 days after operation [1, 2]. Different types of EDH respond to different bleeding causes. For regional hematoma which occurred just in the operative area, incomplete hemostasis, hypertension and coagulopathy are regarded as the most important risk factors [1]. Delayed posterior fossa epidural hematoma (PFEDH) is usually associated with occipital trauma as a result of oozing from the fracture edges or a lacerated venous sinus [3, 4]. PFEDH originating from occipital artery (OA) with a long delay after suboccipital craniotomy has not been reported in the English literature. A 51-year-old normotensive male was diagnosed of multiple mass lesions in the bilateral cerebellar hemispheres, vermis and left cerebellopontine angle region with hydrocephalus (Fig. 1a). Decompressive resection of left cerebellar lesion was performed via suboccipital retrosigmoid approach. The surgical procedure was uneventful. Postoperative CT at 1 day and magnetic resonance imaging (MRI) at 3 days showed no bleeding in the surgical region (Fig. 1b, c). Pathological diagnosis of specimen was anaplastic glioma. On the fifth postoperative day, the patient underwent ventricular external drainage as hydrocephalus worsened. Later, he experienced intracranial infection. On the tenth day, sudden incision pain followed by huge hemorrhage from wound occurred without any warning and the patient fell into coma within minutes. Urgent CT revealed a large fresh epidural hematoma of the surgical area (Fig. 1d). The timely hematoma evacuation was performed and an active source of bleeding was identified from the proximate broken end of the occipital artery (Fig. 1e). Despite the total hematoma removal (Fig. 1f), the patient died of intracranial infection and pneumonia. PFEDH after suboccipital craniotomy occurs uncommonly, representing approximately 1 % of all infratentorial craniotomies usually within three postoperative days [5]. Delayed PFEDHs are rarely reported with most of them caused by trauma [3, 4]. To our knowledge, no delayed PFEDH of occipital artery (OA) origin after craniotomy was published. In this case, OA was cut off together with suboccipital muscles by monopolar electrocoaglulation during craniotomy. Although the hemostasis of the broken ends of OA was enhanced by an additional bipolar electrocautery, the risk of rebleeding is possible because the end may contract by its own elasticity into muscle leading to incomplete or C. Tao H. Feng C. You (&) Department of Neurosurgery, West China Hospital, Sichuan University, 37 Guoxue Alley, Chengdu 610041, Sichuan, China e-mail: tcywjj106@163.com

Unsupervised synthetic aperture radar (SAR) image segmentation is a fundamental preliminary processing step required for sea area detection in military applications. The purpose of this step is to classify large image areas into different segments to assist with identification of the sea area and the ship target within the image. The recently proposed triplet Markov field (TMF) model has been successfully used for segmentation of nonstationary SAR images. This letter presents a hierarchical TMF model in the discrete wavelet domain of unsupervised SAR image segmentation for sea area detection, which we have named the wavelet hierarchical TMF (WHTMF) model. The WHTMF model can precisely capture the global and local image characteristics in the two-pass computation of posterior distribution. The multiscale likelihood and the multiscale energy function are constructed to capture the intrascale and intrascale dependencies in a random field (X,U). To model the SAR data related to radar backscattering sources, the Gaussian distribution is utilized. The effectiveness of the proposed model for SAR image segmentation is evaluated using synthesized and real SAR data.

AIM Prediction of outcome for surgical patients with primary pontine hemorrhage (PPH) is seldom reported although many predictors from clinical and radiological features have been identified in conservative patients. The purpose of this study was to assess the prognostic factors affecting the 30-day mortality and 3-month functional outcome in surgical patients after PPH. MATERIAL AND METHODS Forty-five patients with large PPH ( > 5 ml) and Glasgow Coma Scale (GCS) score < 8 were treated surgically at West China Hospital. The demographic, clinical, imaging and follow-up data were collected retrospectively. Factors affecting the mortality and functional outcome were statistically analyzed. RESULTS Fourteen patients (31.1%) died within 30 days and 7 patients (15.6%) gained a favorable functional recovery within 3 months. A multivariate analysis showed that the hematoma volume, GCS score on admission, age, and type of hemorrhage were all significantly related to the 30-day mortality, while the hematoma volume, GCS score on admission, rostrocaudal extension were associated with the 3-month functional outcome. The presence of hydrocephalus was not found responsible for the surgical outcomes. CONCLUSION The identification of these prognostic factors is helpful for selecting the candidates for surgical treatment. Those with younger age, smaller hematoma without rostrocaudal extension, unilateral hemorrhage, and higher GCS score may benefit from surgery.

The neuregulins (NRGs) are a family of alternatively spliced factors that play important roles in nervous system development and disease. In motor neurons, NRG1 expression is regulated by activity and neurotrophic factors, however, little is known about what controls isoform-specific transcription. Here we show that NRG1 expression in the chick embryo increases in motor neurons that have extended their axons and that limb bud ablation before motor axon outgrowth prevents this induction, suggesting a trophic role from the developing limb. Consistently, NRG1 induction after limb bud ablation can be rescued by adding back the neurotrophic factors BDNF and GDNF. Mechanistically, BDNF induces a rapid and transient increase in type I and type III NRG1 mRNAs that peak at 4 h in rat embryonic ventral spinal cord cultures. Blocking MAPK or PI3K signaling or blocking transcription with Actinomycin D blocks BDNF induced NRG1 gene induction. BDNF had no effect on mRNA degradation, suggesting that transcriptional activation rather than message stability is important. Furthermore, BDNF activates a reporter construct that includes 700bp upstream of the type I NRG1 start site. Protein synthesis is also required for type I NRG1 mRNA transcription as cycloheximide produced a super-induction of type I, but not type III NRG1 mRNA, possibly through a mechanism involving sustained activation of MAPK and PI3K. These results reveal the existence of highly responsive, transient transcriptional regulatory mechanisms that differentially modulate NRG1 isoform expression as a function of extracellular and intracellular signaling cascades and mediated by neurotrophic factors and axon-target interactions.

In this study, we design a homogeneous system consisting of Ag nanoprisms and glucose oxidase (GOx) for simple, sensitive, and low-cost colorimetric sensing of glucose in serum. The unmodified Ag nanoprisms and GOx are first mixed with each other. Glucose is then added in the homogeneous mixture. Finally, the nanoplates are etched from triangle to round by H2O2 produced by the enzymatic oxidation, which leads to a more than 120 nm blue shift of the surface plasmon resonance (SPR) absorption band of the Ag nanoplates. This large wavelength shift can be used not only for visual detection (from blue to mauve) of glucose by naked eyes but for reliable and convenient glucose quantification in the range from 2.0 × 10(-7) to 1.0 × 10(-4) M. The detection limit is as low as 2.0 × 10(-7) M, because the used Ag nanoprisms possess (1) highly reactive edges/tips and (2) strongly tip sharpness and aspect ratio dependent SPR absorption. Owing to ultrahigh sensitivity, only 10-20 μL of serum is enough for a one-time determination. The proposed glucose sensor has great potential in the applications of point-of-care diagnostics, especially for third-world countries where high-tech diagnostics aids are inaccessible to the bulk of the population.

Objective Cerebral vasospasm can occur after skull base tumor removal. Few studies concentrated on the posterior circulation vasospasm after tumor resection in the posterior fossa. We aimed to identify the risk factors associated with postoperative vertebrobasilar vasospasm after tumor resection in the foramen magnum. Methods We retrospectively reviewed the data of 62 patients with tumors in the foramen magnum at our institution from January 2010 to January 2015. The demographic data, tumor features, surgical characteristics were collected. Vertebrobasilar vasospasm was evaluated by bedside transcranial Doppler before surgery and on postoperative day 1, 3, 7. Univariate and multivariate analyses were performed to determine the predictors of postoperative vasospasm in the posterior circulation. Results Vertebrobasilar vasospasm was detected in 28 (53.8%) of the 62 patients at a mean time of 3.5 days after surgery. There were 5 (8%) patients with severe vasospasm according to the grading criteria. Age, tumor type, tumor size, vertebral artery encasement, and surgical time were significantly related to vasospasm in the univariate analysis. Further multivariate analysis demonstrated that only age and vertebral artery encasement were independent risk factors predicting the occurrence of postoperative vertebrobasilar vasospasm. Conclusions The incidence of acute vertebrobasilar vasospasm is not uncommon after foramen magnum tumor resection. Age and vertebral artery encasement are significantly correlated with postoperative vasospasm. Close monitoring of vasospasm should be given to patients with younger age and the presence of vertebral artery encasement on the preoperative imaging to facilitate early diagnosis and intervention.

A rapid and sensitive CEC method with methacrylate ester-based monolithic column has been developed for separation and determination of five coumarins (byakangelicin, oxypeucedanin hydrate, xanthotoxol, 5-hydroxy-8-methoxypsoralen and bergapten) in Angelica dahurica extract. Surfactant sodium desoxycholate (SDC) was introduced into the mobile phase as the pseudostationary to dynamically increase the selectivity of analytes instead of increasing the hydrophobicity of stationary phase. In addition, other factors, pH of phosphate buffer, ACN content and applied voltage, for instance, have also an obvious effect on the resolution but little on the retention time. Satisfactory separation of these five coumarins was achieved within 6 min under a 30:70 v/v ACN-buffer containing 20 mM sodium dihydrogen phosphate (NaH(2) PO(4) ) and 0.25 mM SDC at pH 2.51. The RSDs of intraday and interday for relative peak areas were less than 3.0% and 4.7%, respectively; and the recoveries were between 87.5% and 95.0%. The LODs were lower than 0.15 μg/mL and the LOQs were lower than 0.30 μg/mL, respectively, while calibration curves showed a good linearity (r(2) > 0.9979). Finally, five target coumarins from the crude extracts of A. dahurica were separated, purified, and concentrated by D-101 macroporous resin, and were successfully separated and quantitatively determined within 6 min.

Neuregulin 1 (NRG1) is a neuron-derived trophic molecule that supports axoglial and neuromuscular development through several alternatively spliced isoforms; its possible role in the pathogenesis and progression of amyotrophic lateral sclerosis (ALS) is not known. We analyzed the relationship of NRG1 isoform expression to glial cell activation and motor neuron loss in spinal cords of ALS patients and during disease progression in the superoxide dismutase 1 (SOD1) ALS mouse model. Microgliosis, astrocytosis, and motor neuron loss were observed in the ventral horns in ALS patients and were increased in SOD1 mice along with disease progression. Type III (membrane-bound) NRG1 expression was reduced in parallel with motor neuron loss, but Type I (secreted) NRG1 expression was increased and was associated with glial activation. Increased NRG1 receptor activation was observed on activated microglia in both ALS patients and in SOD1 mice. This activation was observed at the time of disease onset and before upregulation of NRG1 gene expression in the mice. The downregulation of membrane-bound Type III NRG1 forms may reflect motor neuron loss, but increased signaling by secreted-type NRG1 isoforms could contribute to disease pathogenesis through glial cell activation. NRG1 might, therefore, represent a novel therapeutic target against disease progression in ALS.

We propose a novel method that exploits BTI to partially offset variation and thus improve SRAM Vmin and yield. We show correlation between a bitcell's power-up state and its static noise margin. By applying stress with periodic re-power-up, device mismatch can be compensated by BTI induced changes. The proposed method has no extra design and area cost. It can be applied during burn-in test to offset manufacturing variation and/or used during the lifetime of the chip to offset variation from real-time aging and hence continue to improve the margins. Simulations in 45nm show that write, read, and hold Vmin at 6σ can be reduced by 128, 75, and 91 mV, respectively. Measurements from a 16Kb 45nm SRAM demonstrate the improvement of Vmin and yield.

Reduced device dimensions and operating voltages that accompany technology scaling have led to increased design challenges with each successive technology node. Large scale 6T SRAM arrays beyond 65nm will increasingly rely on assist methods to overcome the functional limitations imposed by increased variation, reduced overdrive and the inherent read stability/write margin trade off. Factors such as reliability, leakage and data retention establish the boundary conditions for the maximum voltage bias permitted for a given circuit assist approach. These constraints set an upper limit on the potential yield improvement that can be obtained for a given assist method and limit the minimum operation voltage (Vmin). By application of this set of constraints, we show that the read assist limit contour (ALC) in the margin/delay space can provide insight into the ultimate limits for the nano-scale CMOS 6T SRAM.

WiMAX is one of the most promising technologies which is to go through wireless broadband last mile access. Handover procedure plays a crucial role in the mobile WiMAX application. This paper introduces an implementable enhanced handover target cell selection algorithm for WiMAX network based on the effective capacity estimation and neighbor advertisement which can effectively avoid the ping-pong effect and handover synchronization effect. NS-2 simulation is also given to show the performance enhancement of the enhanced algorithm compared with the traditional algorithm based on signal power and 802.16g quick handover algorithm.

This paper examines the impact of technology scaling to 22nm on sub-threshold circuit design and proposes several solutions for sub-threshold circuits in new processes. To maintain energy-efficient sub-threshold operation, we must reduce variation and suppress leakage current. To combat random variation and minimize energy for nodes below 45nm, we show that special strategies are needed for different categories of sub-threshold circuits.

In the process of the image information hiding, the secret image should be pretreated by used of chaos sequences which are produced by chaos system, in order to improve the robustness of the algorithm. Some popular algorithms can be utilized to solve it, for example, the Logistic map could produce the chaos sequences to complete the image pretreated. But, the security of the unidimensional chaos system is weak because the system is a common chaotic encryption system. In this paper, a compound encryption algorithm of a double unidimensional chaos system is recommended according to the ten-thousand-year experience of human, the algorithm is designed by used of two unidimensional chaos sequences to encrypt the places and grey of the pixels respectively. In order to implement the information hiding in wavelet domain conveniently, the algorithm is based on non-uniform B-spline wavelet. The experiments testify that this algorithm possessed the merit of strong robust and drawing blindly.

This paper analyzes write ability for SRAM cells in deeply scaled technologies, focusing on the relationship between static and dynamic write margin metrics. Reliability has become a major concern for SRAM designs in modern technologies. Both local mismatch and scaled VDD degrade read stability and write ability. Several static approaches, including traditional SNM, BL margin, and the N-curve method, can be used to measure static write margin. However, static approaches cannot indicate the impact of dynamic dependencies on cell stability. We propose to analyze dynamic write ability by considering the write operation as a noise event that we analyze using dynamic stability criteria. We also define dynamic write ability as the critical pulse width for a write. By using this dynamic criterion, we evaluate the existing static write margin metrics at normal and scaled supply voltages and assess their limitations. The dynamic write time metric can also be used to improve the accuracy of VCCmin estimation for active VDD scaling designs.

Circuit reliability under statistical process variation is an area of growing concern. For highly replicated circuits such as SRAMs and flip flops, a rare statistical event for one circuit may induce a not-so-rare system failure. The Statistical Blockade was proposed as a Monte Carlo technique that allows us to efficiently filter-to block-unwanted samples insufficiently rare in the tail distributions we seek. However, there are significant practical problems with the technique. In this work, we show common scenarios in SRAM design where these problems render Statistical Blockade ineffective. We then propose significant extensions to make Statistical Blockade practically usable in these common scenarios. We show speedups of 102+ over standard Statistical Blockade and 104+ over standard Monte Carlo, for an SRAM cell in an industrial 90 nm technology.

This paper presents two fast and accurate methods to estimate the lower bound of supply voltage scaling for standby SRAM/cache leakage power reduction of an SRAM array. The data retention voltage (DRV) defines the minimum supply voltage for a cell to hold its state. Within-die variation causes a statistical distribution of DRV for individual cells in a memory array, and cells far out the tail (i.e. >6sigma) limit the array DRV for large memories. We present two statistical methods to estimate the tail of the DRV distribution. First, we develop a new statistical model based on the connection between DRV and static noise margin (SNM). Second, we apply our Statistical Blockade tool to obtain fast Monte-Carlo simulation and a generalized Pareto distribution (GPD) model for comparison. Both the new model and the GPD model offer a high accuracy ( 104times for 1 G-b memory) over Monte-Carlo simulation. In addition, both models show a very close agreement with each other at the tail even beyond 7sigma.

This paper describes the strong effects on sub-threshold digital circuit operation of the ratio of PMOS and NMOS current in a given process. We define the concept of process balance/imbalance as describing this ratio and explain the impact ofdifferent circuit and environmental parameters on processbalance. Many of these characteristics are best understood by the degree to which they increase or further decrease process balance. We also propose a model that provides accurate estimation of the effects of process balance that is useful for understanding the impact of process variations and the appropriate types of circuits to use for sub-threshold operation in a given process.

Canary bitcells act as online monitors in a feedback architecture to sense the proximity to the data retention voltage (DRV) for core SRAM bitcells during standby voltage scaling. This approach implements aggressive standby VDD scaling by tracking PVT variations and gives the flexibility to tradeoff between the safety of data and decreased leakage power. A 90 nm 128 Kb SRAM test chip confirms that the canary cells track changes in temperature and VDD and that they provide a reliable mechanism for protecting core cells in a closed loop VDD scaling system. Power savings improve by up to 30times compared with the conventional guard-banding approach.

Current-mode approach in register file has the great advantage of high operation speed with low power consumption. Under 0.35-/spl mu/m CMOS technology, we present a 1.85-ns read access, 32/spl times/32-bit, five-port register file in which a modified current-sense amplifier is used. The delay match circuit and TSPC-FF are also used to improve speed. Energy saving is achieved by current mode and other key ideas. Simulation results show it consumes 640 mW at 500 MHz 3.3 V. It can still work at 2.3 V with 350 MHz 300 mW.

This paper reports a 1.8-V 64-kb four-way set-associative CMOS cache memory implemented by 0.18 mm 1.8 V 1P6M logic CMOS technology. This cache is designed for a 32-b RISC microprocessor. Effective latency of 3.4 ns and power consumption of 190 mW at 263 MHz are obtained at a supply voltage of 1.8 V. This performance is achieved by using high speed circuit design techniques such as modified high speed current-mode sense amplifier and split dynamic tag comparators.

The design of fluorescent probes for turn-on sensing of anions has been especially significant because it can effectively enhance sensing sensitivity by decreasing the background interference. In the present work, we have systematically studied the potential applications of fluorescent quantum dots (QDs) in turn-on anion sensing. The fluorescence of QDs are firstly quenched by three different mechanisms, i.e. fluorescence resonance energy transfer, electron transfer and surface states modulated fluorescence. The fluorescence of the pre-quenched QDs can then be recovered by various anions due to the modulating effects of added anions on the interaction between QDs and QDs, the interaction between QDs and quenchers, and the surface chemistry of the quenched QDs, respectively. The results described here indicate that turn-on sensing of various anions by QDs-based systems can be achieved by rationally choosing fluorescence modulating strategies, demonstrating the versatility of QDs in the corresponding applications.