The fabrication of the devices was as follows: SOI layer was thinned down using oxidation and oxide removal. Several consecutive oxidation/oxide-removal steps took place in order to ensure a small thickness variation across the wafers. Eventually, several wafers with SOI thickness in the 10 �C 30 nm range were fabricated with with-in-wafer SOI thickness variation not greater than 10%. The SOI EISFET is fully depleted (FD) for the given SOI resistivity (doping) and SOI thickness. MESA-type isolation was used between the devices. Subsequent arsenic implant (15 keV/5 e14)) for the source and drain regions took place followed 100 nm SiO2 PECVD for inter layer dielectric (ILD) and opening of the contacts. Ti/Al/TiN was sputtered and patterned for interconnection purposes followed by 4,500 ? passivation layer of PECVD nitride.
The seed Ti/Au layer was sputtered followed by Au electroplating in the pad areas. The metal gate of the MOSFETs is located over a 100 nm PECVD SiO2 layer which is significantly thicker than the 30 nm LPCVD SiO2 of the FD EISFETs. The last step of the process was the actual opening of the passivation above the FD EISFETs’ active region. This was performed with dry etch followed by final wet etch in order to ensure no physical and/or electrical damage to the underlying active gate.In the overall die layout (Figure 1), the central gold circle defines the sensing area, and the location of the sealing O-ring of the liquid flow-cell. The lower part contains the test structures zone. On the left side, a chemical window (1.5 mm �� 1.
5 mm) is located that was used in order to perform detailed surface analysis (AFM and ellipsometry).Figure 1.Schematic illustration of die layout (17 mm �� 17 mm).2.2. Electronic MeasurementsI-V measurements were performed for both test structures and FD EISFETs. For the FD EISFETs, I-V measurements were performed both under dry and wet conditions. The electrical setting for both the test structures and the FD EISFETs wet measurements are presented in Figures 2A, B, respectively. In order to work in aqueous conditions we designed a unique liquid application apparatus – a flow cell (Figure 3). This unique design facilitated the work in aqueous GSK-3 environments without the need for contact isolation. The liquids were retained within the O-ring gasket while the thumb screws were tightened against the probe-station chuck.
The connecting pads were left out, providing easy approach for electrical testing (see also Figure 1). The apparatus included additional important features; ultra-low sample volume (30 ��L), fast and convenient way of die replacement and black material to prevent light induced currents. A homemade Ag/AgCl wire type reference electrode (VREF) was used for the wet I-V measurements that were performed with various solutions.
A footprint of 2 to 4 m (see Section 2) is intermediate between narrow footprint (0.15 m) used by commercial lidars for very accurate urban building description and other dedicated research airborne canopy lidars Site URL List 1|]# (~10 m, e.g., [8,9]) and spaceborne lidar like ICESat (60 m, e.g., ).The purpose of the present paper is to demonstrate the performance of a UV lidar for canopy characterization. First, we use the full waveform canopy data to reconstruct the 3D structure of delineated and characterized forest areas in the Landes forest (one of these areas is used for long term monitoring and research activities by Institut National pour la Recherche Agronomique).
Second, we validate the lidar retrievals using in situ measurements taken from the ground by field foresters (e.g., ).
Section 2 presents the lidar instrumentation and the test areas in the Landes forest where the field experiments were conducted. Section 3 introduces the methodology used to retrieve: canopy tops, apparent tree tops, apparent crown bases and undergrowth heights. Section 4 shows the lidar-derived canopy structural parameters for each of the test areas and provides with comparisons to in situ measurements. The performance assessment is conducted in two steps by: (i) a statistical comparison between canopy lidar and in situ observations (of a forest stand and several sample plots), and then (ii) a one-to-one comparison between the canopy lidar and in situ observations.
A summary and perspectives for future work are given in Section 5.2.?Experimental Setup2.1.
Canopy Lidar Payload Onboard an ULAThe UV lidar onboard the ULA looks downward close to nadir (see Figure 1). It is built around a compact 355 nm tripled Nd-YAG laser that provides 16 mJ with 5 ns pulse duration at 20 Hz pulse repetition frequency (see Table 1). Eye safety conditions are met at the exit of the optical head (Figure 1(a)). The full waveform Cilengitide lidar signal is digitized at a 100 MHz sampling frequency or 1.5 m sampling resolution along the lidar line-of-sight. The lidar signal acquisitions are recorded during 1 s (20 consecutive shots) and then the data are stored on an on-board portable computer for 1 s.
The shot to shot separation at ground is about 1 m for an ULA horizontal velocity of 20 m s?1. The laser footprint at ground level has a nearly circular Anacetrapib shape of 2.4 m diameter for a 300 m flying altitude above ground level (agl) and nadir pointing. Depending on the ULA attitude while in the air, the successive laser footprints move randomly within 10 to 40 m around the ULA ground track (see Section 3.4). A global positioning system (GPS) tracks the ULA position with an accuracy of 5 m.
ded and allowed to bind for 1 2 hrs, then the wells were washed extensively with PBS T. The binding phage were eluted by treatment with 100 uL of 100 mM glycine HCl pH 2. 0 for 10 min, and the solution was neutralized by addition of 50 uL of 2 M Tris, pH 8. 0. The neutralized phage solution was then added to 5 mL of log phase XL1 Blue E. coli in 2��YT broth supplemented with tetracycline. After 1 hr, 50 ug mL carbencillin along with helper phage were added and the culture was grown at 37 C for 1 hr. Subsequently, 25 mL of 2��YT containing 50 ug mL carbenicillin and 25 ug mL kanamycin were added and the culture was grown at 30 C for 18 hrs. The cells were removed by centrifugation, then the phage was isolated as above and used immediately for subsequent rounds of infection.
Se lection progress was monitored by 1 large scale sequencing of the phage populations and 2 output phage titers from wells Anacetrapib containing the target to wells containing a BSA control. Individual clones were grown small scale for high throughput phage ELISA analysis in deep 96 well plates. Cultures of 1 mL LB broth containing carbencillin were inoculated with colonies corresponding to selectants, helper phage were added and the culture grown at 30 C for 18 hrs. The cells were removed by centrifugation and the supernatant applied directly to ELISA plate wells in which the antigen or control pro tein had been immobilized. Phage solutions were allowed to bind for 15 mins, the wells washed with PBS T, and then the bound phage detected with the anti M13 HRP conjugate as above.
For specificity profile analysis, LF and KLH were purchased from Sigma Aldrich. Single point competitive ELISAs were similar except that the phage solutions were preincubated with 40 nM 5 Helix for 30 min before addition to wells containing the immobilized 5 Helix. Both specificity pro file analysis and single point competition analysis were spotchecked for reproducibility and, in general, gave consistent results among independent experiments. Competitive phage ELISAs were performed essentially as described. Expression of scFv proteins and monoclonal ELISAs Phagemid vectors were converted to expression vectors by replacement of the hinge, GCN4 and pIII CT seg ment downstream of the scFv segment with a hexahistidine tag. The scFv proteins were expressed in the periplasm of E. coli BL21.
Cultures were grown in low phosphate media at 30 C for 14 16 hrs and the cells harvested by centrifugation. Cell lysis was achieved by treatment with Bug Buster. The lysate was clarified by ultracentrifugation and puri fied by nickel affinity chromatography. Purified scFv pro teins were dialyzed into PBS then used immediately for analysis or flash frozen and stored at 80 C. Analysis by ELISA was similar to phage ELISA except that an anti FLAG HRP conjugate was used to detect the scFv protein. Structural modeling of 25B6 To model the 25B6 5 Helix interaction, we used the FixedBBProteinDesign module in Rosetta3 using the co crystal stru
. Methods Cytokines, culture of human RA synovial fibroblasts, and chemical inhibitors TNF was purchased from R D Systems. Fibroblasts were isolated from RA synovium obtained from RA patients undergoing arthroplasty or synovectomy as described previously. For all hu man specimens used in this study, we obtained written informed consent and all aspects of the study were approved by the University of Michigan Institutional Review Board. Allergies were not reported and no skin tests were performed on these RA patients. MAPK inhibitors, an NF ��B inhibitor or a JAK2 inhibitor were used at 10 uM of each inhibitor, e cept PDTC at 200 uM. All inhibitors were purchased from Calbiochem. All e periments were performed in serum free media e cept e periments for IL 18 detection.
Cell lysis and western blotting To study the effect of TNF on caspase 1 e pression, RA synovial fibroblasts were incubated with TNF in RPMI 1640 and processed, as previously described. We used a rabbit anti human caspase 1 antibody over night at 4 C and then horseradish pero idase conjugated antibody for 1 hour at room tem perature. Blots were scanned and analyzed for band intensities, as previously described. Caspase AV-951 1 activity assay RA synovial fibroblasts were pre incubated with the chemical inhibitors for 2 hours and then treated with TNF for 24 hours in serum free RPMI 1640. Cells were washed and then lysed with the lysis buffer from the caspase 1 activity assay kit. Cell lysates were centrifuged, and the supernatant was assessed. Caspase 1 activity in the supernatant was deter mined using a colorimetric caspase 1 activity assay kit.
IL 18 detection in conditioned media RA synovial fibroblasts were stimulated with TNF in RPMI 1640 with 10% fetal bovine serum supplementation for 72 hours. Conditioned me dium was collected and concentrated 10 fold using Amicon Ultra 3,000 MW concentrators from Millipore. Equal volumes of conditioned media were loaded and processed for western blotting as previously described above e cept that primary poly clonal rabbit anti human IL 18 antibody was used. ELISA for IL 18 and IL 18BP RA synovial fibroblasts were stimulated with TNF for 8 to 48 hours in RPMI with 10% FBS and conditioned medium was collected and concentrated as described above. IL 18 was assessed in conditioned media and cell lysates using an ELISA kit from Bender MedSystems.
IL 18BP was assessed in condi tioned media using an ELISA kit from R D Systems. RNA e traction and quantitative real time polymerase chain reaction Following the manufacturers protocol, RNA was isolated from RA synovial fibroblasts and processed as described previously. IL 18 bioactivity The biologic activity of IL 18 was measured using human myelomonocytic KG 1 cells, as previously described. KG 1 cells, with or without mouse monoclonal anti IL 18 antibody at 1 ug ml, were dispensed into the wells of 96 well Falcon microtiter plates. Ne t, 100 uL of samples or recombinant human IL 18 standard was added to each we
. MTF is composed of tilt, hydrodynamic and velocity bunching modulations. According to Nunziata et al. , VB theory focuses on simple particle scattering. On the other hand, DS model focuses backscattering intensity from the surface. SAR image intensity of each facet is computed to generate numerical SAR images. However, DS model is not aimed to velocity bunching.SARAS , which is based on DS model, is developed in time domain to obtain SAR raw signals. They use PO to compute backscattering intensity of each computational grid. The scale of the computational grids is one-quarter of the resolution cell. SAR signals from the grids are calculated in this simulator.The beneficial features and some limitations of our simulator are described as follows.
The simulation process of obtaining microwave backscattering is similar to that of an actual SAR system. In our simulator, the pulse irradiation area is the calculation area. It is divided into computational grids that are smaller than the wavelength of the transmitted microwave to demonstrate accurate interaction between electromagnetic waves and ocean surface waves. PO is also used to calculate microwave backscattering. The time series of microwave backscattering as SAR raw signals is the summation of backscattered microwave from all computational grids in the pulse irradiation area. The position of the calculation area changes with microwave pulse and platform motions to obtain SAR raw signals for range and azimuth directions.One advantage of our simulator is that the phases of the received signals are based on Bragg scattering.
The backscattered microwaves from computational grids smaller than the microwave are emphasized in the Bragg resonant condition. Therefore the simulation adequately reproduces microwave backscattering from the ocean surface. In addition, our simulator can also obtain the time series of SAR raw signals while considering modulations caused by moving ocean waves. In order to understand sophisticated SAR imaging mechanism of ocean waves, we attempt to develop a simulator that generates numerical SAR images with regard to not only motion induced modulations Brefeldin_A but also scattering intensity based on Bragg scattering. Note that our simulation is not suitable for land SAR images because it ignores shadowing and multi scattering, which are important imaging factors for SAR images of land areas.
However, these are considered to be a minor scattering mechanism in ocean SAR images. In the ocean case, motion-induced modulation and microwave scattering on the sea surface are the key factors. Consequently, we focus on these factors in the SAR image simulation for moving ocean surfaces.This paper is organized as follows: firstly, we have simulated a stationary target case to confirm SAR signal processing.
Further information about the wireless sensor node is available in .Figure 3.Wireless nodes. (a) Sensor node; (b) Master node.The master node shown in Figure 3b [40,41] receives processed data from the sensor nodes through short-range wireless communication (ISM band) and transmits these data to the monitoring server through long-range (Code Division Multiple Access��CDMA, ) communication. Four senso
The human brain consists of approximately one hundred billion neurons interconnected in a complex way to perform computational, cognition and memory tasks. Neurons usually interact via synapses, which allow information transmission from one cell to the other. Each neuron has an average of 7,000 synaptic connections.
Being subserved by a complex molecular mechanism, the synapses are capable of changing the efficiency of signal transmission between neurons by sensing electrical activity and chemical concentrations. It is believed that the flexibility of the synaptic connections (e.g., synaptic plasticity) underlies the implementation of computational and cognitive tasks in brain networks. While in living cells, the synaptic plasticity is mediated by complex molecular transformation, in an artificial biosystem, the synaptic transmission can be regulated by adjusting the parameters of an artificial synapse.Significant efforts have been made to represent a synapse by a single device that mimics synaptic connections and behavioral flexibility. This challenging task for biorobotics would allow a direct linkage between neuroscience and artificial intelligence.
Any attempt to construct an artificial brain must Cilengitide consider its complexity. Several attempts have already been made. For example, Sharp et al.  used an electronic circuit to couple two living stomatogastric ganglia neurons. Synaptic behavior has also been imitated by hardware-based neural networks, such as hybrid complementary metal-oxide-semiconductor analogue circuits and other artificial neural devices [2�C4] capable of mimicking the major features of human memory; namely, sensory, short-term and long-term memories. Great progress in nanotechnology has provided significant advances in the miniaturization of synthetic synapses, e.g., the fabrication of a carbon nanotube synaptic circuit . Artificial synaptic devices based on ion migration have been also designed ; some of them [7,8] have demonstrated spike-timing-dependent plasticity , the important mechanism of brain memory, related to the synaptic connection strength in biological circuits and synthetic devices. These devices require precise control of the signal timing to simulate the pre- and post-synaptic potentials in biological systems.
Finally, conclusions and future work are discussed in Section 6.2.?Theoretical BackgroundEarly publications regarding automated acoustic vehicle recognition algorithms were focused mainly on military vehicle signals, in order to develop a system that improves surveillance for security [4�C6]. Compared to acoustic signals, using seismic signals for detection allows the performance to be independent of wind conditions, which can often cause difficulties in acoustic detection. Moreover, seismic waves are less sensitive to factors such as acoustic noise, Doppler effects. Seismic sensors offer many benefits over acoustic and magnetic sensors, in that the propagation through the earth is less sensitive to atmospheric conditions, such as wind, moisture, and temperature [7,8].
Seismic sensors also provide non-line-of-sight detection capabilities for vehicles at significant ranges [9�C11]. Seismic sensors provide good detection range, increased detection capabilities and have been extensively used in many applications [12�C14]. Xin Jin et al.  presents a symbolic feature extraction method for target detection and classification, where the features are extracted as statistical patterns by symbolic dynamic modeling of the wavelet coefficients generated from time series of seismic and PIR sensors. The potential of exploiting seismic surface waves, in particular Rayleigh waves, for military vehicle and personnel tracking was investigated [16,17]. J. Huang et al.  proposed wavelet packet manifold (WPM) which provides a more robust representation for seismic target classification in Unattended ground sensor (UGS) systems.
Dan Li et al.  have provided some promising preliminary results on classifying between wheeled and tracked vehicles. Outcome was positive regarding military vehicles. However, it was found their method was not suitable for non-military passenger vehicles as signals generated by military are louder and more distinguishable [4,9,20,21].2.1. Vehicle Induced Seismic WavesIn the field of pavement dynamics, a vehicle can be regarded as a set of moving loads acting on the pavement, with the pavement modeled as a beam, plate or a multi-layered system on a viscoelastic foundation . Within this framework, a source-path-receiver scenario can be used to characterize vehicles in terms of induced seismic signals.
Vehicles’ contact with irregularities on the road surface induce dynamic loads on the pavement . When Dacomitinib a vehicle, such as a car or a truck, strikes an irregularity on the road surface, it generates an impact load and an oscillating load due to the subsequent ��axle hop�� of the vehicle. The impact load generates seismic waves that are predominant at the natural seismic frequencies of the soil whereas the axle hop generates seismic excitation at the hop frequency.
1.1. First StageThe first step allows adjustment of the configuration of the registration forces and improvement of the selection of the cutting parameters. For this objective, it is proposed to perform short tests with duration less than 10 seconds under different cutting conditions (cutting parameters and type of tool or material workpiece). During the tests cutting forces must be recorded to analyse their magnitude and their frequency ranges as well as the influence of the different cutting parameters on the forces.2.1.2. Second StageThe second step provides, on the one hand, a surface roughness model based on the cutting forces under different cutting conditions and, on the other hand, the best selection of cutting parameters and material workpiece or type of tool according to the surface roughness requirements.
Therefore, it is proposed to carry out medium tests employing the time consumed for the machining along the length of the bar in which cutting forces and surface roughness measurements must be taken.2.1.3. Third StageIn this stage, a model of surface roughness based on the cutting forces under different states of the tool wear is obtained to simulate the behaviour of the tool during its life. To address this objective, with the combination of the most improved cutting conditions obtained previously, long tests with duration of at least 15 min at different states of tool wear are performed. For each state of tool wear, at different times, cutting forces surface roughness must be taken.
Finally, with the aim of measuring and supervising the surface roughness online, it is necessary to implement the model of surface roughness obtained in the cutting forces acquisition system. In addition, according to the surface roughness requirements for a specific application, the allowed limits of the values of surface roughness must also be configured. In such a way that when the value of surface roughness obtained during the process is higher than the imposed limit, a visual or auditory signal indicates the surface roughness measured online is not adequate.2.2. Experimental Protocols2.2.1. Identification of the Turning Tests and Resources EmployedThis investigation is framed within a series of studies in which different materials, types of tools, turning tests, cutting conditions and measurements are involved.
In order to systematize the experimental procedure, alphanumeric codes are used to identify all the different parameters and conditions that are considered for analysis. The identification of each turning test consists on the use of alphanumeric codes to indicate the Brefeldin_A duration of the turning test and the cutting parameters.The tests are divided mainly into three categories according to the duration of the test in the following way:2.2.2.
Genetically modified yeast cells with human regulatory elements have been successfully used also in assessing estrogenicity [7, 21-25] and androgenicity of compounds  and detecting cell Site URL List 1|]# wall-disturbing agents .In this study we introduce an alternative approach for the assessment of non-specific toxicity of several chemicals, even in real-time. Our toxicity assay is based on S. cerevisiae transformed with a modified firefly (Photinus pyralis) luciferase gene (luc) as a reporter for genetic response. The luc gene is inserted into the plasmid pRS316/GPD-PGK between the constitutive promoter GPD and PGK terminator. The plasmid produces light constitutively . Firefly luciferase catalyses the following reaction: Luc + D-luciferin + ATP �� oxyluciferin + AMP + CO2 + PPi + light.
The resulting luminescence (yellowish light) can be measured very sensitively in real-time. In our assays, we use D-luciferin substrate at a pH of 5.0, because in the modified firefly luciferase the last three amino acids of the enzyme have been truncated. The natural peroxisomal targeting signal (Ser-Lys-Leu)  lacking from the C-terminus of the enzyme results in a cytoplasmic expression, which leads to high level of light emission. Under such conditions, where full length firefly luciferase is used  D-luciferin must traverse cytoplasmic and peroxisomal membranes to give light emission. This together with a D-luciferin substrate at a pH of 3.0 results in a low level of light emission .
We have previously shown that keeping the yeast cells at pH of 5.
0 increases the light emission and the growth rate, providing more viable cells for toxicity measurement . Furthermore, an assay can be done in a multi-well plate and the light Batimastat emission produced by luciferase can be measured simply by adding D-luciferin substrate after an exposure of few hours or even in real-time. We show in this study that the acute toxicity of several model compounds representing completely different kinds of molecular families or structures against eukaryotic organisms can now be performed with light-emitting intact yeast cells on the contrary to Hollis et al. .2.?Results and Discussion2.1.
Bioluminescence assayIn this GSK-3 work, we estimated the toxicity of selected chemicals by exposing genetically modified yeast cells and measuring the luminescence produced in the presence of D-luciferin. In our study, the response to different chemicals varied a lot from activation to complete inhibition of light emission depending on the concentrations used. The toxicity of two compounds, 5,6-benzoflavone and rapamycin were monitored continuously in real-time.
The interface response is digitally tuned, compensating non-linearities in the sensor response and undesired effects due to circuit components mismatching. The power consumption can be reduced by powering off the analogue components when the system is not sampling the sensor outputs. In this way, the battery life in portable systems is extended. The proposed circuits were integrated in a 0.35 ��m standard digital CMOS process. The following sections show the use of current-mode analogue adaptive systems in sensor conditioning: design and characteristics of the proposed circuits, experimental measurements and loading effects. The feasibility of a complex conditioning architecture based on these cells is also demonstrated.2.
?Adaptive SystemsAdaptive circuits in sensor conditioning permit tuning the circuit operation to match changes in sensor response due to ageing, environmental effects or sensor replacement, providing optimum performance under any condition by means of a tuning/calibration process. Perceptron [8-9] features make it a worthy candidate to be used in adaptive analogue-digital signal processing, where system operation is programmed by adjusting the values stored in a set of registers. Due to their robustness to circuit non-idealities, mismatches and offsets, tuning operation can be achieved by means of perturbative algorithms .To embed sensor network units in a portable system, they must work with compact low-voltage batteries, making it difficult to process the data in voltage mode. Current-mode electronics give better results at low bias voltages .
The proposed processing elements were designed to provide good transfer features and impedance matching between them. The main current-mode circuits presented are a four-quadrant analogue-digital current AV-951 multiplier (ADM) and a current amplifier that performs a logistic function. By properly combining both processing cells, it is possible to design a non-linear adaptive unit (Figure 1) which will be the basic cell in a multi-layer perceptron designed to extend the linear range of a sinusoidal sensor. [12-13].Figure 1.Proposed adaptive processing unit.3.?Arithmetic CircuitsThe conditioning circuit basically consists of two main blocks: an analog-digital current-mode four-quadrant multiplier (ADM) and a logistic circuit (LC) that performs a non-linear operation.3.1.
Four-Quadrant MultiplierThe four-quadrant current-mode multiplier (Figure 2) is based on a MOS R-2R current ladder (M-2M ladder) , and a current follower as the sign circuit (SC). This circuit is a modified version of a cell that has been previously reported in the literature [15-16].Figure 2.Four-quadrant analog-digital current multiplier.As shown in Figure 2, the most significant bit (b7) determines the direction of the current flow, that is, it selects the sign of the operation.