745 resultados para voltage-sensor
Resumo:
The potential of visible-near infrared spectra, obtained using a light backscatter sensor, in conjunction with chemometrics, to predict curd moisture and whey fat content in a cheese vat was examined. A three-factor (renneting temperature, calcium chloride, cutting time), central composite design was carried out in triplicate. Spectra (300–1,100 nm) of the product in the cheese vat were captured during syneresis using a prototype light backscatter sensor. Stirring followed upon cutting the gel, and samples of curd and whey were removed at 10 min intervals and analyzed for curd moisture and whey fat content. Spectral data were used to develop models for predicting curd moisture and whey fat contents using partial least squares regression. Subjecting the spectral data set to Jack-knifing improved the accuracy of the models. The whey fat models (R = 0.91, 0.95) and curd moisture model (R = 0.86, 0.89) provided good and approximate predictions, respectively. Visible-near infrared spectroscopy was found to have potential for the prediction of important syneresis indices in stirred cheese vats.
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The cheese industry has continually sought a robust method to monitor milk coagulation. Measurement of whey separation is also critical to control cheese moisture content, which affects quality. The objective of this study was to demonstrate that an online optical sensor detecting light backscatter in a vat could be applied to monitor both coagulation and syneresis during cheesemaking. A prototype sensor having a large field of view (LFV) relative to curd particle size was constructed. Temperature, cutting time, and calcium chloride addition were varied to evaluate the response of the sensor over a wide range of coagulation and syneresis rates. The LFV sensor response was related to casein micelle aggregation and curd firming during coagulation and to changes in curd moisture and whey fat contents during syneresis. The LFV sensor has potential as an online, continuous sensor technology for monitoring both coagulation and syneresis during cheesemaking.
Resumo:
The objective of this study was to investigate a novel light backscatter sensor, with a large field of view relative to curd size, for continuous on-line monitoring of coagulation and syneresis to improve curd moisture content control. A three-level, central composite design was employed to study the effects of temperature, cutting time, and CaCl2 addition on cheese making parameters. The sensor signal was recorded and analyzed. The light backscatter ratio followed a sigmoid increase during coagulation and decreased asymptotically after gel cutting. Curd yield and curd moisture content were predicted from the time to the maximum slope of the first derivative of the light backscatter ratio during coagulation and the decrease in the sensor response during syneresis. Whey fat was affected by coagulation kinetics and cutting time, suggesting curd rheological properties at cutting are dominant factors determining fat losses. The proposed technology shows potential for on-line monitoring of coagulation and syneresis. 2007 Elsevier Ltd. All rights reserved..
Resumo:
Background/Aims: In cerebral arteries, nitric oxide (NO) release plays a key role in suppressing vasomotion. Our aim was to establish the pathways affected by NO in rat middle cerebral arteries. Methods: In isolated segments of artery, isometric tension and simultaneous measurements of either smooth muscle membrane potential or intracellular [Ca 2+ ] ([Ca 2+ ] SMC ) changes were recorded. Results: In the absence of L -NAME, asynchronous propagating Ca 2+ waves were recorded that were sensitive to block with ryanodine, but not nifedipine. L -NAME stimulated pronounced vasomotion and synchronous Ca 2+ oscillations with close temporal coupling between membrane potential, tone and [Ca 2+ ] SMC . If nifedipine was applied together with L -NAME, [Ca 2+ ] SMC decreased and synchronous Ca 2+ oscillations were lost, but asynchronous propagating Ca 2+ waves persisted. Vasomotion was similarly evoked by either iberiotoxin, or by ryanodine, and to a lesser extent by ODQ. Exogenous application of NONOate stimulated endothelium-independent hyperpolarization and relaxation of either L -NAME-induced or spontaneous arterial tone. NO-evoked hyperpolarization involved activation of BK Ca channels via ryanodine receptors (RYRs), with little involvement of sGC. Further, in whole cell mode, NO inhibited current through L-type voltage-gated Ca 2+ channels (VGCC), which was independent of both voltage and sGC. Conclusion: NO exerts sGC-independent actions at RYRs and at VGCC, both of which normally suppress cerebral artery myogenic tone.
Resumo:
We recently found block of NO synthase in rat middle cerebral artery caused spasm, associated with depolarizing oscillations in membrane potential (Em) similar in form but faster in frequency (circa 1 Hz) to vasomotion. T-type voltage-gated Ca2+ channels contribute to cerebral myogenic tone and vasomotion, so we investigated the significance of T-type and other ion channels for membrane potential oscillations underlying arterial spasm. Smooth muscle cell membrane potential (Em) and tension were measured simultaneously in rat middle cerebral artery. NO synthase blockade caused temporally coupled depolarizing oscillations in cerebrovascular Em with associated vasoconstriction. Both events were accentuated by block of smooth muscle BKCa. Block of T-type channels or inhibition of Na+/K+-ATPase abolished the oscillations in Em and reduced vasoconstriction. Oscillations in Em were either attenuated or accentuated by reducing [Ca2+]o or block of KV, respectively. TRAM-34 attenuated oscillations in both Em and tone, apparently independent of effects against KCa3.1. Thus, rapid depolarizing oscillations in Em and tone observed after endothelial function has been disrupted reflect input from T-type calcium channels in addition to L-type channels, while other depolarizing currents appear to be unimportant. These data suggest that combined block of T and L-type channels may represent an effective approach to reverse cerebral vasospasm.
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Voltage-gated potassium (Kv) channels are essential components of neuronal excitability. The Kv3.4 channel protein is widely distributed throughout the central nervous system (CNS), where it can form heteromeric or homomeric Kv3 channels. Electrophysiological studies reported here highlight a functional role for this channel protein within neurons of the dorsal vagal nucleus (DVN). Current clamp experiments revealed that blood depressing substance (BDS) and intracellular dialysis of an anti-Kv3.4 antibody prolonged the action potential duration. In addition, a BDS sensitive, voltage-dependent, slowly inactivating outward current was observed in voltage clamp recordings from DVN neurons. Electrical stimulation of the solitary tract evoked EPSPs and IPSPs in DVN neurons and BDS increased the average amplitude and decreased the paired pulse ratio, consistent with a presynaptic site of action. This presynaptic modulation was action potential dependent as revealed by ongoing synaptic activity. Given the role of the Kv3 proteins in shaping neuronal excitability, these data highlight a role for homomeric Kv3.4 channels in spike timing and neurotransmitter release in low frequency firing neurons of the DVN.
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The phase shift full bridge (PSFB) converter allows high efficiency power conversion at high frequencies through zero voltage switching (ZVS); the parasitic drain-to-source capacitance of the MOSFET is discharged by a resonant inductance before the switch is gated resulting in near zero turn-on switching losses. Typically, an extra inductance is added to the leakage inductance of a transformer to form the resonant inductance necessary to charge and discharge the parasitic capacitances of the PSFB converter. However, many PSFB models do not consider the effects of the magnetizing inductance or dead-time in selecting the resonant inductance required to achieve ZVS. The choice of resonant inductance is crucial to the ZVS operation of the PSFB converter. Incorrectly sized resonant inductance will not achieve ZVS or will limit the load regulation ability of the converter. This paper presents a unique and accurate equation for calculating the resonant inductance required to achieve ZVS over a wide load range incorporating the effects of the magnetizing inductance and dead-time. The derived equations are validated against PSPICE simulations of a PSFB converter and extensive hardware experimentations.
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With a wide range of applications benefiting from dense network air temperature observations but with limitations of costs, existing siting guidelines and risk of damage to sensors, new methods are required to gain a high resolution understanding of the spatio-temporal patterns of urban meteorological phenomena such as the urban heat island or precision farming needs. With the launch of a new generation of low cost sensors it is possible to deploy a network to monitor air temperature at finer spatial resolutions. Here we investigate the Aginova Sentinel Micro (ASM) sensor with a bespoke radiation shield (together < US$150) which can provide secure near-real-time air temperature data to a server utilising existing (or user deployed) Wireless Fidelity (Wi-Fi) networks. This makes it ideally suited for deployment where wireless communications readily exist, notably urban areas. Assessment of the performance of the ASM relative to traceable standards in a water bath and atmospheric chamber show it to have good measurement accuracy with mean errors < ± 0.22 °C between -25 and 30 °C, with a time constant in ambient air of 110 ± 15 s. Subsequent field tests of it within the bespoke shield also had excellent performance (root-mean-square error = 0.13 °C) over a range of meteorological conditions relative to a traceable operational UK Met Office platinum resistance thermometer. These results indicate that the ASM and bespoke shield are more than fit-for-purpose for dense network deployment in urban areas at relatively low cost compared to existing observation techniques.
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Cannabidiol (CBD) is a non-psychoactive, well-tolerated, anticonvulsant plant cannabinoid, although its mechanism(s) of seizure suppression remains unknown. Here, we investigate the effect of CBD and the structurally similar cannabinoid, cannabigerol (CBG), on voltage-gated Na+ (NaV) channels, a common anti-epileptic drug target. CBG’s anticonvulsant potential was also assessed in vivo. CBD effects on NaV channels were investigated using patch-clamp recordings from rat CA1 hippocampal neurons in brain slices, human SH-SY5Y (neuroblastoma) cells and mouse cortical neurons in culture. CBG effects were also assessed in SH-SY5Y cells and mouse cortical neurons. CBD and CBG effects on veratridine-stimulated human recombinant NaV1.1, 1.2 or 1.5 channels were assessed using a membrane potential-sensitive fluorescent dye high-throughput assay. The effect of CBG on pentyleneterazole-induced (PTZ) seizures was assessed in rat. CBD (10M) blocked NaV currents in SH-SY5Y cells, mouse cortical neurons and recombinant cell lines, and affected spike parameters in rat CA1 neurons; CBD also significantly decreased membrane resistance. CBG blocked NaV to a similar degree to CBD in both SH-SY5Y and mouse recordings, but had no effect (50-200mg/kg) on PTZ-induced seizures in rat. CBD and CBG are NaV channel blockers at micromolar concentrations in human and murine neurons and recombinant cells. In contrast to previous reports investigating CBD, CBG had no effect upon PTZ-induced seizures in rat, indicating that NaV blockade per se does not correlate with anticonvulsant effects.
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Body Sensor Networks (BSNs) have been recently introduced for the remote monitoring of human activities in a broad range of application domains, such as health care, emergency management, fitness and behaviour surveillance. BSNs can be deployed in a community of people and can generate large amounts of contextual data that require a scalable approach for storage, processing and analysis. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of data streams generated in BSNs. This paper proposes BodyCloud, a SaaS approach for community BSNs that supports the development and deployment of Cloud-assisted BSN applications. BodyCloud is a multi-tier application-level architecture that integrates a Cloud computing platform and BSN data streams middleware. BodyCloud provides programming abstractions that allow the rapid development of community BSN applications. This work describes the general architecture of the proposed approach and presents a case study for the real-time monitoring and analysis of cardiac data streams of many individuals.
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This work presents a method of information fusion involving data captured by both a standard CCD camera and a ToF camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time of light information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localization. Further development of these methods will make it possible to identify objects and their position in the real world, and to use this information to prevent possible collisions between the robot and such objects.
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The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.
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Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.