99 (Figure 4) Using a parabolic curve fit overlaid on the experi

Posted on October 30, 2015 by admin

99 (Figure 4). Using a parabolic curve fit overlaid on the experimental volume results allowed subsequent measurements to be made Pacritinib phase 3 within 3 mL of the actual values when measuring water (Figure 5). This represents an accuracy of better than ��0.1% Inhibitors,Modulators,Libraries of the resonator��s volume (3 L). Repeatability for a given measurement was generally ��1 mL when successive measurements were made on the same volume.Figure 3.Measured resonant frequency and predicted resonant frequency for varying water fill using 3 L chamber, 170 mm long, Inhibitors,Modulators,Libraries and 44 mm diameter port.Figure 4.Actual water volume versus deviation volume (VP ? VA) using Helmholtz equation with 3 L chamber, 170 mm long, and 44 mm diameter port.Figure 5.Actual water volume versus corrected deviation volume (VP ? VA) using Helmholtz equation with second order correction.

Measured using 3 L chamber, 170 mm long, and 44 mm diameter port.The reason for a second order deviation is unclear, but could be due to secondary effects caused by implicit assumptions Inhibitors,Modulators,Libraries made in simplifying acoustical theory used to generate the Helmholtz equation, see for example Blackstock [3]. These assumptions include the small signal approximations made to allow linearisation and the completion of the wave equation. Also, various small angle approximations are made in lumped parameter analysis within transmission theory. Because frequency measurements were being made to such a high accuracy these seemingly unimportant small terms may now be significant. The Q factor is an important indicator of resonant strength.

It was observed that the Q factor remained steady at approximately 60 (Figure 6) up to a fill of 2.5 L in a 3 L chamber.Figure 6.Q factor with increasing water fill level, measured using 3 L chamber, 170 mm long, and 44 mm diameter port.The success in the predictive capabilities is in part due to the consistently high Q factor. This maintained the resolvability of the resonant Inhibitors,Modulators,Libraries peak. Also, the high Q factor is indicative of low energy absorption by the water. At greater fill levels the water approached the Brefeldin_A
Silicon photonics is a technology for implementing various optical functionalities in silicon, offering the potential for large-scale integration of multiple optical and electronic functions on a single silicon chip.

This should result in revolutionizing applications in microelectronics different (through the replacement of metal/dielectric stacks with optical interconnects), in telecommunications (integrated optical circuits), and in biological and chemical sensing. Significant advantages exist when using silicon as the base material for such devices: in particular, the vast amount of research now available to designers and process engineers on all aspects of the material system, as well as the established, global silicon processing industry that has evolved from almost six decades of silicon-based microelectronics fabrication.

They are potentially useful for other pipeline networks for the d

Posted on October 29, 2015 by admin

They are potentially useful for other pipeline networks for the delivery of oil, water, sewage, chemicals and so on. In the long run, they are also applicable to other physically enclosed harsh environments, such as water tanks, wings of air vehicles, mines and even outer space [7,8].In this paper we utilize the combination of an integral approach and an object-oriented hierarchical structure. either Although there are existing works combining ideas from robotic swarms, artificial intelligence and object-oriented design, the work presented in this paper distinguishes itself by a new research context of natural gas pipeline inspection tasks and a novel integration of the related ideas in the above fields in the same framework of mobile sensor networks.The rest of the paper is organized as follows.

The formulation of the problem and the proposed general solution framework is presented in Section 2. In Section 3, we present a simulated study on how to design algorithms for mobile sensors to learn to adapt Inhibitors,Modulators,Libraries to an unknown environment and benefit from collaborating with its peers. A robotic experimental study for coordinating mobile sensors to maneuver as a team with local information is then discussed in Section 4. We make concluding remarks at the end of the paper.2.?Problem Formulation and Proposed Integral Approach2.1. Problem FormulationWe consider a team of sensor equipped autonomous robots [9] that operate in a given natural gas pipeline network. Each robot is powered by batteries Inhibitors,Modulators,Libraries and can move freely inside the pipeline network.

It can detect within its sensing range a predefined fault on the wall of a tube and then record it in its memory. The information about the detected fault, together with other related sensing data, can be processed by the computational Inhibitors,Modulators,Libraries unit of the robot for further usage. The raw data and the processed information can be communicated between robots when they are within communication ranges of one another. Each robot has a distinguishable identity in the group, which is used to initiate or plan a coordinated action among a subset of the group members. The gas pipeline network environment is assumed to be stationary, i.e., no significant changes of its condition happen while the robots are doing the inspection job. However, the robots have no prior knowledge about the working condition of the pipeline network.

In other words, the robots have to rely on their sensing, computation and communication Inhibitors,Modulators,Libraries capabilities to build up their knowledge about the environment that they are Cilengitide working in.The problem to be studied is how to control and coordinate the robots�� sensing, computation enzalutamide mechanism of action and communication activities so that the robots can cover the given pipeline network with the highest possible accuracy and the shortest possible execution time. Here, the definition for accuracy and execution time may vary for different networks and different robots at hand.

This will provide a more meaningful measure of uncertainty than a

Posted on October 26, 2015 by admin

This will provide a more meaningful measure of uncertainty than a hard classification using data flags;to demonstrate selleck chemicals Sorafenib this approach��s success through its application to marine water monitoring.2.?Research Data Quality and its Evaluation through Measurement UncertaintyStandards, e.g., International Guide to the Expression of Uncertainty in Measurement [4] (or GUM as it is now often called) and its US equivalent ANSI/NCSL Z540-2-1997 US Guide to the Expression of Uncertainty in Measurement [5] request the provision of a quantitative indication of the quality of the measurement result along with the result itself, so those who use the measured data can assess its reliability.
The GUM standard��s approach groups the components of Inhibitors,Modulators,Libraries uncertainty in the result of a measurement into two categories according to the way in which their numerical value is estimated: those which are evaluated by statistical methods are classified as ��Type A��, and those which are evaluated Inhibitors,Modulators,Libraries by other means are classified as ��Type B��. A Type B evaluation of standard uncertainty is usually based on scientific judgment using all of the relevant information available, which may include:previous measurement data;experience with, or general knowledge of, the behavior and property of relevant materials and instruments;manufacturer��s specifications;data provided in calibration and other reports, Inhibitors,Modulators,Libraries and uncertainties assigned to reference data taken from handbooks.As real-time sensor platforms become the norm in environmental sensing, there is a need to develop Inhibitors,Modulators,Libraries automated procedures to incorporate scientific judgments of the streamed data in the evaluation of the measurement uncertainty and associated data quality.
As the judgments are often based on experts�� opinions Dacomitinib and estimates, the data quality assurance systems could be designed within an expert system framework that uses fuzzy rules to characterize the properties and sources of the judgment.Fuzzy systems have been U0126 used in applications where the solution is highly dependent on human experience; because of either imprecise information being available or the empirical nature of the problem (e.g., [6], and references therein). Using a fuzzy system, it is possible to encode linguistic rules and heuristics, reducing the solution time since the expert��s knowledge can be built in directly. In addition, its qualitative representation form makes fuzzy interpretations of data very natural and an intuitively plausible way to formulate and solve several problems. Qualitative aspects can be implemented and can also be updated making this system useful to solve problems that are very difficult or impossible to solve analytically.

In addition, these works are distinguished by

Posted on October 22, 2015 by admin

In addition, these works are distinguished by selleck bio meaningful physical significance, effective sparse data, enhanced classification accuracy and striking time
Debris flow is Inhibitors,Modulators,Libraries a rapid, gravity-induced flow of mixture of rocks, mud, and water [1,2]. Debris flows have the following characteristics: the front resembles a bore and the largest rocks accumulate there; the flow Inhibitors,Modulators,Libraries following the forefront appears as a mudflow with a slowly decreasing discharge; and the flow is accompanied by loud noise and ground vibration [3]. Monitoring ground vibrations, also referred to as seismic signals, is accepted as a reliable means of detecting such natural hazards [4,5].Seismic signals caused by various natural hazards, e.g., earthquakes, landslides, debris flows, rock falls, snow avalanches, and pyroclastic flows are characterized by their frequency ranges and amplitudes.
Suri?ach et al. [6] investigated the seismic data produced by various earthquakes (i.e., local, regional, and teleseism), a landslide, and artificially triggered snow avalanches. According to their results, frequency ranges of seismic signals produced by a local earthquake (52.8 km), regional earthquake (228.2 km) and teleseism (6,931.6 km) are 1�C50 Hz, 1�C12 Hz, Inhibitors,Modulators,Libraries and 0.1�C1 Hz, respectively. While analyzing the seismic data excited by several pyroclastic flows occurring at the Unzen volcano in Kyushu, Japan, Uhira and Yamasata [7] found that the seismic waves contain low frequency components (0.5�C10 Hz). Huang et al. [4] described the detection of debris flows at Ai-Yu-Zi Creek, (Nantou, Taiwan) using geophones (GS-20DX) to monitor ground vibrations produced by these debris flows.
Their results indicate that when the Inhibitors,Modulators,Libraries main front was closest to the sensor, the frequency spectrum covered a wide range, from 10 to 250 Hz. The above studies demonstrate that selecting sensors to detect different natural hazards requires careful attention to the operating frequency range of sensors.Many investigators have studied ground vibrations produced by debris flows [4,8�C19] by using various types of sensors, including seismometers, geophones, microphones, and accelerometers. Of these sensors, geophones are most widely installed in systems for monitoring debris flows. However, ground tremors generated by debris flows are markedly smaller than those caused by earthquakes, and also have a higher range of frequencies. Attenuation of a seismic wave depends on its frequency. Carfilzomib A high frequency is associated with a high spatial decay rate [20]. Therefore, debris flow tremors can only be detected over a relatively short e-book distance.

Posted on October 21, 2015 by admin

new post Thus, trace curve estimation is a crucial problem for zoom tracking methods. A major challenge in this estimation is the one-to-many mapping problem [11], which becomes troublesome Inhibitors,Modulators,Libraries when the zoom is changed from wide-angle to tele-angle. This problem will be further described in Section 2.Figure 3.Trace curves for an 18�� zoom lens.1.2. Existing Zoom Tracking MethodsThe existing Inhibitors,Modulators,Libraries zoom tracking methods can be divided into two categories: (1) geometric methods, such as geometric zoom tracking (GZT) and adaptive zoom tracking (AZT); (2) machine learning methods, such as relational zoom tracking (RZT) and predictive zoom tracking (PZT). The development of zoom tracking can be traced back to the look-up table method [12], which stores a large number of trace curves for various object distances in memory.
The real trace curve is estimated by selecting the closest curve among the stored ones. However, this approach is not often used in practice because of its large memory requirement. To cover the shortage Inhibitors,Modulators,Libraries of memory, the GZT [13,14] has been proposed. The GZT approach obtains an estimate of a trace curve via linear interpolation only based on two trace curves for near and far objects. A drawback of this approach is that the offset between the estimated and the real trace curves gradually increases as the zoom is changed from wide-angle to tele-angle. This approach is later extended to the AZT method [15], which incorporates a recalibration procedure at the boundary zoom position Inhibitors,Modulators,Libraries where the trace curve changes from linear to non-linear.
The RZT [16] and PZT [11] methods were proposed later to improve the estimation Anacetrapib accuracy through machine learning. RZT generates an estimate of the distance range in which the object resides by so-called ��relational curves��. This distance range is then used to estimate a trace curve. PZT uses an input-output better model trained by a priori characteristic trace curves to generate an estimate of a trace curve. The trained model is often based on the Auto-Regression with Exogenous Inputs (ARX) model [17] or the Recurrent Neural Network (RNN) model [18]. Both RZT and PZT solve the one-to-many mapping problem well, but they require a significant amount of a priori knowledge for training. It is not always convenient to obtain these a priori trace curves in practical use. Furthermore, the errors in the learning step will also have an effect on the estimation. Because the variation of the lens or scenes often requires additional time for re-training, the adaptability of these two algorithms is relatively poor.1.3.

Now based on research described in [9], and as consequently addre

Posted on October 20, 2015 by admin

Now based on research described in [9], and as consequently addressed in [10,11], trust is bound to the following important factors:Rationality and irrationality. An agent’s trust is driven by rational and irrational factors.Action binding. Trust CYC202 presents a potential for an agent’s deeds, i.e., ways of interaction with the environment.Feed-back dependence. Trust is not a result of an independent mind, but it is influenced by the agent’s environment. And when an agent is, e.g., forced to behave in a certain wa
Low-cost chemical analysis sensors can have a great impact in fields such as environmental preservation and energy efficiency. There is a growing market for this kind of sensor, especially for low-cost and reliable sensors focused on carbon dioxide (CO2)-methane (CH4) mixtures in biogas quality monitoring applications [1].
Currently, the most studied Inhibitors,Modulators,Libraries method to transform waste into energy is anaerobic digestion, which can convert a variety of wastes, such as agricultural waste from animals and plants and municipal waste, into a full Inhibitors,Modulators,Libraries energy product such as biogas [2]. The preferred technology for the analysis of single components in raw biogas, specifically to determine the CH4 and CO2 content, is optical sensors, which detect infrared absorption in the characteristic wavelengths for these molecules [3]. In the literature, biogas composition has been measured with gas infrared analyzers, such as those used by Sedla?��k and Dvo?��?kov�� [2], who utilized a GASCARD II infrared gas sensor from Edinburgh Instruments [4]; Nordberg et al.
Inhibitors,Modulators,Libraries [5], who used a Model 6500 visible/near-infrared scanning monochromator from FOSS NIRSystems [6] and Steyer et al. [7], who used a Siemens Ultramat 22P, which works on the principle of the nondispersive absorption of infrared light [8]. Additionally, semiconductor diode lasers for use in the mid-infrared spectral region based upon lead-salt operating near 7.8 ��m have also been used for methane measurements [9]. However, there are two main drawbacks to the sensors outlined above: high cost and difficulty of installation at all biogas production sites [1]. For comparison, the cost of a commercial FTIR spectrophotometer is near $20,000 USD [10], while the estimated cost of the gas sensor described here is approximately $5,000 USD. The described sensor is also easy to build and operate.
Methods for the acquisition of biogas methane content based in a variety of measurement principles have been reported in the literature. For example, Mandal et al. [11] determined biogas quality using flame Inhibitors,Modulators,Libraries temperature as the measurement principle. In this case, the steady-state flame temperature was measured using a system Anacetrapib consisting of a thermocouple probe and an analog temperature indicator. In addition, Rego and Mendes [1] and Rego et al. [12] described a permselective somehow gas sensor for determining the composition of carbon dioxide-methane mixtures in the 0�C100% range.

based largely on the effects on later dynamics as opposed to the

Posted on October 13, 2015 by admin

based largely on the effects on later dynamics as opposed to the initial activation, Lapatinib as is the case for all of the feedback parameters, then trying to modify these parameters would be much less effective. Thus, results from our dynamic sensitivity analysis can be of particular importance when trying to identify how to modify a model to correct discre pancies between model simulations and data, as it pro vides valuable information. It is important to note that our particular model, which is developed to reproduce population average measurements of IKK and NF B activity in microglia, is not unique and other models are capable of produ cing the same dynamics. It may be desirable in different contexts to extend or otherwise modify this model to explore aspects not considered here.

For instance, delayed negative feedback from the I B�� isoform may also contribute substantially to later phase NF B sig naling dynamics, but is omitted from the present model. It may be useful to extend the model to include interactions from I B�� in future studies. Using data from bulk population level averages Inhibitors,Modulators,Libraries also masks asyn chronous NF B oscillations at the single cell level. Thus a different approach, such as simulat ing the deterministic model with random parameter dis tributions or using stochastic deterministic hybrid models, may be more appropriate when specifi cally considering individual cell responses.

The analysis from this model for microglial NF B acti vation clearly portrays the canonical NF B response on one hand as very robust, cells are able to parse extracellu lar signals into transient IKK activation to produce Inhibitors,Modulators,Libraries a quick and dynamic rise in NF B activity, even in the face of uncertainty in many of the reaction rates in both the upstream and downstream pathways. This finding is consistent Inhibitors,Modulators,Libraries with sensitivity analysis of related models, in which the response was found to be largely insensitive to the majority of the rate parameters. On the other hand, this analysis reveals the highly responsive nature of the network, evident from the high sensitivity and low robustness of the NF B response to changes in the feed back parameters. We note that although pre vious analyses have identified Inhibitors,Modulators,Libraries the sensitivity of the NF B response to many of the same parameters identified here, none appear to have interpreted the importance of such parameters in the context of feedback control systems.

The behavior of the NF B regulatory network is not unlike that commonly encountered in feedback systems in the engineering world. Consider, for instance, the operation of an amplifier designed to amplify signals in an electronic Batimastat system. High gain amplifiers with nega tive feedback amplify signals robustly even when sub jected to relatively large changes in feedforward system parameters. But the response is sensitive to feedback parameters, which both permits the system to be finely tuned by selecting proper feedback components, and makes Vandetanib molecular weight the system vulnerable to failure if the feedback par

egulating cellular genes when E2 pro tein is e pressed in cervica

Posted on October 10, 2015 by admin

egulating cellular genes when E2 pro tein is e pressed in cervical carcinoma derived cell selleck lines result from repressed e pression of the viral oncogenes E6 and E7. however, in this work, we Inhibitors,Modulators,Libraries demonstrated that HPV16 E2 changes cellular gene e pression independently of viral oncoprotein E6 and E7 regulation. HPV type 16 is the most prevalent type of HPV, which is in agreement with other studies, while the frequency of HPV type 18 is very low com pared with other ethnic Inhibitors,Modulators,Libraries populations. Low grade dysplasias with HPV 16 infection demonstrated an in creased rate of malignancy progression. HPV 16 E6 E7 oncoproteins have been demonstrated to cause im mortalisation of primary human keratinocytes and are e pressed in malignant cancers.

Many studies have previously reported the ability of the HPV 16 E6 E7 oncoproteins to disrupt the normal process of differenti ation of human foreskin keratinocytes by targeting key tumour suppressors, Inhibitors,Modulators,Libraries such as p53 and pRb, resulting in increased levels of cell survival proteins, such as Akt, and disruption of the cell cycle. The HPV E2 protein functions as a repressor or an acti vator of early gene transcription, which regulates viral transcription and genome replication. Disruption of the viral E2 gene, which controls the transcription of on cogenes E6 and E7 that manipulate the cell cycle and the ability of apoptosis, has been associated with poor outcomes. Conversely, the HPV 16 E2 gene acted via mitochondrial dependent pathways to control cellular apoptosis and fate. Among mitochondrial matri proteins, gC1qR controls diverse cellular processes, such as cell growth, differentiation and apoptosis.

The present study provides an essential framework for assessing the role of gC1qR protein in HPV 16 E2 transfected cervical squamous carcinoma cell apoptosis. gC1qR is a multi compartmental and multi functional cellular protein that is distributed in Inhibitors,Modulators,Libraries several tissues and cell types, including lymphocytes, endothelial cells, den dritic cells and platelets. However, in our e peri ment, immunohistochemistry Dacomitinib demonstrated that gC1qR e pression was significantly decreased in human cervical squamous cell carcinoma tissues compared with normal cervical tissues. Al though gC1qR is not overe pressed in human cervical squamous cell carcinoma tissues, its e pression in creased significantly in the HPV16 E2 induced cervical squamous carcinoma cell line.

During complement activation, the biological re sponses mediated by C1q recognise and activate the sig nal that triggers the classical complement pathway. C1q functions as selleckchem a potent e tracellular signal for a wide range of cells, resulting in inhibition of T cell prolifera tion or endothelial cell activation. Additionally, the C1q gC1qR comple not only may be involved in innate and adaptive immunity, but also may be an under lying molecular mechanism in virus infection. u et al. provided evidence that viruses use host gC1qR pro tein to inhibit antiviral responses and to promote viral proliferation by

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