Linear Region Slope Research Articles

Enhanced Synchronization Algorithms for BOC Signals Based on Reconstructed Sub-Correlation Functions

Aiming at the ambiguous synchronization of binary offset carrier (BOC) and composite binary offset carrier (CBOC) modulation signals due to secondary peaks for Global Navigation Satellite System (GNSS), a reconstructed sub-correlation function synchronization algorithm (RSSA) for BOC and CBOC is proposed. The general autocorrelation subfunctions of BOC and CBOC are obtained by deriving the subfunctions of the cross-correlation function between BOC signals with different modulation orders. According to the characteristics of the subfunctions, the corresponding reconstruction rules are set to obtain the unambiguous correlation functions. To further reduce the complexity of the local auxiliary signal, a local auxiliary signal optimization algorithm (LASOA) is proposed based on RSSA, which only needs to generate a local two-level signal compared to the conventional CBOC local four-level signal. The simulations show that the two algorithms proposed in this paper reduce the amplitude of the side peaks of the normalized correlation peaks of BOC by at least 0.09 compared with the autocorrelation side-peak cancellation technique (ASPeCT), maintain a high detection probability, and the multipath error is smaller than that of the autocorrelation side-peak cancellation technique (ASPeCT) and other traditional algorithms. The phase discrimination curves show that the linear region slope gains of the two algorithms in this paper are above 2 dB compared with the ASPeCT and other conventional algorithms.

A Study on the Combination of Enzyme Stabilizers and Low Temperatures in the Long-Term Storage of Glutamate Biosensor

The importance of physiological glutamate has been widely demonstrated in cognitive and memory processes, as well as in neurotransmission. The involvement of physiological glutamate in several pathologies has also been established. Therefore, analytical devices for studying variations in physiological glutamate are of fundamental importance, particularly in preclinical studies. The necessary knowledge to develop and characterize biosensors for glutamate detection is often restricted to only a few research groups. However, many more groups have sought to implant such analytical devices to study the glutamatergic system in vivo. On this basis, a series of studies was undertaken to explore the medium-term storage of biosensors, thereby allowing their usage results to be differentiated from their construction and characterization processes to facilitate the wider diffusion and use of such sensors. Therefore, it has become vital to determine the best storage conditions to extend the life and functionality of these biosensors, especially due to the diachronic instability of the enzyme present on the surface. In the present study, we analyzed the impact of glycols, such as glycerol and triethylene glycol, as enzyme stabilizers coupled with long-term storage at low temperatures (−20 and −80 °C) on biosensor performance. The biosensors were observed for 5 months and evaluated for their enzymatic activity by measuring the VMAX(app) and KM(app). The analytical features were also evaluated in terms of the Linear Region Slope, which is one the most important parameters for indicating the efficiency and the sensitivity of biosensors. Interestingly, both glycols proved to be capable of increasing enzymatic activity and maintaining good biosensor efficiency over time. Moreover, the combination with low-temperature storage highlighted the different behaviors of the two glycols. In particular, glycerol was more effective in stabilizing the enzyme and maintaining analytical performance when the biosensors were stored at −20 °C. Instead, triethylene glycol performed the same function as glycerol but when the biosensors were stored at −80 °C.

A New Perspective on Using Glycols in Glutamate Biosensor Design: From Stabilizing Agents to a New Containment Net

Glutamate is a major excitatory neurotransmitter in the brain. It is involved in many normal physiological brain activities, but also neurological disorders and excitotoxicity. Hence, glutamate measurement is important both in clinical and pre-clinical studies. Pre-clinical studies often use amperometric biosensors due to their low invasiveness and the relatively small size of the devices. These devices also provide fast, real-time measurements because of their high sensitivity. In the present study, diethylene glycol (DEG), neopentyl glycol (NPG), triethylene glycol (TEG), and glycerol (GLY) were used to increase the long-term stability of glutamate biosensors. The evaluation was made by measuring variations of the main enzymatic (VMAX and KM) and analytical (Linear Region Slope (LRS)) parameters. Of the glycols tested, TEG was the most promising stabilizer, showing about twice as high VMAX maintained over a greater duration than with other stabilizers tested. It is also yielded the most stable linear region slope (LRS) values over the study duration. Moreover, we highlighted the ability of glycols to interact with enzyme molecules to form a containment network, able to maintain all the layered components of the biosensor adhering to the transducer.

The Presence of Polysaccharides, Glycerol, and Polyethyleneimine in Hydrogel Enhances the Performance of the Glucose Biosensor.

The use of amperometric biosensors has attracted particular attention in recent years, both from researchers and from companies, as they have proven to be low-cost, reliable, and very sensitive devices, with a wide range of uses in different matrices. The continuous development of amperometric biosensors, since their use involves an enzyme, is specifically aimed at keeping and increasing the catalytic properties of the loaded protein, so as to be able to use the same device over time. The present study aimed to investigate the impact of glycerol and polysaccharides, in the presence of polycationic substances to constitute a hydrogel, in enhancing the enzymatic and analytic performance of a glucose biosensor. Initially, it was possible to verify how the deposition of the starch-based hydrogel, in addition to allowing the electropolymerization of the poly(p-phenylenediamine) polymer and the maintenance of its ability to shield the ascorbic acid, did not substantially limit the permeability towards hydrogen peroxide. Moreover, different biosensor designs, loading a mixture containing all the components (alone or in combination) and the enzyme, were tested in order to evaluate the changes of the apparent enzyme kinetic parameters, such as VMAX and KM, and analytical response in terms of Linear Region Slope, highlighting how the presence of all components (starch, glycerol, and polyethyleneimine) were able to substantially enhance the performance of the biosensors. The surface analysis of the biosensors was performed by scanning electron microscope (SEM). More, it was shown that the same performances were kept unchanged for seven days, proving the suitability of this biosensor design for short- and mid-term use.

Propylene Glycol Stabilizes the Linear Response of Glutamate Biosensor: Potential Implications for In-Vivo Neurochemical Monitoring

L-glutamate is one the most important excitatory neurotransmitter at the central nervous system level and it is implicated in several pathologies. So, it is very important to monitor its variations, in real time in animal models’ brain. The present study aimed to develop and characterize a new amperometric glutamate biosensor design that exploits the selectivity of Glutamate Oxidase (GluOx) for l-glutamate, and the capability of a small molecule as propylene glycol (PG), never used before, to influence and extend the stability and the activity of enzyme. Different designs were evaluated by modifying the main components in their concentrations to find the most suitable design. Moreover, enzyme concentrations from 100 U/mL up to 200 U/mL were verified and different PG concentrations (1%, 0.1% and 0.05%) were tested. The most suitable selected design was Ptc/PPD/PEI(1%)2/GlutOx5/PG(0.1%) and it was compared to the same already described design loading PEDGE, instead of PG, in terms of over-time performances. The PG has proved to be capable of determining an over-time stability of the glutamate biosensor in particular in terms of linear region slope (LRS) up to 21 days.

Clustered impurities and carrier transport in supported graphene

We investigate the effects of charged impurity distributions and carrier-carrier interactions on electronic transport in graphene on SiO$_2$ by employing a self-consistent coupled simulation of carrier transport and electrodynamics. We show that impurity clusters of characteristic width 40--50 nm generate electron--hole puddles of experimentally observed sizes. In the conductivity versus carrier density dependence, the residual conductivity and the linear-region slope are determined by the impurity distribution, and the measured slope can be used to estimate the impurity density in experiment. Furthermore, we show that the high-density sublinearity in the conductivity stems from carrier-carrier interactions.

Methodological Framework for Estimating the Correlation Dimension in HRV Signals

This paper presents a methodological framework for robust estimation of the correlation dimension in HRV signals. It includes (i) a fast algorithm for on-line computation of correlation sums; (ii) log-log curves fitting to a sigmoidal function for robust maximum slope estimation discarding the estimation according to fitting requirements; (iii) three different approaches for linear region slope estimation based on latter point; and (iv) exponential fitting for robust estimation of saturation level of slope series with increasing embedded dimension to finally obtain the correlation dimension estimate. Each approach for slope estimation leads to a correlation dimension estimate, called , , and . and estimate the theoretical value of correlation dimension for the Lorenz attractor with relative error of 4%, and with 1%. The three approaches are applied to HRV signals of pregnant women before spinal anesthesia for cesarean delivery in order to identify patients at risk for hypotension. keeps the 81% of accuracy previously described in the literature while and approaches reach 91% of accuracy in the same database.

Further In-vitro Characterization of an Implantable Biosensor for Ethanol Monitoring in the Brain

Ethyl alcohol may be considered one of the most widespread central nervous system (CNS) depressants in Western countries. Because of its toxicological and neurobiological implications, the detection of ethanol in brain extracellular fluid (ECF) is of great importance. In a previous study, we described the development and characterization of an implantable biosensor successfully used for the real-time detection of ethanol in the brain of freely-moving rats. The implanted biosensor, integrated in a low-cost telemetry system, was demonstrated to be a reliable device for the short-time monitoring of exogenous ethanol in brain ECF. In this paper we describe a further in-vitro characterization of the above-mentioned biosensor in terms of oxygen, pH and temperature dependence in order to complete its validation. With the aim of enhancing ethanol biosensor performance, different enzyme loadings were investigated in terms of apparent ethanol Michaelis-Menten kinetic parameters, viz. IMAX, KM and linear region slope, as well as ascorbic acid interference shielding. The responses of biosensors were studied over a period of 28 days. The overall findings of the present study confirm the original biosensor configuration to be the best of those investigated for in-vivo applications up to one week after implantation.

Amperometric microbiosensor as an alternative tool for investigation of d-serine in brain

This paper discusses the application of a reagentless, selective microbiosensor as a useful alternative tool for monitoring D-serine in neural samples. The main components of the 125-μm-diameter disk biosensor were D-amino acid oxidase for D-serine sensitivity (linear region slope, 61 ± 7 μA cm(-2) mM(-1); limit of detection, 20 nM), and poly-phenylenediamine for rejection of electroactive interference. The response time of the biosensor was of the order of 1 s, ideal for 'real-time' monitoring, and detection of systemically administered D-serine in brain extracellular fluid is demonstrated. Exploitation of this probe might resolve queries involving regulation of D-serine in excitotoxicity, and modulation of N-methyl-D-aspartate receptor function by D-serine and glycine in the central nervous system.

Development and Characterization of an Implantable Biosensor for Telemetric Monitoring of Ethanol in the Brain of Freely Moving Rats

Ethanol is one of the most widespread psychotropic agents in western society. While its psychoactive effects are mainly associated with GABAergic and glutamatergic systems, the positive reinforcing properties of ethanol are related to activation of mesolimbic dopaminergic pathways resulting in a release of dopamine in the nucleus accumbens. Given these neurobiological implications, the detection of ethanol in brain extracellular fluid (ECF) is of great importance. In this study, we describe the development and characterization of an implantable biosensor for the amperometric detection of brain ethanol in real time. Ten different designs were characterized in vitro in terms of Michaelis-Menten kinetics (V(MAX) and K(M)), sensitivity (linear region slope, limit of detection (LOD), and limit of quantification (LOQ)), and electroactive interference blocking. The same parameters were monitored in selected designs up to 28 days after fabrication in order to quantify their stability. Finally, the best performing biosensor design was selected for implantation in the nucleus accumbens and coupled with a previously developed telemetric device for the real-time monitoring of ethanol in freely moving, untethered rats. Ethanol was then administered systemically to animals, either alone or in combination with ranitidine (an alcohol dehydrogenase inhibitor) while the biosensor signal was continuously recorded. The implanted biosensor, integrated in the low-cost telemetry system, was demonstrated to be a reliable device for the short-time monitoring of exogenous ethanol in brain ECF and represents a new generation of analytical tools for studying ethanol toxicokinetics and the effect of drugs on brain ethanol levels.

The energy dependence of electron inelastic mean free paths

AbstractAn analysis has been made of the dependence on electron energy of calculated inelastic mean free paths (IMFPs) for aluminum, copper, silver, and gold from four recent sources of data. The analysis was made using Fano plots which clearly show differences in energy dependences. In addition, the slopes of linear regions in the Fano plots can be compared with values calculated from experimental optical data and with values obtained from Fano plots made with experimental attenuation length (AL) data. It was found that the slopes of the Fano plots using IMFPs from calculations of Powell and Penn agreed well with the optical results; there was generally good agreement for the IMFPs of Ashley et al., but the slopes using the IMFP data of Szajman et al. exceeded the optical values by 9–40%. The slopes in the Fano plots using AL data for Al, Cu, and Au exceeded the optical values by 29–54 %; this result is similar to those found in other analyses and indicates that the electron energies for these AL measurements were not high enough to be in the asymptotic Bethe region. Analysis of the optical data also showed that a lower limit for the electron energy range over which the Fano plots could be expected to be linear (with their asymptotic slopes) was about 400 eV for Al and about 1000 eV for Cu, Ag, and Au. More extensive AL measurements over a wide electron energy range are needed to determine the shapes of the Fano plots for different types of materials.