Mismatch negativity in childhood temporal lobe epilepsy: a proposed paradigm for testing central auditory processing

Background: Temporal lobe epilepsy (TLE) is a neurological disorder that directly affects cortical areas responsible for auditory processing. The resulting abnormalities can be assessed using event-related potentials (ERP), which have high temporal resolution. However, little is known about TLE in terms of dysfunction of early sensory memory encoding or possible correlations between EEGs, linguistic deficits, and seizures. Mismatch negativity (MMN) is an ERP component – elicited by introducing a deviant stimulus while the subject is attending to a repetitive behavioural task – which reflects pre-attentive sensory memory function and reflects neuronal auditory discrimination and perceptional accuracy. Hypothesis: We propose an MMN protocol for future clinical application and research based on the hypothesis that children with TLE may have abnormal MMN for speech and non-speech stimuli. The MMN can be elicited with a passive auditory oddball paradigm, and the abnormalities might be associated with the location and frequency of epileptic seizures. Significance: The suggested protocol might contribute to a better understanding of the neuropsychophysiological basis of MMN. We suggest that in TLE central sound representation may be decreased for speech and non-speech stimuli. Discussion: MMN arises from a difference to speech and non-speech stimuli across electrode sites. TLE in childhood might be a good model for studying topographic and functional auditory processing and its neurodevelopment, pointing to MMN as a possible clinical tool for prognosis, evaluation, follow-up, and rehabilitation for TLE.

Communication protocol for the rempli project

The overall goal of the REMPLI project is to design and implement a communication infrastructure for distributed data acquisition and remote control operations using the power grid as the communication medium. The primary target application is remote meter reading with high time resolution, where the meters can be energy, heat, gas, or water meters. The users of the system (e.g. utility companies) will benefit from the REMPLI system by gaining more detailed information about how energy is consumed by the end-users. In this context, the power-line communication (PLC) is deployed to cover the distance between utility company’s Private Network and the end user. This document specifies a protocol for real-time PLC, in the framework of the REMPLI project. It mainly comprises the Network Layer and Data Link Layer. The protocol was designed having into consideration the specific aspects of the network: different network typologies (star, tree, ring, multiple paths), dynamic changes in network topology (due to network maintenance, hazards, etc.), communication lines strongly affected by noise.

Application of continuous wavelet transform to the analysis of the modulus of the fractional Fourier transform bands for resolving two component mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

The role of molecular imaging in modern drug development

Drug development represents a highly complex, inefficient and costly process. Over the past decade, the widespread use of nuclear imaging, owing to its functional and molecular nature, has proven to be a determinant in improving the efficiency in selecting the candidate drugs that should either be abandoned or moved forward into clinical trials. This helps not only with the development of safer and effective drugs but also with the shortening of time-to-market. The modern concept and future trends concerning molecular imaging will assumedly be hybrid or multimodality imaging, including combinations between high sensitivity and functional (molecular) modalities with high spatial resolution and morphological techniques.

Application of Continuous Wavelet Transform to the Analysis of the Modulus of the Fractional Fourier Transform Bands for Resolving Two Component Mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

Radioactivity levels of 238U and 232Th decay series and related dose rates in the surroundings of a coal power plant using high resolution g-spectrometry

Gamma radiations measurements were carried out in the vicinity of a coal-fired power plant located in the southwest coastline of Portugal. Two different gamma detectors were used to assess the environmental radiation within a circular area of 20 km centred in the coal plant: a scintillometer (SPP2 NF, Saphymo) and a high purity germanium detector (HPGe, Canberra). Fifty urban and suburban measurements locations were established within the defined area and two measurements campaigns were carried out. The results of the total gamma radiation ranged from 20.83 to 98.33 counts per second (c.p.s.) for both measurement campaigns and outdoor doses rates ranged from 77.65 to 366.51 Gy/h. Natural emitting nuclides from the U-238 and Th-232 decay series were identified as well as the natural emitting nuclide K-40. The radionuclide concentration from the uranium and thorium series determined by gamma spectrometry ranged from 0.93 to 73.68 Bq/kg, while for K-40 the concentration ranged from 84.14 to 904.38 Bq/kg. The obtained results were used primarily to define the variability in measured environmental radiation and to determine the coal plant’s influence in the measured radiation levels. The highest values were measured at two locations near the power plant and at locations between the distance of 6 and 20 km away from the stacks, mainly in the prevailing wind direction. The results showed an increase or at least an influence from the coal-fired plant operations, both qualitatively and quantitatively.

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

Analysis of PCBs in soils and sediments by microwave-assisted extraction, headspace-SPME and high resolution gas chromatography with ion-trap tandem mass spectrometry

A procedure for the determination of seven indicator PCBs in soils and sediments using microwave-assisted extraction (MAE) and headspace solid-phase microextraction (HS-SPME) prior to GC-MS/MS is described. Optimization of the HS-SPME was carried out for the most important parameters such as extraction time, sample volume and temperature. The adopted methodology has reduced consumption of organic solvents and analysis runtime. Under the optimized conditions, the method detection limit ranged from 0.6 to 1 ng/g when 5 g of sample was extracted, the precision on real samples ranged from 4 to 21% and the recovery from 69 to 104%. The proposed method, which included the analysis of a certified reference material in its validation procedure, can be extended to several other PCBs and used in the monitoring of soil or sediments for the presence of PCBs.

Multi-elemental analysis of ready-to-eat “baby leaf” vegetables using microwave digestion and high-resolution continuum source atomic absorption spectrometry

The mineral content (phosphorous (P), potassium (K), sodium (Na), calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), zinc (Zn) and copper (Cu)) of eight ready-to-eat baby leaf vegetables was determined. The samples were subjected to microwave-assisted digestion and the minerals were quantified by High-Resolution Continuum Source Atomic Absorption Spectrometry (HR-CS-AAS) with flame and electrothermal atomisation. The methods were optimised and validated producing low LOQs, good repeatability and linearity, and recoveries, ranging from 91% to 110% for the minerals analysed. Phosphorous was determined by a standard colorimetric method. The accuracy of the method was checked by analysing a certified reference material; results were in agreement with the quantified value. The samples had a high content of potassium and calcium, but the principal mineral was iron. The mineral content was stable during storage and baby leaf vegetables could represent a good source of minerals in a balanced diet. A linear discriminant analysis was performed to compare the mineral profile obtained and showed, as expected, that the mineral content was similar between samples from the same family. The Linear Discriminant Analysis was able to discriminate different samples based on their mineral profile.

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.