Motor evoked potentials for multiple sclerosis, a multiyear follow-up dataset.

Multiple sclerosis (MS) is a chronic disease affecting millions of people worldwide. Through the demyelinating and axonal pathology of MS, the signal conduction in the central nervous system is affected. Evoked potential measurements allow clinicians to monitor this process and can be used for decision support. We share a dataset that contains motor evoked potential (MEP) measurements, in which the brain is stimulated and the resulting signal is measured in the hands and feet. This results in time series of 100 milliseconds long. Typically, both hands and feet are measured in one hospital visit. The dataset contains 5586 visits of 963 patients, performed in day-to-day clinical care over a period of 6 years. The dataset consists of approximately 100,000 MEP. Clinical metadata such as the expanded disability status scale, sex, and age is also available. This dataset can be used to explore the role of evoked potentials in MS research and patient care. It may also be used as a benchmark for time series analysis and predictive modelling.

X-ray Absorption (XRA): A New Technique for the Characterization of Granular Activated Carbons.

The X-ray absorption (XRA) method using digital image processing techniques is a reliable technique to determine the exhaustion degree of granular activated carbons (GACs). Using an innovative digital image processing technique, the identification of individual adsorbed molecules or ions in a GAC was possible. Adsorption isotherm models (Langmuir and Freundlich) were used to simulate the adsorption equilibrium data of Methylene Blue (MB), nickel, cobalt and iodine. Freundlich equation was found to have the highest value of R2 compared with Langmuir. The identification of distinctive patterns applying XRA for different adsorbed ions and molecules onto GAC was explored. It is demonstrated that unique XRA configurations for each adsorbed ion or molecule are found, as well as a proportional relationship between its incident energy (needed to achieve maximum photon attenuation) and the (effective) atomic number, the adsorbate mass and the molar or atomic mass of adsorbed molecule or ion. XRA method in combination with image histogram modifications was used to obtain a digital signature of adsorbed ions/molecules, giving distinct GSI values for each one in the used energy range. Probabilistic models prove that XRA results are within relationships between effective atomic number and photonic interaction probability, reinforcing the potentialities of XRA for monitoring (multi-)ion and/or molecule combinations on GAC using advanced digital image processing techniques. It was proved that the proposed approach could assess different adsorbed ions/molecules onto GACs in water purification systems.

Deciphering the Morphology of Motor Evoked Potentials.

Motor Evoked Potentials (MEPs) are used to monitor disability progression in multiple sclerosis (MS). Their morphology plays an important role in this process. Currently, however, there is no clear definition of what constitutes a normal or abnormal morphology. To address this, five experts independently labeled the morphology (normal or abnormal) of the same set of 1,000 MEPs. The intra- and inter-rater agreement between the experts indicates they agree on the concept of morphology, but differ in their choice of threshold between normal and abnormal morphology. We subsequently performed an automated extraction of 5,943 time series features from the MEPs to identify a valid proxy for morphology, based on the provided labels. To do this, we compared the cross-validation performances of one-dimensional logistic regression models fitted to each of the features individually. We find that the approximate entropy (ApEn) feature can accurately reproduce the majority-vote labels. The performance of this feature is evaluated on an independent test set by comparing to the majority vote of the neurologists, obtaining an AUC score of 0.92. The model slightly outperforms the average neurologist at reproducing the neurologists consensus-vote labels. We can conclude that MEP morphology can be consistently defined by pooling the interpretations from multiple neurologists and that ApEn is a valid continuous score for this. Having an objective and reproducible MEP morphological abnormality score will allow researchers to include this feature in their models, without manual annotation becoming a bottleneck. This is crucial for large-scale, multi-center datasets. An exploratory analysis on a large single-center dataset shows that ApEn is potentially clinically useful. Introducing an automated, objective, and reproducible definition of morphology could help overcome some of the barriers that are currently obstructing broad adoption of evoked potentials in daily care and patient follow-up, such as standardization of measurements between different centers, and formulating guidelines for clinical use.

Machine learning analysis of motor evoked potential time series to predict disability progression in multiple sclerosis.

BACKGROUND: Evoked potentials (EPs) are a measure of the conductivity of the central nervous system. They are used to monitor disease progression of multiple sclerosis patients. Previous studies only extracted a few variables from the EPs, which are often further condensed into a single variable: the EP score. We perform a machine learning analysis of motor EP that uses the whole time series, instead of a few variables, to predict disability progression after two years. Obtaining realistic performance estimates of this task has been difficult because of small data set sizes. We recently extracted a dataset of EPs from the Rehabiliation & MS Center in Overpelt, Belgium. Our data set is large enough to obtain, for the first time, a performance estimate on an independent test set containing different patients. METHODS: We extracted a large number of time series features from the motor EPs with the highly comparative time series analysis software package. Mutual information with the target and the Boruta method are used to find features which contain information not included in the features studied in the literature. We use random forests (RF) and logistic regression (LR) classifiers to predict disability progression after two years. Statistical significance of the performance increase when adding extra features is checked. RESULTS: Including extra time series features in motor EPs leads to a statistically significant improvement compared to using only the known features, although the effect is limited in magnitude (ΔAUC = 0.02 for RF and ΔAUC = 0.05 for LR). RF with extra time series features obtains the best performance (AUC = 0.75±0.07 (mean and standard deviation)), which is good considering the limited number of biomarkers in the model. RF (a nonlinear classifier) outperforms LR (a linear classifier). CONCLUSIONS: Using machine learning methods on EPs shows promising predictive performance. Using additional EP time series features beyond those already in use leads to a modest increase in performance. Larger datasets, preferably multi-center, are needed for further research. Given a large enough dataset, these models may be used to support clinicians in their decision making process regarding future treatment.

X-ray absorption as an alternative method to determine the exhausting degree of activated carbon layers in water treatment system for medical services.

Analytical methods based on X-Ray radiation proved to be reliable and sensitive techniques to study activated carbons (ACs). An X-Ray absorption analysis based on digital radiographic images (XRA) is applied for the determination of the exhaustion degree of granular activated carbon (GAC) used in a water purification system for hemodialysis. XRA-method demonstrated the possibility to determine the exhaustion degree at different layers of the GAC filter. The results of the XRA-method were successfully correlated with X-Ray Fluorescence (XRF), TGA, Elemental analysis (EA), SEM, TD-GC/MS, ATR-FTIR, X Ray Diffraction (XRD) and Nuclear Magnetic Resonance relaxometry (NMR) analyses. It was demonstrated that the XRA-method is a fast and reliable analytical tool to give indirect information on the exhaustion degree of GAC at different layers. It is also demonstrated that XRA results can be correlated with the results of the other analytical techniques, rather dealing with the composition and morphology of GAC at different layers.

Adsorption and photocatalytic removal of Ibuprofen by activated carbon impregnated with TiO2 by UV-Vis monitoring.

The removal of Ibuprofen was investigated by activated carbon impregnated with TiO2. Emphasis was given on the effect of different parameters, such as composite type, initial Ibuprofen concentration (5-25 mg/L), temperature (22-28 °C) and pH (acidic and alkaline solution). The experiment was carried out in a self-made tubular flow reactor, with one 15 W monochromatic UV lamp (254 nm). The composite AC90T10 gives the highest removal degree of 92% of Ibuprofen solution under UV light within 4 h, due to synergy of adsorption and photodegradation. It was found that weight ratio of composite/Ibuprofen has limited effect on the removal degree within the concentration range (5-25 mg/L), but reaction time under UV light (4 h) and pH (acidic solution) are very important. The kinetic experimental data obtained at pH 4.3 at 25 °C on different composites were fitted to pseudo-first, pseudo-second and Elovich models, obtaining a high accuracy based on R2 values. From the results, composites of granular activated carbon and TiO2 can enhance removal of Ibuprofen effectively, making recycle process much easier and less costly, which can be a promising method in future water treatment.

A novel acoustic approach for the characterization of granular activated carbons used in the rum production.

Acoustic analysis and sound patterns recognition techniques have been widely used in many branches of science, however; almost none focused on the characterization of granular activated carbon. A new methodology has been developed in order to characterize activated carbon based on the dynamic analysis in audible spectra of the sound's relative amplitude power produced by water flooded on granular activated carbon. A home-build recording set-up and management of acoustic measurements have been presented and correlated with the results of porous structure of carbons characterized by N2 adsorption. Five samples of granular activated carbons used in the rum production of different exhausted level have been evaluated by both methods. Parameters as the BET surface area and total pore volume showed a satisfactory correlation with acoustic measurement data when the signal is processed at 1000Hz. Three frequencies components of the produced sound were analyzed and related with the porous characteristics. The found relationship gives the possibility to predict and calculate textural parameters of granular activated carbons applying the acoustic technique. This methodology approach opens possibilities in using acoustic experiments for the characterization of high-porosity materials and to determine their exhausted level.

Rapeseed and Raspberry Seed Cakes as Inexpensive Raw Materials in the Production of Activated Carbon by Physical Activation: Effect of Activation Conditions on Textural and Phenol Adsorption Characteristics.

The production of activated carbons (ACs) from rapeseed cake and raspberry seed cake using slow pyrolysis followed by physical activation of the obtained solid residues is the topic of this study. The effect of activation temperature (850, 900 and 950 °C), activation time (30, 60, 90 and 120 min) and agent (steam and CO2) on the textural characteristics of the ACs is investigated by N2 adsorption. In general, higher activation temperatures and longer activation times increase the BET specific surface area and the porosity of the ACs, regardless of the activation agent or raw material. Steam is more reactive than CO2 in terms of pore development, especially in the case of raspberry seed cake. The performance of the ACs in liquid adsorption is evaluated by batch phenol adsorption tests. Experimental data are best fitted by the Freundlich isotherm model. Based on total yield, textural characteristics and phenol adsorption, steam activation at 900 °C for 90 min and CO2 activation at 900 °C for 120 min are found as the best activation conditions. Raspberry seed cake turns out to be a better raw material than rapeseed cake. Moreover, AC from raspberry seed cake produced by steam activation at 900 °C for 90 min performs as well as commercial AC (Norit GAC 1240) in phenol adsorption. The adsorption kinetics of the selected ACs are best fitted by the pseudo-second-order model.

A hybridization approach to efficient TiO2 photodegradation of aqueous benzalkonium chloride.

TiO2 get positively charged upon UV-irradiation and repel the cationic pollutants away from the surface. Hybridization of AC onto TiO2 (ACT) tends catalyst surface negatively charged besides providing highly favorable adsorptions sites for cationic pollutants. The photodegradation of benzalkonium chloride (BKC), a quaternary ammonium surfactant and a pharmaceutical, is investigated with ACT. The surface charge of the catalyst in surfactant and non-surfactant aqueous dispersion under UV-irradiation is investigated and explained. The anomalous increase in COD values at the beginning of BKC-photodegradation is explained. The intermediate products formed are identified in both solution and solid phase. Trace amount of dodecane remained adsorbed on the catalyst surface after 1h UV-irradiation, but complete mineralization of BKC is achieved with 2h UV-irradiation. We propose that BKC photodegradation starts by central fission of benzyl CN bond followed by dealkylation, and demethylation steps.

Activated carbon from pyrolysis of brewer's spent grain: Production and adsorption properties.

Brewer's spent grain is a low cost residue generated by the brewing industry. Its chemical composition (high nitrogen content 4.35 wt.%, fibres, etc.) makes it very useful for the production of added value in situ nitrogenised activated carbon. The composition of brewer's spent grain revealed high amounts of cellulose (20.8 wt.%), hemicellulose (48.78 wt.%) and lignin (11.3 wt.%). The fat, ethanol extractives and ash accounted for 8.17 wt.%, 4.7 wt.% and 3.2 wt.%, respectively. Different activated carbons were produced in a lab-scale pyrolysis/activation reactor by applying several heat and steam activation profiles on brewer's spent grain. Activated carbon yields from 16.1 to 23.6 wt.% with high N-contents (> 2 wt.%) were obtained. The efficiency of the prepared activated carbons for phenol adsorption was studied as a function of different parameters: pH, contact time and carbon dosage relative to two commercial activated carbons. The equilibrium isotherms were described by the non-linear Langmuir and Freundlich models, and the kinetic results were fitted using the pseudo-first-order model and the pseudo-second-order model. The feasibility of an activated carbon production facility (onsite and offsite) that processes brewer's spent grain for different input feeds is evaluated based on a techno-economic model for estimating the net present value. Even though the model assumptions start from a rather pessimistic scenario, encouraging results for a profitable production of activated carbon using brewer's spent grain are obtained.

Study of the pyrolysis of sludge and sludge/disposal filter cake mix for the production of value added products.

Slow and fast pyrolysis of sludge and sludge/disposal filter cake (FC) mix are performed to investigate the liquid and solid products for their use as value added products. The obtained slow pyrolysis liquid products separate in an oil, a water rich fraction and a valuable crystalline solid 5,5-dimethyl hydantoin. During fast pyrolysis, mainly an oil fraction is formed. Aliphatic acids and amides present in the water rich fractions can be considered as value added products and could be purified. The oil fractions have properties which make them promising as fuel (25-35 MJ/kg, 14-20 wt% water content, 0.2-0.6 O/C value), but upgrading is necessary. Sludge/FC oils have a lower calorific value, due to evaporation of alcohols present in FC. ICP-AES analyses reveal that almost none of the metals present in sludge or sludge/FC are transferred towards the liquid fractions. The metals are enriched in the solid fractions.

Evaluation of cyclonic ash, commercial Na-silicates, lime and phosphoric acid for metal immobilisation purposes in contaminated soils in Flanders (Belgium).

In order to reduce the health risks associated with historically enriched metal smelting sites in Flanders (Belgium), the capacities of a non-beringite cyclonic ash and commercial Na-silicates to fix metals and create conditions to restore vegetation cover were evaluated and compared to lime and H(3)PO(4). All tested amendments reduced Ca(NO(3))(2)-extractable soil metal concentrations and reduced metal uptake in Agrostis capillaris seedlings. Sodium released by Na-silicates was possibly toxic to bean plants while an isotopic dilution technique revealed that metals were only weakly sorbed by silicates (i.e. reversible sorption). Cyclonic ash appeared more efficient than lime in both reducing oxidative stress in beans and Zn, Cu and Pb uptake in grasses. The metal fixing mechanism for both amendments appeared similar (i.e. irreversible fixation at constant pH), in contrast to H(3)PO(4) where at least part of the immobilised Cd was irreversibly fixed across a range of pH.