Time Decay of the Activity of the Reduction Reaction of NO by CO on a Pd/Al2O3 Catalyst

An experimental study is made of the time decay of activity of the CO–NO reaction on a Pd/Al₂O₃ looking at the effect on reaction order and apparent activation energy. The optimum kinetics parameters fitting the steady state data at moderate pressures are determined. The time decay curves are analyzed through various catalyst deactivation models.     

A smartphone-based virtual white cane

The objective of our research was to develop assistive technology for visually impaired people, with a high appreciation for the human potential to achieve, to learn, and to achieve goals. In this document, we describe a virtual white cane made of a combination of a Smartphone and a laser pointer. In our device, the laser pointer beam reflection is captured by the Smartphone camera. The distance from the virtual white cane to the reflection is computed through active triangulation. Then, a personalized vibration, the magnitude of which corresponds to distance, is generated in the Smartphone. In this way, the users receive information that could prevent collisions with obstacles in the environment. Our contributions include the development of a virtual white cane around a Smartphone and other off-the-shelf accessories and a methodology to provide personalized vibratory feedback to the user. Our experiments show that to navigate, our instrument is better option, in terms of travel time, that the use of the hands. However, the travel time is still better using a traditional white cane than our instrument.     

Ensembles of decision trees based on imprecise probabilities and uncertainty measures

In this paper, we present an experimental comparison among different strategies for combining decision trees built by means of imprecise probabilities and uncertainty measures. It has been proven that the combination or fusion of the information obtained from several classifiers can improve the final process of the classification. We use previously developed schemes, known as Bagging and Boosting, along with a new one based on the variation of the root node via the information rank of each feature of the class variable. To this end, we applied two different approaches to deal with missing data and continuous variables. We use a set of tests on the performance of the methods analyzed here, to show that, with the appropriate approach, the Boosting scheme constitutes an excellent way to combine this type of decision tree. It should be noted that it provides good results, even compared with a standard Random Forest classifier, a successful procedure very commonly used in the literature.     

Non-invasive organization variation assessment in the onset and termination of paroxysmal atrial fibrillation

Atrial Fibrillation (AF) is the most common supraventricular tachyarrhythmia. Recently, it has been suggested that AF is partially organized on its onset and termination, thus being more suitable for antiarrhythmia and to avoid unnecessary therapy. Although several invasive and non-invasive AF organization estimators have been proposed, the organization time course in the first and last minutes of AF has not been quantified yet. The aim of this work is to study non-invasively the organization variation within the first and last minutes of paroxysmal AF. The organization was evaluated making use of sample entropy, which can robustly estimate electrical atrial activity organization from surface ECG recordings. This work proves an organization decrease in the first minutes of AF onset and an increase within the last minute before spontaneous AF termination. These results are in agreement with the conclusions reported by other authors who made use of invasive recordings.     

Analysis of the HLA class I associated peptide repertoire in a hepatocellular carcinoma cell line reveals tumor-specific peptides as putative targets for immunotherapy

HLA class I molecules present peptides on the cell surface to CD8(+) T cells. The repertoire of peptides that associate to class I molecules represents the cellular proteome. Therefore, cells expressing different proteomes could generate different class I-associated peptide repertoires. A large number of peptides have been sequenced from HLA class I alleles, mostly from lymphoid cells. On the other hand, T cell immunotherapy is a goal in the fight against cancer, but the identification of T cell epitopes is a laborious task. Proteomic techniques allow the definition of putative T cell epitopes by the identification of HLA natural ligands in tumor cells. In this study, we have compared the HLA class I-associated peptide repertoire from the hepatocellular carcinoma (HCC) cell line SK-Hep-1 with that previously described from lymphoid cells. The analysis of the peptide pool confirmed that, as expected, the peptides from SK-Hep-1 derive from proteins localized in the same compartments as in lymphoid cells. Within this pool, we have identified 12 HLA class I peptides derived from HCC-related proteins. This confirms that tumor cell lines could be a good source of tumor associated antigens to be used, together with MS, to define putative epitopes for cytotoxic T cells from cancer patients.     

Factorization of multipliers in passivity and IQC analysis

Multipliers are often used to find conditions for the absolute stability of Lur’e systems. They can be used either in conjunction with passivity theory or within the more recent framework of integral quadratic constraints (IQCs). We compare the use of multipliers in both approaches. Passivity theory requires that the multipliers have a canonical factorization and it has been suggested in the literature that this represents an advantage of the IQC theory. We consider sufficient conditions on the nonlinearity class for the associated multipliers to have a canonical factorization.     

A Suite of Tools for Debugging Distributed Autonomous Systems

This paper describes a set of tools that enables developers to log and analyze the run-time behavior of distributed control systems. A feature of the tools is that they can be applied to distributed systems. The logging tools enable developers to instrument C or C++ programs so that data indicating state changes can be logged automatically in a variety of formats. In particular, run-time data from distributed systems can be synchronized into a single relational database. Tools are also provided for visualizing the logged data. Analysis to verify correct program behavior is done using a new interval logic that is described in this paper. The logic enables system engineers to express temporal specifications for the autonomous control program that are then checked against the logged data. The data logging, visualization, and interval logic analysis tools are all fully implemented. Results are given from a NASA distributed autonomous control system application.     

Learning Structure from Data and Its Application to Ozone Prediction

In this paper we propose an algorithm for structure learning in predictive expert systems based on a probabilistic network representation. The idea is to have the simplest structure (minimum number of links) with acceptable predictive capability. The algorithm starts by building a tree structure based on measuring mutual information between pairs of variables, and then it adds links as necessary to obtain certain predictive performance. We have applied this method for ozone prediction in México City, where the ozone level is used as a global indicator for the air quality in different parts of the city. It is important to predict the ozone level a day, or at least several hours in advance, to reduce the health hazards and industrial losses that occur when the ozone reaches emergency levels. We obtained as a first approximation a tree-structured dependency model for predicting ozone in one part of the city. We observe that even with only three parameters, its estimations are acceptable.A causal network representation and the structure learning techniques produced some very interesting results for the ozone prediction problem. Firstly, we got some insight into the dependence structure of the phenomena. Secondly, we got an indication of which are the important and not so important variables for ozone forecasting. Taking this into account, the measurement and computational costs for ozone prediction could be reduced. And thirdly, we have obtained satisfactory short term ozone predictions based on a small set of the most important parameters.     

Effects of the drying method on the oxidative stability of the free and encapsulated fractions of microencapsulated sunflower oil

The influence of the drying method, freeze-drying and spray-drying, on the oxidative stability of microencapsulated sunflower oil depended on the type of encapsulation matrix. For a dairy-type matrix, formed by sodium caseinate and lactose, greater losses of tocopherols were detected during spray-drying, but both the free and encapsulated oil fractions were more stable against lipid oxidation than their freeze-dried counterparts. Results suggested that the free oil was also constituted by droplets that preserved their interfacial membrane and were protected by the matrix. Therefore, the free oil was not necessarily the non-encapsulated fraction. For a matrix constituted by gelatine, maltodextrin and sucrose, the emulsion showed low stability and a great destabilisation during spray-drying. No significant effect of the drying method on the oxidative stability of the encapsulated fraction was found with this matrix, but the free oil of the spray-dried sample oxidised faster, probably due to the emulsion destabilisation observed, which gave rise to a great amount of oil on the particle surface as a consequence of large droplets poorly stabilised.