Influence of hydrogen peroxide in the tribocorrosion behaviour of a CoCrMo biomedical alloy

This paper studies the influence of hydrogen peroxide (H2O2) in simulated body fluids on the wear and corrosion behaviour of a CoCrMo biomedical alloy. CoCrMo are passive materials commonly used in prosthesis and implants because of its high corrosion resistance and mechanical properties. Hydrogen peroxide is produced by bacteria and leukocytes as a consequence of an inflammatory reaction which may modify the tribo-electrochemical response of metals implanted in the human body. Indeed, the oxidizing environment generated by the presence of the peroxide increases the metal dissolution rate. Electrochemical and tribocorrosion tests were carried out in a PBS solution with different addition of H2O2 (0.5, 2, 4 and 12%).The authors acknowledge Generalitat Valencia for the Gerónimo Forteza financial support and to the Electron Microscopy Service of the UPV for the SEM images

Integral mathematical model of power quality disturbances

Power quality (PQ) disturbances lead to severe problems in industries and electrical grids. To mitigate PQ problems, the accurate detection and classification of the possible disturbances are essential. A large number of studies exists in this field. The first research step in these studies is to obtain several distorted signals to test the classification systems. In this regard, the most common trend is the generation of signals from mathematical models. In the literature, we can find several models with significant differences among them. However, to the best of our knowledge, there is no integral model that considers all types of distortions. This work presents an integral mathematical model based on the models found in the literature. The model also includes new types of combined disturbances. Twenty-nine disturbances are considered. Additionally, this work includes a software version of this integral model that is publicly available to be used by any interested researcher. In this way, PQ disturbances can be generated in a fast and automatic way. This software aims to facilitate future studies, supporting researchers in the modelling stage

Detecting Falls as Novelties in Acceleration Patterns Acquired with Smartphones

Despite being a major public health problem, falls in the elderly cannot be detected efficiently yet. Many studies have used acceleration as the main input to discriminate between falls and activities of daily living (ADL). In recent years, there has been an increasing interest in using smartphones for fall detection. The most promising results have been obtained by supervised Machine Learning algorithms. However, a drawback of these approaches is that they rely on falls simulated by young or mature people, which might not represent every possible fall situation and might be different from older people's falls. Thus, we propose to tackle the problem of fall detection by applying a kind of novelty detection methods which rely only on true ADL. In this way, a fall is any abnormal movement with respect to ADL. A system based on these methods could easily adapt itself to new situations since new ADL could be recorded continuously and the system could be re-trained on the fly. The goal of this work is to explore the use of such novelty detectors by selecting one of them and by comparing it with a state-of-the-art traditional supervised method under different conditions. The data sets we have collected were recorded with smartphones. Ten volunteers simulated eight type of falls, whereas ADL were recorded while they carried the phone in their real life. Even though we have not collected data from the elderly, the data sets were suitable to check the adaptability of novelty detectors. They have been made publicly available to improve the reproducibility of our results. We have studied several novelty detection methods, selecting the nearest neighbour-based technique (NN) as the most suitable. Then, we have compared NN with the Support Vector Machine (SVM). In most situations a generic SVM outperformed an adapted NN

The effect of personalization on smartphone-based fall detectors

The risk of falling is high among different groups of people, such as older people, individuals with Parkinson''s disease or patients in neuro-rehabilitation units. Developing robust fall detectors is important for acting promptly in case of a fall. Therefore, in this study we propose to personalize smartphone-based detectors to boost their performance as compared to a non-personalized system. Four algorithms were investigated using a public dataset: three novelty detection algorithms—Nearest Neighbor (NN), Local Outlier Factor (LOF) and One-Class Support Vector Machine (OneClass-SVM)—and a traditional supervised algorithm, Support Vector Machine (SVM). The effect of personalization was studied for each subject by considering two different training conditions: data coming only from that subject or data coming from the remaining subjects. The area under the receiver operating characteristic curve (AUC) was selected as the primary figure of merit. The results show that there is a general trend towards the increase in performance by personalizing the detector, but the effect depends on the individual being considered. A personalized NN can reach the performance of a non-personalized SVM (average AUC of 0.9861 and 0.9795, respectively), which is remarkable since NN only uses activities of daily living for training

Combining novelty detectors to improve accelerometer-based fall detection

Research on body-worn sensors has shown how they can be used for the detection of falls in the elderly, which is a relevant health problem. However, most systems are trained with simulated falls, which differ from those of the target population. In this paper, we tackle the problem of fall detection using a combination of novelty detectors. A novelty detector can be trained only with activities of daily life (ADL), which are true movements recorded in real life. In addition, they allow adapting the system to new users, by recording new movements and retraining the system. The combination of several detectors and features enhances performance. The proposed approach has been compared with a traditional supervised algorithm, a support vector machine, which is trained with both falls and ADL. The combination of novelty detectors shows better performance in a typical cross-validation test and in an experiment that mimics the effect of personalizing the classifiers. The results indicate that it is possible to build a reliable fall detector based only on ADL

Fall Detection Analysis Using a Real Fall Dataset

International Conference on Soft Computing Models in Industrial and Environmental Applications (13th. 2018. San Sebastián

Uncertainty Analysis in the Inverse of Equivalent Conductance Method for Dealing with Crosstalk in 2-D Resistive Sensor Arrays

2-D resistive sensor arrays (RSAs) appear in many applications to measure physical quantities in a surface. However, they suffer from a crosstalk problem when the simplest configuration is used to address a row-column. Thus, the value of a single cell cannot be measured directly. Several hardware solutions have been proposed to solve it totally or partially but all of them make the circuit more complex. In a previous paper we proposed an innovative numerical solution to eliminate crosstalk after a complete scan of the matrix, which is named in this paper as Inverse of Equivalent Conductance Method (IECM). In the current study, we have analyzed the implications of the method for the uncertainty of the calculated cell resistance by first deriving the sensitivity of the solution and then applying uncertainty propagation theory. The theoretical results have been tested in simulated arrays and in a real 6x6 RSA with known values of resistances with good agreement. The uncertainty analysis is able to predict which values are reliable. In general, the lowest resistances of the array are better solved by IECM as expected. In addition, it is also shown that IECM has the potential to be adapted to other hardware configurations that reduce crosstalk, helping to overcome some of its limitations. IEE

<em>Micromonospora parastrephiae</em> sp. nov. and <em>Micromonospora tarensis</em> sp. nov., isolated from the rhizosphere of a <em>Parastrephia quadrangularis</em> plant growing in the Salar de Tara region of the Central Andes in Chile

\ua9 2023 The Authors. Two novel Micromonospora strains, STR1-7T and STR1S-6T, were isolated from the rhizosphere of a Parastrephia quadran-gularis plant growing in the Salar de Tara region of the Atacama Desert, Chile. Chemotaxonomic, cultural and phenotypic features confirmed that the isolates belonged to the genus Micromonospora. They grew from 20 to 37 \ub0C, from pH7 to 8 and in the presence of up to 3 %, w/v NaCl. The isolates formed distinct branches in Micromonospora gene trees based on 16S rRNA gene sequences and on a multi-locus sequence analysis of conserved house-keeping genes. A phylogenomic tree generated from the draft genomes of the isolates and their closest phylogenetic neighbours showed that isolate STR1-7T is most closely related to Micromonospora orduensis S2509T, and isolate STR1S-6T forms a distinct branch that is most closely related to 12 validly named Micromonospora species, including Micromonospora saelicesensis the earliest proposed member of the group. The isolates were separated from one another and from their closest phylogenomic neighbours using a combination of chemo-taxonomic, genomic and phenotypic features, and by low average nucleotide index and digital DNA–DNA hybridization values. Consequently, it is proposed that isolates STR1-7T and STR1S-6T be recognized as representing new species in the genus Micromonospora, namely as Micromonospora parastrephiae sp. nov. and Micromonospora tarensis sp. nov.; the type strains are STR1-7T (=CECT 9665T=LMG 30768T) and STR1S-6T (=CECT 9666T=LMG 30770T), respectively. Genome mining showed that the isolates have the capacity to produce novel specialized metabolites, notably antibiotics and compounds that promote plant growth, as well as a broad-range of stress-related genes that provide an insight into how they cope with harsh abiotic conditions that prevail in high-altitude Atacama Desert soils

Specific Glucoside Transporters Influence Septal Structure and Function in the Filamentous, Heterocyst-Forming Cyanobacterium Anabaena sp Strain PCC 7120

T When deprived of combined nitrogen, some filamentous cyanobacteria contain two cell types: vegetative cells that fix CO2 through oxygenic photosynthesis and heterocysts that are specialized in N2 fixation. In the diazotrophic filament, the vegetative cells provide the heterocysts with reduced carbon (mainly in the form of sucrose) and heterocysts provide the vegetative cells with combined nitrogen. Septal junctions traverse peptidoglycan through structures known as nanopores and appear to mediate intercellular molecular transfer that can be traced with fluorescent markers, including the sucrose analog esculin (a coumarin glucoside) that is incorporated into the cells. Uptake of esculin by the model heterocyst-forming cyanobacterium Anabaena sp. strain PCC 7120 was inhibited by the -glucosides sucrose and maltose. Analysis of Anabaena mutants identified components of three glucoside transporters that move esculin into the cells: GlsC (Alr4781) and GlsP (All0261) are an ATP-binding subunit and a permease subunit of two different ABC transporters, respectively, and HepP (All1711) is a major facilitator superfamily (MFS) protein that was shown previously to be involved in formation of the heterocyst envelope. Transfer of fluorescent markers (especially calcein) between vegetative cells of Anabaena was impaired by mutation of glucoside transporter genes. GlsP and HepP interact in bacterial two-hybrid assays with the septal junction-related protein SepJ, and GlsC was found to be necessary for the formation of a normal number of septal peptidoglycan nanopores and for normal subcellular localization of SepJ. Therefore, beyond their possible role in nutrient uptake in Anabaena, glucoside transporters influence the structure and function of septal junctions.Peer reviewe