Analysis of Li-ion battery degradation using self-organizing maps

This paper proposes a new methodology to identify the different degradation processes of Li-Ion battery cells. The goal of this study is to determine if different degradation factors can be separated by waveform analysis from aged cells with similar remaining capacity. In contrast to other works, the proposed method identifies the past operating conditions in the cell, regardless of the actual State of Health. The methodology is based on a data-driven approach by using a SOM (Self-organizing map), an unsupervised neural network. To verify the hypothesis a SOM has been trained with laboratory data from whole data cycles, to classify cells concerning their degradation path and according to their discharge voltage patterns. Additionally, this new methodology based on the SOM allows discriminating groups of cells with different cycling conditions (based on depth of discharge, ambient temperature and discharge current). This research line is very promising for classification of used cells, not only depending on their current static parameters (capacity, impedance), but also the battery use in their past life. This will allow making predictions of the Remaining Useful Life (RUL) of a battery with greater precision

Exploring the Microbiome of Healthy and Diseased Peri-Implant Sites Using Illumina Sequencing

Aim To compare the microbiome of healthy (H) and diseased (P) peri-implant sites and determine the core peri-implant microbiome. Materials and Methods Submucosal biofilms from 32 H and 35 P sites were analyzed using 16S rRNA sequencing (MiSeq, Illumina), QIIME and HOMINGS. Differences between groups were determined using Principal Coordinate Analysis (PCoA), t-tests and Wilcoxon rank sum test and FDR-adjusted. The peri-implant core microbiome was determined. Results PCoA showed partitioning between H and P at all taxonomic levels. Bacteroidetes, Spirochetes and Synergistetes were higher in P, while Actinobacteria prevailed in H (p\u3c0.05). Porphyromonas and Treponema were more abundant in P and while Rothia and Neisseria were higher in H (p\u3c0.05). The core peri-implant microbiome contained Fusobacterium, Parvimonas and Campylobacter sp. T. denticola and P. gingivalis levels were higher in P, as well as F. alocis, F fastidiosum and T. maltophilum (p\u3c0.05). Conclusion The peri-implantitis microbiome is commensal-depleted and pathogen-enriched, harboring traditional and new pathogens. The core peri-implant microbiome harbors taxa from genera often associated with periodontal inflammation

Finding answers in lipid profile in COVID-19 patients

Introduction: A small percentage of patients will develop a severe form of COVID-19 caused by SARS-CoV-2 infection. Thus, it is important to predict the potential outcomes identifying early markers of poor prognosis. In this context, we evaluated the association of SARS-CoV-2 infection with lipid abnormalities and their role in prognosis. Methods: Single-center, retrospective, observational study of COVID-19 patients admitted from March to October 2020. Clinical and laboratory data, comorbidities, and treatments for COVID-19 were evaluated. Main outcomes including intensive care unit (ICU) admission and mortality were analyzed with a multivariable Cox proportional hazards regression model. Results: We selected 1489 from a total of 2038 consecutive patients with confirmed COVID-19, who had a complete lipid profile before ICU admission. During the follow-up performed in 1109 patients, we observed a decrease in T-c, HDL-c, and LDL-c in 28.6%, 42.9%, and 30.4% of patients, respectively, and an increase in TG in 76.8%. The decrease of both T-c and HDL- c was correlated with a decrease in albumin levels (r = 0.39 and r = 0.37, respectively). Kaplan–Meier survival curves found an increased ICU admission in patients with lower T-c (HR 0.55, CI 0.36–0.86), HDL-c (HR 0.61, CI 0.45–0.84), and LDL-c (HR 0.85, CI 0.74–0.97). Higher values of T-c (HR 0.45, CI 0.36–0.57), HDL-c (HR 0.66, CI 0.54–0.81), and LDL-c (HR 0.86, CI 0.78–0.94) showed a protective effect on mortality. Conclusions: Abnormalities in lipid profile are a frequent complication of SARS-CoV-2 infection and might be related to morbidity and mortalityThis work was supported by the following grants: Proyectos de Investigación en Salud (FIS) PI16-02091 and PI19-00584 (funded by Instituto de Salud Carlos III), TIRONET2-CM, B2017/BMD-3724 (funded by Comunidad de Madrid) and cofinanced by FEDER funds to M.M

The knee prosthesis constraint dilemma: Biomechanical comparison between varus-valgus constrained implants and rotating hinge prosthesis. A cadaver study

The real degree of constriction of rotating hinge knee (RHK) and condylar constrained prostheses (CCK) is a matter of discussion in revision knee arthroplasty. The objectives of this study are to compare the tibial rotation of both implants and validate the use of inertial sensors with optical tracking system as movement measurement tools. A total of 16 cadaver knees were used. Eight knees were replaced using a RHK (Endomodel LINK), and the remaining eight received a CCK prosthesis (LCCK, Zimmer). Tibial rotation range of motion was measured in full extension and at 30°, 60°, and 90° of flexion, with four continuous waveforms for each measurement. Measurements were made using two inertial sensors with specific software and compared with measurements obtained using the gold standard technique - the motion capture camera. The comparison of the accuracy of both measurement methods showed no statistically significant differences between inertial sensors and motion capture cameras, with p > .1; the mean error for tibial rotation was 0.21°. Tibial rotation in the RHK was significantly greater than in the CCK (5.25° vs. 2.28°, respectively), p < .05. We have shown that RHK permit greater tibial rotation, being closer to physiological values than CCKs. Inertial sensors have been validated as an effective and accurate method of measuring knee movement. The clinical significance: RHK appears to represent a lower constriction degree than CCK systems.This study wassupported by Ministerio de Ciencia, Innovación y Universidades, Instituto de Salud Carlos III and European Regional Development Fund "Una manera de hacer Europa" (grant number PI18/01625

Compilation of parameterized seismogenic sources in Iberia for the SHARE European-scale seismic source model.

Abstract: SHARE (Seismic Hazard Harmonization in Europe) is an EC-funded project (FP7) that aims to evaluate European seismic hazards using an integrated, standardized approach. In the context of SHARE, we are compiling a fully-parameterized active fault database for Iberia and the nearby offshore region. The principal goal of this initiative is for fault sources in the Iberian region to be represented in SHARE and incorporated into the source model that will be used to produce seismic hazard maps at the European scale. The SHARE project relies heavily on input from many regional experts throughout the Euro-Mediterranean region. At the SHARE regional meeting for Iberia, the 2010 Working Group on Iberian Seismogenic Sources (WGISS) was established; these researchers are contributing to this large effort by providing their data to the Iberian regional integrators in a standardized format. The development of the SHARE Iberian active fault database is occurring in parallel with IBERFAULT, another ongoing effort to compile a database of active faults in the Iberian region. The SHARE Iberian active fault database synthesizes a wide range of geological and geophysical observations on active seismogenic sources, and incorporates existing compilations (e.g., Cabral, 1995; Silva et al., 2008), original data contributed directly from researchers, data compiled from the literature, parameters estimated using empirical and analytical relationships, and, where necessary, parameters derived using expert judgment. The Iberian seismogenic source model derived for SHARE will be the first regional-scale source model for Iberia that includes fault data and follows an internationally standardized approach (Basili et al., 2008; 2009). This model can be used in both seismic hazard and risk analyses and will be appropriate for use in Iberian- and European-scale assessments

Soil microbiome structure and function in ecopiles used to remediate petroleum-contaminated soil

The soil microbiome consists of a vast variety of microorganisms which contribute to essential ecosystem services including nutrient recycling, protecting soil structure, and pathogen suppression. Recalcitrant organic compounds present in soils contaminated with fuel oil can lead to a decrease in functional redundancy within soil microbiomes. Ecopiling is a passive bioremediation technique involving biostimulation of indigenous hydrocarbon degraders, bioaugmentation through inoculation with known petroleum-degrading consortia, and phytoremediation. The current study investigates the assemblage of soil microbial communities and pollutant-degrading potential in soil undergoing the Ecopiling process, through the amplicon marker gene and metagenomics analysis of the contaminated soil. The analysis of key community members including bacteria, fungi, and nematodes revealed a surprisingly diverse microbial community composition within the contaminated soil. The soil bacterial community was found to be dominated by Alphaproteobacteria (60–70%) with the most abundant genera such as Lysobacter, Dietzia, Pseudomonas, and Extensimonas. The fungal community consisted mainly of Ascomycota (50–70% relative abundance). Soil sequencing data allowed the identification of key enzymes involved in the biodegradation of hydrocarbons, providing a novel window into the function of individual bacterial groups in the Ecopile. Although the genus Lysobacter was identified as the most abundant bacterial genus (11–46%) in all of the contaminated soil samples, the metagenomic data were unable to confirm a role for this group in petrochemical degradation. Conversely, genera with relatively low abundance such as Dietzia (0.4–9.0%), Pusillimonas (0.7–2.3%), and Bradyrhizobium (0.8–1.8%) did possess genes involved in aliphatic or aromatic compound degradation

How low can SUSY go? Matching, monojets and compressed spectra

If supersymmetry (SUSY) has a compressed spectrum then the current mass limits from the LHC can be drastically reduced. We consider a possible 'worst case' scenario where the gluino and/or squarks are degenerate with the lightest SUSY particle (LSP). The most sensitive searches for these compressed spectra are via the final state LSPs recoiling against initial state radiation (ISR). Therefore it is vital that the ISR is understood and possible uncertainties in the predictions are evaluated. We use both MLM (with Pythia 6) and CKKW- L (with Pythia 8) matching and vary matching scales and parton shower properties to accurately determine the theoretical uncertainties in the kinematic distributions. All current LHC SUSY and monojet analyses are employed and we find the most constraining limits come from the CMS Razor and CMS monojet searches. For a scenario of squarks degenerate with the LSP and decoupled gluinos we find $M_{\tilde{q}}>340$ GeV. For gluinos degenerate with the LSP and decoupled squarks, $M_{\tilde{g}}>500$ GeV. For equal mass squarks and gluinos degenerate with the LSP, $M_{\tilde{q},\tilde{g}}>650$ GeV.Comment: References added, version submitted to ep

Critical Role of Oxygen in Silver-Catalyzed Glaser-Hay Coupling on Ag(100) under Vacuum and in Solution on Ag Particles

The essential role of oxygen in enabling heterogeneously catalyzed Glaser-Hay coupling of phenylacetylene on Ag(100) was elucidated by STM, laboratory and synchrotron photoemission, and DFT calculations. In the absence of coadsorbed oxygen, phenylacetylene formed well-ordered dense overlayers which, with increasing temperature, desorbed without reaction. In striking contrast, even at 120 K, the presence of oxygen led to immediate and complete disruption of the organic layer due to abstraction of acetylenic hydrogen with formation of a disordered mixed layer containing immobile adsorbed phenylacetylide. At higher temperatures phenylacetylide underwent Glaser-Hay coupling to form highly ordered domains of diphenyldiacetylene that eventually desorbed without decomposition, leaving the bare metal surface. DFT calculations showed that, while acetylenic H abstraction was otherwise an endothermic process, oxygen adatoms triggered a reaction-initiating exothermic pathway leading to OH(a) + phenylacetylide, consistent with the experimental observations. Moreover, it was found that, with a solution of phenylacetylene in nonane and in the presence of O, Ag particles catalyzed Glaser-Hay coupling with high selectivity. Rigorous exclusion of oxygen from the reactor strongly suppressed the catalytic reaction. Interestingly, too much oxygen lowers the selectivity toward diphenyldiacetylene. Thus, vacuum studies and theoretical calculations revealed the key role of oxygen in the reaction mechanism, subsequently borne out by catalytic studies with Ag particles that confirmed the presence of oxygen as a necessary and sufficient condition for the coupling reaction to occur. The direct relevance of model studies to a mechanistic understanding of coupling reactions under conditions of practical catalysis was reaffirmed.Support from the European Union FEDER Program and MINECO under projects MAT2013-40852-R and 201560E055 is acknowledged. Computational resources were provided by the Spanish Ministerio de Economía y Competitividad, grant CTQ2015-64669-P, and the EU FEDER Program

Nanoinformatics: developing new computing applications for nanomedicine

Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended ?nanotype? to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others