Posterior Interosseous Artery Adipofascial Flap for the Management of Distal Radioulnar Joint Osteoarthritis.

Level IV-therapeutic.

Life cycle assessment to evaluate the integral water cycle in industrial supply: A real case study.

Wastewater recycling technologies are developed in areas where the necessity of water resources cannot be satisfied by natural sources. Nevertheless, nowadays trends and European Union Plans show an increasing interest on using these technologies to reduce environmental impacts. This manuscript aims to address the question of the real environmental results of using these technologies and the differences between each specific case using the Life Cycle Assessment (LCA) methodology.

Boosting ridge for the extreme learning machine globally optimised for classification and regression problems.

This paper explores the boosting ridge (BR) framework in the extreme learning machine (ELM) community and presents a novel model that trains the base learners as a global ensemble. In the context of Extreme Learning Machine single-hidden-layer networks, the nodes in the hidden layer are preconfigured before training, and the optimisation is performed on the weights in the output layer. The previous implementation of the BR ensemble with ELM (BRELM) as base learners fix the nodes in the hidden layer for all the ELMs.

Inclusion of key social indices for a comparative assessment of the sustainability of the life cycle of current and future electricity generation in Spain: A proposed methodology.

The purpose of this work is to offer a methodology for the introduction and consolidation of social indexes within a Life Cycle Sustainability Assessment for the evaluation of large-scale electricity production. This methodology is based on an interrelation of the UNEP subcategories with the global indicator framework for the Sustainable Development Goals, resulting in 9 categories of social impact quantified by 10 indexes. To evaluate the introduction of this methodology in an LCSA a study case is used.

Nonlinear physics opens a new paradigm for accurate transcription start site prediction.

There is evidence that DNA breathing (spontaneous opening of the DNA strands) plays a relevant role in the interactions of DNA with other molecules, and in particular in the transcription process. Therefore, having physical models that can predict these openings is of interest. However, this source of information has not been used before either in transcription start sites (TSSs) or promoter prediction.

The challenge of community mental health interventions with patients, relatives, and health professionals during the COVID-19 pandemic: a real-world 9-month follow-up study.

Since the beginning of the COVID-19 pandemic, the need to implement protocols that respond to the mental health demands of the population has been demonstrated. The PASMICOR programme started in March 2020, involving a total of 210 requests for treatment. Out of those subjects, the intervention was performed in 53 patients with COVID-19 without history of past psychiatric illness, 57 relatives and 60 health professionals, all of them within the area of Salamanca (Spain).

Total hip reconstruction after sarcoma resection in children with a free vascularized fibula without osteotomy of the bone flap: Technique description and case series.

Background: Hip joint reconstruction following intra-articular resection of the femoral head in children is a highly demanding challenge. We aimed to describe the outcomes of hip reconstruction in paediatric patients with a free fibular epiphyso-diaphyseal flap based on both anterior tibial and peroneal vessels within a radius allograft.

Patients And Methods: Four patients underwent hip reconstruction following this technique between 2013 and 2020 at La Paz University Hospital (Madrid, Spain).

Global Negative Correlation Learning: A Unified Framework for Global Optimization of Ensemble Models.

Ensembles are a widely implemented approach in the machine learning community and their success is traditionally attributed to the diversity within the ensemble. Most of these approaches foster diversity in the ensemble by data sampling or by modifying the structure of the constituent models. Despite this, there is a family of ensemble models in which diversity is explicitly promoted in the error function of the individuals.

Floating Search Methodology for Combining Classification Models for Site Recognition in DNA Sequences.

Recognition of the functional sites of genes, such as translation initiation sites, donor and acceptor splice sites and stop codons, is a relevant part of many current problems in bioinformatics. The best approaches use sophisticated classifiers, such as support vector machines. However, with the rapid accumulation of sequence data, methods for combining many sources of evidence are necessary as it is unlikely that a single classifier can solve this problem with the best possible performance.

Adherence to Long-Term Oxygen Therapy. Influence of Tobacco Use.

Introduction: Domiciliary oxygen therapy (DOT) is a treatment that requires a high level of cooperation from patients due to the time it takes every day. A high level of non-compliance has been determined among patients receiving DOT. The aim of our study was to assess the level of non-compliance and the influence of active tobacco consumption on compliance.

Now is the Time for a Postracial Medicine: Biomedical Research, the National Institutes of Health, and the Perpetuation of Scientific Racism.

The consideration of racial differences in the biology of disease and treatment options is a hallmark of modern medicine. However, this time-honored medical tradition has no scientific basis, and the premise itself, that is, the existence of biological differences between the commonly known races, is false inasmuch as races are only sociocultural constructions. It is time to rid medical research of the highly damaging exercise of searching for supposed racial differences in the biological manifestations of disease.

Stepwise approach for combining many sources of evidence for site-recognition in genomic sequences.

Background: Recognizing the different functional parts of genes, such as promoters, translation initiation sites, donors, acceptors and stop codons, is a fundamental task of many current studies in Bioinformatics. Currently, the most successful methods use powerful classifiers, such as support vector machines with various string kernels. However, with the rapid evolution of our ability to collect genomic information, it has been shown that combining many sources of evidence is fundamental to the success of any recognition task.

Improving translation initiation site and stop codon recognition by using more than two classes.

Motivation: The recognition of translation initiation sites and stop codons is a fundamental part of any gene recognition program. Currently, the most successful methods use powerful classifiers, such as support vector machines with various string kernels. These methods all use two classes, one of positive instances and another one of negative instances that are constructed using sequences from the whole genome.

A scalable memetic algorithm for simultaneous instance and feature selection.

Instance selection is becoming increasingly relevant due to the huge amount of data that is constantly produced in many fields of research. At the same time, most of the recent pattern recognition problems involve highly complex datasets with a large number of possible explanatory variables. For many reasons, this abundance of variables significantly harms classification or recognition tasks.

OligoIS: Scalable Instance Selection for Class-Imbalanced Data Sets.

In current research, an enormous amount of information is constantly being produced, which poses a challenge for data mining algorithms. Many of the problems in extremely active research areas, such as bioinformatics, security and intrusion detection, or text mining, share the following two features: large data sets and class-imbalanced distribution of samples. Although many methods have been proposed for dealing with class-imbalanced data sets, most of these methods are not scalable to the very large data sets common to those research fields.

Nephrogenic systemic fibrosis: incidence, associations, and effect of risk factor assessment--report of 33 cases.

Purpose: To describe the presentation and clinical course of patients with nephrogenic systemic fibrosis (NSF) at a large acute-care hospital, to evaluate the overall incidence of NSF, and to assess the effect of a hospital-wide policy regarding gadolinium-based contrast agent (GBCA) use on NSF incidence.

Materials And Methods: A review of all cases of NSF observed at an institution from 2003 to 2008 was conducted. This HIPAA-compliant study was approved by the institutional review board.

Human kinetics of orally and intravenously administered low-dose 1,2-(13)C-dichloroacetate.

Dichloroacetate (DCA) is a putative environmental hazard, owing to its ubiquitous presence in the biosphere and its association with animal and human toxicity. We sought to determine the kinetics of environmentally relevant concentrations of 1,2-(13)C-DCA administered to healthy adults. Subjects received an oral or intravenous dose of 2.