Abstract
Wildlife conservation on private land is an important approach that is increasingly utilized to protect biodiversity and can help contribute to the 30 by 30 target of the Global Biodiversity ...Framework. In 2018, a Chilean non-profit conservation organization launched a land conservation programme aiming to build long-term partnerships with private landowners to protect critical habitat for threatened amphibians in Chilean Patagonia. Here we describe a new locality record of the micro-endemic, Endangered Barrio's frog
Insuetophrynus acarpicus
found at a site that joined the programme in 2020. Barrio's frog is ranked 11th in the list of Evolutionarily Distinct and Globally Endangered amphibians. Our systematic literature search showed that most aspects of the natural history and ecology of this species are unknown, limiting our ability to provide actionable science to inform its conservation. The newly described Barrio's frog population is the eighth known locality of this species and one of only three occurring within a protected area. Habitat quality assessments indicated optimal conditions for most of the measured habitat parameters in the high-gradient stream where the species occurs. This case study illustrates that long-term partnerships between private landowners and conservationists can be used as an effective tool to protect the habitat of highly threatened amphibians.
The new era of information and the needs of our society require continuous change in software and technology. Changes are produced very quickly and software systems require evolving at the same ...velocity, which implies that the decision-making process of software architectures should be (semi-)automated to satisfy changing needs and to avoid wrong decisions. This issue is critical since suboptimal architecture design decisions may lead to high cost and poor software quality. Therefore, systematic and (semi-)automated mechanisms that help software architects during the decision-making process are required. Architectural patterns are one of the most important features of software applications, but the same pattern can be implemented in different ways, leaving to results of different quality. When an application requires to evolve, knowledge extracted from similar applications is useful for driving decisions, since quality pattern implementations can be reproduced in similar applications to improve specific quality attributes. Therefore, clustering methods are especially suitable for classifying similar pattern implementations. In this paper, we apply a novel unsupervised clustering technique, based on the well-known artificial neural network model Self-Organizing Maps, to classify Model-View-Controller (MVC) pattern from a quality point of view. Software quality is analyzed by 24 metrics organized into the categories of Count/Size, Maintainability, Duplications, Complexity, and Design Quality. The main goal of this work is twofold: to identify the quality features that establish the similarity of MVC applications without software architect bias, and to classify MVC applications by means of Self-Organizing Maps based on quality metrics. To that end, this work performs an exploratory study by conducting two analyses with a dataset of 87 Java MVC applications characterized by the 24 metrics and two attributes that describe the technology dimension of the application. The stated findings provide a knowledge base that can help in the decision-making process for the architecture of Java MVC applications.
The COVID-19 pandemic circumstances have varied the pathogens related to acute respiratory infections (ARI), and most specialists have ignored them due to SARS-CoV-2's similar symptomatology. We ...identify respiratory pathogens with multiplex PCR in samples with presumptive SARS-CoV-2 but negative RT-qPCR results. We performed a retrospective transversal study employing clinical data and nasopharyngeal swab samples from patients with suspected clinical SARS-CoV-2 infection and a negative PCR result in a private laboratory in Lima, Peru. The samples were analyzed using the FilmArray respiratory panel. Of 342 samples, we detected at least one pathogen in 50% of the samples. The main ones were rhinovirus (54.38%), influenza A(H3N2) (22.80%), and respiratory syncytial virus (RSV) (14.04%). The clinical characteristics were sore throat (70.18%), cough (58.48%), nasal congestion (56.43%), and fever (40.06%). Only 41.46% and 48.78% of patients with influenza met the definition of influenza-like illness (ILI) by theWorld Health Organization (WHO) (characterized by cough and fever) and the Centers for Disease Control and Prevention (CDC) (characterized by fever and cough and sore throat), respectively. A higher prevalence of influenza was associated with ILI by WHO (aPR: 2.331) and ILI by CDC (aPR: 1.892), which was not observed with other respiratory viruses. The clinical characteristic associated with the increased prevalence of rhinovirus was nasal congestion (aPR: 1.84). For patients with ARI and negative PCR results, the leading respiratory pathogens detected were rhinovirus, influenza, and RSV. Less than half of patients with influenza presented ILI, although its presence was specific to the disease.
An accurate analysis of user behaviour in online learning environments is a useful means of early follow up of students, so that they can be better supported to improve their performance and achieve ...the expected competences. However, that task becomes challenging due to the massive data that learning management systems store and categories. With the COVID-19 pandemic still on-going, face-to-face learning settings have migrate into online and blended ones, meaning an increase of online students and teachers in need for a tailored and effective support to their needs. A novel unsupervised clustering technique based on the Self-Organizing Map (SOM) artificial neural network model is used in this research to analyse 1,709,189 records of online students enrolled from 2015 to 2019 at Universidad Internacional de La Rioja (UNIR), a fully online Higher Education institution. SOM performs a precise and diverse user clustering based on those records. Results highlight that specific clusters are linked to the intake average profile at the university, with a clear relation between user interaction and a higher performance. Further, results show that, out of a targeted desk research compared to the analysis in this paper, face-to-face and online settings are connected through the methodological approach beyond the technology-based environment, which presents a similar behaviour in both contexts.
Human Immunodeficiency Virus type 1 (HIV-1) because of high mutation rates, large population sizes, and rapid replication, exhibits complex evolutionary strategies. For the analysis of evolutionary ...processes, the graphical representation of fitness landscapes provides a significant advantage. The experimental determination of viral fitness remains, in general, difficult and consequently most published fitness landscapes have been artificial, theoretical or estimated. Self-Organizing Maps (SOM) are a class of Artificial Neural Network (ANN) for the generation of topological ordered maps. Here, three-dimensional (3D) data driven fitness landscapes, derived from a collection of sequences from HIV-1 viruses after "in vitro" passages and labelled with the corresponding experimental fitness values, were created by SOM. These maps were used for the visualization and study of the evolutionary process of HIV-1 "in vitro" fitness recovery, by directly relating fitness values with viral sequences. In addition to the representation of the sequence space search carried out by the viruses, these landscapes could also be applied for the analysis of related variants like members of viral quasiespecies. SOM maps permit the visualization of the complex evolutionary pathways in HIV-1 fitness recovery. SOM fitness landscapes have an enormous potential for the study of evolution in related viruses of "in vitro" works or from "in vivo" clinical studies with human, animal or plant viral infections.
RNA viruses replicate as complex mutant spectra termed viral quasispecies. The frequency of each individual genome in a mutant spectrum depends on its rate of generation and its relative fitness in ...the replicating population ensemble. The advent of deep sequencing methodologies allows for the first-time quantification of haplotype abundances within mutant spectra. There is no information on the haplotype profile of the resident genomes and how the landscape evolves when a virus replicates in a controlled cell culture environment. Here, we report the construction of intramutant spectrum haplotype landscapes of three amplicons of the NS5A-NS5B coding region of hepatitis C virus (HCV). Two-dimensional (2D) neural networks were constructed for 44 related HCV populations derived from a common clonal ancestor that was passaged up to 210 times in human hepatoma Huh-7.5 cells in the absence of external selective pressures. The haplotype profiles consisted of an extended dense basal platform, from which a lower number of protruding higher peaks emerged. As HCV increased its adaptation to the cells, the number of haplotype peaks within each mutant spectrum expanded, and their distribution shifted in the 2D network. The results show that extensive HCV replication in a monotonous cell culture environment does not limit HCV exploration of sequence space through haplotype peak movements. The landscapes reflect dynamic variation in the intramutant spectrum haplotype profile and may serve as a reference to interpret the modifications produced by external selective pressures or to compare with the landscapes of mutant spectra in complex
environments.
The study provides for the first time the haplotype profile and its variation in the course of virus adaptation to a cell culture environment in the absence of external selective constraints. The deep sequencing-based self-organized maps document a two-layer haplotype distribution with an ample basal platform and a lower number of protruding peaks. The results suggest an inferred intramutant spectrum fitness landscape structure that offers potential benefits for virus resilience to mutational inputs.
Advanced microscopy techniques currently allow scientists to visualize biomolecules at high resolution. Among them, atomic force microscopy (AFM) shows the advantage of imaging molecules in their ...native state, without requiring any staining or coating of the sample. Biopolymers, including proteins and structured nucleic acids, are flexible molecules that can fold into alternative conformations for any given monomer sequence, as exemplified by the different three-dimensional structures adopted by RNA in solution. Therefore, the manual analysis of images visualized by AFM and other microscopy techniques becomes very laborious and time-consuming (and may also be inadvertently biased) when large populations of biomolecules are studied. Here we present a novel morphology clustering software, based on particle isolation and artificial neural networks, which allows the automatic image analysis and classification of biomolecules that can show alternative conformations. It has been tested with a set of AFM images of RNA molecules (a 574 nucleotides-long functinal region of the hepatitis C virus genome that contains its internal ribosome entry site element) structured in folding buffers containing 0, 2, 4, 6 or 10 mM Mg 2+ . The developed software shows a broad applicability in the microscopy-based analysis of biopolymers and other complex biomolecules.
We report for the first time the occurrence in Uruguay of three species of
Anastrepha
, which belong to the
curvicauda
species group. Specimens of
Anastrepha australis
(Blanchard, 1959),
Anastrepha ...littoralis
(Blanchard, 1959), and
Anastrepha nigra
(Blanchard, 1959) were collected with McPhail traps baited with PBX
®
yeast/borax placed in fruit orchards. These records represent the most southern distribution known for
A. littoralis
and
A. nigra
, in addition to the first host plant records for
A. nigra
, which were reared from larvae on fruits of
Araujia hortorum
E. Fourn. (Apocynaceae).
Emotional Education is more and more present every day in schools and universities. Medicine and Nursing students are maybe the most required to have emotional skills both in the university field and ...later on in the professional field. The aim of our study was to work with Nursing students carrying out practical exercises to train and provide the development of socioemotional skills. At a methodological level, an intervention study with pre-post evaluation was carried out. It was conducted in four practical workshops where they learnt different techniques for the development of the above mentioned socioemotional skills. TMMS-24 was applied to 108 first year Nursing students of Universidad Católica of Murcia. Results showed a statistically significant improvement on Emotional Attention after the intervention. As a conclusion we highlight the positive results obtained after the practical workshops, both shown by final data as per expressed by the students. We find necessary an ongoing Emotional Education which takes account of intercultural diversity to improve the results even more.
The creation of fitness maps from viral populations especially in the case of RNA viruses, with high mutation rates producing quasispecies, is complex since the mutant spectrum is in a very ...high-dimensional space. In this work, a new approach is presented using a class of neural networks, Self-Organized Maps (SOM), to represent realistic fitness landscapes in two RNA viruses: Human Immunodeficiency Virus type 1 (HIV-1) and Hepatitis C Virus (HCV). This methodology has proven to be very effective in the classification of viral quasispecies, using as criterium the mutant sequences in the population. With HIV-1, the fitness landscapes are constructed by representing the experimentally determined fitness on the sequence map. This approach permitted the depiction of the evolutionary paths of the variants subjected to processes of fitness loss and gain in cell culture. In the case of HCV, the efficiency was measured as a function of the frequency of each haplotype in the population by ultra-deep sequencing. The fitness landscapes obtained provided information on the efficiency of each variant in the quasispecies environment, that is, in relation to the entire spectrum of mutants. With the SOM maps, it is possible to determine the evolutionary dynamics of the different haplotypes.
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