A very early estimation of software development time and effort using neural networks

In spite of years of research and development, formal structured estimation of time and effort required to develop a Management Information System (MIS) is still an open problem. Usual estimation techniques applied by now are supported by the not so realistic premise of requirements stability, and often human experts are required to apply them. This paper considers models of estimation based on metrics available on early design phase. Our research work aims to develop formal estimation models for time and effort needed for MIS development. These models use development team efficiency, requirements volatility, development speed and system complexity as input parameters. We also identify which input metrics are adequate for measuring system’s cognitive complexity and found that useful metrics can be obtained automatically from the system users´ data views very early on the life cycle with independence of the technology used and without human intervention. We tested the metrics estimation capability using Artificial Neural Networks (ANN), and thus confirmed an existing functional relation among input and output metrics (time and effort). Once trained, the ANN predicts effort needed with a 15% average error and time needed with a 30% average error.Eje: I - Workshop de Ingeniería de Software y Base de DatosRed de Universidades con Carreras en Informática (RedUNCI

A very early estimation of software development time and effort using neural networks

In spite of years of research and development, formal structured estimation of time and effort required to develop a Management Information System (MIS) is still an open problem. Usual estimation techniques applied by now are supported by the not so realistic premise of requirements stability, and often human experts are required to apply them. This paper considers models of estimation based on metrics available on early design phase. Our research work aims to develop formal estimation models for time and effort needed for MIS development. These models use development team efficiency, requirements volatility, development speed and system complexity as input parameters. We also identify which input metrics are adequate for measuring system’s cognitive complexity and found that useful metrics can be obtained automatically from the system users´ data views very early on the life cycle with independence of the technology used and without human intervention. We tested the metrics estimation capability using Artificial Neural Networks (ANN), and thus confirmed an existing functional relation among input and output metrics (time and effort). Once trained, the ANN predicts effort needed with a 15% average error and time needed with a 30% average error.Eje: I - Workshop de Ingeniería de Software y Base de DatosRed de Universidades con Carreras en Informática (RedUNCI

Methodological considerations in the analysis of fecal glucocorticoid metabolites in tufted capuchins (Cebus apella)

Analysis of fecal glucocorticoid (GC) metabolites has recently become the standard method to monitor adrenocortical activity in primates noninvasively. However, given variation in the production, metabolism, and excretion of GCs across species and even between sexes, there are no standard methods that are universally applicable. In particular, it is important to validate assays intended to measure GC production, test extraction and storage procedures, and consider the time course of GC metabolite excretion relative to the production and circulation of the native hormones. This study examines these four methodological aspects of fecal GC metabolite analysis in tufted capuchins (Cebus apella). Specifically, we conducted an adrenocorticotrophic hormone (ACTH) challenge on one male and one female capuchin to test the validity of four GC enzyme immunoassays (EIAs) and document the time course characterizing GC me- tabolite excretion in this species. In addition, we compare a common field-friendly technique for extracting fecal GC metabolites to an established laboratory extraction methodology and test for effects of storing “field extracts” for up to 1 yr. Results suggest that a corticosterone EIA is most sensitive to changes in GC production, provides reliable measures when extracted according to the field method, and measures GC metabolites which remain highly stable after even 12 mo of storage. Further, the time course of GC metabolite excretion is shorter than that described yet for any primate taxa. These results provide guidelines for studies of GCs in tufted capuchins, and underscore the importance of validating methods for fecal hormone analysis for each species of interest

Stable carbon and nitrogen isotope enrichment in primate tissues

Isotopic studies of wild primates have used a wide range of tissues to infer diet and model the foraging ecologies of extinct species. The use of mismatched tissues for such comparisons can be problematic because differences in amino acid compositions can lead to small isotopic differences between tissues. Additionally, physiological and dietary differences among primate species could lead to variable offsets between apatite carbonate and collagen. To improve our understanding of the isotopic chemistry of primates, we explored the apparent enrichment (ε*) between bone collagen and muscle, collagen and fur or hair keratin, muscle and keratin, and collagen and bone carbonate across the primate order. We found that the mean ε* values of proteinaceous tissues were small (≤1‰), and uncorrelated with body size or phylogenetic relatedness. Additionally, ε* values did not vary by habitat, sex, age, or manner of death. The mean ε* value between bone carbonate and collagen (5.6 ± 1.2‰) was consistent with values reported for omnivorous mammals consuming monoisotopic diets. These primate-specific apparent enrichment values will be a valuable tool for cross-species comparisons. Additionally, they will facilitate dietary comparisons between living and fossil primates

The Household Water Insecurity Experiences (HWISE) Scale: comparison scores from 27 sites in 22 countries

Abstract Household survey data from 27 sites in 22 countries were collected in 2017–2018 in order to construct and validate a cross-cultural household-level water insecurity scale. The resultant Household Water Insecurity Experiences (HWISE) scale presents a useful tool for monitoring and evaluating water interventions as a complement to traditional metrics used by the development community. It can also help track progress toward achievement of Sustainable Development Goal 6 ‘clean water and sanitation for all’. We present HWISE scale scores from 27 sites as comparative data for future studies using the HWISE scale in low- and middle-income contexts. Site-level mean scores for HWISE-12 (scored 0–36) ranged from 1.64 (SD 4.22) in Pune, India, to 20.90 (7.50) in Cartagena, Colombia, while site-level mean scores for HWISE-4 (scored 0–12) ranged from 0.51 (1.50) in Pune, India, to 8.21 (2.55) in Punjab, Pakistan. Scores tended to be higher in the dry season as expected. Data from this first implementation of the HWISE scale demonstrate the diversity of water insecurity within and across communities and can help to situate findings from future applications of this tool

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

4to. Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad. Memoria académica

Este volumen acoge la memoria académica de la Cuarta edición del Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad, CITIS 2017, desarrollado entre el 29 de noviembre y el 1 de diciembre de 2017 y organizado por la Universidad Politécnica Salesiana (UPS) en su sede de Guayaquil. El Congreso ofreció un espacio para la presentación, difusión e intercambio de importantes investigaciones nacionales e internacionales ante la comunidad universitaria que se dio cita en el encuentro. El uso de herramientas tecnológicas para la gestión de los trabajos de investigación como la plataforma Open Conference Systems y la web de presentación del Congreso http://citis.blog.ups.edu.ec/, hicieron de CITIS 2017 un verdadero referente entre los congresos que se desarrollaron en el país. La preocupación de nuestra Universidad, de presentar espacios que ayuden a generar nuevos y mejores cambios en la dimensión humana y social de nuestro entorno, hace que se persiga en cada edición del evento la presentación de trabajos con calidad creciente en cuanto a su producción científica. Quienes estuvimos al frente de la organización, dejamos plasmado en estas memorias académicas el intenso y prolífico trabajo de los días de realización del Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad al alcance de todos y todas