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Ambient intelligence (AmI) focuses on supporting people by designing sensitive and responsive environments to context through implicit and explicit interactions. Explicit interactions in AmI systems have requirements specific to making interactions robust, smooth, intuitive, and reliable. Based on requirements, the designers can detect and eliminate faults from the beginning of the design process and understand the users’ needs and demands. This work presents a UIPatternM model for predicting interaction design patterns from processing text-based requirements through machine learning algorithms. We evaluate the predictions of our proposal. We also present a case study with professional designers who evaluated the UIPatternM recommender predictions according to a set of design-level requirements that emulate everyday needs. Our participants performed a set of tasks based on scenarios, and we evaluated the participants’ using effectiveness, efficiency, and satisfaction as performance metrics. Applying the UIPatternM model helped to endorse the conception and refinement of user interface design for explicit interaction in AmI systems.

Software Engineering is a discipline that encompasses processes associated with the development of interactive systems. The perceived quality of an interactive system is heavily influenced by the user interface design, which may result in many challenges. One such challenge is design-level requirements analysis. The success of the software system is mostly dependent on how well users’ requirements have been understood and translated into appropriate functionalities. During the interactive system design process, it is common to find recurring problems in human–computer interactions, for which reusing solutions is highly feasible. Interaction design patterns seek to support designers in decision making during the design of interactive systems. Due to the design task tends to be subjective and prone to errors. This work aims at presenting and evaluating an interaction design patterns recommendation model based on design-level requirements classification, through the application of supervised machine learning algorithms. To compare the performance of four classification algorithms, a study was carried out, in which the linear support vector machine was the most suitable to this problem. The results of this work can be used for implementing frameworks that can better support designers’ decision making when designing user interfaces.

This work shows the learning results obtained from the use of a technique proposed and applied by the authors called Literature Based Modeling Learning. This technique consists of the development of modeling tasks where the input is a text that represents a literature piece and the output is a set of diagrams that model that LP. The literature piece is typically a well-known short story but it can also be the lyrics of a song or hymn or even a prayer. This technique has been used during the last eight semesters at a Mexican university. A results of a study are presented to identify possible benefits with the use of this technique.

Recent advances in computational and electronic technologies, and the application of artificial intelligence algorithms could make it possible to automate the patient monitoring process in order to improve their care and safety. Patient monitoring involves three main procedures: data gathering, data analysis, and feedback generation. On the other hand, artificial intelligence is a computer science field that makes use of mathematical, statistical, and probabilistic techniques in order to classify, learn, plan, or deduce information. This chapter describes the patient monitoring process and presents current research about how artificial intelligence techniques and computational technologies are able to produce care providers or the same patient with information that could be useful for the patient’s health care.

Ambient intelligence is one of the most exciting fields of application for pervasive, wireless, and embedded computing. However, the design and implementation of real-world systems must be conducted utilizing software engineering approaches. Some types of environments (hospitals, older adults homes, emergency scenarios, etc.) are particularly critical, especially in terms of the issues concerning expressing requirements, verifying and validating them, or ensuring functional correctness. To provide adequate ambient intelligence solutions, it is necessary to place special emphasis on obtaining, specifying, and documenting software requirements. To address this issue, our paper presents a model that integrates both requirements and design patterns. This is done through a natural language processing application in conjunction with other artificial intelligence algorithms. This work aims to support designers when analyzing text requirements and support design decisions. Our results were evaluated according to the cross-validated accuracy of predicting design patterns. The results obtained indicate that this approach could lead to good recommendations of design patterns, as it demonstrated an acceptable classification performance over the balanced dataset of requirements instances.

Source code metrics have been used as indicators of code comprehension according to its complexity. Shao and Wang proposed a cognitive complexity measure based on the cognitive weight of the basic control structures. This cognitive weight is a fixed value assigned to each control structure, which was calculated by means of a series of empirical experiments. Given the lack of information and incompleteness of the experiments, improvements to these experiments must be made before a measure can be used. In this paper, a study on the overall state of the cognitive weight, including its experiments, is presented, along with an empirical experiment which will help us to assess the validity and accuracy of the cognitive weight. The experiment consists of applying a survey to 114 students. It contains source code complexity and comprehension questions that allow us to obtain conclusions about the validity of the cognitive weight.

Computer programming is one of the basic abilities developed in computing science students, but it is important to note that programs are the product of generating code from software design. This work presents the results of examining the design products of students in different stages of their degree program. We have replicated some experiments reported in the literature but a difference between these works and ours is that we analyze the design work of students at all levels of their degree programs. We find results that indicate that the design abilities do not necessarily show a continuous improvement during the passage of time in their studies and we explore possible causes of this and outline future research in this line of investigation.

Source code metrics extraction is a complex task that has to be done automatically given the current size of software. They are extracted using software metric tools and more generic extraction mechanisms. These mechanisms usually work by querying a source code representation model. These models are static, and the information that can be obtained from them is limited. In this work an extraction methodology is presented in which the model is created every time certain information is needed. This is accomplished by querying the language context-free grammar, and from the information obtained by the query, a dynamic model is created. Current extraction mechanisms work by querying a model, while the proposed methodology queries the grammar directly, thus the model is created afterwards from the query result, and contains all the needed information. A metrics tool is created based on the proposed methodology, and in order to prove the correct functioning of extracting the desired information from the source code, not as already predefined as in current tools, several metrics are extracted as defined by four existing metrics tools. Querying the language grammar allows access to all available data in the source code, regardless of the programming language and paradigm.

In the process of designing user interfaces (UI), designers must be aware of the many factors and different contexts that influence design, which are established in the Software requirements. The objective of this Case study is to analyze the identification of patterns of Human-Computer Interaction (HCI) through the understanding of functional requirements by junior programmers. The above, through the identification of important aspects such as tasks, the type of user, and context of use. Twenty-two students were invited to participate in the Case study and generated eight Software Development projects from which their perception was obtained regarding these activities, which will be considered for the classification of Software requirements.

Software development is a human activity typically performed by individuals or groups working in an organization. For this task to be successful, a variety of human factors must be considered, from individual factors (cognitive capacity or motivation of the developer) to group factors (ease of teamwork or to participate in social interaction) This research focuses on the study of the possible correlation between the personality of the software engineer and their individual specific capacity for software design. The fundamentals of characterization of currently accepted personality features and a comparison of these features in the adult population in Mexico, Canada, United States and Brazil are presented. Finally, the results of an experiment with computer engineering students from a Mexican university are presented, relating these characteristics with their ability to develop software design products.

The agile development of Software in companies is increasing because it allows them to reduce costs when producing products and providing services. To do that, agile methodologies are required in which there is a way to identify, from the beginning of the project, the Software requirements and its complexity to make an estimate of the time required for the development of the project. SCRUM, considered a framework, is among the agile methodologies most adopted by companies. The concept of Software requirement translated into SCRUM as User Stories (US). A crucial part for the success of the project is to estimate in each iteration the complexity and time that US requires to its realization. Obtaining this information from each user story allows the development team to estimate the total time that will be required to finish the project. In practice and since human resources need to be considered to meet the requirements of knowledge, experience and skills demanded by the user story for its achievement, this activity is still time consuming and generates poor estimates. In this work, we propose the use of a new version adapted from the Blooms taxonomy, coupled to the life cycle of the Software Development, seeking agilely to classify the complexity of US and to identify the stage in the life cycle of the Software Development to which it corresponds.

Ethanol alters motricity, learning, cognition, and cellular metabolism in the cerebellum. The combination of ethanol with caffeine by consuming "energy drinks" is becoming increasingly popular among young people. We analyzed the use of ethanol and caffeine on apoptosis in the cerebellum of UChB rats. The adult rats were divided into three groups (n = 14/group): UChB group: rats fed with 1:10 (v/v) ethanol ad libitum (free choice for water or ethanol) drinking from1.9 mL of ethanol/kg body weight/day, Control group and UChB/caffeine group (free choice for water or ethanol + caffeine 300 mg/L). The treatments occurred from Day 100 till Day 150, totalizing 50 days of ethanol/caffeine ingestion. Cerebellar sections were subjected to immunohistochemistry and gene expression for Real Time-PCR (RT-PCR) for Caspase-3, XIAP, and insulin-like growth factor 1-receptor (IGF-1R). The results showed a significant increase in the gene expression of Caspase-3 and XIAP in UChB group. On the other hand, the animals of the UChB/caffeine group showed similar results to the Controls. Regarding IGFR-1, there was greater expression in the UChB groups with strong labeling in Purkinje cells. Ethanol produces neuronal and glial neurodegeneration on the cerebellum of UChB rats. The simultaneous ingestion of ethanol and caffeine reversed the ethanol damages acting caffeine with a neuroprotective effect.

Testosterone is often recommended in the treatment of several aging-related conditions. However, there are still questions about the consequences of this therapy in terms of hormonal and inflammatory parameters that are crucial for prostate homeostasis. Thus, we investigate if the testosterone therapy (TT) modulates the hormone receptors and inflammatory cytokines in the ventral prostate of adult rats. Wistar rats aging 150 days were divided into two experimental groups (n = 10/group): T: received subcutaneous injections of testosterone cypionate (5 mg/kg body weight) diluted in corn oil every other day for 4 weeks; and C: received corn oil as vehicle. Animals were euthanized at 180 days old by decapitation. Blood was collected to obtain hormone and cytokines concentrations. The ventral prostate was dissected and processed for light microscope and molecular analyses. Relative ventral prostate weight and epithelial compartment were increased after TT. The number of intact and degranulated mast cells was reduced in the T group. Plasma testosterone, DHT and intraprostatic testosterone concentrations were higher in the T group. TT leads to an increase in cell proliferation and up-regulation of AR, ERβ, PAR-4, and NRF2. Importantly, plasma concentration and tissue expression of IL-10 and TNF-α were higher after TT. In summary, these results indicate that TT can regulate inflammatory response, with impacts in cytokines and mast cell population, and modulates steroids receptors, important parameters for prostatic homeostasis.

BACKGROUND: Preterm newborns have higher thoracic compliance, providing less stability to the different forces of distortion imposed on the rib cage, leading to instability of the chest. Adequate body position may reduce this instability and facilitate respiratory work. OBJECTIVE: To assess the oxygen saturation response of preterm newborns receiving rib cage stabilization with an elastic band in two body positions. METHOD: A clinical, prospective, randomized crossover study was conducted, including sixteen newborns with a gestational age of 31 to 35 weeks (mean 32.8 weeks) at a tertiary care facility, who did not receive supplemental oxygen. The infants were placed in a sequence of prone and supine positions with and without chest stabilization with an elastic band. Respiratory rate, heart rate, and oxygen saturation were measured at 10-minute intervals, corresponding to 7 samplings of 60 minutes. Data collection was interrupted when oxygen saturation was less than 90%. RESULTS: The mean gestational age of the infants was 32.8±1.5 weeks and the mean birth weight was 1,789±255g. Better values for the variables studied were observed in the supine position with an elastic chest band compared to the supine position without the band. The positions using an elastic band resulted in lower mean respiratory rate and heart rate and higher oxygen saturation. CONCLUSION: The use of an elastic chest band improves respiratory indicators such as oxygen saturation. CONTEXTUALIZAÇÃO: Os recém-nascidos pré-termos possuem maior complacência torácica, oferecendo menor estabilidade às diferentes forças de distorção impostas à parede torácica, o que leva à instabilidade da caixa torácica. A posição corporal adequada pode diminuir essa instabilidade, facilitando o trabalho respiratório. OBJETIVO: Verificar a resposta da saturação de oxigênio em recém-nascido pré-termo com estabilização do gradil costal com faixa elástica em dois posicionamentos corporais. MÉTODO: Estudo com delineamento de ensaio clínico prospectivo, randomizado e tipo crossover. Foram avaliados 16 recém-nascidos com idade gestacional de 31 a 35 semanas (média 32,8 semanas) e sem oxigênio suplementar, em instituição de nível terciário. O grupo foi submetido à sequência de decúbitos posturais ventral e dorsal, alterando-os com e sem estabilização do tórax por meio da faixa elástica. Os indicadores biológicos colhidos foram frequência respiratória, frequência cardíaca e saturação de oxigênio. Os dados foram coletados de 10 em 10 minutos, totalizando 60 minutos com sete coletas. O critério de interrupção da coleta se deu pela saturação menor que 90%. RESULTADOS: O grupo estudado apresentou média de idade gestacional de 32,8±1,5 semanas e peso ao nascimento de 1.789±255g. Encontramos melhores valores das variáveis na supinação com faixa quando comparada com supinação sem faixa. Os valores médios menores da frequência respiratória e da frequência cardíaca foram alcançados no decúbito com faixa, já a saturação de oxigênio respondeu com maior valor CONCLUSÃO: O uso da faixa elástica torácica pode favorecer os melhores valores dos indicadores respiratórios, como a saturação de oxigênio.

Software metrics are an essential tool in the software measurement process. As software systems grow, and in consequence their corresponding source code, automated tools for source code metrics extraction, usually known as Software Metric Tools, should be developed in order to aid the user to correctly achieve the process. Even though these tools are of great help, they have certain issues and are limited by the set of accepted metrics and programming languages. This paper propose a new type of metric tool aimed to be user oriented, meaning that the tool provides mechanisms that allow the user to define his own metrics and incorporate new languages. A tool with these characteristics requires more complex methodologies for its construction. In this paper we describe the problematic of current software tools and the construction of a user oriented tool which presents advantages over the current tools.

Human activity inference is not a simple process due to distinct ways of performing it. Our proposal presents the SCAN framework for activity inference. SCAN is divided into three modules: (1) artifact recognition, (2) activity inference, and (3) activity representation, integrating three important elements of Ambient Intelligence (AmI) (artifact-behavior modeling, event interpretation and context extraction). The framework extends the roaming beat (RB) concept by obtaining the representation using three kinds of technologies for activity inference. The RB is based on both analysis and recognition from artifact behavior for activity inference. A practical case is shown in a nursing home where a system affording 91.35% effectiveness was implemented in situ. Three examples are shown using RB representation for activity representation. Framework description, RB description and CALog system overcome distinct problems such as the feasibility to implement AmI systems, and to show the feasibility for accomplishing the challenges related to activity recognition based on artifact recognition. We discuss how the use of RBs might positively impact the problems faced by designers and developers for recovering information in an easier manner and thus they can develop tools focused on the user.

BACKGROUND: Guidelines for red blood cell (RBC) transfusions exist; however, transfusion practices vary among centers. This study aimed to analyze transfusion practices and the impact of patients and institutional characteristics on the indications of RBC transfusions in preterm infants. STUDY DESIGN AND METHODS: RBC transfusion practices were investigated in a multicenter prospective cohort of preterm infants with a birth weight of less than 1500 g born at eight public university neonatal intensive care units of the Brazilian Network on Neonatal Research. Variables associated with any RBC transfusions were analyzed by logistic regression analysis. RESULTS: Of 952 very-low-birth-weight infants, 532 (55.9%) received at least one RBC transfusion. The percentages of transfused neonates were 48.9, 54.5, 56.0, 61.2, 56.3, 47.8, 75.4, and 44.7%, respectively, for Centers 1 through 8. The number of transfusions during the first 28 days of life was higher in Center 4 and 7 than in other centers. After 28 days, the number of transfusions decreased, except for Center 7. Multivariate logistic regression analysis showed higher likelihood of transfusion in infants with late onset sepsis (odds ratio [OR], 2.8; 95% confidence interval [CI], 1.8-4.4), intraventricular hemorrhage (OR, 9.4; 95% CI, 3.3-26.8), intubation at birth (OR, 1.7; 95% CI, 1.0-2.8), need for umbilical catheter (OR, 2.4; 95% CI, 1.3-4.4), days on mechanical ventilation (OR, 1.1; 95% CI, 1.0-1.2), oxygen therapy (OR, 1.1; 95% CI, 1.0-1.1), parenteral nutrition (OR, 1.1; 95% CI, 1.0-1.1), and birth center (p

One of the most basic tasks for any autonomous mobile robot is that of safely navigating from one point to another e.g. service robots should be able to find their way in different kinds of environments. Typically, vision is used to find landmarks in that environment to help the robot localise itself reliably. However, some environments may lack of these landmarks and the robot would need to be able to find its way in a featureless environment. This paper presents a topological vision-based approach for navigating through a featureless maze-like environment using a NAO humanoid robot, where all processing is performed by the robot's embedded computer. We show how our approach allows the robot to reliably navigate in this kind of environment in real-time.

Diversas estrategias han sido identificadas en apoyos tecnológicos para potenciar la adherencia de medicamentos. Sin embargo, cada padecimiento llama a requerimientos diferentes para tener éxito en la adherencia. Este trabajo presenta una propuesta para apoyar la adherencia de medicamentos para pacientes con depresión mayor. Esto a través de un sistema de monitorización y de envío de notificaciones conscientes del contexto a lo largo del tratamiento del paciente. El diseño de las notificaciones fue totalmente asistido por personal profesional en el área médica, la implementación del sistema ha sido concluida y el artículo muestra un sistema de monitorización y presenta datos para una futura evaluación con usuarios reales por un período de más de tres meses.

Chronic ethanol intake leads to reproductive damage including reactive oxygen species formation, which accelerates the oxidative process. Melatonin is known to regulate the reproductive cycle, food/liquid intake, and it may also act as a potent antioxidant indoleamine. The aim of this study was to verify the effects of alcoholism and melatonin treatment on overall feed efficiency and to analyze its protective role against the oxidative stress in the ovarian tissue of UChB rats (submitted to 10% [v/v] voluntary ethanol consumption).Forty adult female rats (n = 10/group) were finally selected for this study: UChB Co: drinking water only; and UChB EtOH: drinking ethanol at 2 to 6 ml/100 g/d + water, both receiving 0.9% NaCl + 95% ethanol 0.04 ml as vehicle. Concomitantly, UChB Co + M and UChB EtOH + M groups were infused with vehicle + melatonin (100 μg/100 g body weight/d) intraperitoneally over 60 days. All animals were euthanized by decapitation during the morning estrus (4 am).Body weight gain was reduced with ethanol plus melatonin after 40 days of treatment. In both melatonin-treated groups, it was observed a reduction in food-derived calories and liquid intake toward the end of treatment. The amount of consumed ethanol dropped during the treatment. Estrous cycle was longer in rats that received both ethanol and melatonin, with prolonged diestrus. Following to oxidative status, lipid hydroperoxide levels were higher in the ovaries of ethanol-preferring rats and decreased after melatonin treatment. Additionally, antioxidant activities of superoxide dismutase, glutathione peroxidase activity, and glutathione reductase activity were increased in melatonin-treated groups.We suggest that melatonin is able to affect feed efficiency and, conversely, it protects the ovaries against the oxidative stress arising from ethanol consumption.

Automatic estimation of human activities is a topic widely studied. However the process becomes difficult when we want to estimate activities from a video stream, because human activities are dynamic and complex. Furthermore, we have to take into account the amount of information that images provide, since it makes the modelling and estimation activities a hard work. In this paper we propose a method for activity estimation based on object behavior. Objects are located in a delimited observation area and their handling is recorded with a video camera. Activity estimation can be done automatically by analyzing the video sequences. The proposed method is called "signature recognition" because it considers a space-time signature of the behaviour of objects that are used in particular activities (e.g. patients' care in a healthcare environment for elder people with restricted mobility). A pulse is produced when an object appears in or disappears of the observation area. This means there is a change from zero to one or vice versa. These changes are produced by the identification of the objects with a bank of nonlinear correlation filters. Each object is processed independently and produces its own pulses; hence we are able to recognize several objects with different patterns at the same time. The method is applied to estimate three healthcare-related activities of elder people with restricted mobility.

This paper describes an approach to estimate the activity being performed by caregivers in a nursing home. The approach is based on information gathered from a workplace study conducted in a nursing home, in which 400 hours of detailed observation caregivers' activities were recorded. Automatic identification of objects based in composite correlation filters was implemented in order to generate a descriptive behavior of objects. When the behavior of the artifacts related with the activities is validated, the estimation of an activity is found. The activities estimated with a 92.72% of accuracy (on average) include hygiene, feeding and taking vital signs.

La calidad de los programas de software (SW) es considerada cuando éstos se realizan bajo estrictas metodologías y siguiendo estándares que intentan reducir la probabilidad de presentar defectos. La obtención de métricas de SW es un método útil para minimizar dicha probabilidad. Para evaluar la calidad de un programa de SW, uno de los indicadores más importantes es la mantenibilidad, la cual se puede medir mediante la obtención de un conjunto de métricas. La mantenibilidad es la facilidad con la que un sistema de SW puede ser modificado y es un atributo que afecta de manera crucial al costo de desarrollo del mismo. La literatura muestra estudios sobre mantenibilidad y la alteración de este parámetro cuando los programas evolucionan. Este trabajo muestra los resultados de analizar 315 programas realizados por estudiantes universitarios de carreras en Ingeniería en Computación e Informática y la evolución que la mantenibilidad y otras métricas básicas presentan en función del progreso en la formación académica de sus autores.

OBJECTIVE: Considering the rarity and the significance of early diagnosis for planning appropriate treatment, a case of congenital tuberculosis is reported.CASE REPORT: After a prolonged stay in the Neonatal Intensive Care Unit (NICU) of a male pre-term infant without improvement, the diagnosis of tuberculosis was suspected when his mother underwent thoracotomy for valve replacement due to a subacute endocarditis. At this time, multiple pleural granulomas were detected and the diagnosis of tuberculosis was confirmed by histology. His mother seldom went to the NICU to see the baby and she was rarely very close to him in these occasions. After tuberculosis therapy, the baby gradually improved. CONCLUSION: Among the possible ways of transmission, the reported case was probably transmitted by aspiration of contaminated amniotic fluid in utero or at the time of delivery.

The present study evaluates the relationships of pulmonary volumes and flows and the anthropometric variables of standing height, sitting height, and arm span in 100 6-10-year-old children. To be included in the study, all children were required to be healthy and above the 3rd percentile of the curve of Tanner et al. (Arch Dis Child 1966;41:454-471; Arch Dis Child 1966;41:613-635) for height and weight. Standing height, sitting height, and arm span were measured according to standard protocol. The pulmonary function measurements were: tidal volume, minute respiratory volume, respiratory rate, expiratory reserve volume, inspiratory capacity, vital capacity, residual volume (RV), functional residual capacity, total lung capacity (TLC), forced vital capacity (FVC), forced expiratory volume in 1 sec of FVC (FEV(1)), forced expiratory flow measured between 25-75% of FVC, and FEV(1)/FVC and RV/TLC ratios. Simple linear regression best expressed the correlation between pulmonary function and the anthropometric variables. Significant correlations between anthropometric and pulmonary function measurements were observed, with FVC and FEV(1) showing the highest and RV the lowest r(2) values. There was a significant positive correlation between standing height and arm span according to linear regression and Bland-Altman comparison (Bland and Altman, Lancet 1968;8:307-310). Our results suggest that when an accurate determination of standing height cannot be obtained, arm span could be used interchangeably, using the same regression equation. However, for patients with limb deformities, regression equations of pulmonary function measurements in relation to sitting height may be a better choice for estimating pulmonary function.