Evaluation of alternatives for the broadcast operation in Kademlia under churn

During recent years, considerable effort has been devoted to the enhancement of Distributed Hash Table (DHT) systems with broadcasting capabilities. Such systems typically provide individual node routing but a broadcast primitive is required for functionalities such as information dissemination or data aggregation. Broadcasting can also be used as the basis for partial keyword searches. Little work has however specifically addressed Kademlia, a well known DHT, used in real applications. Our work exposes the particularities of this system, notably its XOR-based distance metrics, and analytically studies what broadcasting techniques can be applied to it. A model that estimates node coverage as a function of the probability that individual messages reach their destination has been also developed. For validation, several broadcasting algorithms have been implemented and comprehensively evaluated, considering node coverage, messages to nodes ratio, latency and imbalance factor. Moreover, several techniques are proposed to enhance the bare protocols when adverse circumstances such as churn and failure rate conditions are present. These include redundancy, resubmissions or flooding, and also combinations of those. All have been implemented and fully tested. An analysis of the strengths and weaknesses of algorithms and additional techniques, and a discussion on the choices and compromises to make, depending on system characteristics or application priorities, is finally presented.     

Stability and mechanical evaluation of bovine pericardium cross-linked with polyurethane prepolymer in aqueous medium

The present study investigates the potential use of non-catalyzed water-soluble blocked polyurethane prepolymer (PUP) as a bifunctional cross-linker for collagenous scaffolds. The effect of concentration (5, 10, 15 and 20%), time (4, 6, 12 and 24 h), medium volume (50, 100, 200 and 300%) and pH (7.4, 8.2, 9 and 10) over stability, microstructure and tensile mechanical behavior of acellular pericardial matrix was studied. The cross-linking index increased up to 81% while the denaturation temperature increased up to 12 °C after PUP crosslinking. PUP-treated scaffold resisted the collagenase degradation (0.167 ± 0.14 mmol/g of liberated amine groups vs. 598 ± 60 mmol/g for non-cross-linked matrix). The collagen fiber network was coated with PUP while viscoelastic properties were altered after cross-linking. The treatment of the pericardial scaffold with PUP allows (i) different densities of cross-linking depending of the process parameters and (ii) tensile properties similar to glutaraldehyde method.     

Augmented reality annotations to assist persons with Alzheimers and their caregivers

Persons with Alzheimer’s disease (AD) and their caregivers implement diverse strategies to cope with memory loss. A common strategy involves placing tags on drawers or removing cabinet doors to make their contents visible. This study describes the Ambient aNnotation System (ANS), aimed at assisting people suffering from AD and their caregivers with this task. The system has two main modules: The tagging subsystem allows caregivers to create and manage ambient annotations in order to assist people with memory problems. The second subsystem allows people with AD to use a mobile phone to recognize tags in the environment and to receive relevant information in the form of audio, text, or images. The identification of these tags is performed in real time by uploading images from the mobile phone to a server, which uses the SURF algorithm for object recognition. We describe the design and implementation of the system as well as results of the evaluation of its performance and efficiency. ANS can process query images approximately every 2 s and is able to locate users in their homes with a precision of 0.93. A usability study conducted with six subjects determined that audio notifications are more effective than vibrating notifications to alert the user about tags in the environment.     

RF Power Amplifier Behavioral Modeling Based on Takenaka–Malmquist–Volterra Series

In this paper, a Takenaka–Malmquist–Volterra (TMV) model structure is employed to improve the approximations in the low-pass equivalent behavioral modeling of radio frequency (RF) power amplifiers (PAs). The Takenaka–Malmquist basis generalizes the orthonormal basis functions previously used in this context. In addition, it allows each nonlinearity order in the expanded Volterra model to be parameterized by multiple complex poles (dynamics). The state-space realizations for the TMV models are introduced. The pole sets for the TMV model and also for the previous Laguerre–Volterra (LV) and Kautz–Volterra (KV) models are obtained using a constrained nonlinear optimization approach. Based on experimental data measured on a GaN HEMT class AB RF PA excited by a WCDMA signal, it is observed that the TMV model reduces the normalized mean-square error and the adjacent channel error power ratio for the upper adjacent channel (upper ACEPR) by 1.6 dB when it is compared to the previous LV and KV models under the same computational complexity.     

Forecasting Financial Failure of Firms via Genetic Algorithms

Given a wide amount of possible ratios available for constructing a LOGIT model for forecasting bankruptcy, this paper provides a computational search methodology, only guided by data, for selecting the financial ratios employed in the model. This procedure is based on genetic algorithms which are used to explore the universe of models made available by all possible existing financial ratios (with very redundant information). This search process of the correct model is guided by the Schwarz information criterion. As an empirical illustration, the methodology is applied to forecasting the failure of firms in the Spanish building industry using annual public accounting information.     

Characterization of Salmonella Enteritidis isolated from human samples

This study aimed to characterize Salmonella Enteritidis (SE) isolated from blood (n = 12) and feces (n = 68) of salmonellosis victims in Southern Brazil. All isolates were submitted to antimicrobial susceptibility testing, PCR-ribotyping, and XbaI macrorestriction Pulsed-Field Gel Eletrophoresis (PFGE). Results demonstrated high levels of ampicillin and nalidixic acid resistance, and strains isolated in different geographic regions were clustered together, presenting a common resistance profile. All strains demonstrated similar and related PCR-ribotyping patterns (R1, R2, and R3); being that the predominant profile R1 grouped 47.5% of the strains. PFGE profile P1 grouped the majority of the strains (96.25%), suggesting a clonal relationship among the strains or inability of molecular typing methods to discriminate strains of this serovar. Results suggested on an increase in antimicrobial resistance and that strains of S. Enteritidis with similar PFGE and PCR-ribotyping profiles were involved in several salmonellosis outbreaks in Southern Brazil.     

Case-base maintenance with multi-objective evolutionary algorithms

Case-Base Reasoning is a problem-solving methodology that uses old solved problems, called cases, to solve new problems. The case-base is the knowledge source where the cases are stored, and the amount of stored cases is critical to the problem-solving ability of the Case-Base Reasoning system. However, when the case-base has many cases, then performance problems arise due to the time needed to find those similar cases to the input problem. At this point, Case-Base Maintenance algorithms can be used to reduce the number of cases and maintain the accuracy of the Case-Base Reasoning system at the same time. Whereas Case-Base Maintenance algorithms typically use a particular heuristic to remove (or select) cases from the case-base, the resulting maintained case-base relies on the proportion of redundant and noisy cases that are present in the case-base, among other factors. That is, a particular Case-Base Maintenance algorithm is suitable for certain types of case-bases that share some indicators, such as redundancy and noise levels. In the present work, we consider Case-Base Maintenance as a multi-objective optimization problem, which is solved with a Multi-Objective Evolutionary Algorithm. To this end, a fitness function is introduced to measure three different objectives based on the Complexity Profile model. Our hypothesis is that the Multi-Objective Evolutionary Algorithm performing Case-Base Maintenance may be used in a wider set of case-bases, achieving a good balance between the reduction of cases and the problem-solving ability of the Case-Based Reasoning system. Finally, from a set of the experiments, our proposed Multi-Objective Evolutionary Algorithm performing Case-Base Maintenance shows regularly good results with different sets of case-bases with different proportion of redundant and noisy cases.     

Freeze‐drying concentration of Rangpur lime juice

The use of freeze‐drying for concentrating lime Rangpur juice was investigated. This procedure allowed obtaining concentrated Rangpur lime juices between 23 and 51.3 °Brix, without affecting their organoleptic and nutritional characteristics. The efficiency of the procedure was inversely related to the film thickness of the matrix to be lyophilised. The sublimation speed per unit area diminished with the reduction in the residual moisture content of the juice. The mathematical model that fitted to the concentration procedure allowed to predict the time required for concentrating Rangpur lime by freeze‐drying starting from samples of different thickness. When compared with other citric juices evaluated, the Rangpur lime juice was the most suitable for freeze‐drying concentration. The results could be used to devise optimal industrial freeze‐drying cycles for processing Rangpur lime juices at different concentrations.     

LRA: Local Rigid Averaging of Stretchable Non-rigid Shapes

We present a novel algorithm for generating the mean structure of non-rigid stretchable shapes. Following an alignment process, which supports local affine deformations, we translate the search of the mean shape into a diagonalization problem where the structure is hidden within the kernel of a matrix. This is the first step required in many practical applications, where one needs to model bendable and stretchable shapes from multiple observations.