Discovering Hidden Mental States in Open Multi-Agent Systems by Leveraging Multi-Protocol Regularities with Machine Learning.

The agent paradigm and multi-agent systems are a perfect match for the design of smart cities because of some of their essential features such as decentralization, openness, and heterogeneity. However, these major advantages also come at a great cost. Since agents' mental states are hidden when the implementation is not known and available, intelligent services of smart cities cannot leverage information from them.

Halogen-atom effect on the ultrafast photodissociation dynamics of the dihalomethanes CHICl and CHBrI.

A comparative study of the ultrafast photodissociation dynamics of the dihalomethanes CH2ICl and CH2BrI has been carried out at 268 nm, around the maximum of the first absorption band, employing femtosecond velocity map ion imaging in conjunction with high level ab initio electronic structure calculations and full dimension on-the-fly trajectory calculations including surface hopping. Total translational energy distributions and angular distributions of the iodine fragments as well as reaction times for the C-I bond cleavage are presented and discussed along with the computed absorption spectra, potential energy curves and trajectories. The revealed dynamics is mainly governed by absorption to the 5A' state for CH2BrI while two dissociation pathways, through the 4A' or 5A' states, are in competition for CH2lCI.

Smart Waste Collection System with Low Consumption LoRaWAN Nodes and Route Optimization.

New solutions for managing waste have emerged due to the rise of Smart Cities and the Internet of Things. These solutions can also be applied in rural environments, but they require the deployment of a low cost and low consumption sensor network which can be used by different applications. Wireless technologies such as LoRa and low consumption microcontrollers, such as the SAM L21 family make the implementation and deployment of this kind of sensor network possible.

A Context-Aware Indoor Air Quality System for Sudden Infant Death Syndrome Prevention.

Context-aware monitoring systems designed for e-Health solutions and ambient assisted living (AAL) play an important role in today's personalized health-care services. The majority of these systems are intended for the monitoring of patients' vital signs by means of bio-sensors. At present, there are very few systems that monitor environmental conditions and air quality in the homes of users.

Increasing the Intensity over Time of an Electric-Assist Bike Based on the User and Route: The Bike Becomes the Gym.

Nowadays, many citizens have busy days that make finding time for physical activity difficult. Thus, it is important to provide citizens with tools that allow them to introduce physical activity into their lives as part of the day's routine. This article proposes an app for an electric pedal-assist-system (PAS) bicycle that increases the pedaling intensity so the bicyclist can achieve higher and higher levels of physical activity.

Combination of Multi-Agent Systems and Wireless Sensor Networks for the Monitoring of Cattle.

Precision breeding techniques have been widely used to optimize expenses and increase livestock yields. Notwithstanding, the joint use of heterogeneous sensors and artificial intelligence techniques for the simultaneous analysis or detection of different problems that cattle may present has not been addressed. This study arises from the necessity to obtain a technological tool that faces this state of the art limitation.

Multi-Sensor Information Fusion for Optimizing Electric Bicycle Routes Using a Swarm Intelligence Algorithm.

The use of electric bikes (e-bikes) has grown in popularity, especially in large cities where overcrowding and traffic congestion are common. This paper proposes an intelligent engine management system for e-bikes which uses the information collected from sensors to optimize battery energy and time. The intelligent engine management system consists of a built-in network of sensors in the e-bike, which is used for multi-sensor data fusion; the collected data is analysed and fused and on the basis of this information the system can provide the user with optimal and personalized assistance.

Combining Multi-Agent Systems and Wireless Sensor Networks for Monitoring Crop Irrigation.

Monitoring mechanisms that ensure efficient crop growth are essential on many farms, especially in certain areas of the planet where water is scarce. Most farmers must assume the high cost of the required equipment in order to be able to streamline natural resources on their farms. Considering that many farmers cannot afford to install this equipment, it is necessary to look for more effective solutions that would be cheaper to implement.

Retreatment Predictions in Odontology by means of CBR Systems.

The field of odontology requires an appropriate adjustment of treatments according to the circumstances of each patient. A follow-up treatment for a patient experiencing problems from a previous procedure such as endodontic therapy, for example, may not necessarily preclude the possibility of extraction. It is therefore necessary to investigate new solutions aimed at analyzing data and, with regard to the given values, determine whether dental retreatment is required.

aCGH-MAS: analysis of aCGH by means of multiagent system.

There are currently different techniques, such as CGH arrays, to study genetic variations in patients. CGH arrays analyze gains and losses in different regions in the chromosome. Regions with gains or losses in pathologies are important for selecting relevant genes or CNVs (copy-number variations) associated with the variations detected within chromosomes.

Interplay of radiative and nonradiative transitions in surface hopping with radiation-molecule interactions.

We implemented a method for the treatment of field induced transitions in trajectory surface hopping simulations, in the framework of the local diabatization scheme, especially suited for on-the-fly dynamics. The method is applied to a simple one-dimensional model with an avoided crossing and compared with quantum wavepacket dynamics. The results show the importance of introducing a proper decoherence correction to surface hopping, in order to obtain meaningful results.

Ambient agents: embedded agents for remote control and monitoring using the PANGEA platform.

Ambient intelligence has advanced significantly during the last few years. The incorporation of image processing and artificial intelligence techniques have opened the possibility for such aspects as pattern recognition, thus allowing for a better adaptation of these systems. This study presents a new model of an embedded agent especially designed to be implemented in sensing devices with resource constraints.

Monitoring and detection platform to prevent anomalous situations in home care.

Monitoring and tracking people at home usually requires high cost hardware installations, which implies they are not affordable in many situations. This study/paper proposes a monitoring and tracking system for people with medical problems. A virtual organization of agents based on the PANGEA platform, which allows the easy integration of different devices, was created for this study.

Automatic knowledge extraction in sequencing analysis with multiagent system and grid computing.

Advances in bioinformatics have contributed towards a significant increase in available information. Information analysis requires the use of distributed computing systems to best engage the process of data analysis. This study proposes a multiagent system that incorporates grid technology to facilitate distributed data analysis by dynamically incorporating the roles associated to each specific case study.

Mixed quantum-classical dynamics in the adiabatic representation to simulate molecules driven by strong laser pulses.

The dynamics of molecules under strong laser pulses is characterized by large Stark effects that modify and reshape the electronic potentials, known as laser-induced potentials (LIPs). If the time scale of the interaction is slow enough that the nuclear positions can adapt to these externally driven changes, the dynamics proceeds by adiabatic following, where the nuclei gain very little kinetic energy during the process. In this regime we show that the molecular dynamics can be simulated quite accurately by a semiclassical surface-hopping scheme formulated in the adiabatic representation.

Hybrid neural intelligent system to predict business failure in small-to-medium-size enterprises.

During the last years there has been a growing need of developing innovative tools that can help small to medium sized enterprises to predict business failure as well as financial crisis. In this study we present a novel hybrid intelligent system aimed at monitoring the modus operandi of the companies and predicting possible failures. This system is implemented by means of a neural-based multi-agent system that models the different actors of the companies as agents.

Relationship between the lung function and anthropometric measures and indexes in adolescents from Córdoba, Argentina.

Objectives: The objectives of this study were to determine the degrees of association between the Forced Vital Capacity (FVC) with four anthropometric variables: height, sitting height, surface, and body volume, and two somatometrics indexes: Body Mass Index (BMI) and Cormic index, and to confront the values of FVC obtained with the predicted ones by the method of Polgar.

Methods: One sample of 54 boys and 31 girls was selected. All of them were 11-18 years of age, and were students of the National School of Monserrat (Cordoba, Argentina).

Applying wearable solutions in dependent environments.

This paper proposes a multiagent system (MAS) that uses smart wearable devices and mobile technology for the care of patients in a geriatric home care facility. The system is based on an advanced ZigBee wireless sensor network (WSN) and includes location and identification microchips installed in patient clothing and caregiver uniforms. The use of radio-frequency identification and near-field communication technologies allows remote monitoring of patients, and makes it possible for them to receive treatment according to preventive medical protocol.

Using heterogeneous wireless sensor networks in a telemonitoring system for healthcare.

Ambient intelligence has acquired great importance in recent years and requires the development of new innovative solutions. This paper presents a distributed telemonitoring system, aimed at improving healthcare and assistance to dependent people at their homes. The system implements a service-oriented architecture based platform, which allows heterogeneous wireless sensor networks to communicate in a distributed way independent of time and location restrictions.

Model of experts for decision support in the diagnosis of leukemia patients.

Objective: Recent advances in the field of biomedicine, specifically in the field of genomics, have led to an increase in the information available for conducting expression analysis. Expression analysis is a technique used in transcriptomics, a branch of genomics that deals with the study of messenger ribonucleic acid (mRNA) and the extraction of information contained in the genes. This increase in information is reflected in the exon arrays, which require the use of new techniques in order to extract the information.

Raloxifene plus ossein-hydroxyapatite compound versus raloxifene plus calcium carbonate to control bone loss in postmenopausal women: a randomized trial.

Objective: To compare the efficacy and safety of adding ossein-hydroxyapatite compound (OHC) or calcium carbonate (CC) to raloxifene (RLX) therapy for controlling bone loss in postmenopausal women.

Design: : Ninety postmenopausal women were assigned to treatment with RLX plus OHC (group 1, 48 women) or RLX plus CC (group 2, 42 women) for up to 3 years in an open-label, comparative study. Ultrasound measurement of amplitude-dependent speed of sound (ADSoS) was used to evaluate mean changes in bone mineral density.

Clinical usefulness of 3-dimensional sonography and power Doppler angiography for diagnosis of endometrial carcinoma.

Objective: The purpose of this study was to assess whether endometrial volume (EV) and 3-dimensional (3D) power Doppler indices can discriminate between hyperplasia and endometrial carcinoma and can predict extension of the endometrial carcinoma.

Methods: Eighty-four women with uterine bleeding and a histopathologic diagnosis of endometrial hyperplasia (n = 29) or carcinoma (n = 55) were preoperatively examined by transvaginal 3D sonography and power Doppler angiography. Endometrial thickness (ET), EV, the vascularization index (VI), the flow index (FI), the vascularization-flow index (VFI), and the intratumoral resistive index (RI) were measured.

The labor induction: integrated clinical and sonographic variables that predict the outcome.

Objective: To analyze the clinical and sonographic variables that predicts the success of labor induction.

Study Design: We studied the Bishop score, cervical length and parity in 196 pregnant women in the prediction of successful vaginal delivery within 24 h of induction. Logistic regression and segmentation analysis were performed.

Endometrial volume and vascularity measurements by transvaginal three-dimensional ultrasonography and power Doppler angiography in stimulated and tumoral endometria: intraobserver reproducibility.

Objectives: To assess intraobserver reproducibility of the endometrial volume (EV) and 3D power Doppler indices (vascularization index, VI; flow index, FI; and vascularization flow index, VFI) of the endometrium and subendometrial area using three-dimensional power Doppler angiography (3D-PDA).

Methods: Twenty-five women on the hCG day after controlled ovarian stimulation and 15 patients presenting with uterine bleeding and suspicious endometrial thickening (10 endometrial cancers and 5 endometrial hyperplasias) were scanned. Eighty volume data sets were analyzed using the VOCAL imaging program.

Variables that predict the success of labor induction.

Background: To analyze the clinical and sonographic variables that affect the success of labor induction.

Methods: Bishop score, cervical length, and parity were studied in 196 pregnant women in the prediction of successful vaginal delivery within 24 hr of induction. Logistic regression and segmentation analysis were performed.