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The objective of this study is to describe the frequency and type of victimization in a Spanish child and adolescent clinical ADHD sample and to analyze the association between the types of victimization and the severity of the symptoms. The sample is composed of 106 outpatients in treatment for ADHD, according to Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV) criteria. Symptom severity was measured by the Conners-3 scales. ADHD and comorbid diagnostics were evaluated with the Mini-Kid interview. The victimization experiences were studied using the Juvenile Victimization Questionnaire (JVQ). Children with child maltreatment history showed a greater intensity of hyperactivity/impulsivity, aggression and behavioral disorders as well as depression and anxiety disorders. The presence of peer victimization was associated with inattention, learning disorders, executive functioning, and relationship problems. Episodes of victimization should be considered in the treatment of the ADHD. Child maltreatment history is more associated with hyperactivity-impulsivity symptoms, while peer victimization is more associated with attentional symptoms. [ABSTRACT FROM AUTHOR]

Cellular ferroelectrets exhibit interesting electromechanical- acoustical characteristics. Their recent appearance and remarkable properties open up new possibilities for the design and development of ultrasonic transducers. In particular, the feasibility of fabricating ultrasonic vortex generators using ferroelectret films is demonstrated in this work. To this end, a transducer prototype was built by gluing the material onto a tangential-helical surface (outer diameter: 40 mm, pitch: 3.45 mm). Experimental results agree well with the theoretical estimation of the pressure and phase of the acoustic field in the near field and far field, which corroborates the potential of ferroelectrets to customize special acoustic fields. Furthermore, the proposed fabrication procedure is inexpensive and represents a new alternative for exploring and analyzing the special characteristics of acoustical helical wavefronts. [ABSTRACT FROM PUBLISHER]

Tetracyclin is a group of antimicrobial permitted in animal food production, but their concentrations in food of animal origin should not exceed 100 μg kg−1 (in meat and milk). Although the detection of these substances above these limits involves fines and jail for the producer, residues of tetracyclines are still being detected in food a potential risk to consumer health, especially babies. In the past, baby foods were carefully prepared at homes. However, modern lifestyles have led to the commercialization of ready-made baby food. Generally, these products are made with vegetable and meat from different animals, such as pork, chicken or beef. The presence of tetracyclines in meat at concentrations above 100 μg kg−1 is forbidden in Europe by the Regulation 37/2010. Consequently this concentration is also applicable to the portion of meat present in baby food. Even if the presence of tetracyclines is controlled regularly in meat, they should also be monitored in baby food as babies are vulnerable to such as drugs. A rapid analytical method based on high-performance liquid chromatography coupled to a tandem mass spectrometer (HPLC-MS/MS) for quantification of four tetracyclines (tetracycline, chlortetracycline, doxycycline and oxytetracycline) in baby food is presented. The tetracyclines are extracted with EDTA-McIlvaine buffer, acidified at pH 4.0, followed by liquid-liquid extraction with ethyl acetate. The final extract is analysed within 19 min on a Sunfire HPLC column from Waters. Validation was performed according to the Commission Decision 2002/657/EC. The mean accuracy was 103 μg kg−1, and the mean precision, was less than 23% for all the tetracyclines. The method was tested on 31 prepared baby food samples containing vegetable and beef. The presence of oxytetracycline was detected in one of the samples at a concentration of 5 μg kg−1. [ABSTRACT FROM AUTHOR]

The urban setting is a challenging environment for GNSS receivers. Multipath and other anomalies typically increase the positioning error of the receiver. Moreover, the error estimate of the position is often unreliable. In this study, we detect GNSS trajectory anomalies by using similarity comparison methods between a pedestrian dead reckoning trajectory, recorded using a foot-mounted inertial measurement unit, and the corresponding GNSS trajectory. During a normal walk, the foot-mounted inertial dead reckoning setup is trustworthy up to a few tens of meters. Thus, the differing GNSS trajectory can be detected using form similarity comparison methods. Of the eight tested methods, the Hausdorff distance (HD) and the accumulated distance difference (ADD) give slightly more consistent detection results compared to the rest. [ABSTRACT FROM AUTHOR]

The development of indoor positioning solutions using smartphones is a growing activity with an enormous potential for everyday life and professional applications. The research activities on this topic concentrate on the development of new positioning solutions that are tested in specific environments under their own evaluation metrics. To explore the real positioning quality of smartphone-based solutions and their capabilities for seamlessly adapting to different scenarios, it is needed to find fair evaluation frameworks. The design of competitions using extensive pre-recorded datasets is a valid way to generate open data for comparing the different solutions created by research teams. In this paper, we discuss the details of the 2017 IPIN indoor localization competition, the different datasets created, the teams participating in the event, and the results they obtained. We compare these results with other competition-based approaches (Microsoft and Perf-loc) and on-line evaluation web sites. The lessons learned by organising these competitions and the benefits for the community are addressed along the paper. Our analysis paves the way for future developments on the standardization of evaluations and for creating a widely-adopted benchmark strategy for researchers and companies in the field. [ABSTRACT FROM AUTHOR]

In recent years, indoor localization systems have been the object of significant research activity and of growing interest for their great expected social impact and their impressive business potential. Application areas include tracking and navigation, activity monitoring, personalized advertising, Active and Assisted Living (AAL), traceability, Internet of Things (IoT) networks, and Home-land Security. In spite of the numerous research advances and the great industrial interest, no canned solutions have yet been defined. The diversity and heterogeneity of applications, scenarios, sensor and user requirements, make it difficult to create uniform solutions. From that diverse reality, a main problem is derived that consists in the lack of a consensus both in terms of the metrics and the procedures used to measure the performance of the different indoor localization and navigation proposals. This paper introduces the general lines of the EvAAL benchmarking framework, which is aimed at a fair comparison of indoor positioning systems through a challenging competition under complex, realistic conditions. To evaluate the framework capabilities, we show how it was used in the 2016 Indoor Positioning and Indoor Navigation (IPIN) Competition. The 2016 IPIN competition considered three different scenario dimensions, with a variety of use cases: (1) pedestrian versus robotic navigation, (2) smartphones versus custom hardware usage and (3) real-time positioning versus off-line post-processing. A total of four competition tracks were evaluated under the same EvAAL benchmark framework in order to validate its potential to become a standard for evaluating indoor localization solutions. The experience gained during the competition and feedback from track organizers and competitors showed that the EvAAL framework is flexible enough to successfully fit the very different tracks and appears adequate to compare indoor positioning systems. [ABSTRACT FROM AUTHOR]

This paper presents the analysis and discussion of the off-site localization competition track, which took place during the Seventh International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016). Five international teams proposed different strategies for smartphone-based indoor positioning using the same reference data. The competitors were provided with several smartphone-collected signal datasets, some of which were used for training (known trajectories), and others for evaluating (unknown trajectories). The competition permits a coherent evaluation method of the competitors’ estimations, where inside information to fine-tune their systems is not offered, and thus provides, in our opinion, a good starting point to introduce a fair comparison between the smartphone-based systems found in the literature. The methodology, experience, feedback from competitors and future working lines are described. [ABSTRACT FROM AUTHOR]

Highlights: [•] Fusion of pedestrian dead reckoning and range measurements with a particle filter. [•] Definition of an adaptive stride movement model on the prediction stage. [•] Dynamic estimation of the measurements model in the update stage. [•] Tracking the personl's position without an initial position/heading or calibration. [•] Measurements of the position accuracy compared with the Cramer-Rao lower bound. [ABSTRACT FROM AUTHOR]

Local Positioning Systems (LPSs) based on acoustic transducers (mainly ultrasonic) offer accurate localization in indoor environments. However, their performance is commonly limited by the transducers' frequency bandwidth and emission pattern. 3D-LOCUS is a new advanced acoustic LPS that claims subcentimeter accuracy even in turbulent environments. This is achieved through the use of broadband omnidirectional transducers, suitable design of emitted signals, proper calibration, and bidirectional emissions. This paper evaluates the 3D-LOCUS LPS by providing results in terms of some positioning metrics such as accuracy, resolution, and coverage, which show how it outperforms other state-of-the-art LPS prototypes. 3D-LOCUS operating in bidirectional mode minimizes environmental effects, such as temperature and airflows, attaining localization errors below 9 mm with a 90% confidence level, an RMS error below 7.4 mm, and 5 mm resolution in a localization volume of 2 × 2 × 0.4 m³. [ABSTRACT FROM AUTHOR]

The navigation of Autonomous Guided Vehicles (AGVs) in industrial environments is often controlled by positioning systems based on landmarks or artificial beacons. In these systems, the position of an AGV navigating in an interior space is determined by the calculation of its relative distance to beacons, whose location is known in advance. A fundamental design problem associated with landmark navigation systems consists in determining the optimal location of the minimum number of beacons necessary to achieve a desired level of accuracy and reliability. A local search procedure coupled with a diversification strategy is developed for this problem. Comparisons with an earlier solution method based on genetic algorithms are provided and it is shown that the proposed procedure finds better designs in a fraction of the computational time employed by the genetic algorithm. [ABSTRACT FROM AUTHOR]

In the elderly, geriatric problems such as the risk of fall or frailty are a challenge for society. Patients with frailty present difficulties in walking and higher fall risk. The use of sensors for gait analysis allows the detection of objective parameters related to these pathologies and to make an early diagnosis. Inertial Measurement Units (IMUs) are wearables that, due to their accuracy, portability, and low price, are an excellent option to analyze human gait parameters in health-monitoring applications. Many relevant gait parameters (e.g., step time, walking speed) are used to assess motor, or even cognitive, health problems in the elderly, but we perceived that there is not a full consensus on which parameters are the most significant to estimate the risk of fall and the frailty state. In this work, we analyzed the different IMU-based gait parameters proposed in the literature to assess frailty state (robust, prefrail, or frail) or fall risk. The aim was to collect the most significant gait parameters, measured from inertial sensors, able to discriminate between patient groups and to highlight those parameters that are not relevant or for which there is controversy among the examined works. For this purpose, a literature review of the studies published in recent years was carried out; apart from 10 previous relevant reviews using inertial and other sensing technologies, a total of 22 specific studies giving statistical significance values were analyzed. The results showed that the most significant parameters are double-support time, gait speed, stride time, step time, and the number of steps/day or walking percentage/day, for frailty diagnosis. In the case of fall risk detection, parameters related to trunk stability or movements are the most relevant. Although these results are important, the total number of works found was limited and most of them performed the significance statistics on subsets of all possible gait parameters; this fact highlights the need for new frailty studies using a more complete set of gait parameters. [ABSTRACT FROM AUTHOR]

Falls are a severe problem in older adults, often resulting in severe consequences such as injuries or loss of consciousness. It is crucial to screen fall risk in order to prescribe appropriate therapies that can potentially prevent falls. Identifying individuals who have experienced falls in the past, commonly known as fallers, is used to evaluate fall risk, as a prior fall indicates a higher likelihood of future falls. The methods that have the most support from evidence are Gait Speed (GS) and Time Up and Go (TUG), which use specific cut-off values to evaluate the fall risk. There have been proposals for alternative methods that use wearable sensor technology to improve fall risk assessment. Although these technological alternatives are promising, further research is necessary to validate their use in clinical settings. In this study, we propose a method for identifying fallers based on a Support Vector Machine (SVM) classifier. The inputs for the classifier are the gait parameters obtained from a 30-minute walk recorded using an Inertial Measurement Unit (IMU) placed at the foot of patients. We validated our proposed method using a sample of 157 patients aged over 70 years. Our findings indicate significant differences (p< 0.05) in stride speed, clearance, angular velocity, acceleration, and coefficient of variability among steps between fallers and non-fallers. The proposed method demonstrates the its potential to classify fallers with an accuracy of [79.6]%, slightly outperforming the GS method which provides an accuracy of [77.0]%, and also overcomes its dependency on the cut-off speed to determine fallers. This method could be valuable in detecting fallers during long-term monitoring that does not require periodic evaluations in a clinical setting.

The location of people, robots, and Internet-of-Things (IoT) devices has become increasingly important. Among the available location technologies, solutions based on ultrawideband (UWB) radio are having much success due to their accuracy, which is ideally at a centimeter level. However, this accuracy is degraded in most common indoor environments due to the presence of obstacles which block or reflect the radio signals used for ranging. One way to circumvent this difficulty is through robust estimation algorithms based on measurement redundancy, permitting to minimize the effect of significantly erroneous ranges (outliers). This need for redundancy often conflicts with hardware restraints put up by the location system's designers. In this work, we present a procedure to increase the redundancy of UWB systems and demonstrate it with the help of a commercial system made by Decawave. This system is particularly easy to deploy, by configuring a network of beacons (anchors) and devices (tags) to be located; however, its architecture presents a major disadvantage as each tag to be located can only measure ranges to a maximum of four anchors. This limitation is embedded in the Positioning and Networking Stack (PANS) protocol designed by Decawave, and therefore is not easy to bypass without a total redesign of the firmware. In this paper, we analyze the strategies that we have been able to identify in order to provide this equipment with multiple range measurements, and thus enable each tag to be positioned with more than four measured ranges. We will see the advantages and disadvantages of each of these strategies, and finally we will adopt a solution that we implemented to be able to measure up to eight ranges for each mobile device (tag). This solution implies the duplication of the tags at the mobile user, and the creation of a double interleaved network of anchors. The range among tags and the eight beacons is obtained through an API via a wireless BLE protocol at a 10 Hz rate. A robustified Extended Kalman filter (EKF) is designed to estimate, by trilateration, the position of the pair of mobile tags, using eight ranges. Two different scenarios are used to make localization experimentation: a laboratory and an apartment. Our position estimation, which exploits redundant information and performs outlier removal, is compared with the commercial solution limited to four ranges, demonstrating the need and advantages of our multi-range approach.

Background: Borderline personality disorder (BPD) usually begins in adolescence and manifests itself in adult life. Early intervention can improve the prognosis or reduce its severity. Nevertheless, there are currently few studies of adolescent patients with severe emotion instability and borderline personality traits., Aims: To evaluate the effectiveness of the Systems Training for Emotional Predictability and Problem Solving (STEPPS) programme in a sample of 21 adolescents (aged 13-17 years) in the Child and Adolescents Mental Health Center of Tarragona in Spain., Method: We evaluated BPD traits using the Diagnostic Interview for Borderline Disorder-Revised (DIB-R) and the Global Clinical Impression Scale of Illness Severity for TLP (CGI-TLP). We compared pre- and post-treatment scores for the DIB-R, CGI-GI scale, general psychopathology using the Personality Inventory for Adolescents (PAI-A) and impulsivity with the Barratt Impulsivity Scale (BIS-11). The therapeutic objectives were evaluated with the Borderline Estimate Severity over Time (BEST) scale., Results: There was a statistically significant improvement in the scores for the affective area and in the total score of the DIB-R, a decrease in the percentage of patients who failed to meet criteria for BPD, and an improvement (although not statistically significant) in the scores of the BEST scale throughout the treatment. The results of the CGI-GI scale showed global improvement in almost 72% of patients., Conclusion: Our study suggests that STEPPS can be an effective treatment to improve BPD symptoms and is very useful in community settings with limited resources in which efficient treatment alternatives must be sought. However, this conclusion must be interpreted with caution, as there is no comparison control group.

Aim: To document adherence to influenza, pneumococcal and hepatitis B virus (HBV) vaccination programme in adult type 1 diabetes mellitus (T1DM) patients., Materials and Methods: Observational retrospective study using data obtained from computerized clinical records. We contacted all adult T1DM registered in our database from a tertiary diabetes care hospital. Primary efficacy outcome was to describe influenza, pneumococcal and HBV vaccination status., Results: Three hundred patients were analyzed (male 53%). Mean age was 40.0±14.4years and T1DM duration was 19.7±11.8years. Thirty-five percent of the patients had complementary indications for studied vaccines. Adherence to vaccination program for influenza, pneumococcal and HBV was achieved by 55%, 18% and 17% of the patients, respectively. Only 3% of the subjects were vaccinated against the three microorganisms. Predictor of correct vaccination were: age, shorter diabetes duration, insulin pump treatment, better diabetes control and being a health professional. We detected 17 sick leaves, 127 lost working days and 3 hospitalizations due to flue during the follow-up., Conclusions: The uptake of recommended vaccinations against influenza, pneumococcal and HBV in adult T1DM patients was below desirable levels. A special effort is required to all health professionals to implement immunization among adult people with T1DM. Clinical Trials NCT03478254., (Copyright © 2019 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.)

Aim: Liraglutide and lixisenatide improved glycemic control, weight and cardiovascular risk factors (CVRF) in type 2 diabetes mellitus (T2DM) patients. Our objective was to analyze clinical efficacy and safety differences in routine clinical practice., Methods: A 24-week prospective observational study to compare the effect of liraglutide versus lixisenatide in obese T2DM patients in routine clinical practice. The main objective was to analyze between-group glycosylated hemoglobin (HbA 1c ) differences at the end of the study. Secondary objectives included differences in body weight, other CVRF, changes in medication, side effects, satisfaction and safety., Results: A total of 100 patients (50 liraglutide, 50 lixisenatide) were included. Both groups experienced a decrease in HbA 1c values (liraglutide, -1.4%, CI 95% -2, -0.8, P < 0.001 vs. lixisenatide, -0.8%, 95% CI -1.2, -0.5, P < 0.001). No differences were found in final HbA 1c values between both groups (liraglutide 7.3 ± 0.9% vs. lixisenatide 7.2 ± 1.5%, P = 0.7). We did not detect between groups differences in anthropometric variables or CVRF at the study end. A lower proportion of patients received treatment with a maximum dose of liraglutide compared with lixisenatide (27% vs. 95%, P < 0.001). In contrast, a greater percentage of patients in the lixisenatide group than in liraglutide group (29% vs. 9%, P = 0.026) intensified treatment by the addition of sodium-glucose transporter type 2 inhibitors. Adverse events were less frequently reported in liraglutide treated patients compared with lixisentatide (80% vs. 96%, P = 0.014). No serious adverse events were detected., Conclusions: These results confirm the efficacy and safety of liraglutide and lixisenatide in routine clinical practice. Moreover, a different therapeutic effect between liraglutide and lixisenatide was detected., (Copyright © 2019 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.)

In GPS-denied indoor environments, localization and tracking of people can be achieved with a mobile device such as a smartphone by processing the received signal strength (RSS) of RF signals emitted from known location beacons (anchor nodes), combined with Pedestrian Dead Reckoning (PDR) estimates of the user motion. An enhacement of this localization technique is feasible if the users themselves carry additional RF emitters (mobile nodes), and the cooperative position estimates of a group of persons incorporate the RSS measurements exchanged between users. We propose a centralized cooperative particle filter (PF) formulation over the joint state of all users that permits to process RSS measurements from both anchor and mobile emitters, as well as PDR motion estimates and map information (if available) to increase the overall positioning accuracy, particularly in regions with low density of anchor nodes. Smartphones are used as a convenient mobile platform for sensor measurements acquisition, low-level processing, and data transmission to a central unit, where cooperative localization processing takes place. The cooperative method is experimentally demonstrated with four users moving in an area of 1600 m 2 , with 7 anchor nodes comprised of active RFID (radio frequency identification) tags, and additional mobile tags carried by each user. Due to the limited coverage provided by the anchor beacons, RSS-based individual localization is inaccurate (6.1 m median error), but this improves to 4.9 m median error with the cooperative PF. Further gains are produced if the PDR information is added to the filter: median error of 3.1 m (individual) and 2.6 m (cooperative); and if map information is also considered, the results are 1.8 m (individual) and 1.6 m (cooperative). Thus, for each version of the particle filter, cooperative localization outperforms individual localization in terms of positioning accuracy., Competing Interests: The authors declare no conflict of interest.