Development of Self-Sensing Asphalt Pavements: Review and Perspectives.

The digitalization of the road transport sector necessitates the exploration of new sensing technologies that are cost-effective, high-performing, and durable. Traditional sensing systems suffer from limitations, including incompatibility with asphalt mixtures and low durability. To address these challenges, the development of self-sensing asphalt pavements has emerged as a promising solution. These pavements are composed of stimuli-responsive materials capable of exhibiting changes in their electrical properties in response to external stimuli such as strain, damage, temperature, and humidity. Self-sensing asphalt pavements have numerous applications, including in relation to structural health monitoring (SHM), traffic monitoring, Digital Twins (DT), and Vehicle-to-Infrastructure Communication (V2I) tools. This paper serves as a foundation for the advancement of self-sensing asphalt pavements by providing a comprehensive review of the underlying principles, the composition of asphalt-based self-sensing materials, laboratory assessment techniques, and the full-scale implementation of this innovative technology.

Post-FEC performance evaluation of optical SDM systems with mode-dependent loss.

This work is focused on the bit error rate (BER) performance of spatial division multiplexing (SDM) systems over an optical channel with mode-dependent loss or gain (collectively referred to in this paper as MDL). When the latter is non-negligible, the BER has a random nature that introduces the outage probability as an important performance metric for the system design and also impacts on the selection of a forward-error correction (FEC) scheme. In MDL-impaired SDM systems, the pre-FEC BER is a random variable whose probability density function (PDF) and coding gain depend on the signal-to-noise ratio (SNR) at the receiver input. Hence, the common and simple approach of adding a coding gain factor to the pre-FEC BER to obtain the post-FEC BER is not adequate, and numerical simulations are needed. In this paper, we simulate and analyze the performance in terms of post-FEC BER for two proposals of applying low-density parity check (LDPC) FEC encoder/decoder in a SDM system MDL-impaired and an optimal linear multiple input multiple output (MIMO) receiver. In the first one, the LDPC is applied independently to each mode, and in the second one, the LDPC is applied among all SDM modes. Simulation results indicate that the first proposal outperforms the second. Simplifications in the log-likelihood ratio (LLR) computations have also been considered.

BER analysis of an optimum MIMO linear receiver in optical SDM systems with mode-dependent loss.

Multiple-input multiple-output (MIMO) receivers designed to optimize the minimum mean square error (MMSE) are a common choice in coherent optical communication systems based on spatial division multiplexing (SDM). This kind of receivers naturally integrate both MIMO equalization and matched filtering functions. However, when the optical channel exhibits significant mode-dependent loss (MDL) and/or mode-dependent gain (MDG), the impact of inter-symbol interference (ISI) and crosstalk that arise, even using an ideal MIMO MMSE linear receiver, is barely analyzed. Moreover, due to the random nature of the MDL/MDG model, the resulting ISI, crosstalk, and bit error rate (BER) also become random variables and, hence the system performance is more unpredictable. In this paper, we first evaluate the residual distortion (ISI and crosstalk) after the MIMO receiver and then we study the validity of assuming it as an additional Gaussian noise term independent of the channel noise. Next, the probability density distribution (PDF) of the BER is analyzed, from both an analytical perspective and numerical simulations. For the latter, we use a single-carrier 2-PAM (pulse amplitude modulation) system, with pulse shaping, and the MIMO MMSE receiver implementation by means of a MIMO fractionally-spaced equalizer (FSE). We carry out simulations of the system under different conditions of MDL/MDG level and signal to noise ratio (SNR), measured at the receiver input. Additionally, we address possible fits of the BER PDF to known closed-form distributions, among which the Generalized Extreme Value (GEV) family of distributions is selected, and polynomial functions are proposed that relate the system parameters with the GEV PDF parameters. Finally, we present contour maps of BER according to a giving target of system outage probability (OP) that depend on the MDL/MDG and SNR conditions.

UroSound: A Smartwatch-Based Platform to Perform Non-Intrusive Sound-Based Uroflowmetry.

Leveraging consumer technology such as smartwatches to objectively and remotely assess people with voiding dysfunction could capture unique features for prompt diagnosis of a disease. This paper presents the UroSound, the first platform that performs non-intrusive sound-based uroflowmetry with a smartwatch. We study the feasibility of using a smartwatch to assess how well the urinary tract functions by processing the sound generated when the urine stream hits the water level in the toilet bowl, which can be modelled through the sound envelope. Signal-based features related to the sound envelope were extracted from a smartwatch's built-in microphone. The constructed model achieves a good correlation between acoustic and standard uroflowmetry in terms of the voiding shape and it can extract relevant voiding parameters. This indicates that accurate and remote measurement of the ambulatory characteristics of voiding dysfunction can be achieved with smartwatch-based uroflowmetry. UroSound also facilitates the collection of a voiding diary by measuring multiple uroflows during daytime and nighttime. Finally, the performance of 6 commercial smartwatches was analysed while recording a voiding event. The results demonstrate that the presence of an automatic gain control in the smartwatch microphone has a negative impact on the signal envelope, and should be avoided. Overall, this work demonstrates the potential for the use of smartwatches in the assessment of voiding dysfunction, to deliver more personalized and effective health care at home with less waste of time and resources, in particular in rural or less developed areas where access to a urology specialist is more difficult.

Automatic Classification of Audio Uroflowmetry with a Smartwatch.

Prior work has shown the classification of voiding dysfunctions from uroflowmeter data using machine learning. We present the use of smartwatch audio, collected through the UroSound platform, in order to automatically classify voiding signals as normal or abnormal, using classical machine learning techniques. We train several classification models using classical machine learning and report a maximal test accuracy of 86.16% using an ensemble method classifier. Clinical relevance- This classification task has the potential to be part of an essential toolkit for urology telemedicine. It is especially useful in areas that lack proper medical infrastructure but still host ubiquitous audio capture devices such as smartphones and smartwatches.

Delay and Energy Consumption of MQTT over QUIC: An Empirical Characterization Using Commercial-Off-The-Shelf Devices.

The QUIC protocol, which was originally proposed by Google, has recently gained a remarkable presence. Although it has been shown to outperform TCP over a wide range of scenarios, there exist some doubts on whether it might be an appropriate transport protocol for IoT. In this paper, we specifically tackle this question, by means of an evaluation carried out over a real platform. In particular, we conduct a thorough characterization of the performance of the MQTT protocol, when used over TCP and QUIC. We deploy a real testbed, using commercial off-the-shelf devices, and we analyze two of the most important key performance indicators for IoT: delay and energy consumption. The results evince that QUIC does not only yield a notable decrease in the delay and its variability, over various wireless technologies and channel conditions, but it does not hinder the energy consumption.

A role for the diabetes nurse educator to telemedically support children with type 1 diabetes on continuous glucose monitoring? The COVID-19 lockdown experience.

The role of diabetes nurse educators during the COVID-19 lockdown to telematically provide routine reviews of glycaemic control in children with type 1 diabetes (T1D) using continuous glucose monitoring systems is evaluated. Implementing these routines in the day-to-day clinical practice could reduce in-person clinic visits and improve glucose control.

Matched Filtering for MIMO Coherent Optical Communications with Mode-Dependent Loss Channels.

The use of digital signal processors (DSP) to equalize coherent optical communication systems based on spatial division multiplexing (SDM) techniques is widespread in current optical receivers. However, most of DSP implementation approaches found in the literature assume a negligible mode-dependent loss (MDL). This paper is focused on the linear multiple-input multiple-output (MIMO) receiver designed to optimize the minimum mean square error (MMSE) for a coherent SDM optical communication system, without previous assumptions on receiver oversampling or analog front-end realizations. The influence of the roll-off factor of a generic pulse-amplitude modulation (PAM) transmitter on system performance is studied as well. As a main result of the proposed approach, the ability of a simple match filter (MF) based MIMO receiver to completely eliminate inter-symbol interference (ISI) and crosstalk for SDM systems under the assumption of negligible MDL is demonstrated. The performance of the linear MIMO fractionally-spaced equalizer (FSE) receiver for an SDM system with a MDL-impaired channel is then evaluated by numerical simulations using novel system performance indicators, in the form of signal to noise and distortion ratio (SNDR) loss, with respect to the case without MDL. System performance improvements by increasing the transmitter roll-off factor are also quantified.

Inadequate empirical antimicrobial treatment in older people with bacteremic urinary tract infection who reside in nursing homes: A multicenter prospective observational study.

AIM: The aim of the study was to determine the rate of inadequate empirical antimicrobial treatment in older nursing home residents with bacteremic urinary tract infection and its influence on prognosis. METHODS: We carried out a multicentric prospective observational study in five Spanish hospitals. Patients aged >65 years with pyelonephritis or urinary sepsis with bacteremia were included. Clinical characteristics, the percentage of inadequate empirical antibiotic treatment, length of hospital stay and mortality were evaluated. RESULTS: A total of 181 patients, 54.7% women, were included in the study, and 35.9% of the patients came from nursing homes. These patients had higher percentages of ultimately or rapidly fatal disease (92.3% vs 53.4%; P < 0.001), were older (83.15 ± 6.97 years vs 79.34 ± 7.25 years; P = 0.001) and had higher Acute Physiology And Chronic Health Evaluation II (28.38 ± 8.57 vs 19.83 ± 5.88). The percentage of extended-spectrum beta-lactamases was higher in patients from nursing homes (30.6% vs 16.3%; P = 0.045), as was the percentage of inadequate empirical antibiotic treatment (40% vs 20.7%; P = 0.005). Length of hospital stay was longer (10.82 ± 3.62 days vs 9.04 ± 4.88 days; P < 0.001). However, 30-day mortality was not related to nursing home by multivariate analysis (OR 1.905, 95% CI 0.563-6.446; P = 0.300). CONCLUSIONS: Nursing home patients with bacteremic urinary tract infections had a higher rate of extended-spectrum beta-lactamase-producing enterobacteriacea and inadequate empirical antimicrobial treatment. Clinicians should consider these findings and avoid inappropriate antimicrobial agents for empirical treatment. Geriatr Gerontol Int 2019; 19: 1112-1117.

Experimentation Management in the Co-Created Smart-City: Incentivization and Citizen Engagement.

Under the smart city paradigm, cities are changing at a rapid pace. In this context, it is necessary to develop tools that allow service providers to perform rapid deployments of novel solutions that can be validated by citizens. In this sense, the OrganiCity experimentation-as-a-service platform brings about a unique solution to experiment with new urban services in a co-creative way, among all the involved stakeholders. On top of this, it is also necessary to ensure that users are engaged in the experimentation process, so as to guarantee that the resulting services actually fulfill their needs. In this work, we present the engagement monitoring framework that has been developed within the OrganiCity platform. This framework permits the tailored definition of metrics according to the experiment characteristics and provides valuable information about how citizens react to service modifications and incentivization campaigns.

Managing Pervasive Sensing Campaigns via an Experimentation-as-a-Service Platform for Smart Cities.

The adoption of technologies like the IoT in urban environments, together with the intensive use of smartphones, is driving transformation towards smart cities. Under this perspective, Experimentation-as-a-Service within OrganiCity aims to create an experimental facility with technologies, services, and applications that simplify innovation within urban ecosystems. We discuss here tools that facilitate experimentation, implementing ways to organize, execute, and administer experimentation campaigns in a smart city context. We discuss the benefits of our framework, presenting some preliminary results. This is the first time such tools are paired with large-scale smart city infrastructures, enabling both city-scale experimentation and cross-site experimentation.

The clinical impact of bacteremia on outcomes in elderly patients with pyelonephritis or urinary sepsis: A prospective multicenter study.

BACKGROUND: Bacteremia is common in severe urinary infections, but its influence on the outcomes is not well established. The aim of this study was to assess the association of bacteremia with outcomes in elderly patients admitted to hospital with pyelonephritis or urinary sepsis. METHODS: This prospective muticenter observational study was conducted at 5 Spanish hospitals. All patients aged >65 years with pyelonephritis or urinary sepsis admitted to the departments of internal medicine and with urine and blood cultures obtained at admission to hospital were eligible. Transfer to ICU, length of hospital stay, hospital mortality and all cause 30-day mortality in bacteremic and non-bacteremic groups were compared. Risk factors for all cause 30-day mortality was also estimated. RESULTS: Of the 424 patients included in the study 181 (42.7%) had bacteremia. Neither transfer to ICU (4.4% vs. 2.9%, p = 0.400), nor length of hospital stay (9.7±4.6 days vs. 9.0±7.3 days, p = 0.252), nor hospital mortality (3.3% vs. 6.2%, p = 0.187), nor all cause 30-day mortality (9.4% vs. 13.2%, p = 0.223) were different between bacteremic and non-bacteremic groups. By multivariate analysis, risk factors for all cause 30-day mortality were age (OR 1.05, 95% CI 1.00-1.10), McCabe index ≥2 (OR 10.47, 95% CI 2.96-37.04) and septic shock (OR 8.56, 95% CI 2.86-25.61); whereas, bacteremia was inversely associated with all cause 30-day mortality (OR 0.33, 95% CI 0.15-0.71). CONCLUSIONS: In this cohort, bacteremia was not associated with a worse prognosis in elderly patients with pyelonephritis or urinary sepsis.

Electromagnetic Field Assessment as a Smart City Service: The SmartSantander Use-Case.

Despite the increasing presence of wireless communications in everyday life, there exist some voices raising concerns about their adverse effects. One particularly relevant example is the potential impact of the electromagnetic field they induce on the population's health. Traditionally, very specialized methods and devices (dosimetry) have been used to assess the strength of the E-field, with the main objective of checking whether it respects the corresponding regulations. In this paper, we propose a complete novel approach, which exploits the functionality leveraged by a smart city platform. We deploy a number of measuring probes, integrated as sensing devices, to carry out a characterization embracing large areas, as well as long periods of time. This unique platform has been active for more than one year, generating a vast amount of information. We process such information, and the obtained results validate the whole methodology. In addition, we discuss the variation of the E-field caused by cellular networks, considering additional information, such as usage statistics. Finally, we establish the exposure that can be attributed to the base stations within the scenario under analysis.

Heart-cut achiral-chiral LC-LC method development using factorial design: application to the chiral separation of ketoprofen.

A two-dimensional achiral-chiral LC-LC method in heart-cut mode for ketoprofen and its enantiomeric fraction determination was proposed. A C8 column was used in the first dimension, and the chiral column was an α1-acid glycoprotein. The mobile phase of the chiral system was optimized by a factorial design. The effect of temperature on retention and on enantiomeric resolution was studied. Particular attention was paid to mobile phase compatibility for the two columns and to transferring time, using ketoprofen standards. The R-(-) and S-(+)-ketoprofen retention times were 9 and 11 min, respectively; the resolution was higher than 1.1 and enantiomeric fraction close to 0.5. The method was applied to capsules and gels containing ketoprofen. Factorial design was also used to establish the best conditions for gel sample preparation. Recoveries were 84 and 105 % for capsules and gels, respectively. Graphical abstract Two-dimensional chromatogram for KPF and its enantiomers.

Co-Creating the Cities of the Future.

In recent years, the evolution of urban environments, jointly with the progress of the Information and Communication sector, have enabled the rapid adoption of new solutions that contribute to the growth in popularity of Smart Cities. Currently, the majority of the world population lives in cities encouraging different stakeholders within these innovative ecosystems to seek new solutions guaranteeing the sustainability and efficiency of such complex environments. In this work, it is discussed how the experimentation with IoT technologies and other data sources form the cities can be utilized to co-create in the OrganiCity project, where key actors like citizens, researchers and other stakeholders shape smart city services and applications in a collaborative fashion. Furthermore, a novel architecture is proposed that enables this organic growth of the future cities, facilitating the experimentation that tailors the adoption of new technologies and services for a better quality of life, as well as agile and dynamic mechanisms for managing cities. In this work, the different components and enablers of the OrganiCity platform are presented and discussed in detail and include, among others, a portal to manage the experiment life cycle, an Urban Data Observatory to explore data assets, and an annotations component to indicate quality of data, with a particular focus on the city-scale opportunistic data collection service operating as an alternative to traditional communications.

Conditional Random Field-Based Offline Map Matching for Indoor Environments.

In this paper, we present an offline map matching technique designed for indoor localization systems based on conditional random fields (CRF). The proposed algorithm can refine the results of existing indoor localization systems and match them with the map, using loose coupling between the existing localization system and the proposed map matching technique. The purpose of this research is to investigate the efficiency of using the CRF technique in offline map matching problems for different scenarios and parameters. The algorithm was applied to several real and simulated trajectories of different lengths. The results were then refined and matched with the map using the CRF algorithm.

Determination of free cholesterol oxide products in food samples by gas chromatography and accelerated solvent extraction: influence of electron-beam irradiation on cholesterol oxide formation.

BACKGROUND: The aim of this study was to develop an efficient method for cholesterol oxide product (COP) determination in irradiated and non-irradiated ready-to-eat foods with high water content by gas chromatography-flame ionisation detector after accelerated solvent extraction (ASE), and derivatisation with a silylating reagent. RESULTS: The ASE solvent was an 85:15 v/v petroleum ether/chloroform mixture at 40 °C and 1500 psi followed by solid phase extraction. The ASE method was compared with the established lixiviation method, proving an advantageous alternative which reduces analysis time by a factor of 15 and solvent volume by 50%, and minimises the use of chlorinated solvents. COP derivative structures were identified by gas chromatography coupled with mass spectrometry. Analytical characteristics were determined from standards and recoveries were 63-95%, establishing the validity of the method. CONCLUSION: The results obtained and their analysis by chemometric techniques established COP formation in food samples after e-beam irradiation. Increase in COP concentration depended on both irradiation doses and food composition, mainly water and fat content, although linear correlations among variables were not found. © 2016 Society of Chemical Industry.

Enhancing improved heuristic drift elimination for step-and-heading based pedestrian dead-reckoning systems.

Location based services can improve the quality of patient care and increase the efficiency of the healthcare systems. Among the different technologies that provide indoor positioning, inertial sensors based pedestrian dead-reckoning (PDR) is one of the more cost-effective solutions, but its performance is limited by drift problems. Regarding the heading drift, some heuristics make use of the building's dominant directions in order to reduce this problem. In this paper, we enhance the method known as improved heuristic drift elimination (iHDE) to be implemented in a Step-and-Heading (SHS) based PDR system, that allows to place the inertial sensors in almost any location of the user's body. Particularly, wrist-worn sensors will be used. Tests on synthetically generated and real data show that the iHDE method can be used in a SHS-based PDR without losing its heading drift reduction capability.

Duodenal involvement by seminomatous tumors

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