Values and preferences towards the use of prophylactic low-molecular-weight heparin during pregnancy: a convergent mixed-methods secondary analysis of data from the decision analysis in shared decision making for thromboprophylaxis during pregnancy (DASH-TOP) study.

BACKGROUND: Venous thromboembolism (VTE) in pregnancy is a major cause of maternal morbidity and mortality, and the use of preventive low-molecular-weight heparin (LMWH) can be challenging. Clinical guidelines recommend eliciting pregnant individuals' preferences towards the use of daily injections of LMWH and discussing the best option through a shared decision-making (SDM) approach. Our aim was to identify individuals' preferences concerning each of the main clinical outcomes, and categorize attributes influencing the use of LMWH during pregnancy. METHODS: Design: Convergent mixed-methods. PARTICIPANTS: Pregnant women or those planning a pregnancy with VTE recurrence risk. INTERVENTION: A SDM intervention about thromboprophylaxis with LMWH in pregnancy. ANALYSIS: Quantitatively, we report preference scores assigned to each of the health states. Qualitatively, we categorized preference attributes using Burke's pentad of motives framework: act (what needs to be done), scene (patient's context), agent (perspectives and influence of people involved in the decision), agency (aspects of the medication), and purpose (patient's goals). We use mixed-method convergent analysis to report findings using side-by-side comparison of concordance/discordance. RESULTS: We comprehensively determined preferences for using LMWH by pregnant individuals at risk of VTE: through value elicitation exercises we found that the least valued health state was to experience a pulmonary embolism (PE), followed by major obstetrical bleeding (MOB), deep vein thrombosis (DVT), and using daily injections of LMWH (valued as closest to a 'healthy pregnancy'); through interviews we found that: previous experiences, access to care (scene) and shared decision-making (agent) affected preferences. LMWH's benefits were noted, but substantial drawbacks were described (agency). For participants, the main goal of using LMWH was avoiding any risks in pregnancy (purpose). Side-by-side comparisons revealed concordance and discordance between health states and motives. CONCLUSIONS: Mixed-methods provide a nuanced understanding of LMWH preferences, by quantifying health states preferences and exploring attributes qualitatively. Incorporating both methods may improve patient-centered care around preference-sensitive decisions in thromboprophylaxis during pregnancy.

Prenatal current-use pesticide exposure and children's neurodevelopment at one year of age in the Infants' Environmental Health (ISA) birth cohort, Costa Rica.

BACKGROUND: Pesticide exposure may affect young children's neurodevelopment, but only few cohort studies have addressed possible effects of non-organophosphate pesticides. OBJECTIVE: We evaluated associations between prenatal current-use pesticide exposure and neurodevelopmental outcomes among 1-year-old children from the Infants' Environmental Health (ISA) birth cohort. METHODS: To determine prenatal pesticide exposure, we measured biomarkers of pyrimethanil, chlorpyrifos, synthetic pyrethroids, and 2,4-D in urine samples among 355 women, 1-3 times during pregnancy. One-year post-partum, we evaluated children's neurodevelopment with the Bayley Scales of Infant and Toddler Development 3rd edition (BSID-III). We assessed associations between exposures and neurodevelopmental outcomes (composite and z-scores) using single-chemical linear regression models adjusted for possible confounders (maternal education, parity, sex, gestational age at birth, child age, HOME-score, location of assessment, biomarkers of mancozeb), and studied effect-modification by sex. We evaluated non-linear associations of multiple pesticide exposures with Bayesian kernel machine regression (BKMR). RESULTS: We found higher prenatal urinary 2,4-D concentrations were associated with lower language (ßper ten-fold increase = -2.0, 95 % confidence interval (CI) = -3.5, -0.5) and motor (ßper ten-fold increase = -2.2, 95 %CI = -4.2, -0.1) composite scores among all children. Also, higher chlorpyrifos exposure [measured as urinary 3,5,6-trichloro-2-pyridinol (TCPy)] was associated with lower cognitive composite scores (ßper ten-fold increase = -1.9, 95 %CI = -4.7, 0.8), and lower motor composite scores among boys (ßper ten-fold increase = -3.8, 95 % CI = -7.7, 0.1) but not girls (ßper ten-fold increase = 2.3, 95 %CI = -1.6, 6.3, pINT = 0.11). Finally, higher pyrimethanil was associated with lower language abilities among girls, but not boys. Pyrethroid metabolite concentrations did not explain variability in BSID-III composite scores. Associations were similar for BSID-III z-scores, and we found no evidence for non-linear associations or mixture effects. DISCUSSION: Prenatal exposure to common-use pesticides may affect children's neurodevelopment at 1-year of age, some effects may be sex-specific.

The Dejour classification for trochlear dysplasia shows slight interobserver and substantial intraobserver reliability.

PURPOSE: Trochlear dysplasia is one of the main risk factors for recurrent patellar dislocation. The Dejour classification identifies four categories that can be used to classify trochlear dysplasia. The purpose of this study is to evaluate the inter- and intraobserver reliability of the Dejour classification for trochlear dysplasia. The hypothesis was that both intra- and interobserver reliability would be at least moderate. METHODS: This is a cross-sectional, reliability study. Twenty-eight examiners from the International Patellofemoral Study Group 2022 meeting evaluated lateral radiographs of the knee and axial magnetic resonance images from 15 cases of patellofemoral instability with trochlear dysplasia. They classified each case according to Dejour's classification for trochlear dysplasia (A-D). There were three rounds: one with only computed radiograph (CR), one with only magnetic resonance imaging (MRI) and one with both. Inter- and intraobserver reliability were calculated using κ coefficient (0-1). RESULTS: The mean age of patients was: 14.6 years; 60% were female and 53% had open physis. The interobserver reliability κ probabilities were 0.2 (CR), 0.13 (MRI) and 0.12 (CR and MRI). The intraobserver reliability κ probabilities were 0.45 (CR), 0.44 (MRI) and 0.65 (CR and MRI). CONCLUSION: The Dejour classification for trochlear dysplasia has slight interobserver reliability and substantial intraobserver reliability. LEVEL OF EVIDENCE: Level I.

[Gaps in primary mental health care in Chocó, Colombia: barriers and challengesLacunas na atenção primária à saúde mental em Chocó, Colômbia: barreiras e desafios]. / Brechas en la atención primaria en salud mental en Chocó, Colombia: barreras y desafíos.

Objective: Describe barriers and challenges in the implementation of the global Mental Health Gap Action Program (mhGAP), and determine the association between facilitators of implementation, accessibility, acceptability, and supervision, in Chocó, Colombia. Methods: Cross-sectional evaluation study, with mixed and sequential methods. Forty-one people participated: 30 health personnel and 11 administrative workers. Five focus groups were formed within the framework of the mhGAP training. The Likert scale of implementation drivers was used to determine factors affecting the strategy, such as system facilitators, accessibility of the strategy, adaptation and acceptability, and training and supervision. Semi-structured interviews were also conducted, with a subsequent thematic analysis. Results: A statistically significant correlation was found between the components of implementation. This was reaffirmed by the information from the interviews. Notable barriers include dispersion, armed conflict, difficulty in changing one's perspective on the area where they live, and administrative problems in accessing treatment. These factors are addressed in a proposed care pathway. Conclusions: With respect to mhGAP in the department of Chocó, despite adequate acceptability, access, and supervision, there are barriers and challenges at the social, geographical, political, cultural, and health administration levels, which could be overcome through implementation of locally-built intersectoral recovery routes.

Objetivo: Descrever barreiras e desafios na implementação do Programa de Ação para Reduzir as Lacunas em Saúde Mental (mhGAP, na sigla em inglês) e determinar a associação entre facilitadores de implementação, acessibilidade, aceitabilidade e supervisão em Chocó, Colômbia. Métodos: Estudo avaliativo de corte transversal, com métodos mistos e sequenciais, que contou com 41 participantes (30 da equipe de saúde e 11 da equipe administrativa). Um total de cinco grupos focais foram formados como parte do treinamento do mhGAP. Utilizou-se a escala de motivadores de implementação, que determinou fatores como facilitadores do sistema para implementação, acessibilidade da estratégia, adaptação e aceitabilidade, treinamento e supervisão da estratégia. Também foram realizadas entrevistas semiestruturadas, com posterior análise temática. Resultados: Foi encontrada uma correlação estatisticamente significativa entre os componentes da implementação, o que foi reafirmado com as informações das entrevistas. Em termos das barreiras identificadas, destacam-se fatores como dispersão, conflito armado, a dificuldade de mudar a perspectiva da pessoa sobre a área em que vive e problemas administrativos no acesso ao tratamento. Esses fatores são abordados em uma proposta de via de atendimento. Conclusões: Apesar da aceitabilidade, do acesso e da supervisão adequados, há barreiras e desafios sociais, geográficos, políticos, culturais e de administração de saúde no mhGAP do departamento de Chocó que poderiam ser superados com a implementação de rotas de recuperação intersetoriais, construídas a partir do próprio território.

Experience of a TelEmergency program in Colombia South America: descriptive observational study between 2019 and 2021.

INTRODUCTION: Colombia has 50,912,429 inhabitants, but only 50-70% of the population can effectively access health care services. The emergency room (ER) is a main contributor to the in-hospital care system since up to half of the admissions come through it. Telemedicine has become a tool to facilitate effective access to health care services, improve the timeliness of care, reduce diagnostic variability, and reduce costs associated with health. The aim of this study is to describe the experience of a Distance Emergency Care Program through Telemedicine (TelEmergency) to improve specialist access for patients at the Emergency Room (ER) in low- and medium-level care hospitals in Colombia. METHODS: An observational descriptive study of a cohort including 1,544 patients during the program's first two years was conducted. Descriptive statistics were used to analyze the available data. The data are presented with summarized statistics of sociodemographic, clinical, and patient-care variables. RESULTS: The study included a total of 1,544 patients, and the majority were adults between 60 and 79 years of age (n = 491, 32%). More than half were men (n = 832, 54%), and 68% (n = 1,057) belonged to the contributory health care regime. The service was requested from 346 municipalities, 70% (n = 1,076) from intermediate and rural settings. The most common diagnoses were related to COVID-19 (n = 356, 22%), respiratory diseases (n = 217, 14%), and cardiovascular diseases (n = 162, 10%). We observed 44% (n = 681) of local admissions either under observation (n = 53, 3%) or hospitalization (n = 380, 24%), limiting the need for hospital transfers. Program operation data revealed that 50% (n = 799) of requests were answered within two hours by the medical staff. The initial diagnosis was modified in 7% (n = 119) of the patients after being evaluated by specialists at the TelEmergency program. CONCLUSIONS: This study shows the operational data collected during the first two years after the implementation of the TelEmergency program in Colombia, the first of its kind in the country. Its implementation offered specialized timely management of patients at the ER in low- and medium-level care hospitals, where there is no availability of specialized doctors.

Indication-prescription study for the management of conjunctivitis in a Colombian population.

PURPOSE: Conjunctivitis is one of the most common ocular pathologies. Its treatment depends on its etiology, but an excessive use of antibiotics and corticosteroids, which in many cases are contraindicated, has been described. The objective was to describe the prescription patterns of medications used to treat conjunctivitis in a Colombian population. METHODS: This was a cross-sectional study on the pharmacological treatment of patients diagnosed with conjunctivitis between April 1, 2020, and March 31, 2021; based on a drug-dispensing database of approximately 8.5 million people affiliated with the Colombian Health System. Some sociodemographic and pharmacological variables and comorbidities were considered. A descriptive analysis was performed. RESULTS: A total of 8708 patients were identified; they had a median age of 44.7 years, and 59.3% were women. The most common causes of conjunctivitis were unspecified (53.1%) and allergic (37.4%). The most commonly used drug was olopatadine (26.1%), followed by dexamethasone with neomycin and polymyxin B (25.0%). A total of 97.0% of the patients received ophthalmic prescriptions, while 12.8% received systemic medications. Glucocorticoids (40.3%), antibiotics (37.7%) and antihistamines (31.7%) were the most commonly used groups of ophthalmic drugs. Glucocorticoids and ophthalmic antibiotics were the medications most frequently prescribed by general practitioners for the treatment of viral or bacterial conjunctivitis. CONCLUSIONS: Many patients with conjunctivitis are not being managed according to the recommendations of clinical practice guidelines, which highlights that the widespread use of antibiotics with ophthalmic glucocorticoids could be considered potentially inappropriate prescriptions in many cases.

Magnetic resonance imaging overestimates patellar height compared with radiographs.

PURPOSE: To evaluate the inter-observer and inter-method reliability for patellar height measurements between conventional radiographs (CR) and magnetic resonance imaging (MRI) using one or two slices. METHODS: This was a reliability study, with 60 patients divided in two groups: 30 patients with patellar instability (patella group) and 30 patients with anterior cruciate ligament or meniscus injury (control group). CR and MRI were evaluated by two independent observers. Insall-Salvati index (IS) and Caton-Deschamps index (CD) were measured using three different methods: CR, one-slice MRI or two-slice MRI. Intra-class correlation coefficients (ICC) were calculated for inter-observer reliability and inter-method reliability. Bland-Altman agreement was also calculated. RESULTS: The inter-observer reliability was very good for the IS with ICCs of 0.93, 0.84 and 0.82, for the CR, one-slice MRI and two-slice MRI, respectively. Similarly, for the CD the ICCs were good, 0.76, 0.80 and 0.75 for the CR, one-slice MRI and two-slice MRI, respectively. No differences were found between the patella and the control group. The inter-method analysis results were: ICCs for IS (0.83, 0.86, 0.93) and CD (0.72, 0.82, 0.83), for the comparisons of CR/one-slice MR, CR/two-slice MRI and one-slice MRI/two-slice MRI, respectively. The Bland-Altman mean differences showed an 8% and a 7% increase on IS values with one-slice MRI and two-slice MRI compared to CR results, while the increase was of 9% and 1% in CD for the respective comparisons with CR. CONCLUSION: MRI can overestimate patellar height compared to CR, as much as an 8% increase in Insall-Salvati values when using one- or two-slice MRI measurements, and up to a 9% increase in Caton-Deschamps value when using the one-slice MRI method. It is recommended to use the CR as the preferred method when measuring patellar height. LEVEL OF EVIDENCE: III.

NOTA: a novel online teaching and assessment scheme using Blockchain for emergency cases.

Technology advancements promote a redefinition of traditional instructional methodologies, as well as the roles of teachers and learners towards an efficient e-learning ecosystem. To date, all existing solutions are combined with the conventional face-to-face learning process. However, the latter can be unexpectedly hindered in some emergency cases, like the Coronavirus (COVID-19) pandemic. To handle such unexpected scenarios, this paper presents NOTA, a novel online teaching and assessment scheme that takes advantage of Blockchain technology to maintain the expected teaching quality and assessment fairness while respecting the courses' and examinations' schedule. Besides, NOTA also motivates both learners and teachers to persist in their endeavours, even from home, through Blockchain's incentive strategies. The preliminary results taken during the CoronaVirus period showed a very high satisfaction ratio, exceeding the 90%. This made us feel very optimistic about the potential of our proposal when deployed at a larger scale.

Distinct alterations of gut morphology and microbiota characterize accelerated diabetes onset in nonobese diabetic mice.

The rising prevalence of type 1 diabetes (T1D) over the past decades has been linked to lifestyle changes, but the underlying mechanisms are largely unknown. Recent findings point to gut-associated mechanisms in the control of T1D pathogenesis. In nonobese diabetic (NOD) mice, a model of T1D, diabetes development accelerates after deletion of the Toll-like receptor 4 (TLR4). We hypothesized that altered intestinal functions contribute to metabolic alterations, which favor accelerated diabetes development in TLR4-deficient (TLR4-/-) NOD mice. In 70-90-day-old normoglycemic (prediabetic) female NOD TLR4+/+ and NOD TLR4-/- mice, gut morphology and microbiome composition were analyzed. Parameters of lipid metabolism, glucose homeostasis, and mitochondrial respiratory activity were measured in vivo and ex vivo Compared with NOD TLR4+/+ mice, NOD TLR4-/- animals showed lower muscle mass of the small intestine, higher abundance of Bacteroidetes, and lower Firmicutes in the large intestine, along with lower levels of circulating short-chain fatty acids (SCFA). These changes are associated with higher body weight, hyperlipidemia, and severe insulin and glucose intolerance, all occurring before the onset of diabetes. These mice also exhibited insulin resistance-related abnormalities of energy metabolism, such as lower total respiratory exchange rates and higher hepatic oxidative capacity. Distinct alterations of gut morphology and microbiota composition associated with reduction of circulating SCFA may contribute to metabolic disorders promoting the progression of insulin-deficient diabetes/T1D development.

Editorial Commentary: Anterolateral Hinge Position Decreases the Slope in Opening-Wedge High Tibial Osteotomy: A Key Point in Treating an Anterior Cruciate Ligament-Deficient, Varus Knee.

The orthopaedic surgeon who performs opening-wedge high tibial osteotomy (HTO) has to be aware of the behavior of the tibial slope depending on variations in the location of the hinge and in the inclination of the osteotomy. The most important point is that changing both the inclination and the rotation axis of the osteotomy cut affects the tibial slope. There is a natural trend to unintentionally increase the tibial slope when performing an opening-wedge HTO. However, an increased tibial slope has been established as a risk factor for both primary and recurrent anterior cruciate ligament (ACL) injuries, whereas slope-reducing osteotomies decrease anterior tibial translation and protect the ACL graft. To reduce tibial slope in opening-wedge HTO, it seems more practical to internally rotate the osteotomy, establishing an anterolateral hinge, than to change the inclination of the cut, given that it seems more predictable and technically easier to perform internal rotation during surgery. Trying to achieve both internal rotation and extension increases the complexity of the osteotomy. Not every osteotomy needs to have an anterolateral hinge; in fact, decreasing the tibial slope would be a disadvantage in the posterior cruciate ligament-deficient knee. However, for the ACL-deficient knee with varus malalignment, aiming to decrease the tibial slope using an anterolateral hinge could be considered during preoperative planning.

Towards a Sustainable City for Cyclists: Promoting Safety through a Mobile Sensing Application.

Riding a bicycle is a great manner to contribute to the preservation of our ecosystem. Cycling helps to reduce air pollution and traffic congestion, and so, it is one of the simplest ways to lower the environmental footprint of people. However, the cohabitation of cars and vulnerable road users, such as bikes, scooters, or pedestrians, is prone to cause accidents with serious consequences. In this context, technological solutions are sought that enable the generation of alerts to prevent these accidents, thereby promoting a safer city for these road users, and a cleaner environment. Alert systems based on smartphones can alleviate these situations since nearly all people carry such a device while traveling. In this work, we test the suitability of a smartphone based alert system, determining the most adequate communications architecture. Two protocols have been designed to send position and alert messages to/from a centralized server over 4G cellular networks. One of the protocols is implemented using a REST architecture on top of the HTTP protocol, and the other one is implemented over the UDP protocol. We show that the proposed alarm system is feasible regarding communication response time, and we conclude that the application should be implemented over the UDP protocol, as response times are about three times better than for the REST implementation. We tested the applications in real deployments, finding that drivers are warned of the presence of bicycles when closer than 150 m, having enough time to pay attention to the situation and drive more carefully to avoid a collision.

Should We Be Concerned about the Association of Diabetes Mellitus and Periodontal Disease in the Risk of Infection by SARS-CoV-2? A Systematic Review and Hypothesis.

The objective of this article was to conduct a systematic review of the literature to contrast the existing evidence regarding the relationship between periodontal disease (PD) and diabetes mellitus (DM) with the possibly increased risk of SARS-CoV-2 infection, as well as to establish a hypothesis that explains the ways in which this interaction could take place. A literature search up from 1 January 2020 to 21 March 2021 was conducted in three electronic databases, namely, PubMed, Web of Science, and Scopus, in order to identify studies on periodontal disease alone or in conjunction with diabetes mellitus, reporting any relation with SARS-CoV-2 infection as a primary outcome. Only articles published in the English language were included. Due to the lack of studies, we decided to collect all the theoretical and clinical evidence suggesting a possible biological pathway evidencing the relationship among PD, DM, and SARS-CoV-2 infection. From a total of 29 articles, 12 were included for final review studies (five reviews, two hypotheses, one Special Issue, one perspective, one commentary, one case-control study, and one case report). In addition, this systematic review article hypothesizes the correlation between PD and type 2 diabetes mellitus (T2DM) by expression of angiotensin-converting enzyme 2 (ACE2) in periodontal tissue and the risk of SARS-CoV-2 infection. T2DM is a metabolic disorder characterized by high blood glucose levels resulting from altered insulin secretion or action. Likewise, periodontitis and T2DM are inflammatory disorders with a bidirectional association, and both diseases have a similar immunomodulatory cascade and cytokine profile. ACE2 is a crucial component of the renin-angiotensin system (RAS) and the key factor of entry in the cells by the new SARS-CoV-2. ACE2 is widely distributed in the lung and kidneys, and interestingly has a great distribution in the oral cavity, principally in the tongue and periodontal tissue. ACE2 in periodontal tissue plays a crucial role between health and disease. Moreover, the ACE2/Ang-(1-7)/MasR axis is downregulated in the dysbiotic and inflammatory periodontal environment. Nevertheless, the balance of ACE2 activity is modified in the context of concurrent diabetes, increasing the expression of ACE2 by the uncontrolled glycemia chronic in T2DM. Therefore, the uncontrolled hyperglycemia possibly increases the risk of developing periodontitis and triggering overexpression of ACE2 in periodontal tissue of T2DM patients, with these events potentially being essential to SARS-CoV-2 infection and the development of mild-to-severe form of COVID-19. In this sense, we would like to point out that the need for randomized controlled trials is imperative to support this association.

Evaluation of Clustering Algorithms on GPU-Based Edge Computing Platforms.

Internet of Things (IoT) is becoming a new socioeconomic revolution in which data and immediacy are the main ingredients. IoT generates large datasets on a daily basis but it is currently considered as "dark data", i.e., data generated but never analyzed. The efficient analysis of this data is mandatory to create intelligent applications for the next generation of IoT applications that benefits society. Artificial Intelligence (AI) techniques are very well suited to identifying hidden patterns and correlations in this data deluge. In particular, clustering algorithms are of the utmost importance for performing exploratory data analysis to identify a set (a.k.a., cluster) of similar objects. Clustering algorithms are computationally heavy workloads and require to be executed on high-performance computing clusters, especially to deal with large datasets. This execution on HPC infrastructures is an energy hungry procedure with additional issues, such as high-latency communications or privacy. Edge computing is a paradigm to enable light-weight computations at the edge of the network that has been proposed recently to solve these issues. In this paper, we provide an in-depth analysis of emergent edge computing architectures that include low-power Graphics Processing Units (GPUs) to speed-up these workloads. Our analysis includes performance and power consumption figures of the latest Nvidia's AGX Xavier to compare the energy-performance ratio of these low-cost platforms with a high-performance cloud-based counterpart version. Three different clustering algorithms (i.e., k-means, Fuzzy Minimals (FM), and Fuzzy C-Means (FCM)) are designed to be optimally executed on edge and cloud platforms, showing a speed-up factor of up to 11× for the GPU code compared to sequential counterpart versions in the edge platforms and energy savings of up to 150% between the edge computing and HPC platforms.

Three Dimensional UAV Positioning for Dynamic UAV-to-Car Communications.

In areas with limited infrastructure, Unmanned Aerial Vehicles (UAVs) can come in handy as relays for car-to-car communications. Since UAVs are able to fully explore a three-dimensional environment while flying, communications that involve them can be affected by the irregularity of the terrains, that in turn can cause path loss by acting as obstacles. Accounting for this phenomenon, we propose a UAV positioning technique that relies on optimization algorithms to improve the support for vehicular communications. Simulation results show that the best position of the UAV can be timely determined considering the dynamic movement of the cars. Our technique takes into account the current flight altitude, the position of the cars on the ground, and the existing flight restrictions.

A Distributed Approach for Collision Avoidance between Multirotor UAVs Following Planned Missions.

As the number of potential applications for Unmanned Aerial Vehicles (UAVs) keeps rising steadily, the chances that these devices get close to each other during their flights also increases, causing concerns regarding potential collisions. This paper proposed the Mission Based Collision Avoidance Protocol (MBCAP), a novel UAV collision avoidance protocol applicable to all types of multicopters flying autonomously. It relies on wireless communications in order to detect nearby UAVs, and to negotiate the procedure to avoid any potential collision. Experimental and simulation results demonstrated the validity and effectiveness of the proposed solution, which typically introduces a small overhead in the range of 15 to 42 s for each risky situation successfully handled.

Leveraging a Publish/Subscribe Fog System to Provide Collision Warnings in Vehicular Networks.

Fog computing, an extension of the Cloud Computing paradigm where routers themselves may provide the virtualisation infrastructure, aims at achieving fluidity when distributing in-network functions, in addition to allowing fast and scalable processing, and exchange of information. In this paper we present a fog computing architecture based on a "content island" which interconnects sets of "things" to exchange and process data among themselves or with other content islands. We then present a use case that focuses on a smartphone-based forward collision warning application for a connected vehicle scenario. This application makes use of the optical sensor of smartphones to estimate the distance between the device itself and other vehicles in its field of view. The vehicle travelling directly ahead is identified relying on the information from the GPS, camera, and inter-island communication. Warnings are generated at both content islands, if the driver does not maintain a predefined safe distance towards the vehicle ahead. Experiments performed with the application show that with the developed method, we are able to estimate the distance between vehicles, and the inter-island communication has a very low overhead, resulting in improved performance. On comparing our proposed solution based on edge/fog computing with a cloud-based api, it was observed that our solution outperformed the cloud-based api, thus making us optimistic of the utility of the proposed architecture.

FSF: Applying Machine Learning Techniques to Data Forwarding in Socially Selfish Opportunistic Networks.

Opportunistic networks are becoming a solution to provide communication support in areas with overloaded cellular networks, and in scenarios where a fixed infrastructure is not available, as in remote and developing regions. A critical issue, which still requires a satisfactory solution, is the design of an efficient data delivery solution trading off delivery efficiency, delay, and cost. To tackle this problem, most researchers have used either the network state or node mobility as a forwarding criterion. Solutions based on social behaviour have recently been considered as a promising alternative. Following the philosophy from this new category of protocols, in this work, we present our "FriendShip and Acquaintanceship Forwarding" (FSF) protocol, a routing protocol that makes its routing decisions considering the social ties between the nodes and both the selfishness and the device resources levels of the candidate node for message relaying. When a contact opportunity arises, FSF first classifies the social ties between the message destination and the candidate to relay. Then, by using logistic functions, FSF assesses the relay node selfishness to consider those cases in which the relay node is socially selfish. To consider those cases in which the relay node does not accept receipt of the message because its device has resource constraints at that moment, FSF looks at the resource levels of the relay node. By using the ONE simulator to carry out trace-driven simulation experiments, we find that, when accounting for selfishness on routing decisions, our FSF algorithm outperforms previously proposed schemes, by increasing the delivery ratio up to 20%, with the additional advantage of introducing a lower number of forwarding events. We also find that the chosen buffer management algorithm can become a critical element to improve network performance in scenarios with selfish nodes.

Supporting Beacon and Event-Driven Messages in Vehicular Platoons through Token-Based Strategies.

Timely and reliable inter-vehicle communications is a critical requirement to support traffic safety applications, such as vehicle platooning. Furthermore, low-delay communications allow the platoon to react quickly to unexpected events. In this scope, having a predictable and highly effective medium access control (MAC) method is of utmost importance. However, the currently available IEEE 802.11p technology is unable to adequately address these challenges. In this paper, we propose a MAC method especially adapted to platoons, able to transmit beacons within the required time constraints, but with a higher reliability level than IEEE 802.11p, while concurrently enabling efficient dissemination of event-driven messages. The protocol circulates the token within the platoon not in a round-robin fashion, but based on beacon data age, i.e., the time that has passed since the previous collection of status information, thereby automatically offering repeated beacon transmission opportunities for increased reliability. In addition, we propose three different methods for supporting event-driven messages co-existing with beacons. Analysis and simulation results in single and multi-hop scenarios showed that, by providing non-competitive channel access and frequent retransmission opportunities, our protocol can offer beacon delivery within one beacon generation interval while fulfilling the requirements on low-delay dissemination of event-driven messages for traffic safety applications.

Crowdsensing in Smart Cities: Overview, Platforms, and Environment Sensing Issues.

Evidence shows that Smart Cities are starting to materialise in our lives through the gradual introduction of the Internet of Things (IoT) paradigm. In this scope, crowdsensing emerges as a powerful solution to address environmental monitoring, allowing to control air pollution levels in crowded urban areas in a distributed, collaborative, inexpensive and accurate manner. However, even though technology is already available, such environmental sensing devices have not yet reached consumers. In this paper, we present an analysis of candidate technologies for crowdsensing architectures, along with the requirements for empowering users with air monitoring capabilities. Specifically, we start by providing an overview of the most relevant IoT architectures and protocols. Then, we present the general design of an off-the-shelf mobile environmental sensor able to cope with air quality monitoring requirements; we explore different hardware options to develop the desired sensing unit using readily available devices, discussing the main technical issues associated with each option, thereby opening new opportunities in terms of environmental monitoring programs.

Modeling and Characterization of Traffic Flows in Urban Environments.

Currently, one of the main challenges faced in large metropolitan areas is traffic congestion. To address this problem, adequate traffic control could produce many benefits, including reduced pollutant emissions and reduced travel times. If it were possible to characterize the state of traffic by predicting future traffic conditions for optimizing the route of automated vehicles, and if these measures could be taken to preventively mitigate the effects of congestion with its related problems, the overall traffic flow could be improved. This paper performs an experimental study of the traffic distribution in the city of Valencia, Spain, characterizing the different streets of the city in terms of vehicle load with respect to the travel time during rush hour traffic conditions. Experimental results based on realistic vehicular traffic traces from the city of Valencia show that only some street segments fall under the general theory of vehicular flow, offering a good fit using quadratic regression, while a great number of street segments fall under other categories. Although in some cases such discrepancies are related to lack of traffic, injecting additional vehicles shows that significant mismatches still persist. Thus, in this paper we propose an equation to characterize travel times over a segment belonging to the sigmoid family; specifically, we apply logistic regression, being able to significantly improve the curve fitting results for most of the street segments under analysis. Based on our regression results, we performed a clustering analysis of the different street segments, showing that they can be classified into three well-defined categories, which evidences a predictable traffic distribution using the logistic regression throughout the city during rush hours, and allows optimizing the traffic for automated vehicles.