Crowd sensing and forecasting for Smart Cities

Dissertação de mestrado integrado em Engenharia InformáticaA utilização de inteligência sob forma de tecnologia no nosso dia-a-dia é uma realidade em crescimento e, portanto, devemos fazer uso da tecnologia disponível para melhorar várias áreas do nosso quotidiano. Por exemplo, a tecnologia atual permite a conceção de sensores inteligentes, mais especificamente sensores de multidão, para detetar passiva mente dispositivos como smartphones ou smartwatches através de probe requests emitidos por estes dispositivos que, por sua vez, fazem parte de um processo de comunicação que ocorre sempre que o Wi-Fi dos dispositivos está ativado. Adicionalmente, crowd sensing - uma solução de Ambient Intelligence (AmI) - é estudada hoje em dia em várias áreas com bons resultados. Portanto, esta dissertação visa investigar e utilizar sensores de multidão para capturar passivamente dados acerca da densidade de multidões, explorar as capacidades do sensor escolhido, analisar e processar os dados para obter melhores estimativas, e conceber e desenvolver modelos de Machine Learning (ML) para prever a densidade nas áreas sensorizadas. Áreas nas quais o sensor de multidão está inserido - AmI, Smart Cities, Wi-Fi Probing - são estudadas, juntamente com a análise de diferentes abordagens ao crowd sensing, assim como paradigmas e algoritmos de ML. Em seguida, é explicado como os dados foram capturados e analisados, seguido por uma experiência feita às capacidades do sensor. Além disso, é apresentado como os modelos de ML foram concebidos e otimizados. Finalmente, os resultados dos vários testes de ML são discutidos e o modelo com melhor desempenho é apresentado. A investigação e os resultados práticos abrem perspetivas importantes para a implementação deste tipo de soluções na nossa vida diária.Bringing intelligence to our everyday environments is a growing reality and therefore we should take advantage of the technology available to improve several areas of our daily life. For example, current technology allows the conception of smart scanners, more specifically crowd sensors, to passively detect devices such as smartphones or smartwatches through probe requests emitted by such devices, that, in turn, are part of a communication process that happens every time the devices’ Wi-Fi is enabled. Additionally, crowd sensing - an Ambient Intelligence (AmI) solution - is being studied nowadays in several areas with good results. Therefore, this dissertation aims to research and use crowd sensors to passively collect crowd density data, explore the capabilities of the chosen sensor, analyse and process the data to get better estimations and conceive and develop Machine Learning (ML) models to forecast the density of the sensed areas. Areas in which crowd sensing is inserted - AmI, Smart Cities, Wi-Fi probing - are studied, along with the analysis of different crowd sensing approaches and ML paradigms and algorithms. Then, it’s explained how the data was collected and analysed together with the insights obtained from it, followed by an experiment done on the crowd sensor capabilities. Moreover, it’s presented how the ML models were conceived and tuned. Finally, the results from the ML several tests are discussed and the best performing model is found. The investigation, together with practical results, opens important perspectives for the implementation of these kinds of solutions in our daily lives

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe

Post-intervention Status in Patients With Refractory Myasthenia Gravis Treated With Eculizumab During REGAIN and Its Open-Label Extension

OBJECTIVE: To evaluate whether eculizumab helps patients with anti-acetylcholine receptor-positive (AChR+) refractory generalized myasthenia gravis (gMG) achieve the Myasthenia Gravis Foundation of America (MGFA) post-intervention status of minimal manifestations (MM), we assessed patients' status throughout REGAIN (Safety and Efficacy of Eculizumab in AChR+ Refractory Generalized Myasthenia Gravis) and its open-label extension. METHODS: Patients who completed the REGAIN randomized controlled trial and continued into the open-label extension were included in this tertiary endpoint analysis. Patients were assessed for the MGFA post-intervention status of improved, unchanged, worse, MM, and pharmacologic remission at defined time points during REGAIN and through week 130 of the open-label study. RESULTS: A total of 117 patients completed REGAIN and continued into the open-label study (eculizumab/eculizumab: 56; placebo/eculizumab: 61). At week 26 of REGAIN, more eculizumab-treated patients than placebo-treated patients achieved a status of improved (60.7% vs 41.7%) or MM (25.0% vs 13.3%; common OR: 2.3; 95% CI: 1.1-4.5). After 130 weeks of eculizumab treatment, 88.0% of patients achieved improved status and 57.3% of patients achieved MM status. The safety profile of eculizumab was consistent with its known profile and no new safety signals were detected. CONCLUSION: Eculizumab led to rapid and sustained achievement of MM in patients with AChR+ refractory gMG. These findings support the use of eculizumab in this previously difficult-to-treat patient population. CLINICALTRIALSGOV IDENTIFIER: REGAIN, NCT01997229; REGAIN open-label extension, NCT02301624. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that, after 26 weeks of eculizumab treatment, 25.0% of adults with AChR+ refractory gMG achieved MM, compared with 13.3% who received placebo

Minimal Symptom Expression' in Patients With Acetylcholine Receptor Antibody-Positive Refractory Generalized Myasthenia Gravis Treated With Eculizumab

The efficacy and tolerability of eculizumab were assessed in REGAIN, a 26-week, phase 3, randomized, double-blind, placebo-controlled study in anti-acetylcholine receptor antibody-positive (AChR+) refractory generalized myasthenia gravis (gMG), and its open-label extension

Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity

Safety and efficacy of eculizumab in anti-acetylcholine receptor antibody-positive refractory generalised myasthenia gravis (REGAIN): a phase 3, randomised, double-blind, placebo-controlled, multicentre study

Background Complement is likely to have a role in refractory generalised myasthenia gravis, but no approved therapies specifically target this system. Results from a phase 2 study suggested that eculizumab, a terminal complement inhibitor, produced clinically meaningful improvements in patients with anti-acetylcholine receptor antibody-positive refractory generalised myasthenia gravis. We further assessed the efficacy and safety of eculizumab in this patient population in a phase 3 trial. Methods We did a phase 3, randomised, double-blind, placebo-controlled, multicentre study (REGAIN) in 76 hospitals and specialised clinics in 17 countries across North America, Latin America, Europe, and Asia. Eligible patients were aged at least 18 years, with a Myasthenia Gravis-Activities of Daily Living (MG-ADL) score of 6 or more, Myasthenia Gravis Foundation of America (MGFA) class II\ue2\u80\u93IV disease, vaccination against Neisseria meningitides, and previous treatment with at least two immunosuppressive therapies or one immunosuppressive therapy and chronic intravenous immunoglobulin or plasma exchange for 12 months without symptom control. Patients with a history of thymoma or thymic neoplasms, thymectomy within 12 months before screening, or use of intravenous immunoglobulin or plasma exchange within 4 weeks before randomisation, or rituximab within 6 months before screening, were excluded. We randomly assigned participants (1:1) to either intravenous eculizumab or intravenous matched placebo for 26 weeks. Dosing for eculizumab was 900 mg on day 1 and at weeks 1, 2, and 3; 1200 mg at week 4; and 1200 mg given every second week thereafter as maintenance dosing. Randomisation was done centrally with an interactive voice or web-response system with patients stratified to one of four groups based on MGFA disease classification. Where possible, patients were maintained on existing myasthenia gravis therapies and rescue medication was allowed at the study physician's discretion. Patients, investigators, staff, and outcome assessors were masked to treatment assignment. The primary efficacy endpoint was the change from baseline to week 26 in MG-ADL total score measured by worst-rank ANCOVA. The efficacy population set was defined as all patients randomly assigned to treatment groups who received at least one dose of study drug, had a valid baseline MG-ADL assessment, and at least one post-baseline MG-ADL assessment. The safety analyses included all randomly assigned patients who received eculizumab or placebo. This trial is registered with ClinicalTrials.gov, number NCT01997229. Findings Between April 30, 2014, and Feb 19, 2016, we randomly assigned and treated 125 patients, 62 with eculizumab and 63 with placebo. The primary analysis showed no significant difference between eculizumab and placebo (least-squares mean rank 56\uc2\ub76 [SEM 4\uc2\ub75] vs 68\uc2\ub73 [4\uc2\ub75]; rank-based treatment difference \ue2\u88\u9211\uc2\ub77, 95% CI \ue2\u88\u9224\uc2\ub73 to 0\uc2\ub796; p=0\uc2\ub70698). No deaths or cases of meningococcal infection occurred during the study. The most common adverse events in both groups were headache and upper respiratory tract infection (ten [16%] for both events in the eculizumab group and 12 [19%] for both in the placebo group). Myasthenia gravis exacerbations were reported by six (10%) patients in the eculizumab group and 15 (24%) in the placebo group. Six (10%) patients in the eculizumab group and 12 (19%) in the placebo group required rescue therapy. Interpretation The change in the MG-ADL score was not statistically significant between eculizumab and placebo, as measured by the worst-rank analysis. Eculizumab was well tolerated. The use of a worst-rank analytical approach proved to be an important limitation of this study since the secondary and sensitivity analyses results were inconsistent with the primary endpoint result; further research into the role of complement is needed. Funding Alexion Pharmaceuticals

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press

Consistent improvement with eculizumab across muscle groups in myasthenia gravis

Objective: To assess whether eculizumab, a terminal complement inhibitor, improves patient- and physician-reported outcomes (evaluated using the myasthenia gravis activities of daily living profile and the quantitative myasthenia gravis scale, respectively) in patients with refractory anti-acetylcholine receptor antibody-positive generalized myasthenia gravis across four domains, representing ocular, bulbar, respiratory, and limb/gross motor muscle groups. Methods: Patients with refractory anti-acetylcholine receptor antibody-positive generalized myasthenia gravis were randomized 1:1 to receive either placebo or eculizumab during the REGAIN study (NCT01997229). Patients who completed REGAIN were eligible to continue into the open-label extension trial (NCT02301624) for up to 4 years. The four domain scores of each of the myasthenia gravis activities of daily living profile and the quantitative myasthenia gravis scale recorded throughout REGAIN and through 130 weeks of the open-label extension were analyzed. Results: Of the 125 patients who participated in REGAIN, 117 enrolled in the open-label extension; 61 had received placebo and 56 had received eculizumab during REGAIN. Patients experienced rapid improvements in total scores and all four domain scores of both the myasthenia gravis activities of daily living profile and the quantitative myasthenia gravis scale with eculizumab treatment. These improvements were sustained through 130 weeks of the open-label extension. Interpretation: Eculizumab treatment elicits rapid and sustained improvements in muscle strength across ocular, bulbar, respiratory, and limb/gross motor muscle groups and in associated daily activities in patients with refractory anti-acetylcholine receptor antibody-positive generalized myasthenia gravis