Polytechnic Institute of Porto

IMPORTANCE: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEW: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). FINDINGS: In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCE: The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

Adipose tissue is no longer considered to be an inert tissue that stores fat. This tissue is capable of expanding to accommodate increased lipids through hypertrophy of existing adipocytes and by initiating differentiation of pre-adipocytes. Adipose tissue metabolism exerts an impact on whole-body metabolism. As an endocrine organ, adipose tissue is responsible for the synthesis and secretion of several hormones. These are active in a range of processes, such as control of nutritional intake (leptin, angiotensin), control of sensitivity to insulin and inflammatory process mediators (tumor necrosis factor α (TNF-α), interleukin-6 (IL-6), resistin, visfatin, adiponectin, among others) and pathways (plasminogen activator inhibitor 1 (PAI-1) and acylation stimulating protein (ASP) for example). This paper reviews some of the biochemical and metabolic aspects of adipose tissue and its relationship to inflammatory disease and insulin resistance.

Reactivation of telomerase has been implicated in human tumorigenesis, but the underlying mechanisms remain poorly understood. Here we report the presence of recurrent somatic mutations in the TERT promoter in cancers of the central nervous system (43%), bladder (59%), thyroid (follicular cell-derived, 10%) and skin (melanoma, 29%). In thyroid cancers, the presence of TERT promoter mutations (when occurring together with BRAF mutations) is significantly associated with higher TERT mRNA expression, and in glioblastoma we find a trend for increased telomerase expression in cases harbouring TERT promoter mutations. Both in thyroid cancers and glioblastoma, TERT promoter mutations are significantly associated with older age of the patients. Our results show that TERT promoter mutations are relatively frequent in specific types of human cancers, where they lead to enhanced expression of telomerase. Reactivation of telomerase has been implicated in human tumorigenesis. Here, somatic mutations in the TERT promoter are reported in cancers of the central nervous system, bladder, follicular cell-derived thyroid and melanoma, thus demonstrating that TERTpromoter mutations are a frequent event in human cancer.

Abstract Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities 1,2 . This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity 3–6 . Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017—and more than 80% in some low- and middle-income regions—was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing—and in some countries reversal—of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.

Chromones are a group of naturally occurring compounds that are ubiquitous in nature, especially in plants. The word chromone is derived from the Greek word chroma, meaning “color”, which point out that many chromone derivatives can exhibit a diversity of colors.

Radio link quality estimation in Wireless Sensor Networks (WSNs) has a fundamental impact on the network performance and also affects the design of higher-layer protocols. Therefore, for about a decade, it has been attracting a vast array of research works. Reported works on link quality estimation are typically based on different assumptions, consider different scenarios, and provide radically different (and sometimes contradictory) results. This article provides a comprehensive survey on related literature, covering the characteristics of low-power links, the fundamental concepts of link quality estimation in WSNs, a taxonomy of existing link quality estimators, and their performance analysis. To the best of our knowledge, this is the first survey tackling in detail link quality estimation in WSNs. We believe our efforts will serve as a reference to orient researchers and system designers in this area.

Sustainable development addresses humanity’s aspiration for a better life while observing the limitations imposed by nature. In 2015, the United Nations General Assembly approved the 17 Sustainable Development Goals (SDGs) with the aim to foster the organizational operationalization and integration of sustainability and, therefore, to address the current and forthcoming stakeholder needs and ensure a better and sustainable future for all, balancing the economic, social, and environmental development. However, it is not entirely clear which are the mutual relationships among the 17 SDGs and this study aims to tackle this research gap. The results of the correlation confirm that Poverty elimination (SDG1) and Good health and well-being (SDG3) have synergetic relationships with most of the other goals. SDG7 (Affordable and clean energy) has significant relationships with other SDGs (e.g., SDG1 (No poverty), SDG2 (Zero hunger), SDG3 (Good health and well-being), SDG8 (Decent work and economic growth), SDG13 (Climate action)). However, there is a moderate negative correlation with SDG12 (Responsible consumption and production), which emphasizes the need to improve energy efficiency, increase the share of clean and renewable energies and improve sustainable consumption patterns worldwide. There is also confirmation that SDG12 (Responsible consumption and production) is the goal strongly associated with trade-offs. To sum up, this research suggests that change towards achieving the Sustainable Development Goals offers many opportunities for reinforcing rather than inhibiting itself. However, some SDGs show no significant correlation with other SDGs (e.g., SDG13 (Climate action) and SDG17 (Partnerships for the goals), which highlights the need for future research.

This paper presents a review of definitions of fractional order derivatives and integrals that appear in mathematics, physics, and engineering.

Plants and microbes coexist or compete for survival and their cohesive interactions play a vital role in adapting to metalliferous environments, and can thus be explored to improve microbe-assisted phytoremediation. Plant root exudates are useful nutrient and energy sources for soil microorganisms, with whom they establish intricate communication systems. Some beneficial bacteria and fungi, acting as plant growth promoting microorganisms (PGPMs), may alleviate metal phytotoxicity and stimulate plant growth indirectly via the induction of defense mechanisms against phytopathogens, and/or directly through the solubilization of mineral nutrients (nitrogen, phosphate, potassium, iron, etc.), production of plant growth promoting substances (e.g., phytohormones), and secretion of specific enzymes (e.g., 1-aminocyclopropane-1-carboxylate deaminase). PGPM can also change metal bioavailability in soil through various mechanisms such as acidification, precipitation, chelation, complexation, and redox reactions. This review presents the recent advances and applications made hitherto in understanding the biochemical and molecular mechanisms of plant-microbe interactions and their role in the major processes involved in phytoremediation, such as heavy metal detoxification, mobilization, immobilization, transformation, transport, and distribution.

Physical vapour deposition (PVD) is a well-known technology that is widely used for the deposition of thin films regarding many demands, namely tribological behaviour improvement, optical enhancement, visual/esthetic upgrading, and many other fields, with a wide range of applications already being perfectly established. Machining tools are, probably, one of the most common applications of this deposition technique, sometimes used together with chemical vapour deposition (CVD) in order to increase their lifespan, decreasing friction, and improving thermal properties. However, the CVD process is carried out at higher temperatures, inducing higher stresses in the coatings and substrate, being used essentially only when the required coating needs to be deposited using this process. In order to improve this technique, several studies have been carried out optimizing the PVD technique by increasing plasma ionization, decreasing dark areas (zones where there is no deposition into the reactor), improving targets use, enhancing atomic bombardment efficiency, or even increasing the deposition rate and optimizing the selection of gases. These studies reveal a huge potential in changing parameters to improve thin film quality, increasing as well the adhesion to the substrate. However, the process of improving energy efficiency regarding the industrial context has not been studied as deeply as required. This study aims to proceed to a review regarding the improvements already studied in order to optimize the sputtering PVD process, trying to relate these improvements with the industrial requirements as a function of product development and market demand.

COVID-19 has caused dramatic effects on the world economy, business activities, and people. But digitization is also helping many companies to adapt and overcome the current situation caused by COVID-19. The growth in the use of technology in the daily lives of people and companies to face this exceptional situation is an evidence of the digital acceleration process. This exploratory study analyzes the impact of digital transformation processes in three business areas: labor and social relations, marketing and sales, and technology. The impact of digitalization is expected to be transversal to each area and will encourage the emergence of new digital products and services based on the principle of flexibility. Additionally, new ways of working will foster the demand for new talent regardless of people's geographical location. Moreover, cybersecurity and privacy will become two key elements that will support the integrated development of the Internet of Things technology solutions, artificial intelligence, big data, and robotics.

The integration of artificial intelligence (AI) into medical imaging has guided in an era of transformation in healthcare. This literature review explores the latest innovations and applications of AI in the field, highlighting its profound impact on medical diagnosis and patient care. The innovation segment explores cutting-edge developments in AI, such as deep learning algorithms, convolutional neural networks, and generative adversarial networks, which have significantly improved the accuracy and efficiency of medical image analysis. These innovations have enabled rapid and accurate detection of abnormalities, from identifying tumors during radiological examinations to detecting early signs of eye disease in retinal images. The article also highlights various applications of AI in medical imaging, including radiology, pathology, cardiology, and more. AI-based diagnostic tools not only speed up the interpretation of complex images but also improve early detection of disease, ultimately delivering better outcomes for patients. Additionally, AI-based image processing facilitates personalized treatment plans, thereby optimizing healthcare delivery. This literature review highlights the paradigm shift that AI has brought to medical imaging, highlighting its role in revolutionizing diagnosis and patient care. By combining cutting-edge AI techniques and their practical applications, it is clear that AI will continue shaping the future of healthcare in profound and positive ways.

Thin films of Cu 2 SnS 3 and Cu 3 SnS 4 were grown by sulfurization of dc magnetron sputtered Sn–Cu metallic precursors in a S 2 atmosphere. Different maximum sulfurization temperatures were tested which allowed the study of the Cu 2 SnS 3 phase changes. For a temperature of 350 °C the films were composed of tetragonal ( I -42 m ) Cu 2 SnS 3 . The films sulfurized at a maximum temperature of 400 °C presented a cubic ( F -43 m ) Cu 2 SnS 3 phase. On increasing the temperature up to 520 °C, the Sn content of the layer decreased and orthorhombic ( Pmn 21) Cu 3 SnS 4 was formed. The phase identification and structural analysis were performed using x-ray diffraction (XRD) and electron backscattered diffraction (EBSD) analysis. Raman scattering analysis was also performed and a comparison with XRD and EBSD data allowed the assignment of peaks at 336 and 351 cm −1 for tetragonal Cu 2 SnS 3 , 303 and 355 cm −1 for cubic Cu 2 SnS 3 , and 318, 348 and 295 cm −1 for the Cu 3 SnS 4 phase. Compositional analysis was done using energy dispersive spectroscopy and induced coupled plasma analysis. Scanning electron microscopy was used to study the morphology of the layers. Transmittance and reflectance measurements permitted the estimation of absorbance and band gap. These ternary compounds present a high absorbance value close to 10 4 cm −1 . The estimated band gap energy was 1.35 eV for tetragonal ( I -42 m ) Cu 2 SnS 3 , 0.96 eV for cubic ( F -43 m ) Cu 2 SnS 3 and 1.60 eV for orthorhombic ( Pmn 21) Cu 3 SnS 4 . A hot point probe was used for the determination of semiconductor conductivity type. The results show that all the samples are p-type semiconductors. A four-point probe was used to obtain the resistivity of these samples. The resistivities for tetragonal Cu 2 SnS 3 , cubic Cu 2 SnS 3 and orthorhombic ( Pmn 21) Cu 3 SnS 4 are 4.59 × 10 −2 Ω cm, 1.26 × 10 −2 Ω cm, 7.40 × 10 −4 Ω cm, respectively.

Quinoxaline derivatives are an important class of heterocycle compounds, where N replaces some carbon atoms in the ring of naphthalene. Its molecular formula is C8H6N2, formed by the fusion of two aromatic rings, benzene and pyrazine. It is rare in natural state, but their synthesis is easy to perform. In this review the State of the Art will be presented, which includes a summary of the progress made over the past years in the knowledge of the structure and mechanism of the quinoxaline and quinoxaline derivatives, associated medical and biomedical value as well as industrial value. Modifying quinoxaline structure it is possible to obtain a wide variety of biomedical applications, namely antimicrobial activities and chronic and metabolic diseases treatment.

Experience economy is the last segment in the evolution of the market, and it is characterized by the fact that consumers do not acquire goods, products or services, but experiences that they integrate in their biography, and consequently in their identity. Customer Experience, possibly the latest revolution in business thinking along with the digital transformation, seeks the design and management of truly customer-centric experiences. This revolution is spreading across different sectors, among which the health sector should necessarily be considered. This talk covers the fundamental ideas within the concept of customer experience, as well as it provides information and suggestions about how to design and deliver an optimal patient experience.

This manuscript describes the detailed characterization of edible films made from two different protein products e whey protein isolate (WPI) and whey protein concentrate (WPC), added with three levels of glycerol (Gly) e i.e. 40, 50 and 60%(w/w). The molecular structure, as well as barrier, tensile, thermal, surface and optical properties of said films were determined, in attempts to provide a better understanding of the effects of proteinaceous purity and Gly content of the feedstock. WPI films exhibited statistically lower (p < 0.05) moisture content (MC), film solubility (S), water activity, water vapor permeability (WVP), oxygen and carbon dioxide permeabilities (O 2 P and CO 2 P, respectively) and color change values, as well as statistically higher (p < 0.05) density, surface hydrophobicity, mechanical resistance, elasticity, extensibility and transparency values than their WPC counterparts, for the same content of Gly. These results are consistent with data from thermal and FTIR analyses. Furthermore, a significant increase (p < 0.05) was observed in MC, S, WVP, O 2 P, CO 2 P, weight loss and extensibility of both protein films when the Gly content increased; whereas a significant decrease (p < 0.05) was observed in thermal features, as well as in mechanical resistance and elasticity e thus leading to weaker films. Therefore, fundamental elucidation was provided on the features of WPI and WPC germane to food packaging e along with suggestions to improve the most critical ones, i.e. extensibility and WVP.

This paper presents an electricity consumer characterization framework based on a knowledge discovery in databases (KDD) procedure, supported by data mining (DM) techniques, applied on the different stages of the process. The core of this framework is a data mining model based on a combination of unsupervised and supervised learning techniques. Two main modules compose this framework: the load profiling module and the classification module. The load profiling module creates a set of consumer classes using a clustering operation and the representative load profiles for each class. The classification module uses this knowledge to build a classification model able to assign different consumers to the existing classes. The quality of this framework is illustrated with a case study concerning a real database of LV consumers from the Portuguese distribution company.

BACKGROUND: Levels of physical activity and variation in physical activity and sedentary time by place and person in European children and adolescents are largely unknown. The objective of the study was to assess the variations in objectively measured physical activity and sedentary time in children and adolescents across Europe. METHODS: Six databases were systematically searched to identify pan-European and national data sets on physical activity and sedentary time assessed by the same accelerometer in children (2 to 9.9 years) and adolescents (≥10 to 18 years). We harmonized individual-level data by reprocessing hip-worn raw accelerometer data files from 30 different studies conducted between 1997 and 2014, representing 47,497 individuals (2-18 years) from 18 different European countries. RESULTS: Overall, a maximum of 29% (95% CI: 25, 33) of children and 29% (95% CI: 25, 32) of adolescents were categorized as sufficiently physically active. We observed substantial country- and region-specific differences in physical activity and sedentary time, with lower physical activity levels and prevalence estimates in Southern European countries. Boys were more active and less sedentary in all age-categories. The onset of age-related lowering or leveling-off of physical activity and increase in sedentary time seems to become apparent at around 6 to 7 years of age. CONCLUSIONS: Two third of European children and adolescents are not sufficiently active. Our findings suggest substantial gender-, country- and region-specific differences in physical activity. These results should encourage policymakers, governments, and local and national stakeholders to take action to facilitate an increase in the physical activity levels of young people across Europe.

We develop a systematic derivation for the Limber approximation to the angular cross-power spectrum of two random fields, as a series expansion in $(\ensuremath{\ell}+1/2{)}^{\ensuremath{-}1}$. This extended Limber approximation can be used to test the accuracy of the Limber approximation and to improve the rate of convergence at large $\ensuremath{\ell}$'s. We show that the error in ordinary Limber approximation is $\mathcal{O}({\ensuremath{\ell}}^{\ensuremath{-}2})$. We also provide a simple expression for the 2nd order correction to the Limber formula, which improves the accuracy to $\mathcal{O}({\ensuremath{\ell}}^{\ensuremath{-}4})$. This correction can be especially useful for narrow redshift bins, or samples with small redshift overlap, for which the 0th order Limber formula has a large error. We also point out that using $\ensuremath{\ell}$ instead of $\ensuremath{\ell}+1/2$, as is often done in the literature, spoils the accuracy of the approximation to $\mathcal{O}({\ensuremath{\ell}}^{\ensuremath{-}1})$.

Ambient intelligence (AmI) deals with a new world of ubiquitous computing devices, where physical environments interact intelligently and unobtrusively with people. These environments should be aware of people's needs, customizing requirements and forecasting behaviors. AmI environments can be diverse, such as homes, offices, meeting rooms, schools, hospitals, control centers, vehicles, tourist attractions, stores, sports facilities, and music devices. Artificial intelligence research aims to include more intelligence in AmI environments, allowing better support for humans and access to the essential knowledge for making better decisions when interacting with these environments. This article, which introduces a special issue on AmI, views the area from an artificial intelligence perspective.