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The most comprehensive exhibition catalog dedicated to the work of Brazilian artist Tarsila do Amaral (1886-1973), a pioneering figure in Latin American modernism. The focus of the exhibition is the popular, or the vernacular, a notion as complex in Brazil as it is contested, and which Tarsila explored in different ways throughout her career. The popular is associated with debates on national art or identity and the invention or construction of brasilidade, Brazilianness. In Tarsila, the popular is manifested in landscapes of the countryside or the suburbs, the farm or the favela, populated by people of indigenous or African descent, characters from Brazilian folklore, full of animals and plants, both real and fantastic. But Tarsila's palette (which served as inspiration for the colors of the exhibition design) is also popular: \"pure blue, violaceous rose, bright yellow, singing green.\" Much of the art criticism on Tarsila to this day in Brazil has emphasized her French affiliations and genealogies, possibly in search of the artist's international legitimization, but thus marginalizing the themes, characters, and popular narratives that she constructed. Today, after successful shows in the United States and Europe, we can look at Tarsila in other ways. In this sense, the essays and commentaries on her works included in the exhibition and in the catalog are central elements of this project. It is not by chance that the controversial painting A Negra [The Negress] has received special attention from the authors and is a central work in the exhibition. Tarsila do Amaral: Cannibalizing Modernism does not seek to exhaust all these discussions, which take into account questions of race, class and colonialism. But the project does point to the need to study this artist, so fundamental in our art history, from new perspectives and approaches. This exhibition is part of a series that MASP has organized reassessing the notion of the popular in Brazil: from A mنao do povo brasileiro, 1969/2016 [The Hand of the Brazilian People, 1969/2016] and Portinari popular [Popular Portinari] in 2016 to Agostinho Batista de Freitas in 2017 and Maria Auxiliadora in 2018. Tarsila do Amaral: Cannibalizing Modernism is contextualized in a full year dedicated to women artists at the museum in 2019 under the heading Women's Histories, Feminist Histories. The exhibition dialogues with two others dedicated to artists who explored the notion of the popular through different approaches: Djanira: Picturing Brazil, on view through May 19th, and Lina Bo Bardi: Habitat, on view through July 28th.

Lupinus albus L. (lupine) is a legume whose grain/seed has gained increasing interest. Its recognized nutritional properties, namely a high content of protein, dietary fiber and its low fat content, make lupine a suitable alternative not only for animal protein, but also as a substitute for more processed and less balanced flours from a nutritional point of view, used in the preparation of bread, cakes and cookies, among others. In addition, its nutritional and bioactive compounds have potential benefits for human health in the prevention and treatment of some diseases. However, the existence of some anti-nutritional compounds and contaminants reveal some concern, requiring effective methods for their detection and eventual removal. This review intends to address the potential of lupine (L. albus) in food and human health and to balance the pros and cons. Nutritional and anti-nutritional components of L. albus seeds and possible contaminants of lupine seeds are examined. The potential health benefits of lupine (seeds), including energy metabolism, cardiovascular diseases, hypertension, glucose and insulin metabolism, bower function and anticonvulsant action, are discussed based on scientific evidence (both clinical trials and studies performed with animal models).

Known as a degenerative and progressive dementia, Alzheimer's disease (AD) affects about 25 million elderly people around the world. This illness results in a decrease in the productivity of people and places limits on their daily lives. Electroencephalography (EEG), in which the electrical brain activity is recorded in the form of time series and analyzed using signal processing techniques, is a well-known neurophysiological AD biomarker. EEG is noninvasive, low-cost, has a high temporal resolution, and provides valuable information about brain dynamics in AD. Here, we present an original approach based on the use of quantile graphs (QGs) for classifying EEG data. QGs map frequency, amplitude, and correlation characteristics of a time series (such as the EEG data of an AD patient) into the topological features of a network. The five topological network metrics used here-clustering coefficient, mean jump length, betweenness centrality, modularity, and Laplacian Estrada index-showed that the QG model can distinguish healthy subjects from AD patients, with open or closed eyes. The QG method also indicates which channels (corresponding to 19 different locations on the patients' scalp) provide the best discriminating power. Furthermore, the joint analysis of delta, theta, alpha, and beta wave results indicate that all AD patients under study display clear symptoms of the disease and may have it in its late stage, a diagnosis known a priori and supported by our study. Results presented here attest to the usefulness of the QG method in analyzing complex, nonlinear signals such as those generated from AD patients by EEGs.

At a moment when the population is increasingly aware and involved in what it eats, both consumers and the food sector are showing more interest in natural foods. This review work discusses, addresses and provides details of the most important aspects of consumer’s perceptions of and attitudes to natural foods and in-depth research into natural sweeteners. It also includes issues about their use and development as regards health impacts, food security and sustainability. In line with our main research outcome, we can assume that consumers are very keen on choosing foods with clean labelling, natural ingredients, preferably with other functional properties, without the loss of taste. In response to such a phenomenon, the food industry offers consumers alternative natural sweeteners with the advantage of added health benefits. It is noteworthy that Nature is a superb source of desirable substances, and many have a sweet taste, and many still need to be studied. Finally, we must stress that being natural does not necessarily guarantee market success.

Computational analysis of electroencephalographic (EEG) signals have shown promising results in detecting brain disorders, such as Alzheimer’s disease (AD). AD is a progressive neurological illness that causes neuron cells degeneration, resulting in cognitive impairment. While there is no cure for AD, early diagnosis is critical to improving the quality of life of affected individuals. Here, we apply six computational time-series analysis methods (wavelet coherence, fractal dimension, quadratic entropy, wavelet energy, quantile graphs and visibility graphs) to EEG records from 160 AD patients and 24 healthy controls. Results from raw and wavelet-filtered (alpha, beta, theta and delta bands) EEG signals show that some of the time-series analysis methods tested here, such as wavelet coherence and quantile graphs, can robustly discriminate between AD patients from elderly healthy subjects. They represent a promising non-invasive and low-cost approach to the AD detection in elderly patients.

Studying the interaction between a system's components and the temporal evolution of the system are two common ways to uncover and characterize its internal workings. Recently, several maps from a time series to a network have been proposed with the intent of using network metrics to characterize time series. Although these maps demonstrate that different time series result in networks with distinct topological properties, it remains unclear how these topological properties relate to the original time series. Here, we propose a map from a time series to a network with an approximate inverse operation, making it possible to use network statistics to characterize time series and time series statistics to characterize networks. As a proof of concept, we generate an ensemble of time series ranging from periodic to random and confirm that application of the proposed map retains much of the information encoded in the original time series (or networks) after application of the map (or its inverse). Our results suggest that network analysis can be used to distinguish different dynamic regimes in time series and, perhaps more importantly, time series analysis can provide a powerful set of tools that augment the traditional network analysis toolkit to quantify networks in new and useful ways.

Food texture is a major food quality parameter. The physicochemical properties of food changes when processed in households or industries, resulting in modified textures. A better understanding of these properties is important for the sensory and textural characteristics of foods that target consumers of all ages, from children to the elderly, especially when food product development is considered for dysphagia. Texture modifications in foods suitable for dysphagic patients will grow as the numbers of elderly citizens increase. Dysphagia management should ensure that texture-modified (TM) food is nutritious and easy to swallow. This review addresses how texture and rheology can be assessed in the food industry by placing particular emphasis on dysphagia. It also discusses how the structure of TM food depends not only on food ingredients, such as hydrocolloids, emulsifiers, and thickening and gelling agents, but also on the applied processing methods, including microencapsulation, microgels as delivery systems, and 3D printing. In addition, we address how to modify texture for individuals with dysphagia in all age groups, and highlight different strategies to develop appropriate food products for dysphagic patients.

Mycobacterium tuberculosis is the main causative agent of tuberculosis. BCG, the only licensed vaccine, provides inadequate protection against pulmonary tuberculosis. Controlled human infection models are useful tools for vaccine development. We aimed to determine a safe dose of aerosol-inhaled live-attenuated Mycobacterium bovis BCG as a surrogate for M tuberculosis infection, then compare the safety and tolerability of infection models established using aerosol-inhaled and intradermally administered BCG. This phase 1 controlled human infection trial was conducted at two clinical research facilities in the UK. Healthy, immunocompetent adults aged 18–50 years, who were both M tuberculosis-naive and BCG-naive and had no history of asthma or other respiratory diseases, were eligible for the trial. Participants were initially enrolled into group 1 (receiving the BCG Danish strain); the trial was subsequently paused because of a worldwide shortage of BCG Danish and, after protocol amendment, was restarted using the BCG Bulgaria strain (group 2). After a dose-escalation study, during which participants were sequentially allocated to receive either 1 × 103, 1 × 104, 1 × 105, 1 × 106, or 1 × 107 colony-forming units (CFU) of aerosol BCG, the maximum tolerated dose was selected for the randomised controlled trial. Participants in this trial were randomly assigned (9:12), by variable block randomisation and using sequentially numbered sealed envelopes, to receive aerosol BCG (1 × 107 CFU) and intradermal saline or intradermal BCG (1 × 106 CFU) and aerosol saline. Participants were masked to treatment allocation until day 14. The primary outcome was to compare the safety of a controlled human infection model based on aerosol-inhaled BCG versus one based on intradermally administered BCG, and the secondary outcome was to evaluate BCG recovery in the airways of participants who received aerosol BCG or skin biopsies of participants who received intradermal BCG. BCG was detected by culture and by PCR. The trial is registered at ClinicalTrials.gov, NCT02709278, and is complete. Participants were assessed for eligibility between April 7, 2016, and Sept 29, 2018. For group 1, 15 participants were screened, of whom 13 were enrolled and ten completed the study; for group 2, 60 were screened and 33 enrolled, all of whom completed the study. Doses up to 1 × 107 CFU aerosol-inhaled BCG were sufficiently well tolerated. No significant difference was observed in the frequency of adverse events between aerosol and intradermal groups (median percentage of solicited adverse events per participant, post-aerosol vs post-intradermal BCG: systemic 7% [IQR 2–11] vs 4% [1–13], p=0·62; respiratory 7% [1–19] vs 4% [1–9], p=0·56). More severe systemic adverse events occurred in the 2 weeks after aerosol BCG (15 [12%] of 122 reported systemic adverse events) than after intradermal BCG (one [1%] of 94; difference 11% [95% CI 5–17]; p=0·0013), but no difference was observed in the severity of respiratory adverse events (two [1%] of 144 vs zero [0%] of 97; 1% [−1 to 3]; p=0·52). All adverse events after aerosol BCG resolved spontaneously. One serious adverse event was reported—a participant in group 2 was admitted to hospital to receive analgesia for a pre-existing ovarian cyst, which was deemed unrelated to BCG infection. On day 14, BCG was cultured from bronchoalveolar lavage samples after aerosol infection and from skin biopsy samples after intradermal infection. This first-in-human aerosol BCG controlled human infection model was sufficiently well tolerated. Further work will evaluate the utility of this model in assessing vaccine efficacy and identifying potential correlates of protection. Bill & Melinda Gates Foundation, Wellcome Trust, National Institute for Health Research Oxford Biomedical Research Centre, Thames Valley Clinical Research Network, and TBVAC2020.

The development of renewable energy sources plays a fundamental role in the transition towards a low carbon economy. Considering that renewable energy resources have an intrinsic relationship with meteorological conditions and climate patterns, methodologies based on the remote sensing of the atmosphere are fundamental sources of information to support the energy sector in planning and operation procedures. This Special Issue is intended to provide a highly recognized international forum to present recent advances in remote sensing to data acquisition required by the energy sector. After a review, a total of eleven papers were accepted for publication. The contributions focus on solar, wind, and geothermal energy resource. This editorial presents a brief overview of each contribution.

Mycotoxins are compounds produced by several fungi that contaminate agricultural fields and, either directly or by carry-over, final food products. Animal exposure to these compounds through contaminated feed can lead to their excretion into milk, posing threats to public health. Currently, aflatoxin M1 is the sole mycotoxin with a maximum level set in milk by the European Union, as well as the most studied. Nonetheless, animal feed is known to be contaminated by several groups of mycotoxins with relevance from the food safety point of view that can be carried over into milk. To evaluate the multi-mycotoxin occurrence in this highly consumed food product it is crucial to develop precise and robust analytical methodologies towards their determination. In this sense, an analytical method for the simultaneous identification of 23 regulated, non-regulated, and emerging mycotoxins in raw bovine milk using ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS) was validated. A modified QuEChERS protocol for extraction purposes was used, and further validation was performed by assessing the selectivity and specificity, limits of detection and quantification (LOD and LOQ), linearity, repeatability, reproducibility, and recovery. The performance criteria were compliant with mycotoxin-specific and general European regulations for regulated, non-regulated, and emerging mycotoxins. The LOD and LOQ ranged between 0.001 and 9.88 ng mL−1 and 0.005 and 13.54 ng mL−1, respectively. Recovery values were between 67.5 and 119.8%. The repeatability and reproducibility parameters were below 15 and 25%, respectively. The validated methodology was successfully applied to determine regulated, non-regulated, and emerging mycotoxins in raw bulk milk from Portuguese dairy farms, proving the importance of widening the monitoring scope of mycotoxins in dairy products. Additionality, this method presents itself as a new strategic and integrated biosafety control tool for dairy farms for the analysis of these natural and relevant human risks.