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Introdução: Foi definido pela Organização Mundial da Saúde (OMS) em 2002, o cuidado paliativo comouma abordagem que proporciona qualidade de vida aos pacientes e sua família, frente a doenças que ameaçam a vida, entre elas podemos destacar o câncer. Os cuidados de enfermagem, juntamente com os cuidados paliativos éde grande importância para um bom tratamento e uma boa qualidade de vida para o paciente com o diagnóstico oncológico. Objetivo: Identificar os cuidados de enfermagem, prestados aos pacientes oncológicos em cuidados paliativos, identificar as principais intervenções de enfermagem ao paciente oncológico e sua família, e identificar intervenções de humanização do cuidado. Metodologia: Estudo de abordagem qualitativa, do tipo revisão integrativa da literatura, onde a construção se iniciou através da pergunta de pesquisa ‘’Quais as principais intervenções de enfermagem ao paciente oncológico em cuidados paliativos?’’. Resultados: Da utilização dos critérios de inclusão e exclusão, no total foram selecionados 7 artigos, entre os anos de 2017 e 2022, para compor este estudo, onde 3 artigos são da BDENF e 4 da LILACS. Quanto à metodologia empregada, houve predomínio de estudos com abordagem quantitativa (2) seguidos de qualitativos (4), revisão integrativa da literatura (1). Conclusão: Evidenciou-se a importância e as contribuições do profissional enfermeiro nos cuidados paliativos, a descrição desse profissional para a oferta de uma assistência adequada, humanizada e com qualidade, e a importância de uma comunicação de qualidade entre todos os envolvidos.

Hyperspectral and multispectral image fusion allows us to overcome the hardware limitations of hyperspectral imaging systems inherent to their lower spatial resolution. Nevertheless, existing algorithms usually fail to consider realistic image acquisition conditions. This paper presents a general imaging model that considers inter-image variability of data from heterogeneous sources and flexible image priors. The fusion problem is stated as an optimization problem in the maximum a posteriori framework. We introduce an original image fusion method that, on the one hand, solves the optimization problem accounting for inter-image variability with an iteratively reweighted scheme and, on the other hand, that leverages light-weight CNN-based networks to learn realistic image priors from data. In addition, we propose a zero-shot strategy to directly learn the image-specific prior of the latent images in an unsupervised manner. The performance of the algorithm is illustrated with real data subject to inter-image variability., Comment: IEEE Trans. Geosci. Remote sens., to be published. Manuscript submitted August 23, 2022; revised Dec. 15, 2022, and Mar. 13, 2023; and accepted Apr. 07, 2023

O presente artigo aborda o Estado Democrático de Direito, a partir de contextualização histórica de seu surgimento à concepção atual, que tem como sustentáculo, além das consagradas legalidade, isonomia e participação, a dignidade da pessoa humana. Nesse aspecto, verifica-se não há se falar em dignidade da pessoa humana sem sustentabilidade, já que o ser humano e o meio ambiente são inseparáveis. Em cotejo com a crise ambiental sem precedentes vivenciada, exsurge a necessidade de garantir o Estado Democrático de Direito, que só é atingido com a implementação da sustentabilidade, diante da insuficiência de conceitos outros como desenvolvimento sustentável.

Introduction: Health state valuation and diagnostic-therapeutic pathways at the junction between non-metastatic and metastatic castration-resistant prostate cancer (CRPC) are not well documented. We aimed at: (i) estimating the disability weights (DWs) for health states across a continuum of disease from asymptomatic non-metastatic (nmCRPC) to symptomatic metastatic state (mCRPC); (ii) mapping the diagnostic-therapeutic pathway of nmCRPC in Italy. Methods: Structured qualitative interviews were performed with clinical experts to gather information on nmCRPC clinical pathway. An online survey was administered to clinical experts to estimate DWs for four CRPC health states defined from interviews and literature review (i.e., nmCRPC, asymptomatic mCRPC, symptomatic mCRPC, mCRPC in progression during or after chemotherapy). Clinicians’ preferences for health states were elicited using the Person-Trade-Off (PTO) and Visual Analogue Scale (VAS) methods. DWs associated with each health state, from 0 (best imaginable health state) and 1 (worst imaginable health state), were estimated. Results: We found that the management of nmCRPC is heterogeneous across Italian regions and hospitals, especially with respect to diagnostic imaging techniques. DWs for PTO ranged from 0.415 (95% confidence interval [CI] 0.208-0.623) in nmCRPC to 0.740 (95% CI 0.560-0.920) in mCRPC, in progression during or after chemotherapy. DWs for VAS ranged between 0.246 (95% CI 0.131-0.361) in nmCRPC to 0.689 (95% CI 0.583-0.795) in mCRPC, in progression during or after chemotherapy. Conclusions: Estimated DWs suggest that delaying transition to a metastatic state might ease the disease burden at both patient and societal levels.

A Physalis angulata L. se desenvolve como planta silvestre nas zonas tropicais da América, sendo o seu centro de origem indeterminado. Objetivou-se avaliar diferentes doses de giberelina na germinação de sementes Physalis. A pesquisa foi realizada no laboratório de Sementes e propagação de plantas do Instituto Federal do Espírito Santo (IFES) – Campus Santa Teresa. Foram utilizadas 500 sementes de Physalis, distribuídas em delineamento inteiramente casualizado com 5 tratamentos e 4 repetições, sendo cada tratamento composto por 50 sementes imersas durante 30 minutos em água 26°C (testemunha), água com gelo (0°C), água fervente (100°C), geladeira (10°C) por 24 horas e congelador (-10°C) por 6 horas, conduzido em rolo de papel germitest, umedecido com água destilada na proporção de 2,5 vezes o peso do papel, armazenado em câmara de germinação tipo BOD, com temperatura de 25º C e luz controlada 12x12 horas. Após início de germinação e durante 30 dias, foram avaliados a porcentagem de germinação, o índice de velocidade de germinação e o tempo médio de germinação ao longo do período de germinação. Os tratamentos térmicos com Gelo (0°C), geladeira (10°C) por 24 horas e congelador (-10°C) por 6 horas apresentaram os melhores resultados para germinação, sendo que no tempo médio de germinação, o tratamento Congelador (-10°C), apresentou-se superior aos demais tratamentos com menor tempo médio de germinação. O tratamento térmico atuou de forma positiva para germinação de sementes de Physalis, sendo que o tratamento em congelador (-10°C), apresentou no geral, os melhores resultados.

A pesquisa foi realizada com o objetivo de avaliar diferentes doses de giberelina na emergência de plântulas de urucum e realizado no viveiro de mudas do Instituto Federal do Espírito Santo – Campus Santa Teresa, submetendo as sementes aos seguintes tratamentos: imersão por 30 minutos em: água (testemunha); solução de giberelina a 1.000 mg.L-1, 2.000 mg.L-1, 3.000 mg.L-1 e 4.000 mg.L-1. O delineamento experimental foi inteiramente casualizado (DIC), com 5 tratamentos e quatro repetições, com cada unidade experimental composto de 25 sementes, semeadas em tubetes de 280 mL. Após 30 dias do início da germinação, foi avaliada a porcentagem de emergência (E), índice de velocidade de germinação (IVE) e tempo médio de emergência (TME). O tratamento com giberelina na dosagem de 4.000 mg.L-1 apresentou o melhor resultado para emergência em plântulas de urucuzeiro, podendo este tratamento ser recomendado para esta espécie.

O substrato é importante na formação da muda, devendo apresentar condições adequadas à germinação e desenvolvimento do sistema radicular das plântulas. Objetivou-se, com este trabalho, avaliar a emergência de plântulas de tomate (Solanum lycopersicum) submetidas à diferentes doses de PROTAMIN GR. O experimento foi conduzido em viveiro instalado no setor de Fruticultura do Instituto Federal do Espirito Santo Campus Santa Teresa, ES. O delineamento experimental utilizado foi o de blocos casualizados, sendo composto por seis tratamentos de 25 plantas em quatro repetições, perfazendo 100 plantas por tratamento. Os tratamentos utilizados foram: Bioplant®; Bioplant® + 2% Protamin; Bioplant® + 4% Protamin; Bioplant® + 6% Protamin; Bioplant® + 8% Protamin e Bioplant® + 10% Protamin. Foram avaliados Emergência (E), Índice de Velocidade de Emergência (IVE) e Tempo médio de Emergência (TME). As mudas produzidas nas misturas com 4% de Protamin GR apresentaram melhor desempenho para emergência das plântulas. O uso deste fertilizante incorporados no substrato pode ser uma alternativa viável na produção de mudas de tomate.

Few extracts of plant species from the Brazilian flora have been validated from a pharmacological and clinical point of view, and it is important to determine whether their traditional use is proven by pharmacological effects. Cenostigma pluviosum var. peltophoroides is one of those plants, which belongs to the Fabaceae family that is widely used in traditional medicine and is very rich in tannins. Due to the lack of effective drugs to treat severe cases of Covid-19, the main protease of SARS-CoV-2 (Mpro) becomes an attractive target in the research for new antivirals since this enzyme is crucial for virus replication and does not have homologs in humans. This study aimed to prospect inhibitor candidates among the compounds from C. pluviosum extract, by virtual screening simulations using SARS-CoV-2 Mpro as target. Experimental validation was made by inhibitory proteolytic assays of recombinant Mpro and by antiviral activity with infected Vero cells. Docking simulations identify four compounds with potential inhibitory activity of Mpro present in the extract. The compound pentagalloylglucose showed the best result in proteolytic kinetics experiments, with suppression of recombinant Mpro activity by approximately 60%. However, in experiments with infected cells ethyl acetate fraction and sub-fractions, F2 and F4 of C. pluviosum extract performed better than pentagalloylglucose, reaching close to 100% of antiviral activity. The prominent activity of the extract fractions in infected cells may be a result of a synergistic effect from the different hydrolyzable tannins present, performing simultaneous action on Mpro and other targets from SARS-CoV-2 and host. Communicated by Ramaswamy H. Sarma

The folder contains the scripts and the datasets to generate the figures presented in our manuscript and supplementary material. Details on how to run the scripts are given in the readme file.

The folder contains the scripts and the datasets to generate the figures presented in our manuscript and supplementary material. Details on how to run the scripts are given in the readme file.

Multitemporal hyperspectral unmixing (MTHU) is a fundamental tool in the analysis of hyperspectral image sequences. It reveals the dynamical evolution of the materials (endmembers) and of their proportions (abundances) in a given scene. However, adequately accounting for the spatial and temporal variability of the endmembers in MTHU is challenging, and has not been fully addressed so far in unsupervised frameworks. In this work, we propose an unsupervised MTHU algorithm based on variational recurrent neural networks. First, a stochastic model is proposed to represent both the dynamical evolution of the endmembers and their abundances, as well as the mixing process. Moreover, a new model based on a low-dimensional parametrization is used to represent spatial and temporal endmember variability, significantly reducing the amount of variables to be estimated. We propose to formulate MTHU as a Bayesian inference problem. However, the solution to this problem does not have an analytical solution due to the nonlinearity and non-Gaussianity of the model. Thus, we propose a solution based on deep variational inference, in which the posterior distribution of the estimated abundances and endmembers is represented by using a combination of recurrent neural networks and a physically motivated model. The parameters of the model are learned using stochastic backpropagation. Experimental results show that the proposed method outperforms state of the art MTHU algorithms.

Made available in DSpace on 2022-04-28T17:23:33Z (GMT). No. of bitstreams: 0 Previous issue date: 2022-04-06 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) UNIVATES Tobacco is a rich source of cellulosic material and one of the most cultivated non-food plants in the world with great potential for incorporation in polymeric matrices. The use of tobacco residues as reinforcing filler requires chemical/physical fiber treatment aiming to maximize compatibility with the polymer. In this study, tobacco residues were treated with two concentrations of NaOH (10 or 15 wt.%) at two-time exposures (3 or 5 h). Four distinct heating rates were used for each condition. It was applied an artificial neural network to model the thermogravimetric curves. After, the fitted ANN curves were used to create a 3D surface response. The equations from 3D surface response allowed the creation of thermogravimetric curves in any heating rate situated between the minimum and maximum range tested. Univ Caxias Sul, Programa Posgrad Engn Proc Tecnol PGEPROTEC, Rua Francisco Getulio Vargas, BR-1130 Caxias Do Sul, RS, Brazil Univ Vale Taquari UNIVATES, Ciencias Exatas & Engn, Av Avelino Talini 171, Lajeado, RS, Brazil Univ Fed Integracao LatinoAmer UNILA, Engn Mat, Foz Do Iguacu, Brazil Univ Estadual Paulista Unesp, Escola Engn, Dept Mat & Tecnol, Guaratingueta, SP, Brazil Univ Estadual Paulista Unesp, Escola Engn, Dept Mat & Tecnol, Guaratingueta, SP, Brazil

Cardiac rehabilitation (CR) is a class I recommendation after valvular surgery. Few data exist on the level of access to CR after surgical aortic valve replacement (SAVR), and the factors affecting the probability of timely access to CR after SAVR have never been empirically investigated. This study aims at estimating the proportion of SAVR patients who initiated timely CR and understanding to what extent timely access to CR for SAVR patients is influenced by specific characteristics of patients and hospitals.We conducted a real-world, retrospective, population-based study by identifying from the Italian National Hospital Discharge Records all the discharged alive SAVR patients who accessed timely CR from 2009-2016. Two different cutoffs for timely access were considered, i.e. one and 21 days after discharge. A unique dataset was constructed by merging several data sources. Multiple logistic regressions were performed to identify the factors influencing the probability to access to timely CR.107,545 patients underwent SAVR in Italy from 2009-2016 and were discharged alive. Overall, 71,593 SAVR patients (66.6%) accessed timely CR, with an increasing trend over time. Additional 6,149 patients (5.7%) started CR from 2-21 days after discharge, slightly decreasing over time. The probability of timely CR (one-day cutoff) was significantly higher in older (OR=1.025, p0.001) female patients (OR = 1.003, p0.05) and patients with cardiovascular and cerebrovascular comorbidities. Presence of rehabilitation wards and number of rehabilitation beds in the index hospital significantly increased the probability of timely access to CR (OR = 1.105, p0.001 and OR = 1.006, p0.001 respectively). Patients hospitalized in private teaching hospitals had the highest predicted probability of timely CR after SAVR. A substantial variation in access to CR was found across Italian regions. Similar results were obtained with the alternative 21-days cutoff.Approximately one-third of SAVR patients did not benefit from CR in Italy, mainly due to shortness of rehabilitation facilities, with relevant disparities across the country. The cessation of CR services during the COVID-19 pandemic provides the opportunity to re-think and innovate CR, shifting from center-based to home-based models. Digital health technologies can supplement traditional health services and grant safe, effective, and equitable access to care, especially for countries with insufficient rehabilitation bed capacity. As CR is associated with better outcomes, we recommend decision-makers to use our results to plan adequate healthcare services, also investing in digital health, to ensure patients' access to cost-effective care.

Este trabalho é fruto de discussões e aprendizados de duas pesquisadoras e de suas análises geográficas feministas. Tivemos como objetivo, discutir como a ciência geográfica, principalmente na área da saúde, necessita utilizar de metodologias feministas para compreender as iniquidades sociais, bem como os determinantes de saúdes, pois é a partir do olhar dessas teorias, como o conceito de interseccionalidade, que será passível de compreender as formas de opressão-dominação existentes na sociedade, pois é o alicerce do sistema patriarcal-capitalista-racista que determina desigualdades nos sujeitos sociais. Entendendo que para promovermos saúdes necessitamos dos feminismos, como luta, movimento social e metodologia, para que seja possível atingir o objetivo na busca de uma sociedade mais igualitária. Para isso, foram utilizados relatos orais, entrevistas e grupos focais realizadas pelas autoras nos trabalhos de monografia e dissertação de mestrado; o que contribui para a análise da interseccionalidades existentes entre as diferenças e semelhanças nas produções acadêmicas em que uma Geografia Feminista para a Saúde pode oferecer.

In many areas such as computational biology, finance or social sciences, knowledge of an underlying graph explaining the interactions between agents is of paramount importance but still challenging. Considering that these interactions may be based on nonlinear relationships adds further complexity to the topology inference problem. Among the latest methods that respond to this need is a topology inference one proposed by the authors, which estimates a possibly directed adjacency matrix in an online manner. Contrasting with previous approaches based on linear models, the considered model is able to explain nonlinear interactions between the agents in a network. The novelty in the considered method is the use of a derivative-reproducing property to enforce network sparsity, while reproducing kernels are used to model the nonlinear interactions. The aim of this paper is to present a thorough convergence analysis of this method. The analysis is proven to be sane both in the mean and mean square sense. In addition, stability conditions are devised to ensure the convergence of the analyzed method., 24 pages, 11 of which of which are supplementary material; 4 figures

Real-time satellite imaging has a central role in monitoring, detecting and estimating the intensity of key natural phenomena such as floods, earthquakes, etc. One important constraint of satellite imaging is the trade-off between spatial/spectral resolution and their revisiting time, a consequence of design and physical constraints imposed by satellite orbit among other technical limitations. In this paper, we focus on fusing multi-temporal, multi-spectral images where data acquired from different instruments with different spatial resolutions is used. We leverage the spatial relationship between images at multiple modalities to generate high-resolution image sequences at higher revisiting rates. To achieve this goal, we formulate the fusion method as a recursive state estimation problem and study its performance in filtering and smoothing contexts. Furthermore, a calibration strategy is proposed to estimate the time-varying temporal dynamics of the image sequence using only a small amount of historical image data. Differently from the training process in traditional machine learning algorithms, which usually require large datasets and computation times, the parameters of the temporal dynamical model are calibrated based on an analytical expression that uses only two of the images in the historical dataset. A distributed version of the Bayesian filtering and smoothing strategies is also proposed to reduce its computational complexity. To evaluate the proposed methodology we consider a water mapping task where real data acquired by the Landsat and MODIS instruments are fused generating high spatial-temporal resolution image estimates. Our experiments show that the proposed methodology outperforms the competing methods in both estimation accuracy and water mapping tasks., arXiv admin note: substantial text overlap with arXiv:2204.12566

A wide variety of applications of fundamental importance for security, environmental protection and urban development need access to accurate land cover monitoring and water mapping, for which the analysis of optical remote sensing imagery is key. Classification of time-series images, particularly with recursive methods, is of increasing interest in the current literature. Nevertheless, existing recursive approaches typically require large amounts of training data. This paper introduces a recursive classification framework that improves the decision-making process in multitemporal and multispectral land cover classification algorithms while requiring low computational cost and minimal supervision. The proposed approach allows the conversion of an instantaneous classifier into a recursive Bayesian classifier by using a probabilistic framework that is robust to non-informative image variations. Three experiments are conducted using Sentinel-2 data. The first one consists in the water mapping of an embankment dam in California (United States), the second one is a land cover classification experiment of the Charles river area in Boston (United States) and the last experiment addresses deforestation detection in the Amazon rainforest (Brazil). A classifier based on the Gaussian mixture model (GMM), a logistic regression (LR) classifier, and a spectral index classifier (SIC) are compared to their recursive counterparts. SICs are introduced to convert the NDWI, MNDWI and NDVI spectral indices into predictive probabilities. Two state-of-the-art deep learning-based models are also used as a benchmark for the water mapping experiment. Results show that the proposed method significantly increases the robustness of existing instantaneous classifiers in multitemporal settings. Our method also improves the performance of deep learning-based classifiers without the need for additional training data., Without supplementary results: 30 pages, 11 figures. With supplementary results: 40 pages, 21 figures

Highly uniform quantum systems are essential for the practical implementation of scalable quantum processors. While quantum dot spin qubits based on semiconductor technology are a promising platform for large-scale quantum computing, their small size makes them particularly sensitive to their local environment. Here, we present a method to electrically obtain a high degree of uniformity in the intrinsic potential landscape using hysteretic shifts of the gate voltage characteristics. We demonstrate the tuning of pinch-off voltages in quantum dot devices over hundreds of millivolts that then remain stable at least for hours. Applying our method, we homogenize the pinch-off voltages of the plunger gates in a linear array for four quantum dots, reducing the spread in pinch-off voltages by one order of magnitude. This work provides a new tool for the tuning of quantum dot devices and offers new perspectives for the implementation of scalable spin qubit arrays.

The deaths caused by the covid-19 pandemic have recently decreased due to a worldwide effort in vaccination campaigns. However, even vaccinated people can develop a severe form of the disease that requires ICU admission. As a result, the search for antiviral drugs to treat these severe cases has become a necessity. In this context, natural products are an interesting alternative to synthetic medicines used in drug repositioning, as they have been consumed for a long time through traditional medicine. Many natural compounds found in plant extracts have already been shown to be effective in treating viral and bacterial diseases, making them possible hits to exploit against covid-19. The objective of this work was to evaluate the antiviral activity of different plant extracts available in the library of natural products of the Universidade Estadual de Maringá, by inhibiting the SARS-CoV-2 main protease (Mpro), and by preventing viral infection in a cellular model. As a result, the extract of Cytinus hypocistis, obtained by ultrasound, showed a Mpro inhibition capacity greater than 90%. In the infection model assays using Vero cells, an inhibition of 99.6% was observed, with a selectivity index of 42.7. The in silico molecular docking simulations using the extract compounds against Mpro, suggested Tellimagrandin II as the component of C. hypocistis extract most likely to inhibit the viral enzyme. These results demonstrate the potential of C. hypocistis extract as a promising source of natural compounds with antiviral activity against covid-19. Communicated by Ramaswamy H. Sarma

Semiconductor spin qubits have gained increasing attention as a possible platform to host a fault-tolerant quantum computer. First demonstrations of spin qubit arrays have been shown in a wide variety of semiconductor materials. The highest performance for spin qubit logic has been realized in silicon, but scaling silicon quantum dot arrays in two dimensions has proven to be challenging. By taking advantage of high-quality heterostructures and carefully designed gate patterns, we are able to form a tunnel coupled 2 $\times$ 2 quantum dot array in a $^{28}$Si/SiGe heterostructure. We are able to load a single electron in all four quantum dots, thus reaching the (1,1,1,1) charge state. Furthermore we characterise and control the tunnel coupling between all pairs of dots by measuring polarisation lines over a wide range of barrier gate voltages. Tunnel couplings can be tuned from about $30~\rm \mu eV$ up to approximately $400~\rm \mu eV$. These experiments provide a first step toward the operation of spin qubits in $^{28}$Si/SiGe quantum dots in two dimensions., Comment: 8 pages, 6 figures

Introduction: A timely diagnosis of osteoporosis is key to reducing its growing clinical and economic burden. Radiofrequency Echographic Multi Spectrometry (REMS), a new diagnostic technology using an ultrasound approach, has been recognized by scientific associations as a facilitator of patients’ care pathway. We aimed at evaluating the costs of REMS vs. the conventional ionizing technology (dual-energy X-ray absorptiometry, DXA) for the diagnosis of osteoporosis from the perspective of the Italian National Health Service (NHS) using a cost-minimization analysis (CMA). Methods: We carried out structured qualitative interviews and a structured expert elicitation exercise to estimate healthcare resource consumption with a purposeful sample of clinical experts. For the elicitation exercise, an Excel tool was developed and, for each parameter, experts were asked to provide the lowest, highest and most likely value. Estimates provided by experts were averaged with equal weights. Unit costs were retrieved using different public sources. Results: Considering the base-case scenario (most likely value), the cost of professionals amounts to €31.9 for REMS and €48.8 for DXA, the cost of instrumental examinations and laboratory tests to €45.1 for REMS and €68.2 for DXA. Overall, in terms of current costs, REMS is associated with a mean saving for the NHS of €40.0 (range: €27.6-71.5) for each patient. Conclusions: REMS is associated with lower direct healthcare costs with respect to DXA. These results may inform policy-makers on the value of the REMS technology in the earlier diagnosis for osteoporosis, and support their decision regarding the reimbursement and diffusion of the technology in the Italian NHS.

Funding Information: The authors thank the Coordination for the Improvement of Higher Education Personnel (CAPES) and the National Council for Scientific and Technological Development (CNPq) for their financial support. This study was supported by the CAPES — number 88887.505029/2020–00 . Cecilia Gomes Barbosa receives a scholarship funded by CAPES — number 88887.643352/2021–00 . Publisher Copyright: © 2023 Elsevier B.V. The compound 3a,10b-dihydro-1H-cyclopenta[b]naphtho[2,3-d]furan-5,10-dione (IVS320) is a naphthoquinone with antifungal and antichagasic potential, which however has low aqueous solubility. To increase bioavailability, inclusion complexes with β-cyclodextrin (βCD) and methyl-β-cyclodextrin (MβCD) were prepared by physical mixture (PM), kneading (KN) and rotary evaporation (RE), and their in vitro anti-SARS-CoV-2 and antichagasic potential was assessed. The formation of inclusion complexes led to a change in the physicochemical characteristics compared to IVS320 alone as well as a decrease in crystallinity degree that reached 74.44% for the IVS320-MβCD one prepared by RE. The IVS320 and IVS320-MβCD/RE system exhibited anti-SARS-CoV-2 activity, showing half maximal effective concentrations (EC50) of 0.47 and 1.22 μg/mL, respectively. Molecular docking simulation suggested IVS320 ability to interact with the SARS-CoV-2 viral protein. Finally, the highest antichagasic activity, expressed as percentage of Tripanosoma cruzi growth inhibition, was observed with IVS320-βCD/KN (70%) and IVS320-MβCD/PM (72%), while IVS320 alone exhibited only approximately 48% inhibition at the highest concentration (100 μg/mL). publishersversion published

Objectives The management of non-metastatic castration-resistant prostate cancer (nmCRPC) is rapidly evolving; however, little is known about the direct healthcare costs of nmCRPC. We aimed to estimate the cost-of-illness (COI) of nmCRPC from the Italian National Health Service perspective. Methods Structured, individual qualitative interviews were carried out with clinical experts to identify what healthcare resources are consumed in clinical practice. To collect quantitative estimates of healthcare resource consumption, a structured expert elicitation was performed with clinical experts using a modified version of a previously validated interactive Excel-based tool, EXPLICIT (EXPert eLICItation Tool). For each parameter, experts were asked to provide the lowest, highest, and most likely value. Deterministic and probabilistic sensitivity analyses (PSA) were carried out to test the robustness of the results. Results Ten clinical experts were interviewed, and six of them participated in the expert elicitation exercise. According to the most likely estimate, the yearly cost per nmCRPC patient is €4,710 (range, €2,243 to €8,243). Diagnostic imaging (i.e., number/type of PET scans performed) had the highest impact on cost. The PSA showed a 50 percent chance for the yearly cost per nmCRPC patient to be within €5,048 using a triangular distribution for parameters, and similar results were found using a beta-PERT distribution. Conclusions This study estimated the direct healthcare costs of nmCRPC in Italy based on a mixed-methods approach. Delaying metastases may be a reasonable goal also from an economic standpoint. These findings can inform decision-making about treatments at the juncture between non-metastatic and metastatic prostate cancer disease.

Discovering components that are shared in multiple datasets, next to dataset-specific features, has great potential for studying the relationships between different subjects or tasks in functional Magnetic Resonance Imaging (fMRI) data. Coupled matrix and tensor factorization approaches have been useful for flexible data fusion, or decomposition to extract features that can be used in multiple ways. However, existing methods do not directly recover shared and dataset-specific components, which requires post-processing steps involving additional hyperparameter selection. In this paper, we propose a tensor-based framework for multi-task fMRI data fusion, using a partially constrained canonical polyadic (CP) decomposition model. Differently from previous approaches, the proposed method directly recovers shared and dataset-specific components, leading to results that are directly interpretable. A strategy to select a highly reproducible solution to the decomposition is also proposed. We evaluate the proposed methodology on real fMRI data of three tasks, and show that the proposed method finds meaningful components that clearly identify group differences between patients with schizophrenia and healthy controls.

Semiconducting nanowire Josephson junctions represent an attractive platform to investigate the anomalous Josephson effect and detect topological superconductivity by studying Josephson supercurrent. However, an external magnetic field generally suppresses the supercurrent through hybrid nanowire junctions and significantly limits the field range in which the supercurrent phenomena can be studied. In this work, we investigate the impact of the length of InSb-Al nanowire Josephson junctions on the supercurrent resilience against magnetic fields. We find that the critical parallel field of the supercurrent can be considerably enhanced by reducing the junction length. Particularly, in 30 nm-long junctions supercurrent can persist up to 1.3 T parallel field - approaching the critical field of the superconducting film. Furthermore, we embed such short junctions into a superconducting loop and obtain the supercurrent interference at a parallel field of 1 T. Our findings are highly relevant for multiple experiments on hybrid nanowires requiring a magnetic field-resilient supercurrent., 17 pages, 5 figures in main text. 22 pages, 10 figures in supporting information

The folder contains the scripts and the datasets to generate the figures presented in our manuscript posted on arXiv. Details on how to run the scripts are given in the readme file.

Plants of the Calea genus have been reported to contain lipophilic compounds, such as sesquiterpene lactones, with cytotoxic effect against different cancer cell lines. The aim of this manuscript was to investigate the chemical profile and cytotoxic activity of different fractions from Calea phylolepis leaves on different human cancer cell lines. The fractions were prepared using solvent extraction of increasing polarity, yielding hexane, ethyl acetate and methanolic fractions. All fractions were chemically analysed by thin layer chromatography (TLC), and their cytotoxic activity against HT-29 (colon adenocarcinoma), MCF-7 (breast cancer), U-251MG (malignant glioblastoma) and L929 (mouse fibroblast) cell lines was investigated. Among these, the hexane and ethyl acetate fractions showed higher cytotoxic effects, while the methanolic fraction did not show any cytotoxic effects. The major bioactive compound from the hexane fraction (12.15%) was isolated using chromatographic methods and was identified by nuclear magnetic resonance spectroscopy (NMR) and gas chromatography-mass spectrometry (GC-MS) analysis as 6-epi-β-verbesinol coumarate. This compound showed activity against breast cancer cells (IC50 = 5.8 ± 1.0 μg/ml), similar to etoposide. Furthermore, 6-epi-β-verbesinol coumarate showed low cytotoxicity to normal fibroblast cells, suggesting a high selectivity index (SI = 7.39) against breast cancer cells.

The aim of this work was to evaluate the influence of the use of coupling agent (CA) on the properties of thermoplastic composites produced from post-consumer polypropylene (rPP) and malt bagasse fibers (MB) of brewing industry. The CA used was maleic anhydride graft polypropylene copolymer (MAgPP). The study was carried out in two stages: in first step the best concentration of MB fibers was verified, where was varied the fiber contents between 0, 10, 20 and 30% (w/w); in the second step, the best MB concentration evaluated was used with different CA concentrations (0, 1, 3, 5 and 7% w/w). Of the three MB concentrations evaluated as reinforcing filler, the sample with a 30% (w/w) ratio presented 44% lower deformation than the others, presenting better mechanical resistance, although it also presented the highest water absorption. Thus, the 30% MB fiber content was chosen for two step, where the results showed that the PP/MB-30 composite treated with 3% (w/w) CA had a modulus of elasticity 10.3% higher than the same composite without CA, corroborating with the morphological analysis, which indicated better interfacial adhesion between composite components when CA was used. The PP/MB-30 composite treated with 1% (w/w) CA showed the highest thermal stability among all samples.

The realization of hybrid superconductor–semiconductor quantum devices, in particular a topological qubit, calls for advanced techniques to readily and reproducibly engineer induced superconductivity in semiconductor nanowires. Here, we introduce an on-chip fabrication paradigm based on shadow walls that offers substantial advances in device quality and reproducibility. It allows for the implementation of hybrid quantum devices and ultimately topological qubits while eliminating fabrication steps such as lithography and etching. This is critical to preserve the integrity and homogeneity of the fragile hybrid interfaces. The approach simplifies the reproducible fabrication of devices with a hard induced superconducting gap and ballistic normal-/superconductor junctions. Large gate-tunable supercurrents and high-order multiple Andreev reflections manifest the exceptional coherence of the resulting nanowire Josephson junctions. Our approach enables the realization of 3-terminal devices, where zero-bias conductance peaks emerge in a magnetic field concurrently at both boundaries of the one-dimensional hybrids., Advanced fabrication techniques enable a wide range of quantum devices, such as the realization of a topological qubit. Here, the authors introduce an on-chip fabrication technique based on shadow walls to implement topological qubits in an InSb nanowire without fabrication steps such as lithography and etching.

The work presents a methodology for assessing the safety of electrical system designs for non-conventional nuclear facilities in shutdown. The methodology adopts the core damage frequency as the main risk measure to assess the different architectures of power systems in a non-conventional nuclear facility. Among the reasons is the absence of a specific regulatory basis for this type of installation. The adoption of standards for nuclear power plants by non-conventional nuclear facilities does not take into account the functional and operational particularities of these installations, imposing criteria that are often overestimated, which can even lead to an increase in the financial risk for carrying out the projects. Safety probabilistic analyzes become essential tools for the facilities design and licensing. The modeling and quantification of systems failures in charge of ensuring the nuclear safety of non-conventional nuclear facilities are carried out in the CAFTA software environment. In these studies, the analysis of electrical system configurations and their influence on the overall risk of the installation stand out.

In general terms, safety demonstration of nuclear installations is carried out through an assessment of compliance with design criteria and safety requirements established in national and international codes and standards applicable to each type of installation. In addition, a safety analysis consisting of installation behavior study during its useful lifetime, shall be developed considering normal operating conditions, transients, and postulated accidents, to determine safety margins and verify the adequacy of items designed to prevent accidents or mitigate their consequences. Also, design requirements applicable to each installation item depend on its classification with respect to safety. Thus, safety classification of structures, systems, and components (SSCs) must be performed based on adequate methods and clear and consistent criteria to ensure that an overall safety level expected for the installation is achieved. It is worth emphasizing the importance of the terminology adopted and the understanding of concepts definitions used in a safety classification process. The objective of this paper is to present a review of the application of “safety related item” and “item important to safety” terminology, evaluating definitions and interpretations given by the International Atomic Energy Agency (IAEA), the United States Nuclear Regulatory Commission (U.S.NRC) and the National Nuclear Energy Commission (CNEN) of Brazil. In this work, this subject is raised to demonstrate that divergent definitions and misinterpretations of concepts may result in inconsistencies in SSCs safety classification.

The nuclear licensing process is a fundamental stage for the design and deployment of a nuclear facility. In Brazil, the licensing process of Central Nuclear Almirante Álvaro Alberto (CNAAA) nuclear power plants, in Angra dos Reis - RJ, was established mainly based on the U.S. Nuclear Regulatory Commission (U.S.NRC) guidelines. However, for each purpose specific requirements are established which promote a standardisation appropriate to the type of installation in question. Thus, not every nuclear installation can be adequately framed in the standards and requirements established for the licensing of a nuclear power plant, especially when considering nuclear facilities for strategic and defense purposes. For instance, the Specialized Maintenance Complex (CME) project that is being developed by the Brazilian Navy and aims to offer all the structure and systems for support on land to the first Brazilian nuclear-powered submarine. Therefore, when considering the interfaces between maritime/naval systems and operations, the purpose and specificity of installations such as CME extrapolate the commonly established nuclear normative framework. Due to the innovation of this type of installation in Brazil, there is no specific regulation for its licensing, constituting a unique situation for both the Brazilian Navy (applicant) and the National Nuclear Energy Commission - CNEN (Brazilian Nuclear Licensing Agency, which, in the near future, will have its function incorporated into the National Nuclear Safety Authority, ANSN). Even when researching standards and other guides in ostensible sources of nations that holds nuclear reactor technology for naval propulsion (and land support facilities), no normative guidance dealing specifically with the safety analysis and licensing of this type of installation has been identified. Thus, this paper proposes a first approach and analysis of the standards used by the U.S. Department of Defense (U.S.DOE) comparing them to the standards of the U.S. Nuclear Regulatory Commission (U.S.NRC) aiming to compose a specific normative proposition to carry out the safety analysis and licensing of a nuclear-powered submarines land support facility.

O presente artigo versa sobre a proteção de dados pessoais diante dos complexos desafios, destinando-se seu enfoque a proteção de dados e ao direito à privacidade, presentes na atual constituição. Sabe-se que umas das características dos direitos fundamentais são o seu semblante não absoluto, proporcionando, de tal maneira, divergências entre tais direitos. Nesse contexto, a análise do artigo 5º incisos IV, X, XXXIII da Constituição Federal, está diante de um conflito constitucional, tendo em vista a liberdade de pensamento e a violação da privacidade, trazendo consigo a vida privada. Necessário considerar que tais direitos são um exemplo clássico da colisão dos direitos fundamentais, ressalta-se dessa forma a importância da liberdade de pensamento em conjunto com o direito à informação. A globalização é peça fundamental deste esquema, visto que, a difusão da informação atualmente é dada de forma imediata, relevando acontecimento a uma velocidade quase instantânea. Em contrapartida, o direito à privacidade se faz, mas que necessário, tendo em vista como base fundamental a Constituição Federal em seu inciso X, e juntamente com o novo código civil, Lei 10.406/02 em seus artigos 11 ao 21 bem como a Lei 13.709, que trata da Proteção de Dados. Analisando-se a pertinência destes conflitos, faz mister a utilização de um meio eficaz e alternativos para correção. Assim sendo, a problemática sobre a qual se desdobrará a análise é a respeito dos desafios destinados a proteção de dados e ao direito a privacidade tendo em vista também um olhar sobre o viés da tutela penal a respeito do presente tema, possuindo como base doutrinas modernas, revistas jurídicas e sites remetentes ao conteúdo. Bem como planeja analisar pontos da Constituição Federal, do Código Civil e Código Penal, em conjunto com leis referentes às infrações e suas atualizações.

The efficient control of a large number of qubits is one of most challenging aspects for practical quantum computing. Current approaches in solid-state quantum technology are based on brute-force methods, where each and every qubit requires at least one unique control line, an approach that will become unsustainable when scaling to the required millions of qubits. Here, inspired by random access architectures in classical electronics, we introduce the shared control of semiconductor quantum dots to efficiently operate a two-dimensional crossbar array in planar germanium. We tune the entire array, comprising 16 quantum dots, to the few-hole regime and, to isolate an unpaired spin per dot, we confine an odd number of holes in each site. Moving forward, we establish a method for the selective control of the quantum dots interdot coupling and achieve a tunnel coupling tunability over more than 10 GHz. The operation of a quantum electronic device with fewer control terminals than tunable experimental parameters represents a compelling step forward in the construction of scalable quantum technology., 33 pages including supplementary information

The folder contains the scripts and the datasets to generate the figures presented in our manuscript posted on arXiv on September 2022. Specific information on how to run the scripts are detailed in the README file.

Few extracts of plant species from the Brazilian flora have been validated from a pharmacological and clinical point of view, and it is important to determine whether their traditional use is proven by pharmacological effects.

International audience; Nous proposons une solution conjointe aux problèmes de super-résolution et de démélange de l'image super-résolue. Cette approche utilise la décomposition tensorielle LL1 et tient compte d'un phénomène de variabilité spectrale. Des garanties théoriques de reconstruction sont fournies. Nous proposons un algorithme sous contraintes de positivité, dont les performances sont illustrées sur des images réelles.

International audience; In this paper we propose a hyperspectral and multispectral image fusion framework accounting for inter-image variability. The images are represented as three dimensional tensors, and both the high-resolution image and inter-image variations are assumed to admit a Tucker decomposition. Two algorithms are proposed, one purely algebraic and computationally fast and another based on an optimization procedure. Exact recovery conditions are provided. Experimental results illustrate the performance of the proposed methods.; Dans cet article, nous proposons une approche pour la reconstruction d'images à haute résolution par fusion d'images hyperspectrales et multispectrales prenant en compte la variabilité entre les images. L'image haute résolution et la variabilité inter-images sont représentées sous forme de tenseurs et sont supposées admettre une décomposition de Tucker. Deux algorithmes sont proposés, et des conditions pour une reconstruction exacte de l'image à haute résolution sont fournies. Les résultats expérimentaux illustrent les performances des méthodes proposées.