Análise dos impactos da inserção de fontes fotovoltaicas na rede elétrica, considerando-se o caráter probabilístico da irradiação solar e da alocação dos painéis solares em unidades consumidoras

Trabalho de conclusão de curso (graduação)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2016.As fontes renováveis têm se mostrado cada vez mais populares por apresentarem viabilidade de projetos de produção de energia elétrica com impactos ambientais reduzidos. Por esta razão, diversos países buscam aumentar o uso de tais fontes, em especial da geração distribuída fotovoltaica (GDFV), por meio da aplicação de políticas de incentivo. A escolha da política atua na maneira como são instalados os sistemas solares e, por consequência, nos seus efeitos nos parâmetros da rede elétrica. Neste sentido, o presente trabalho tem por objetivo nuclear aplicar um método de análise existente a um caso específico e, a partir dele, realizar a identificação dos impactos nos níveis de tensões e correntes da inserção de GDFV em um alimentador radial real, considerando-se as incertezas quanto à alocação dos painéis fotovoltaicos e da curva de irradiância. Em linhas gerais, para se atingir tal objetivo, adota-se o emprego de dados reais no software OpenDSS, sem geração distribuída e com diferentes níveis de penetrações de GDFV. A metodologia é aplicada a três políticas de incentivo, a saber, feed in pequena e média, e net metering. A variação dos locais de inserção dos painéis e da irradiância solar, tornam os resultados das simulações mais próximos ao que de fato ocorre na prática. Este trabalho, portanto, caracteriza-se como uma primeira etapa de uma avaliação que visa identificar qual a mais adequada política de incentivo para cada nível de penetração de GDFV na rede.Renewable sources are becoming more popular as they constitute feasible projects, in order to reduce environmental hazards when producing energy. Therefore, several countries seek to generates electrical energy by these means of production, especially in the solar photovoltaic development, which has been diffused due to the creation of incentive polices. The latter impacts on how the solar systems are installed on the power network and, thus, alters the effects arising from the integration of this sort of electricity production. In this sense, the mainly purpose of this study is to use an existing method in a specific case in order to investigate some of the head impacts on the grid, given the addition of solar photovoltaic, and considering uncertainties related to solar irradiance and systems placement. By using real data as input of a software called OpenDSS, the analysis is made for feed in and net metering policies. Two conditions are analysed: with or without photovoltaic solar panels on the grid. Moreover, the uncertainties considered make simulation results closer to what happens in reality. Furthermore, this study designs a first step to identify which policy is more suitable to each penetration level of distributed solar systems on the power grid

Lithium cobalt(II) pyrophosphate, Li1.86CoP2O7, from synchrotron X-ray powder data

Structure refinement of high-resolution X-ray powder diffraction data of the title compound gave the composition Li1.865CoP2O7, which is also verified by the ICP measurement. Two Co sites exist in the structure: one is a CoO5 square pyramid and the other is a CoO6 octa­hedron. They share edges and are further inter­connected through P2O7 groups, forming a three-dimensional framework, which exhibits different kinds of inter­secting tunnels containing Li cations and could be of great inter­est in Li ion battery chemistry. The structure also exhibits cation disorder with 13.5% Co residing at the lithium (Li1) site. Co seems to have an average oxidation state of 2.135, as obtained from the strutural stochiometry that closely supports the magnetic susceptibility findings

Understanding, Categorizing and Predicting Semantic Image-Text Relations

Two modalities are often used to convey information in a complementary and beneficial manner, e.g., in online news, videos, educational resources, or scientific publications. The automatic understanding of semantic correlations between text and associated images as well as their interplay has a great potential for enhanced multimodal web search and recommender systems. However, automatic understanding of multimodal information is still an unsolved research problem. Recent approaches such as image captioning focus on precisely describing visual content and translating it to text, but typically address neither semantic interpretations nor the specific role or purpose of an image-text constellation. In this paper, we go beyond previous work and investigate, inspired by research in visual communication, useful semantic image-text relations for multimodal information retrieval. We derive a categorization of eight semantic image-text classes (e.g., "illustration" or "anchorage") and show how they can systematically be characterized by a set of three metrics: cross-modal mutual information, semantic correlation, and the status relation of image and text. Furthermore, we present a deep learning system to predict these classes by utilizing multimodal embeddings. To obtain a sufficiently large amount of training data, we have automatically collected and augmented data from a variety of data sets and web resources, which enables future research on this topic. Experimental results on a demanding test set demonstrate the feasibility of the approach.Comment: 8 pages, 8 Figures, 5 table

SFRP4 drives invasion in gastric cancer and is an early predictor of recurrence.

OBJECTIVE: Gastric cancer patients generally have a poor outcome, particularly those with advanced-stage disease which is defined by the increased invasion of cancer locally and is associated with higher metastatic potential. This study aimed to identify genes that were functional in the most fundamental hallmark of cancer, namely invasion. We then wanted to assess their value as biomarkers of gastric cancer progression and recurrence. DESIGN: Data from a cohort of patients profiled on cDNA expression arrays was interrogated using K-means analysis. This genomic approach classified the data based on patterns of gene expression allowing the identification of the genes most correlated with the invasion of GC. We evaluated the functional role of a key protein from this analysis in invasion and as a biomarker of recurrence after curative resection. RESULTS: Expression of secreted frizzled-related protein 4 (SFRP4) was identified as directly proportional to gastric cancer invasion. This finding was validated in multiple, independent datasets and its functional role in invasion was also confirmed using invasion assays. A change in serum levels of SFRP4 after curative resection, when coupled with AJCC stage, can accurately predict the risk of disease recurrence after curative therapy in an assay we termed PredictR. CONCLUSIONS: This simple ELISA-based assay can help predict recurrence of disease after curative gastric cancer surgery irrespective of adjuvant therapy. The results require further evaluation in a prospective trial but would help in the rational prescription of cancer therapies and surveillance to prevent under or over treatment of patients after curative resection

Analysis of Breast Cancer Mortality in the US-1975 to 2019

IMPORTANCE: Breast cancer mortality in the US declined between 1975 and 2019. The association of changes in metastatic breast cancer treatment with improved breast cancer mortality is unclear. OBJECTIVE: To simulate the relative associations of breast cancer screening, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer with improved breast cancer mortality. DESIGN, SETTING, AND PARTICIPANTS: Using aggregated observational and clinical trial data on the dissemination and effects of screening and treatment, 4 Cancer Intervention and Surveillance Modeling Network (CISNET) models simulated US breast cancer mortality rates. Death due to breast cancer, overall and by estrogen receptor and ERBB2 (formerly HER2) status, among women aged 30 to 79 years in the US from 1975 to 2019 was simulated. EXPOSURES: Screening mammography, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer. MAIN OUTCOMES AND MEASURES: Model-estimated age-adjusted breast cancer mortality rate associated with screening, stage I to III treatment, and metastatic treatment relative to the absence of these exposures was assessed, as was model-estimated median survival after breast cancer metastatic recurrence. RESULTS: The breast cancer mortality rate in the US (age adjusted) was 48/100 000 women in 1975 and 27/100 000 women in 2019. In 2019, the combination of screening, stage I to III treatment, and metastatic treatment was associated with a 58% reduction (model range, 55%-61%) in breast cancer mortality. Of this reduction, 29% (model range, 19%-33%) was associated with treatment of metastatic breast cancer, 47% (model range, 35%-60%) with treatment of stage I to III breast cancer, and 25% (model range, 21%-33%) with mammography screening. Based on simulations, the greatest change in survival after metastatic recurrence occurred between 2000 and 2019, from 1.9 years (model range, 1.0-2.7 years) to 3.2 years (model range, 2.0-4.9 years). Median survival for estrogen receptor (ER)-positive/ERBB2-positive breast cancer improved by 2.5 years (model range, 2.0-3.4 years), whereas median survival for ER-/ERBB2- breast cancer improved by 0.5 years (model range, 0.3-0.8 years). CONCLUSIONS AND RELEVANCE: According to 4 simulation models, breast cancer screening and treatment in 2019 were associated with a 58% reduction in US breast cancer mortality compared with interventions in 1975. Simulations suggested that treatment for stage I to III breast cancer was associated with approximately 47% of the mortality reduction, whereas treatment for metastatic breast cancer was associated with 29% of the reduction and screening with 25% of the reduction

Solution fibre spinning technique for the fabrication of tuneable decellularised matrix-laden fibres and fibrous micromembranes.

UNLABELLED: Recreating tissue-specific microenvironments of the extracellular matrix (ECM) in vitro is of broad interest for the fields of tissue engineering and organ-on-a-chip. Here, we present biofunctional ECM protein fibres and suspended membranes, with tuneable biochemical, mechanical and topographical properties. This soft and entirely biologic membrane scaffold, formed by micro-nano-fibres using low voltage electrospinning, displays three unique characteristics for potential cell culture applications: high-content of key ECM proteins, single-layered mesh membrane, and flexibility for in situ integration into a range of device setups. Extracellular matrix (ECM) powder derived from urinary bladder, was used to fabricate the ECM-laden fibres and membranes. The highest ECM concentration in the dry protein fibre was 50 wt%, with the rest consisting of gelatin. Key ECM proteins, including collagen IV, laminin, and fibronectin, were shown to be preserved post the biofabrication process. The single fibre tensile Young's modulus can be tuned for over two orders of magnitude between ∼600 kPa and 50 MPa depending on the ECM content. Combining the fibre mesh printing with 3D printed or microfabricated structures, culture devices were constructed for endothelial layer formation, and a trans-membrane co-culture formed by glomerular cell types of podocytes and glomerular endothelial cells, demonstrating feasibility of the membrane culture. Our cell culture observation points to the importance of membrane mechanical property and re-modelling ability as a factor for soft membrane-based cell cultures. The ECM-laden fibres and membranes presented here would see potential applications in in vitro assays, and tailoring structure and biological functions of tissue engineering scaffolds. STATEMENT OF SIGNIFICANCE: Recreating tissue-specific microenvironments of the extracellular matrix (ECM) is of broad interest for the fields of tissue engineering and organ-on-a-chip. Both the biochemical and biophysical signatures of the engineered ECM interplay to affect cell response. Currently, there are limited biomaterials processing methods which allow to design ECM membrane properties flexibly and rapidly. Solvents and additives used in many existing processes also induced unwanted ECM protein degradation and toxic residues. This paper presents a solution fibre spinning technique, where careful selection of the solution combination led to well-preserved ECM proteins with tuneable composition. This technique also provides a highly versatile approach to fabricate ECM fibres and membranes, leading to designable fibre Young's modulus for over two orders of magnitude.This work is supported by the Engineering and Physical Sciences Research Council (EPSRC) UK (EP/M018989/1) and European Research Council (ERC-StG, 758865). The authors thank the studentship and funding supports from the EPSRC DTA (Z.L.), the WD Armstrong Trust (I.M.L), the Swiss National Science Foundation (P300P2_171219) and the Centre for Misfolding Disease of the University of Cambridge (F.S.R.)

Degradation of high affinity HuD targets releases Kv1.1 mRNA from miR-129 repression by mTORC1

Little is known about how a neuron undergoes site-specific changes in intrinsic excitability during neuronal activity. We provide evidence for a novel mechanism for mTORC1 kinase–dependent translational regulation of the voltage-gated potassium channel Kv1.1 messenger RNA (mRNA). We identified a microRNA, miR-129, that repressed Kv1.1 mRNA translation when mTORC1 was active. When mTORC1 was inactive, we found that the RNA-binding protein, HuD, bound to Kv1.1 mRNA and promoted its translation. Unexpectedly, inhibition of mTORC1 activity did not alter levels of miR-129 and HuD to favor binding to Kv1.1 mRNA. However, reduced mTORC1 signaling caused the degradation of high affinity HuD target mRNAs, freeing HuD to bind Kv1.1 mRNA. Hence, mTORC1 activity regulation of mRNA stability and high affinity HuD-target mRNA degradation mediates the bidirectional expression of dendritic Kv1.1 ion channels

Visually identified Tau 18F-MK6240 PET patterns in symptomatic Alzheimer\u27s disease

Background: In Alzheimer\u27s disease, heterogeneity has been observed in the postmortem distribution of tau neurofibrillary tangles. Visualizing the topography of tau in vivo may facilitate clinical trials and clinical practice. Objective: This study aimed to investigate whether tau distribution patterns that are limited to mesial temporal lobe (MTL)/limbic regions, and those that spare MTL regions, can be visually identified using 18F-MK6240, and whether these patterns are associated with different demographic and cognitive profiles. Methods : Tau 18F-MK6240 PET images of 151 amyloid-β positive participants with mild cognitive impairment (MCI) and dementia were visually rated as: tau negative, limbic predominant (LP), MTL-sparing, and Typical by two readers. Groups were evaluated for differences in age, APOE ɛ4 carriage, hippocampal volumes, and cognition (MMSE, composite memory and non-memory scores). Voxel-wise contrasts were also performed. Results: Visual rating resulted in 59.6 % classified as Typical, 17.9 % as MTL-sparing, 9.9 % LP, and 12.6% as tau negative. Intra-rater and inter-rater reliability was strong (Cohen\u27s kappa values of 0.89 and 0.86 respectively). Tracer retention in a hook -like distribution on sagittal sequences was observed in the LP and Typical groups. The visually classified MTL-sparing group had lower APOE ɛ4 carriage and relatively preserved hippocampal volumes. Higher MTL tau was associated with greater amnestic cognitive impairment. High crtical tau was associated with greater impairments on non-memory domains of cognition, and individuals with high cortical tau were more likely to have dementia than MCI. Conclusion: Tau distribution patterns can be visually identified using 18F-MK6240 PET and are associated with differences in APOE ɛ4 carriage, hippocampal volumes, and cognition