Miracle-dz/UniFAR-FTUs huggingface dataset:
The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use

Abstract. Population data represent an essential component in studies focusing on human–nature interrelationships, disaster risk assessment and environmental health. Several recent efforts have produced global- and continental-extent gridded population data which are becoming increasingly popular among various research communities. However, these data products, which are of very different characteristics and based on different modeling assumptions, have never been systematically reviewed and compared, which may impede their appropriate use. This article fills this gap and presents, compares and discusses a set of large-scale (global and continental) gridded datasets representing population counts or densities. It focuses on data properties, methodological approaches and relative quality aspects that are important to fully understand the characteristics of the data with regard to the intended uses. Written by the data producers and members of the user community, through the lens of the “fitness for use” concept, the aim of this paper is to provide potential data users with the knowledge base needed to make informed decisions about the appropriateness of the data products available in relation to the target application and for critical analysis.
A generalization of the exponential function to model growth

We generalize the exponential function to model instantaneous relative growth. The modified function is defined by a linear relationship between a continuous quantity (rather than time) and logarithmic relative growth. The corresponding formula is       ln t t q q a b q t         , where     q t q t  is instantaneous relative growth of a quantity q , t refers to time, a denotes initial logarithmic relative growth, and b is a shape parameter in terms of its sign, as well as a scaling parameter in terms of its magnitude. For calculating   q t , the exponential integral       Ei exp d b q b q q q       is needed. The problem of taking the inverse of   Ei Ei x z  is addressed. In order to distinguish two possible solutions for given Ei z , we define the two inverse functions ( 1) 0 Ei Ei x z       and ( 1) 0 Ei Ei x z       . An indirect method for their numerical evaluation is developed. With the generalized exponential function, one can model sigmoid growth ( 0) b  , exponential growth ( 0) b  , and explosive growth ( 0) b  , where the term “explosive growth” refers to a relative growth rate that increases with time. The resulting formula of generalized exponential growth is               ( 1) 0 ( 1) 0 1 Ei exp +Ei for 0, 1 Ei exp +Ei for 0, C C
Determination of enteric methane emissions of dairy cows fed with different diets and relationship with milk yield and ruminal function in order to improve advice for farmers

Methane from ruminal fermentation, termed enteric methane, contributes 40% of the total agricultural emissions (Gerber et al., 2014). Mitigation of methane production could allow for a reduction in the impact of livestock on climate change and may improve the public perception towards this sector. Milk yield, methane emissions, carbon footprint and dietary costs were measured in experimental and commercial farms in different diet conditions: enriched fat diet (linseed or canola), high concentrate diet, high level of starch in diet or grazing. Individual milk samples were analysed monthly for milk quality and for methane emissions predicted by milk spectra analysis. The first results showed that methane emissions per kg of milk can vary from 11 to 20 g. Preliminary comparison between the diets demonstrated that feeding with grazed grass was beneficial in terms of feeding costs and environmental impact while methane emissions per kg milk were higher. Diets with low fibre content can have a beneficial impact to decrease methane emissions but could disturb ruminal function. These results will allow us to predict methane emissions and environmental impacts of milk production according to the diet composition, dietary costs, lactation stage and milk production. From these results, advice about feeding strategies could be given to reach the best compromise between environmental and economic objectives.
Estudos QSAR e Ancoragem Molecular de Inibidores da Atividade Biológica do Fator de Inibição da Migração dos Macrófagos (MIF)

Cumarina e 4-Cromonas sao promissores inibidores de fator inibicao da migracao de macrofagos (MIF), uma proteina envolvida em doencas inflamatorias, como artrite reumatoide e outras patologias. Estudos teoricos de QSAR e ancoragem molecular de um conjunto de compostos mostraram correlacao com estudos experimentais. Os descritores doadores de ligacao hidrogenio e momento dipolo total foram capazes de prever atividade inibitoria de compostos contra o MIF (MIFi). Paralelamente, estudos de ancoragem molecular tambem foram capazes de identificar ligacoes hidrogenio e hidrofobicas entre os ligantes e o MIF. Como resultado, ambas as metodologias mostraram as contribuicoes de ligacao de hidrogenio e interacoes hidrofobicas para explicar a atividade de compostos inibidores de MIF, descrevendo os grupos farmacoforicos destes compostos. Adicionalmente, um conjunto de cumarinas naturais e sinteticas foi submetido aos modelos QSAR e de ancoragem molecular a fim de que as suas atividades contra MIF fossem preditas. Ambas as metodologias de modelagem molecular puderam estimar as interacoes intermoleculares entre inibidores e a enzima, os quais foram muito similares a compostos descritos previamente. Estes resultados podem ser uteis para o desenho de novos compostos contra doencas inflamatorias como artrite reumatoide. Palavras-chave: MIF. REA. AINES. Artrite Reumatoide. Desenho Farmacos com Auxilio do Computador (CADD). ABSTRACT QSAR Modeling and Molecular Docking Study of Inhibitors of Macrophage Migration Inhibitory Factor (MIF)Coumarin and Chromen-4-one are promising inhibitors of Macrophage Migration Inhibitory Factor (MIF), a protein involved in rheumatoid arthritis and other inflammatory diseases. Quantum structure-activity relationship (QSAR) and docking theoretical studies were undertaken on a set of compounds of known activity and showed agreement with previous experimental studies. Two descriptors, hydrogen donor sites and the total dipole, were able to predict MIF inhibitory activity (MIFi). The docking studies corroborated the QSAR studies. As a result, both methods indicated contributions of hydrogen bonds and hydrophobic interactions that explain the activity of the MIF inhibitors, describing the pharmacophore groups these molecules. Additionally, a set of natural and synthetic coumarins was subjected to the QSAR and docking models in order to predict their possible MIF inhibitory activity. Both molecular modeling methods were able to estimate the intermolecular interactions between inhibitors and enzyme, which were very similar to those of previously described compounds. These results could be useful to design new compounds against inflammatory diseases such as rheumatoid arthritis. Keywords: MIF. SAR. NSAIDS. Rheumatoid Arthitis. Computer Aided Drug Design.
Recursive and sequential tests for unít roots and structural breaks in long annual GNP series

Recur s i ve and sequentia.l estimation procedures are applied to each of two long annual data ser'ies on the logarithm of real per' capi tal U. S, GNP, each of which includes the G,'eat Depression, The recursively--calculated Augmented Dickey-Fuller statistic for' a unit root, and several sequentially-calculated F-type s tatistics for str'uctural break s. are compared wi th cri tical values appropriate to such sets of statistics, The results for the long data series are consistent with those found on shorter (post"",ar) data sets; we do not find statistically significant evidence of a trend break ,
Análise da capacidade de descarregamento de dados usando o sistema de transporte público de uma metrópole

Cidades inteligentes melhorarao a qualidade de vida de seus cidadaos com a ajuda das tecnologias da informacao e da comunicacao. Entre outras tarefas, e necessario o monitoramento ambiental e a analise das informacoes para determinar acoes apropriadas. A realizacao dessas tarefas depende de infraestrutura de comunicacao confiavel e ubiqua, como uma rede celular. No entanto, a rede celular pode nao ser capaz de lidar com as necessidades de pico, deixando de prestar servicos quando a cidade mais precisa. Uma solucao promissora, objeto deste estudo, e utilizar canais de comunicacao alternativos para aliviar a infraestrutura da rede celular. Nesta tese investiga-se a transmissao de dados usando redes veiculares como um canal de descarregamento de dados. Mais especificamente, e analisada uma rede veicular formada por veiculos de transporte publico, onibus e taxis, que circulam pela cidade ao longo de todo o dia. Utilizar a onipresenca de onibus e taxis para ajudar a reunir e mover dados, parece promissor; entretanto, deve-se garantir que eles possam fornecer coletivamente a dinâmica e a capacidade necessarias para satisfazer os requisitos de transmissao. Analisa-se tambem a dinâmica e a capacidade da rede veicular considerando diferentes tecnologias sem-fio atualmente disponiveis. Dada a escala da rede e o grande numero de interacoes entre veiculos, inicialmente foi necessario reduzir a complexidade do sistema adotando uma topologia de grade e agrupando em clusters veiculos proximos usando o algoritmo STING. As analises revelam aspectos interessantes, como o fato dos veiculos apresentarem diferentes padroes de movimentos. Alem disso, onibus possuem um tempo medio inferior ao dos taxis para alcancar o proximo ponto de transferencia. Finalmente, os resultados mostram que quantidades significativas de dados podem ser transportadas na cidade do Rio de Janeiro, da ordem de 500 TB por dia.
Channel Correlation-Based Approach for Feedback Overhead Reduction in Massive MIMO

For frequency-division duplex multiple-input–multiple-output (MIMO) systems, the channel state information at the transmitter is usually obtained by sending pilots or reference signals from all elements of the antenna array. The channel is then estimated by the receiver and communicated back to the transmitter. However, for massive MIMO, this periodical estimation of the full transfer matrix can lead to prohibitive overhead. To reduce the amount of data, we propose to estimate the updated channel matrix from the knowledge of the full correlation matrix at the transmitter made during some initialization time and the instantaneous measured channel matrix of smaller size, characterizing the link between the user and a limited number of reference array elements. The proposed algorithm is validated with measured massive MIMO channel transfer functions at 3.5 GHz between a $9 \times 9$ uniform rectangular array and different user positions. Since measurements were made in static conditions, the criteria chosen for evaluating the performance of the algorithm are based on a comparison of the predicted channel capacity calculated from either the measured or estimated channel matrix.
Roles of novel biomarkers in progression of cutaneous squamous cell carcinoma

Cutaneous squamous cell carcinoma (cSCC) is the most common metastatic skin cancer. The incidence of cSCC is increasing worldwide due to lifestyle changes such as recreational exposure to sunlight and the aging of the population. Because of an emerging need for molecular markers for the progression of cSCC, we set our goal to characterize three distinct novel markers overexpressed in cSCC cells. Our results identified overexpression of serpin peptidase inhibitor clade A member 1 (SerpinA1), EphB2 and absent in melanoma 2 (AIM2) in cSCC cell lines compared with normal human epidermal keratinocytes (NHEKs). Immunohistochemical analysis of SerpinA1, EphB2 and AIM2 revealed abundant tumor cell-specific expression of cytoplasmic SerpinA1 and AIM2 and cytoplasmic and membranous EphB2 in cSCC tumors in vivo. The staining intensity of SerpinA1, EphB2 and AIM2 was significantly stronger in cSCC as compared with carcinoma in situ (cSCCIS) and actinic keratosis (AK). Tumor cell-associated SerpinA1 and EphB2 was noted in chemically induced mouse skin SCC, and the staining intensity was stronger in mouse cSCCs than in untreated skin. AIM2 staining intensity was significantly more abundant in cSCC of organ transplant recipients (OTR) than in sporadic cSCC in vivo. EphB2 knockdown resulted in inhibition of migration in cSCC cells. In addition, knockdown of EphB2 and AIM2 was found to inhibit the proliferation and invasion of cSCC cells and to delay the growth and vascularization of cSCC xenografts in vivo. Altogether, these findings identify SerpinA1 as a novel biomarker for cSCC. In addition, characterization of the roles of EphB2 and AIM2 in the progression of cSCC was implicated them as possible therapeutic targets for the treatment of cSCC particularly in unresectable and metastatic tumors.
Classification of Inter-Floor Noise Type/Position Via Convolutional Neural Network-Based Supervised Learning

Inter-floor noise, i.e., noise transmitted from one floor to another floor through walls or ceilings in an apartment building or an office of a multi-layered structure, causes serious social problems in South Korea. Notably, inaccurate identification of the noise type and position by human hearing intensifies the conflicts between residents of apartment buildings. In this study, we propose a robust approach using deep convolutional neural networks (CNNs) to learn and identify the type and position of inter-floor noise. Using a single mobile device, we collected nearly 2000 inter-floor noise events that contain 5 types of inter-floor noises generated at 9 different positions on three floors in a Seoul National University campus building. Based on pre-trained CNN models designed and evaluated separately for type and position classification, we achieved type and position classification accuracy of 99.5% and 95.3%, respectively in validation datasets. In addition, the robustness of noise type classification with the model was checked against a new test dataset. This new dataset was generated in the building and contains 2 types of inter-floor noises at 10 new positions. The approximate positions of inter-floor noises in the new dataset with respect to the learned positions are presented.
Agronomic performance of colored cotton influenced by irrigation with treated domestic sewage and potassium fertilization in semi-arid region of Brazil

This study evaluated the contribution of potassium (K) nutrition and application of wastewater depths to the agronomic performance of colored cotton. Treatments consisted of five irrigation depths (50, 75, 100, 125 and 150% of crop evapotranspiration -ETC) and five K doses (0, 50, 100, 150 and 200% of the recommendation for the crop) and an absolute control irrigated with 100% ETCwater depth and fertilized with 100% N-P-K recommendation. Each treatment and the control had four replicates. Plant height, stem diameter, leaf area and shoot dry matter accumulation of cotton were evaluated at 130 days after emergence (DAE), whereas seed cotton weight was evaluated at 135 DAE. Our findings indicate that the use of treated domestic sewage for 100% ETCreplacement promotes greater gains of weight and growth in colored cotton without the need for K fertilization, evidencing the potential of wastewater for colored cotton for sustainable agriculture.
Age replacement policy in the case of no data: the effect of Weibull parameter estimation

Age replacement is a common maintenance policy when wear-out failures occur, and it is characterised by periodic replacement of components. Data on time to failure (TTF), often modelled with the Weibull function, are necessary for estimating optimal replacement intervals to minimise the total maintenance costs. In many cases, such as new components, new machines or new installations, no TTF data are available, so the Weibull parameters and optimal replacement interval cannot be estimated. To overcome this problem, these parameters can be assessed from the experience of the maintenance engineers and technicians. The aim of this study is investigating the relationship between the error in parameter estimation and additional maintenance costs related to this error. Analysis of variance (ANOVA) and multifactorial analysis are carried out for investigating the influence of these estimations on the final costs. Economic decision maps are introduced for supporting maintenance engineering in defining the maintenance policy with minimal additional cost in the case of no data being available. The analysis shows that, when no data are available, the application of the age replacement policy can result in a global saving of more than 50% compared with corrective maintenance.
Water-level attenuation in global-scale assessments of exposure to coastal flooding: a sensitivity analysis

Abstract. This study explores the uncertainty introduced in global assessments of coastal flood exposure and risk when not accounting for water-level attenuation due to land-surface characteristics. We implement a range of plausible water-level attenuation values for characteristic land-cover classes in the flood module of the Dynamic and Integrated Vulnerability Assessment (DIVA) modelling framework and assess the sensitivity of flood exposure and flood risk indicators to differences in attenuation rates. Results show a reduction of up to 44 % in area exposure and even larger reductions in population exposure and expected flood damages when considering water-level attenuation. The reductions vary by country, reflecting the differences in the physical characteristics of the floodplain as well as in the spatial distribution of people and assets in coastal regions. We find that uncertainties related to not accounting for water attenuation in global assessments of flood risk are of similar magnitude to the uncertainties related to the amount of sea-level rise expected over the 21st century. Despite using simplified assumptions to account for the process of water-level attenuation, which depends on numerous factors and their complex interactions, our results strongly suggest that an improved understanding and representation of the temporal and spatial variation of water levels across floodplains is essential for future impact modelling.
Inspection of an underwater structure using point‐cloud SLAM with an AUV and a laser scanner

This paper presents experimental results using a newly developed 3D underwater laser scanner mounted on an autonomous underwater vehicle (AUV) for real‐time simultaneous localization and mapping (SLAM). The algorithm consists of registering point clouds using a dual step procedure. First, a feature‐based coarse alignment is performed, which is then refined using iterative closest point. The robot position is estimated using an extended Kalman filter (EKF) that fuses the data coming from navigation sensors of the AUV. Moreover, the pose from where each point cloud was collected is also stored in the pose‐based EKF‐SLAM state vector. The results of the registration algorithm are used as constraint observations among the different poses within the state vector, solving the full‐SLAM problem. The method is demonstrated using the Girona 500 AUV, equipped with a laser scanner and inspecting a 3D sub‐sea infrastructure inside a water tank. Our results prove that it is possible to limit the navigation drift and deliver a consistent high‐accuracy 3D map of the inspected object.
Simvastatin Modulates Extracellular Matrix Assembly by Displaying an Antifibrotic Activity in Vitro

Statins, competitive inhibitors of 3-hydroxy-3-methylglutaryl coenzyme A reductase, are known to possess properties beyond their cholesterol-lowering effect including anti-inflammatory, antiproliferative and anti-immunomodulatory effects. We examined the effect of simvastatin on extracellular matrix (ECM) assembly by human skin fibroblasts (HSFs) in vitro. Using collagen gel contraction (CGC) assay we showed that simvastatin inhibits contraction of type I collagen-rich gels in a dose-dependent manner. This effect of simvastatin could be overcome by co-incubating the cells with mevalonate. Actin staining revealed that inhibition of CGC by simvastatin is associated with diminished ability of the cells to form aggregates. Using whole human genome Illumina microarray we sought to search for new candidate genes whose expression is regulated by simvastatin during CGC and focused specifically on the genes related to ECM synthesis and remodeling. We found that simvastatin profoundly downregulated gene expression of 27 ECM molecules including proteoglycans decorin and versican, both of which are known to be essential constituents of proper ECM. Expression of these two molecules was further verified by Northern blot analysis. Finally, when simvastatin treated HSFs were activated with TGF-β1, the cell-mediated contraction of collagen gel was restored. Our results indicate that simvastatin markedly alters ECM assembly in vitro possessing an antifibrotic activity.
The effects of cloud–aerosol interaction complexity on simulations of presummer rainfall over southern China

Abstract. Convection-permitting simulations are used to understand the effects of cloud–aerosol interactions in a case of heavy rainfall over southern China. The simulations are evaluated using radar observations from the Southern China Monsoon Rainfall Experiment (SCMREX) and remotely sensed estimates of precipitation, clouds and radiation. We focus on the effects of complexity in cloud–aerosol interactions, especially the depletion and transport of aerosol material by clouds. In particular, simulations with aerosol concentrations held constant are compared with a fully cloud–aerosol-interacting system to investigate the effects of two-way coupling between aerosols and clouds on a line of organised deep convection. It is shown that the cloud processing of aerosols can change the vertical structure of the storm by using up aerosols within the core of line, thereby maintaining a relatively clean environment which propagates with the heaviest rainfall. This induces changes in the statistics of surface rainfall, with a cleaner environment being associated with less-intense but more-frequent rainfall. These effects are shown to be related to a shortening of the timescale for converting cloud droplets to rain as the aerosol number concentration is decreased. The simulations are compared to satellite-derived estimates of surface rainfall, a condensed-water path and the outgoing flux of short-wave radiation. Simulations for fewer aerosol particles outperform the more polluted simulations for surface rainfall but give poorer representations of top-of-atmosphere (TOA) radiation.