Miracle-dz/UniFAR-FTUs huggingface dataset:
REFAME: Rain Estimation Using Forward-Adjusted Advection of Microwave Estimates

A new multiplatform multisensor satellite rainfall estimation technique is proposed in which sequences of Geostationary Earth Orbit infrared (GEO-IR) images are used to advect microwave (MW)-derived precipitation estimates along cloud motion streamlines and to further adjust the rainfall rates using local cloud classification. The main objective of the Rain Estimation using Forward-Adjusted advection of Microwave Estimates (REFAME) is to investigate whether inclusion of GEO-IR information can help to improve the advected MW precipitation rate as it gets farther in time from the previous MW overpass. The technique comprises three steps. The first step incorporates a 2D cloud tracking algorithm to capture cloud motion streamlines through successive IR images. The second step classifies cloudy pixels to a number of predefined clusters using brightness temperature (Tb) gradients between successive IR images along the cloud motion streamlines in combination with IR cloud-top brightness temperatures and textural features. A mean precipitation rate for each cluster is calculated using available MW-derived precipitation estimates. In the third step, the mean cluster precipitation rates are used to adjust MW precipitation intensities advected between available MW overpasses along cloud motion streamlines. REFAME is a flexible technique, potentially capable of incorporating diverse precipitation-relevant information, such as multispectral data. Evaluated over a range of spatial and temporal scales over the conterminous United States, the performance of the full REFAMEalgorithmcomparedfavorablywithproductsincorporatingeitherno cloudtrackingorno intensity adjustment. The observed improvements in root-mean-square error and especially in correlation coefficient between REFAME outputs and ground radar observations demonstrate that the new approach is effective in reducing the uncertainties and capturing the variation of precipitation intensity along cloud advection streamlines between MW sensor overpasses. An extended REFAME algorithm combines the adjusted advected MW rainfall rates with infrared-derived precipitation rates in an attempt to capture precipitation events initiating and decaying during the interval between two consecutive MW overpasses. Evaluation statistics indicate that the extended algorithm is effective to capture the life cycle of the convective precipitation, particularly for the interval between microwave overpasses in which precipitation starts or ends.
MODELING ISOSTERIC HEAT OF BANANA FOAM MAT USING NEURAL NETWORK APPROACH

Information on the adsorption isotherm and the ther modynamic properties can assist in optimizing food processing operations such as drying, packaging and storage in the assessment of the quality of food. In this study, an Artificial Neural Network (ANN) was used for modelling the water activity/Equilibrium Relati ve Humidity (ERH) of banana foam mat under a range of values of the Experimental Equilibrium Moisture Content (EMC) to calculate the isosteric heat of so rption (qst ) by applying the Clausius-Clapeyron equation. The EMC of three dry banana foam samples at different densities of 0.21, 0.26 and 0.30 g/cm 3 was determined by a standard gravimetric method over a temperature range of 35-45°C and a relative humidit y range of 32-83%. The modified-GAB model best fitted the EMC data. However, the modified-GAB model was not acceptable for predicting the heat sorption behaviour. A negative value of q st estimated using the modified-GAB equation was found at a moisture content above 0.24 kg/kg d.b. , showing the poor fit of t he model. A multilayer feed-forward ANN trained by back-propagation algorithms was developed to correlate the output ERH to three exogenous inputs (foam density, EMC and temperature). The developed ANN models could predict the ERH more accurately than the modified-GAB model. The predictions from the ANN models produced R 2 values higher than 0.97. No negative q st values were found using the ANN method.
Evaluation of the API 50CHB system for the identification and biochemical characterization of Bacillus larvae

Bacillus larvae White est l'agent de la loque americaine, maladie tres repandue dans les colonies d'abeilles et pour laquelle sont prevues des mesures d'eradication par les services veterinaires. Le systeme API 50CHB a ete teste dans ce but. Le test, applique a 29 souches de provenances geographiques differentes (Italie, Pologne, Republiques tcheque et slovaque), a permis de definir pour B larvae un profil biochimique concernant l'acidification des 49 substrats (hydrates de carbone et leurs derives) prevus par la methode. Le substrat de developpement utilise avait la composition suivante: extrait de levure, 10 g; neo-peptone, 10 g; thiamine, 0,1 mg; agar, 15 g; eau distillee, 1000 ml; pH 6,8. Toutes les souches examinees ont presente une reaction positive (acidification) avec le ribose, D-glucose, D-mannose, N-acetylglucosamine, trehalose, D-tagatose; mis a part une souche, toutes ont acidifie le glycerol; des resultats variables ont ete observes avec la salicine et le 5-chetogluconate; une seule souche a acidifie le galactose et le D-fructose. Le profil biochimique obtenu pour B larvae au moyen du systeme API 50CHB est suffisamment caracteristique pour differencier B larvae des autres especes du meme genre. Les substrats les plus discriminatifs sont le fructose (presque toujours negatif), l'esculine (negatif) et le D-tagatose (positif)
Dynamical and biogeochemical control on the decadal variability of ocean carbon fluxes

Abstract. Several recent observation-based studies suggest that ocean anthropogenic carbon uptake has slowed down due to the impact of anthropogenic forced climate change. However, it remains unclear whether detected changes over the recent time period can be attributed to anthropogenic climate change or rather to natural climate variability (internal plus naturally forced variability) alone. One large uncertainty arises from the lack of knowledge on ocean carbon flux natural variability at the decadal time scales. To gain more insights into decadal time scales, we have examined the internal variability of ocean carbon fluxes in a 1000 yr long preindustrial simulation performed with the Earth System Model IPSL-CM5A-LR. Our analysis shows that ocean carbon fluxes exhibit low-frequency oscillations that emerge from their year-to-year variability in the North Atlantic, the North Pacific, and the Southern Ocean. In our model, a 20 yr mode of variability in the North Atlantic air-sea carbon flux is driven by sea surface temperature variability and accounts for ~40% of the interannual regional variance. The North Pacific and the Southern Ocean carbon fluxes are also characterised by decadal to multi-decadal modes of variability (10 to 50 yr) that account for 20–40% of the interannual regional variance. These modes are driven by the vertical supply of dissolved inorganic carbon through the variability of Ekman-induced upwelling and deep-mixing events. Differences in drivers of regional modes of variability stem from the coupling between ocean dynamics variability and the ocean carbon distribution, which is set by large-scale secular ocean circulation.
The Corporate Governance and Firm Performance: A Review of Existing Empirical Evidence

The study aims to review and expand general understanding on the relationship between corporate governance and firm performance. The study is motivated by the current debate on the role of corporate governance on firm performance and sustainability and an assertion that corporate failure is a result of failures in corporate governance mechanisms. Prior studies have confirmed notable roles played by corporate governance on firm performance. The study has analysed and comprehended key issues of corporate governance and key factors affecting its general mechanism in protecting shareholders’ interest. It further analyses and presents key players of corporate governance which in one way or other have strong influence on the effectiveness of the corporate governance. The study adds on the existing debate and widens stock of literature relating to roles of corporate governance in maximising shareholders’ value. It is considerably of usefulness to investors, practitioners and other stakeholders who are interested with firm’s operations performance in particular. Key words: Corporate governance, firm’s performance.
Factors Related to Late-Life Immigration and QoL Political / Legal Context of Late-Life Immigrants

Late-life immigration among seniors for purposes of family reunification is a growing phenomenon in developed countries. Using the World Health Organization’s Quality of Life instrument short form (WHOQOL-BREF) and other psychosocial measures related to the political/legal context of immigration, and personal and environmental autonomy (mastery, immigration status, access to transportation, and language barrier), this study examined quality of life (QoL) in Asian Indian seniors (N = 109), who immigrated to the United States to reunite with their adult children. The sample scores on Overall QoL and QoL domains (physical and psychological health, social relationships, and environment) were similar to established norms. Although all QoL domains correlated significantly with Overall QoL at the bivariate level, multivariate analysis showed that only environmental domain contributed significantly to Overall QoL. Linear regressions indicated: Mastery contributed significantly to Overall QoL and all QoL domains; access to transport contributed to Overall QoL, physical health, and environmental QoL; immigration status (a proxy for political/legal context) contributed to environmental QoL whereas language barrier contributed to none. Implications for improving perceptions of QoL, mastery, access to transport and other services are discussed.
Upwelling characteristics derived from satellite sea surface temperature data in the Gulf of Finland, Baltic Sea

The seven-year (2000-2006) satellite sea surface temperature (SST) data were examined to determine characteristics of coastal upwellings during the warm period of the year (June-September) in the Gulf of Finland. A total of 20 sufficiently cloud-free SST images depicting well-expressed coastal upwelling were found. The area covered by upwelling water, the temperature difference between the upwelling and surrounding waters, and the location and area of filaments were estimated. The average area covered by the upwelling water was 4820 km 2 and for the largest upwelling event 12 140 km 2 , i.e. 38% of the Gulf surface area. The average upwelling area along the Finnish coast (6120 km 2 ) was larger than the upwelling area along the Estonian coast (4070 km 2 ) which likely results from a larger cumulative wind stress (the product of wind stress and its duration) of westerly winds during the observed upwellings. The detected upwelling filaments were predominantly related to an upwelling along the Finnish coast. The area of a single filament usually varied from 80 to 680 km 2 while the total area of filaments reached the maximal value of 1420 km 2 during the strongest upwelling event.
Offspring development and life‐history variation in a water flea depends upon clone‐specific integration of genetic, non‐genetic and environmental cues

Theory predicts that offspring developmental strategies involve the integration of genetic, non-genetic and environmental ‘cues’. But it is unclear how cue integration is achieved during development, and whether this pattern is general or genotype-specific. In order to test this, we manipulated the maternal and offspring environments of three genetically distinct clones of the water flea Daphnia magna taken from different populations. We then quantified the effect that the genotype, maternal environment and the offspring environment had on the development and life-histories of the three different clones. Mothers responded to the same maternal environments in different ways, resulting in clone-specific maternal effects on neonate size. Offspring responses to maternal cues varied according to the trait in question and were also clone-specific. The integration of these maternal effects during development was highly context-dependent in two clones but more consistent across environments in the third. Genetic, non-genetic and environmental cues contributed to offspring phenotypic variation in all three clones, but there was no general pattern linking traits to specific cues. In fact, two clones used different combinations of cues at different points in development to achieve similar phenotypic outcomes. Reaction norms for the age and size at which maturation was initiated differed among genotypes, between maternal environments and across current environments. Developmental transitions such as the decision to mature may thus play an important role in determining patterns of cue integration. Considering multiple traits during development demonstrated that variation in the integration of genetic, non-genetic and environmental cues was an important determinant of life-history variation among D. magna genotypes. This variation is likely to influence phenotypic evolution.
Title Energy Harvesting Wireless Communications : A Review ofRecent Advances

This paper summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access, and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed, as well as models for energy consumption at the nodes.
Transfer Capability : development dynamics in higher education institutions

Starting in the 1980s, several national governments were explicitly fostering the generation of new technologies in higher education institutions (HEIs) and the transfer of their respective outcomes into the productive sector (SANTOS; TOLEDO; LOTUFO, 2009; CLARIM, 2011). The assumption is that HEIs may reduce steps in the development of new goods, as well as mitigate the limitations of keeping a Research and Development sector (R&D) in a firm (HELLMAN, 2007; MATHEWS; HU, 2007). However, despite its importance and the efforts made by governments, technology transfer is still a bottleneck in most of Brazilian public HEIs (ADES, 2013; CADORI, 2013; MCTI, 2015). We can define technology transfer as the action of transferring technology originating in one organization to another or to other organizations, through the necessary comprehension, interpretation, Corresponding author: † Universidade Federal da Paraíba, João Pessoa, Paraíba E-mail: cleverton.ufpb@hotmail.com Ω Universidade Federal da Paraíba, João Pessoa, Paraíba E-mail: agcmachado@gmail.com ABSTRACT
Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis

We use the GARCH-MIDAS model to extract the long- and short-term volatility components of cryptocurrencies. As potential drivers of Bitcoin volatility, we consider measures of volatility and risk in the US stock market as well as a measure of global economic activity. We find that S&P 500 realized volatility has a negative and highly significant effect on long-term Bitcoin volatility. The finding is atypical for volatility co-movements across financial markets. Moreover, we find that the S&P 500 volatility risk premium has a significantly positive effect on long-term Bitcoin volatility. Finally, we find a strong positive association between the Baltic dry index and long-term Bitcoin volatility. This result shows that Bitcoin volatility is closely linked to global economic activity. Overall, our findings can be used to construct improved forecasts of long-term Bitcoin volatility.
Remnants of Antarctic Vegetation on King George Island During the Early Miocene Melville Glaciation

Palynological analyses of 12 samples from the Cape Melville Formation, which crops out on easternmost King George Island, Antarctica, provide new information on the type of vegetation that covered the South Shetland Islands during the early Miocene Melville Glaciation, c. 23–21 Ma. The assemblage recovered was mostly characterised by in situ algae such as leiospheres along with acanthomorph acritarchs, both glacial indicators. The sparse in situ terrestrial palynomorph assemblage included tundra-indicative moss spores Coptospora sp. , rare podocarp conifer and various angiosperm pollen. The latter includes pollen of several species of Nothofagidites, plus rare Asteraceae, Caryophyllaceae (Colobanthus-type) and Chenopodipollis. The majority of the palynomorphs recovered are interpreted as reworked, denoting glacial scouring and redeposition from various sites in the Antarctic Peninsula and the South Shetland Islands. These reworked palynomorphs are of Permian to Paleogene age. This reworked component provides insight into the potential sources of reworking, and is consistent with multiple cycles of glacial advances to the Melville Peninsula at the time of deposition. The penecontemporaneous palynomorphs recovered provide new data on the climatic regime and glacial intensification during the early Miocene on King George Island.
UpLIFTing PFI: Does LIFT improve Public-Private Procurement?

The Private Finance Initiative (PFI) and Local Improvement Finance Trust (LIFT) were both introduced by the UK government as part of a drive to improve public service provision. Both PFI and LIFT focus on leveraging the key strengths of the public and private sectors when developing new facilities. This paper does not seek to question the need for new infrastructure, but rather discusses the difficulties encountered when trying to analyse LIFT as a system and when evaluating whether it can address earlier concerns about the PFI procurement process. Our analysis suggests that it is difficult to predict whether LIFT will be capable of delivering on its promise of providing cost-effective, bespoke Primary Care facilities.
THE MASS–METALLICITY AND LUMINOSITY–METALLICITY RELATIONS FROM DEEP2 AT z ∼ 0.8

We present the mass–metallicity (MZ) and luminosity–metallicity (LZ) relations at z ∼ 0.8 from ∼1350 galaxies in the Deep Extragalactic Evolutionary Probe 2 survey. We determine stellar masses by fitting the spectral energy distribution inferred from photometry with current stellar population synthesis models. This work raises the number of galaxies with metallicities at z ∼0.8 by more than an order of magnitude. We investigate the evolution in the MZ and LZ relations in comparison with local MZ and LZ relations determined in a consistent manner using ∼21, 000 galaxies in the Sloan Digital Sky Survey. We show that high stellar mass galaxies (M ∼ 1010.6 M☉) at z ∼0.8 have attained the chemical enrichment seen in the local universe, while lower stellar mass galaxies (M ∼ 109.2 M☉) at z ∼0.8 have lower metallicities (Δlog(O/H) ∼ 0.15 dex) than galaxies at the same stellar mass in the local universe. We find that the LZ relation evolves in both metallicity and B-band luminosity between z ∼0.8 and z ∼ 0, with the B-band luminosity evolving as a function of stellar mass. We emphasize that the B-band luminosity should not be used as a proxy for stellar mass in chemical evolution studies of star-forming galaxies. Our study shows that both the metallicity evolution and the B-band luminosity evolution for emission-line galaxies between the epochs are a function of stellar mass, consistent with the cosmic downsizing scenario of galaxy evolution.
Comparison of the Edwards SAPIEN XT and the Medtronic CoreValve prosthesis

Heart Center, Segeberger Kliniken GmbH (Academic Teaching Hospital of the Universities of Kiel and Hamburg), Bad Segeberg, Germany *Author for correspondence: Tel. : +49 4551 802 4801 Fax: +49 4551 802 4805 gert.richardt@segebergerkliniken.de Transcatheter aortic valve implantation (TAVI) has become the preferred treatment option for patients with symptomatic severe aortic stenosis who are inoperable or at high risk for surgical aortic valve replacement. TAVI has shown a clear mortality benefit compared to conservative treatment in inoperable patients, and is at least non-inferior to surgical aortic valve replacement in high-risk operable patients. Through improvements in the field of imaging, refinement in valve technologies, increasing operator and team experience and continuous valuable research, TAVI has developed rapidly in the past years and is expected to further boost in the near future. In this review, we discuss the technical and procedural aspects of TAVI, the acute and late outcomes, and highlight the current expectations and potential future development of this rapidly evolving technology.
A numerical classification of some Thermus isolates

Summary: A numerical classification was performed on a collection of 45 Thermus isolates recovered from New Zealand hot pools and on six type strains including T. aquaticus and “T. thermophilus”. Unweighted average linking (UPGMA) and single linkage clustering methods were applied to similarity matrices derived from simple matching (SSM ) and Jaccard similarity (SJ ) coefficients. Differences were observed between phenograms derived from SSM and SJ coefficients, indicating that some of the clusters formed were derived from a significant component of negative matches. Test error was estimated at 2.9%. In the UPGMA/SSM phenogram, seven clusters were formed. A majority of the New Zealand isolates did not cluster with non-New Zealand isolates. Analysis of variance showed that there was a relationship between the composition of the clusters and the temperature and pH of the source of the isolate. Chi-squared testing showed that, within New Zealand, the geographical source of the isolate had no bearing on the clusters formed.
MRI Foreground -‐ Background Multi -‐ task CNN Segmentation Multi -‐ task CNN

We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is an end-to-end learning-based approach to brain segmentation that jointly learns an abstract feature representation and a multi-class classification. We propose a 3D patch-based approach, where we do not only predict the center voxel of the patch but also neighbors, which is formulated as multi-task learning. To address a class imbalance problem, we arrange two networks hierarchically, where the first one separates foreground from background, and the second one identifies 25 brain structures on the foreground. Since patches lack spatial context, we augment them with coordinates. To this end, we introduce a novel intrinsic parameterization of the brain volume, formed by eigenfunctions of the Laplace-Beltrami operator. As network architecture, we use three convolutional layers with pooling, batch normalization, and non-linearities, followed by fully connected layers with dropout. The final segmentation is inferred from the probabilistic output of the network with a 3D fully connected conditional random field, which ensures label agreement between close voxels. The roughly 2.7 million parameters in the network are learned with stochastic gradient descent. Our results show that DeepNAT compares favorably to state-of-the-art methods. Finally, the purely learning-based method may have a high potential for the adaptation to young, old, or diseased brains by fine-tuning the pre-trained network with a small training sample on the target application, where the availability of larger datasets with manual annotations may boost the overall segmentation accuracy in the future.