Miracle-dz/UniFAR-FTUs huggingface dataset:
Land Classiﬁcation Using Deep Neural Networks Applied to Satellite Imagery Combined with Ground-Level Images

—With the exponential growth of georeferenced labeled and high-detailed imagery information of our world available on the web, combined with both computational power and the algorithms improvements from the last years, the land classiﬁcation task becomes more reliable from the start, and thus it is possible to achieve sharper results when applying deep learning techniques to that imagery. Besides using exclusively high resolution data to train deep learning models, we can now apply it to terrain elevation models in order to have a more precise information about the visibility areas of a picture to better classify the land. Mapping the multiple sources of human activity involved in land or minimizing natural hazards, are two of many applications of a Geographic Information System (GIS), and our geographic knowledge discovery beneﬁts from having this kind of information. This work advances a new study on the feasibility of applying deep neural networks and visibility analysis techniques to a combination of satellite imagery and ground-level images to classify land, either from nowadays (that contain satellite imagery) and also from past periods of time, when satellite imagery was not available but only ground-level photographs.
The outcome of the ECB’s evaluation of its monetary policy strategy

In October 1998 the Governing Council of the ECB announced the main elements of its stabilityoriented monetary policy. The strategy consists of a quantitative definition of price stability and a twopillar framework for assessing risks to price stability. After more than four years, the Governing Council felt it would be useful to evaluate its strategy in the light of its experience. On 8 May 2003 it confirmed the definition of price stability as a year-on-year increase in the Harmonised Index of Consumer Prices (HICP) for the euro area of below 2%. Price stability is to be maintained over the medium term. The Council also clarified that, in the pursuit of price stability, it aims to maintain inflation rates below, but close to, 2% over the medium term. Furthermore, the Governing Council confirmed that its monetary policy decisions will continue to be based on a comprehensive analysis of the risks to price stability, comprising an economic analysis and a monetary analysis. It thereby retains the two-pillar approach to the organisation, assessment and cross-checking of policy-relevant information. The President’s Introductory Statement to the ECB’s monthly press conference has been restructured to better reflect this approach. Furthermore, the Governing Council decided to no longer review the monetary reference value on an annual basis.
Overview of thyroid disease in pregnancy-UpToDate

Thyroxine-binding globulin — During pregnancy, serum TBG concentrations rise almost twofold because estrogen increases TBG production and TBG sialylation, which results in decreased clearance of TBG [2]. To maintain adequate free thyroid hormone concentrations during this period, thyroxine (T4) and triiodothyronine (T3) production by the thyroid gland must increase. The TBG excess leads to an increase in both serum total, but not free, T4 and T3 concentrations. Levels of total T4 and T3 rise by approximately 50 percent during the first half of pregnancy, plateauing at approximately 20 weeks of gestation, at which time a new steady state is reached and the overall production rate of thyroid hormones returns to prepregnancy rates. (See "Euthyroid hyperthyroxinemia and hypothyroxinemia".)
LC-MS method development for the quantitation of potential genotoxic impurity 2-Methyl-6-nitro aniline in Telmisartan API

Current work discloses the sensitive LC-MS/MS method development for the trace level determination of genotoxic impurity 2-Methyl-6-nitro aniline in Telmisartan. 2-Methyl-6-nitro aniline was determined by LC-MS/MS method in selected ion monitoring mode using LiChrospher RP-18 (100 × 4.6 mm) 5.0 μm column. Gradient technique was applied for the elution of analytes using acetonitrile (mobile phase A) and 0.01 M ammonium acetate buffer (mobile phase B) in different ratios. The gradient program (T/%B) was set as 0/5, 2.50/15, 5.00/30, 10.00/50, 15.00/95, and 20.00/95. Developed method was validated as per International Conference on Harmonization guidelines. The limit of detection and limit of quantitation values found for 2-Methyl-6-nitro aniline were 0.05 and 0.1 μg/ml. The developed method serves as an upright tool in quality control for quantitation of 2-Methyl-6-nitro aniline impurity at trace levels in Telmisartan.
Root Heterogeneity and Developmental Stage Determine the Pattern of Cellulose Synthase and Cinnamyl Alcohol Dehydrogenase Gene Expression Profiles during Xylogenesis in Populus trichocarpa (Torr. et Gray)

Premise of research. Woody plants show clear divergence among first-order roots. The functions of pioneer roots are mostly for structural support and transport, whereas fibrous roots are responsible for the absorption of water and nutrients. These roots significantly differ in growth rate and rate of xylogenesis, which strongly influence their function. We hypothesized that differences in histogenesis of individual roots of a known age strongly contribute to the different gene expression profiles observed during the course of xylogenesis. Methodology. We monitored xylogenesis in the roots of Populus trichocarpa under field conditions along with expression analyses (quantitative RT-PCR) of the cinnamyl alcohol dehydrogenase family (CAD and CAD-like) and the cellulose synthase superfamily genes (CesA, Csl). Pivotal results. A close relationship between root structure and the results obtained from molecular analyses was demonstrated. The expression profiles of the genes analyzed changed with root development and varied significantly, even between two consecutive days of root growth. A uniform pattern of expression profiles of the different genes was observed during xylogenesis, with the highest increase of expression in roots that contain tracheary elements (TEs) differentiation. TE maturation resulted in decreased expression of the analyzed genes in fibrous roots, while in pioneer roots, high expression was maintained when TEs continued differentiation and along with the beginning of secondary development. Conclusions. Our results show that the structure of individual roots strongly influences gene expression involved in different stages of xylogenesis among different root types, emphasizing the importance of their functional diversity within the root system. The results highlight the value of anatomical characterization of plants before interpretation of physiological, biochemical, and molecular analyses.
University of Birmingham On the Learnability of Programming Language Semantics

Game semantics is a powerful method of semantic analysis for programming languages. It gives mathematically accurate models (“fully abstract”) for a wide variety of programming languages. Game semantic models are combinatorial characterisations of all possible interactions between a term and its syntactic context. Because such interactions can be concretely represented as sets of sequences, it is possible to ask whether they can be learned from examples. Concretely, we are using long short-term memory neural nets (LSTM), a technique which proved effective in learning natural languages for automatic translation and text synthesis, to learn game-semantic models of sequential and concurrent versions of Idealised Algol (IA), which are algorithmically complex yet can be concisely described. We will measure how accurate the learned models are as a function of the degree of the term and the number of free variables involved. Finally, we will show how to use the learned model to perform latent semantic analysis between concurrent and sequential Idealised Algol.
Detecting Fake Accounts on Twitter Social Network Using Multi-Objective Hybrid Feature Selection Approach

The frequency of fake accounts or social bots is considered as one of serious challenges of online social networks, which are controlled by automatic operators and often used for malicious purposes. The researchers have performed many efforts to identify these entities in online social networks, which Machine Learning classifier technique using a distinctive feature set is the most common one and feature selection is the principal process of such feature-based classifiers. The present study was carried out the fake accounts detection by using a multi-objective hybrid feature selection approach that helps the feature set selection with optimal classification performance. First, the candidate feature set was identified based on the highest relation to the target class and the least redundancy among the features by the Minimum Redundancy – Maximum Relevance algorithm (mRMR). Then, the stable feature set with the minimum number of features, which can achieve optimal performance, is selected as the final feature set for the detection operations. The proposed approach is tested on two datasets from Twitter's social network and the results were compared to the results of efficient existing methods. According to the results, the performance of the proposed classifier approach is higher compared to existing methods.
Crystallographic analysis of the intact metal centres [3Fe–4S] and [4Fe–4S] in a Zn-containing ferredoxin

Detailed structural models of di-cluster seven-iron ferredoxins constitute a valuable resource for folding and stability studies relating the metal cofactors role in protein stability. The here reported, hemihedric twinned crystal structure at 2.0 Å resolution from Acidianus ambivalens ferredoxin, shows an integral 103 residues, physiologically relevant native form composed by a N-terminal extension comprising a His/Asp Zn site and the ferredoxin (bab)2 core, which harbours intact clusters I and II, a [3Fe–4S] and a [4Fe–4S] centres. This is in contrast with the previously available ferredoxin structure from Sulfolofus tokodai, which was obtained from an artificial oxidative conversion with two [3Fe–4S] centres and poor definition around cluster II. 2008 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
Thermal properties at Äspö HRL Analysis of distribution and scale factors

The aim of this study is to show how the maximum temperature at the canisters is influenced by a variation of the rock thermal properties in the vicinity of the waste repository. The thermal process has been simulated with use of a model based on the finite difference method (FDM). The model assumes conductive heat transfer in the rock mass and symmetrical location of canisters and tunnels. The considered region is bounded by symmetry planes. The temperature difference between the canister and average temperature in the considered region is calculated at “steady-flux” conditions. The rock thermal conductivities in this region are assigned randomly based on an assumed statistical normal distribution. Three idealized situations outlined in Figures A2-3, A2-4, and A2-6 are considered. The calculations are performed 100 times with random thermal conductivities for each set of parameter values and the mean value and standard deviation of the resulting distribution of steady-flux temperatures are evaluated.
Testing the Permanent Income Hypothesis in the Developing and Developed Countries: A Comparison between Fiji and Australia

Hall (1978) has stimulated considerable controversy and empirical work on testing the permanent income hypothesis (PIH). Much of the empirical work is on the developed countries where opportunities for inter-temporal substitution are generally higher than in the developing countries. Therefore, it is expected that PIH would be valid for only a smaller proportion of consumers in the developing countries. This paper uses the extended framework of Campbell and Mankiw (1989) to estimate the proportion of consumers for whom PIH is valid in Fiji and Australia. Our results show that PIH consumers are about 40% higher in Australia than in Fiji.
inFlow: Adapting gameplay to player personality

Neste artigo, propomos uma solução na forma de um jogo adaptativo que está constantemente a monitorizar o desempenho do jogador. Usando modelos de jogador baseados em diferentes tipos de personalidade, o jogo tentará adaptar-se continuamente às preferências do jogador, até o jogador se instalar num estado de flow. Uma série de testes aleatórios serão feitos para entender se a solução proposta tem, efectivamente, um efeito positivo sobre o divertimento dos jogadores. In this research we propose a solution in the form of an adaptive game that is constantly monitoring the player’s performance while playing. Using personality-based player models, the game will continuously try to adapt to the preferences of the player, until the player hopefully settles in a flow state. A series of random trials will be made to understand if the proposed solution has indeed a positive effect on the enjoyment of players.
Department of Mechanical Engineering, Federal University of Paraná, Brazil

Nine chemical reaction models for the pair hydrogen/oxygen are studied, taking into account different conditions found in real rocket engines. For chemical equilibrium, it is used equilibrium constants methodology. Comparisons between two models with eight chemical species have shown that the model with 18 chemical reactions has converged with smaller time than the model with 6 chemical reactions. It was also seen that the most complex model (eight species and 18 chemical reactions) has been the fastest, or nearly the one, among models with six and eight species. Results from models with six species have been very close to the ones obtained with eight species. A model with only four species, however, can have significant errors. Both combustion temperature and thermochemical properties depend only on the chemical species taken into account by the used model. Comparisons among results from the implemented program (Gibbs 1.3), CEA and Teqworks (these last two, programs from NASA) have shown that Gibbs 1.3 evaluates correctly both combustion temperature and mixtures of gases thermochemical properties.
Multiplicação in vitro de plantas juvenis de mamoeiro

The seminiferous propagation of Carica papaya L. presents a mixture of genotypes with a strong influence on fruit production costs, quality and yield , prevailing due to the lack of efficient protocols for vegetative propagation . In this context , the tissue culture emerges as a promising alternative, because it can provide, to farmers, sex determination in seedlings, with a high quality standard and enough amounts to supply commercial demands in all seasons . This study aimed at developing an in vitro micropropagation protocol from young papaya material, in two experiments. In the first experiment, the explants were multiplied in vitro and the cytokinins BAP, 2iP and KIN were tested at the concentrations of 0.0 mg L -1 , 2.5 mg L -1 , 5.0 mg L -1 and 10.0 mg L -1 , with the best results observed for 2iP, especially at the 2.5 mg L -1 concentration. In the second one, the 2iP cytokinin was used at the concentrations of 0.0 mg L -1 , 1.0 mg L -1 , 2.0 mg L -1 and 4.0 mg L -1 , with and without GA 3 (0.0 mg L -1 and 1.0 mg L -1 ), with beneficial effects of GA 3 observed in the multiplication process, especially when combined with 1.0 mg L -1 of 2iP, with the best results for plants height, number of leaves and explants sprouting.
Terminação em Confinamento de Vacas e Novilhas sob Dietas com ou sem Monensina Sódica

Feedlot parameters of two categories of cull females, cows and heifers, fed two diets, with and without monensin, were studied. The daily amount of monensin supplied was 150 mg/animal. The roughage:concentrate ratio was 65:35. The roughage used was sorghum silage. The inclusion of monensin to the diet caused a significant reduction of the daily voluntary dry matter intake (DDMI), which was more pronounced for the cows (9.1%) than for the heifers (1.7%). The animal category x diet interaction affected significantly the average daily weight gain (ADG). Monensin caused a slight increase in heifers ADG (1.92 vs 1.86 kg) while for the cows it reduced the ADG (1.56 vs 1.74 kg). Feed:gain ratio (DDMI/ADG) was not affected by monensin. Cows showed a higher DDMI than the heifers. However when DDMI was expressed per 100 kg of live weight and per unit of metabolic weight the difference disappeared. Heifers were more efficient than cows in converting feed into weight gain (6.40 vs 8.28 kg of DM/kg of live weight gain). The cost of feed per quilogram of live weight gain was R$ . 66 and . 69 for the heifers, and . 84 and . 74 for the cows, respectively, for the diets that included or not monensin.
Report on the 1st

This documents reports the activities performed in the context of the 1st Euro-TM Doctoral School on Transactional Memory, which took place in La Plagne (FR) from March 17 to March 22 2013. The school has been co-located with one of most renowned European doctoral schools on distributed computing, namely the PhD School on Hot Topics in Distributed Computing (HTDC). The high visibility of HTDC, together with a prestigious selection of lectures composed by widely known scientists, have been key to guarantee the success of the event. The school had 50 participants (doctoral students) from 15 countries, and 6 lecturers from some of the leading academic and industrial institutions (2 of whom from non-COST countries). The program has been designed to address a broad range of interdisciplinary topics. Three lectures were dedicated to analyse state of the art on diﬀerent aspects of TM, namely its theoretical foundations (Prof. P. Fatouru, University of Crete, Greece), hardware supports (Prof. Christos Kozyriakis, Stanford University, USA) as well as algorithms, language features and implementation (Dr. Mark Moir, Oracle Labs, USA). Three lectures were instead devoted to some of the hottest topics in the areas of distributed computing and software engineering, namely self-adaptive systems (Prof. Carlo Ghezzi, Politecnico di Milano, IT), Byzantine Fault Tolerance (Dr. Marco Vukolic, Eurecom, FR) and data center management (Dr. Paolo Costa, Microsoft Research, UK). By combining TM-focused lectures with talks on some of the currently most relevant topics in distributed computing, the school brought together experts and students having diﬀerent backgrounds and expertise, creating an ideal environment for interdisciplinary networking. Finally, students have been provided ample opportunities to present their current research activities and gather feedback both from the lecturers of the school and from the other students. The students’ presentations were organized in 3 doctoral sessions, hosting a total of 28 presentations that gave raise to lively discussions and triggered several new collaborations.
Short Sea Shipping Feasibility Study for the Carriage of RoRo Cargo to Northern European Ports

This paper aims to assess the competitiveness of Short Sea Shipping (SSS) by comparing the total amount of cargo between Portugal and Northern Europe that may be attracted by SSS (using RoRo ships) and by road. The total amount of cargo is evaluated according to a transportation demand evaluation model, which calculates transit times and costs between different regions in Europe. A decision-making process between transport modes is also included. The model also calculates external costs implied by both transport solutions and evaluates the effects of integrating these costs in the SSS potential demand. The model is tested for four alternative sea routes from Portugal to the Northern Europe, considering different destination ports: Le Havre, Rotterdam, Hamburg and Szczecin. The results allow the identification of the regions for which an intermodal solution (including SSS) is more competitive and quantifies its demand. SSS potential demand increases with lower freight rates, higher sailing speeds and external costs internalization. In all routes, apart from Le Havre, demand is more sensible to time than to costs. Rotterdam is the most interesting route due to its overall potential demand as well as its enlarged hinterland region. The results may be applied in determining the required cargo capacity of RoRo ships to be deployed in the different routes.
The importance of credit transfer in the decision to undertake post-compulsory education: an exercise in experimental choice analysis

The increasing value that education provides to the economy and society is now well established (Samier, 2000; McKenzie, 1999) and makes understanding the motivations for 'buying' formalised learning significant. From a supply-side perspective, providers must respond in a strategic manner to an increasingly complex environment. Reductions in Government funding have been accompanied by increased competition between providers for both students and funding. The result has, in part, led to pressure to treat education as a 'product', increasingly focusing on factors such as institutional standing, product differentiation and niche markets, relentlessly seeking new opportunities to achieve strategic objectives. Finally, there is the increased influence of stakeholders. From a demand-side perspective, the individual must be proactive in an environment where knowledge becomes rapidly obsolescent and workers are under constant pressure to up-grade their skills and knowledge throughout their working life. This paper reports findings relating to the relative importance of a number of product attributes, such as cost and the extent of credit transfer, in the individual’s decision to undertake post-compulsory education and training. The methodology utilised is experimental choice analysis which is a stated preference technique. This method combines an extensive iterative qualitative phase of data collection with a rigorous statistical technique to ultimately determine the marginal rate of substitution for the various product attributes.
The Role of Job Seekers’ Expectations on the Effects of Active Labor Market Policies

It has been shown that unemployed workers who anticipate participation in an active labor market policy (ALMP) program adjust their job search behavior. Depending on the expected effect of such a program, they search more intensively to leave unemployment and prevent the treatment or reduce their effort to wait out until the program start. Theoretical considerations suggest that these expectations (with respect to the participation probability and the treatment effect) also influence the job seekers labor market outcomes after the actual treatment has been realized, if there exists an inter-temporal dependency of the unemployeds’ behavior. Using German survey data on newly unemployed job seekers, the study shows that participants in long-term training programs who are not aware of the treatment ex ante face significantly lower long-run employment rates compared to their participating counterparts expecting the treatment. A further analysis of the job search behavior is conducted to understand the effect mechanisms. It shows that job seekers who do not expect a treatment also receive less support by their caseworker and fewer information about ALMP programs, which results in a lower willingness to adjust their job search behavior in association with a treatment. A structural model is estimated to account for the endogenous formation of expectations. The findings suggest that adjustments of the search behavior during the unemployment spell create additional search costs and therefore job seekers who have not been sufficiently informed about the possibility of a future program participation choose behavioral patterns that result in lower employment rates once the treatment is realized.