Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring intergenerational transmission of poverty

In this paper we examine the causal channels through which being born poor affects the individual’s economic outcomes as an adult, assessing the role of both parental and child human capital. We contribute to the growing literature on intergenerational transmission, applying different modern statistical techniques, refining measurement of causal effects. On one hand, we propose to apply a propensity score matching method to select a control group of non-treated individuals. The matched samples of poor and non-poor children will then be used to assess impacts on adulthood outcomes, primarily income and poverty. Moreover, because we are interested also on inequality of opportunity, we focus not only on mean impacts estimation, but also on the distributional effects of growing up poor. To this end, we apply semi-parametric and non-parametric estimators of the Quantile Treatment Effects (QTE). The analysis is based on a wide-ranging cross-country comparison using EU-SILC data. For the specific purpose of this project we use the module on intergenerational transmission of 2005 , where retrospective questions about parental characteristics (such as education, age, occupation) were asked. We find that being poor in childhood significantly decreases the level of income in adulthood (of around 3,000 euro on average), increasing the probability of being poor by 3%.
Apoplastic and symplastic solute concentrations contribute to osmotic adjustment in bean genotypes during drought stress

The present study investigates changes in the inorganic ions, proline, and endogenous abscisic acid (ABA) contents of the apoplastic and symplastic compartments of leaves from drought-tolerant (Yakutiye) and drought-sensitive (Zulbiye) cultivars of the common bean (Phaseolus vulgaris L.). Drought stress caused a decrease in leaf water potential and stomatal conductance in both cultivars. Concentrations of proline in the drought-tolerant and drought-sensitive cultivars increased in response to drought stress in both compartments. The symplastic K+ concentration decreased in both cultivars. However, the opposite trend was observed concerning K+ concentrations in the apoplastic areas. While the symplastic Na+ concentrations significantly decreased in the drought-tolerant cultivar, the apoplastic Na+ concentrations increased during drought stress. However, Na+ concentrations did not significantly change in either of the compartments in the drought-sensitive cultivar. The Ca2+ concentrations in the sensitive cultivar significantly decreased in both compartments during drought stress. In the tolerant cultivar, the Ca2+ concentration significantly increased in the symplast but decreased in the apoplast. Cl- concentrations in the tolerant cultivar did not significantly change in either compartment. In the sensitive cultivar, the Cl- concentration increased in the apoplastic area but decreased in the symplastic area. In addition, while the symplastic sap of the leaves exhibited a constant pH value, it diminished in the apoplast during drought stress. Symplastic and apoplastic ABA concentrations significantly increased in both cultivars. It might be said that inorganic ions (especially Na+, K+, and Ca2+) and ABA concentrations changed between the apoplastic and symplastic spaces to contribute to osmotic adjustment under drought stress. In addition, the drought-tolerant cultivar showed a much higher capacity to maintain osmotic adjustment between the symplast and the apoplast.
Flare pilot system safety

One of the worst nightmares a plant manager can experience is a complete flare system outage. The flare system is the last line of defense for many refining and petrochemical facilities and, when out of commission, can cause the shutdown of the entire facility. Flare ignition failure may lead to unburned venting of dangerous gases, and may develop into an explosive hazard leading to the loss of property and equipment, or worse, injury to personnel or loss of life. The safety and effectiveness of flaring are dependent upon one or more continuously burning pilots for immediate and sustained ignition of gases exiting a flare burner. Because pilot failure can compromise safety and effectiveness, it should be detected quickly and accurately to allow prompt automatic and/or operator response. Proper disposal of process and waste gases during routine and/or emergency conditions is crucial to help operating facilities protect plant employees and the surrounding community, and to avoid hundreds of thousands of dollars in fines. These reasons alone make the pilot monitoring and ignition system the most important component of any flare system. The advanced flare pilot systems explained in this article offer increased protection from harsh environmental conditions and rapid notice of pilot flame failure. Recently published industry standards for flare pilot design and performance are also discussed. © 2006 American Institute of Chemical Engineers Process Saf Prog, 2007
The environmental Kuznets curve in the case of Russia

This study explores the relationships between carbon emissions and their main determinants such as energy consumption, real income, international trade, level of education and level of urbanization in the Russian Federation, employing data for the period 1991–2016. Support for the environmental Kuznets curve hypothesis is found in this study, stating that environment pollution decreases in Russia after income achieves a certain threshold. The ARDL bounds test is employed in order to estimate short-run and long-run relationships in the estimated model. Energy consumption, real income, education and urbanization levels are found to be significant determinants of carbon emissions, while trade openness does not have an impact. The Granger causality test indicates two-way relationships between carbon emissions and energy use, real income and education. Only a single one-way causality runs from carbon emission to trade and no causality was found between carbon emissions and level of urbanization.
A new fabrication process for ultra-thick microfluidic microstructures utilizing SU-8 photoresist

In this paper we describe a new process for fabricating ultra-thick microfluidic devices utilizing SU-8 50 negative photoresist (PR) by standard UV lithography. Instead of using a conventional spin coater, a simple 'constant-volume-injection' method is used to create a thick SU-8 PR film up to 1.5 mm with a single coating. The SU-8 PR is self-planarized during the modified soft-baking process and forms a highly-uniform surface without any edge bead effect, which commonly occurs while using a spin coater. Photomasks can be in close contact with the PR and a better lithographic image can be generated. Experimental data show that the average thickness is 494.32 ± 17.13 μm for a 500 μm thick film (n = 7) and the uniformity is less than 3.1% over a 10 × 10 cm2 area. In this study, the temperatures for the soft-baking process and post-exposure baking are 120 °C and 60 °C, respectively. These proved to be capable of reducing the processing time and of obtaining a better pattern definition of the SU-8 structures. We also report on an innovative photomask design for fabricating ultra-deep trenches, which prevents the structures from cracking and distorting during developing and hard-baking processes. In this paper, two microfluidic structures have been demonstrated using the developed novel methods, including a micronozzle for thruster applications and a microfluidic device with micropost arrays for bioanalytical applications.
Near-surface monitoring strategies for geologic carbon dioxide storage verification

Geologic carbon sequestration is the capture of anthropogenic carbon dioxide (CO{sub 2}) and its storage in deep geologic formations. Geologic CO{sub 2} storage verification will be needed to ensure that CO{sub 2} is not leaking from the intended storage formation and seeping out of the ground. Because the ultimate failure of geologic CO{sub 2} storage occurs when CO{sub 2} seeps out of the ground into the atmospheric surface layer, and because elevated concentrations of CO{sub 2} near the ground surface can cause health, safety, and environmental risks, monitoring will need to be carried out in the near-surface environment. The detection of a CO{sub 2} leakage or seepage signal (LOSS) in the near-surface environment is challenging because there are large natural variations in CO{sub 2} concentrations and fluxes arising from soil, plant, and subsurface processes. The term leakage refers to CO{sub 2} migration away from the intended storage site, while seepage is defined as CO{sub 2} passing from one medium to another, for example across the ground surface. The flow and transport of CO{sub 2} at high concentrations in the near-surface environment will be controlled by its high density, low viscosity, and high solubility in water relative to air. Numerical simulations of leakage and seepage show that CO{sub 2} concentrations can reach very high levels in the shallow subsurface even for relatively modest CO{sub 2} leakage fluxes. However, once CO{sub 2} seeps out of the ground into the atmospheric surface layer, surface winds are effective at dispersing CO{sub 2} seepage. In natural ecological systems with no CO{sub 2} LOSS, near-surface CO{sub 2} fluxes and concentrations are controlled by CO{sub 2} uptake by photosynthesis, and production by root respiration, organic carbon biodegradation in soil, deep outgassing of CO{sub 2}, and by exchange of CO{sub 2} with the atmosphere. Existing technologies available for monitoring CO{sub 2} in the near-surface environment include (1) the infrared gas analyzer (IRGA) for measuring point concentrations using IR absorption by the CO{sub 2} molecule, (2) the accumulation chamber (AC) method for measuring soil CO{sub 2} fluxes at discrete points, (3) the eddy correlation (EC) tower that measures net flux over a given area, and (4) light distancing and ranging (LIDAR) that can measure CO{sub 2} concentrations over an integrated path. Novel technologies that could potentially be useful for CO{sub 2} concentration and flux measurement include hyperspectral remote sensing of vegetative stress as an indication of elevated CO{sub 2} concentrations, tunable lasers for long distance integrated concentration measurements, microelectronic mechanical systems (MEMS) that can be dispersed to make widespread point measurements, and trained animals such as dogs as used for landmine detection.
Willingness to pay for individual greenhouse gas emissions reductions

In the climate policy debate, a rhetoric has evolved that attributes a high potential to “voluntary climate action”. We turn to the population of Germany, the fourth largest cumulative GHG emitter, to obtain an (Internet-)representative estimate of the individual willingness to abate one ton of CO2, the equivalent of 10 percent of annual per-capita CO2 emissions. The estimate derives from a large-scale (n=2,440) framed …eld experiment in which subjects choose between a guaranteed reduction of one ton of EU CO2 emissions and a randomly drawn cash award between e2 and e100. At e6.30, estimated mean WTP is considerably lower than prior hypothetical or non-representative estimates. Median WTP is non-positive. The almost bimodal nature of WTP in the population has important policy implications.
The impact of information technology capability on firm performance; a focus on employee- customer profit chain

Employee-customer-profit(ECP) chain is one of the guidelines for organizations 'success in their life cycle. Strong relationships have been found between employees' attitudes and behaviors, employees' behaviors and customers' impressions, and customers' impressions and revenue growth. Out of this chain, there are some factors that can influence the processes through which these factors interact. One of these factors is information technology (IT) capability. In this research, we modeled the effect of IT capability on ECP chain using structural equation modeling (SEM). Service process innovation (SPI) was also used as a mediating variable between IT capability and ECP chain. This was accomplished based upon quantitative data gathered from a sample of 212 employees of the Technical and Vocational organization in Mashhad city. Results revealed a strong support for the proposed model. In particular, the association between IT capability and SPI with ECP chain and their leverage effect facilitate the organizations' movements along with the chain which was significantly confirmed.
POTENTIAL BENEFITS, CHALLENGES, AND BUSINESS MODEL OF CLOUD LEARNING: A CASE STUDY OF INDONESIA

During the last years, the most of educational institution have applying e-learning, however it is becoming not in line for social changes and educational progress. Hence, redesign the educational system is strong required. At the same time, Cloud computing is growing rapidly and created a global phenomenon on Information and Communication Technology (ICT) which playing cross over in any area, including education and often called Cloud Learning. In this paper we elaborate why cloud learning is widely accepted today, what considerable risk when adopting this practices, and what about the business model on Cloud Learning. Kata kunci: cloud computing, e-learning, benefit, challenges, business model, cloud learning
Phytochemical and Antimicrobial Screening of Cola gigantea Leaves, Stem and Bark

Phytochemical and antimicrobial analysis were carried out on the leaves, stem and bark extracts of Cola gigantea. The Phytochemicals present in the plant were Flavonoid, Tannins, Alkaloid, Cardiac glycoside, Steroids, Terpenoids and phenol. Flavonoid, Alkaloid and steroids were present in high amount in the plant than the other phytochemicals. For antimicrobial screening, the well-in-agar diffusion method was employed and the various zones of inhibition produced by the extract of the various plant parts on Escherichia coli, Bacillus subtilis, Staphylococcus aureus and Candida albicans were observed and recorded in millimeters (mm). The leaves of the plant had highest antimicrobial activities on Escherichia coli, Bacillus subtilis and Staphylococcus aureus, while the stem had highest antimicrobial activity on Candida albicans. The observed antimicrobial activity of the extract suggests its potential use in the treatment of diseases produced by the various test pathogenic microorganisms.
INSTITUTIONAL ENVIRONMENTS IN THE FORMATION OF INTERNATIONAL JOINT VENTURE: A BRAZILIAN CASE STUDY

A pesquisa foi conduzida numa joint venture internacional formada entre uma empresa brasileira e uma espanhola, localizada no Brasil, operando na industria de cosmeticos. Os CEOS de ambas empresas foram entrevistados. As entrevistas ocorreram em agosto de 2001 e maio de 2003 acompanhando a evolucao do fenomeno pesquisado. Todas as entrevistas foram transcritas e a analise de conteudo foi utilizada para desvendar temas teoricos que estruturavam os discursos de acordo ao modelo de pesquisa desenvolvido com base numa extensiva revisao da literatura. O modelo muniu a pesquisa de uma estrutura para tracar elementos teoricos diversos no desenvolvimento da joint venture. Em termos da compreensao de diferentes racionalidades dispostas pelos diferentes parceiros em seus discursos, foram desenvolvidas etapas dos dois paises que possibilitaram um melhor mecanismo de interpretacao. Teoricamente, aspectos da Teorias de Custo de Transacao, da Teoria Institucional e da Dependencia de Recursos puderam ser analisadas, em termos de racionalidades moldando os discursos, configurando as formas de decisao da joint venture. Com respeito as praticas, essas teorias devem ser consideradas como complementares em vez de caminhos alternativos para moldar o mundo: cada uma representa um elemento do trabalho discursivo que compoe a constituicao da joint venture.
Speaker Identification using SVM during Oriya Speech Recognition

In this research paper, we have developed a system that identifies users by their voices and helped them to retrieve the information using their voice queries. The system takes into account speaker identification as well as speech recognition i.e. two pattern recognition techniques in speech domain. The conglomeration of speaker identification task and speech recognition task provides multitude of facilities in comparison to isolated approach. The speaker identification task is achieved by using SVM where as speech recognition is based on HMM. We have used two different types of corpora for training the system. Gamma tone cepstral coefficients and mel frequency cepstral coefficients are extracted for speaker identification and speech recognition respectively. The accuracy of the system is measured from two perspective i.e. accuracy of speaker identity and accuracy of speech recognition task. The accuracy of the speaker identification is enhanced by adopting the speech recognition at the initial stage of speaker identification.
The Safe Haven Property of Gold in Turkish Financial Markets: An Investigation of the Global Financial Crisis

This paper investigates whether gold acts as a safe haven, a hedge or a diversifier for stocks and bonds in Turkey. We employ the dynamic conditional correlation (DCC-GARCH) model which is a class of multivariate generalized autoregressive conditional heteroskedastic (GARCH) models. DCC-GARCH has two steps; the first step models the volatility dynamics in a univariate context and the second step involves computing dynamic correlations. We use daily data from June 2006 to November 2013, a period witnessing the most recent global financial crisis and its aftermath. Our univariate GARCH model results reveal that current volatility is conditional on past shocks and volatilities for gold, stocks and bonds in Turkey. In this study, we hypothesize that gold is a hedge if the gold and the asset class are uncorrelated or negatively correlated on average, while it is a safe haven if the correlations are negative in times of market stress. The second step analyses show that gold acts as a hedge on average and a safe haven during equity market downturns for stocks. Across bonds, we show that gold acts as a hedge on the average, however it is not a safe haven during turmoil periods. Our results are of significance for portfolio managers, international investors and policy makers.
An open-source development environment for Self- driving vehicles

in English, 250 words or less): During this thesis, a development environment for self-driving vehicles has been developed, along with two Deep Learning models that make use of it, one for object detection and the other for steering angle regression. The development environment has been built in top of the famous game Grand Theft Auto V, while the Deep Learning models have been developed by using the popular Tensorflow library. The thesis has had worldwide success and several universities and research centers are using the development environment to conduct their own research. The project has more than 260 stars and 70 forks on GitHub.
Estimation of aerosol water and chemical composition from AERONET Sun-sky radiometer measurements at Cabauw, the Netherlands

Remote sensing of aerosols provides important information on atmospheric aerosol abundance. However, due to the hygroscopic nature of aerosol particles observed aerosol optical properties are influenced by atmospheric humidity, and the measurements do not unambiguously characterize the aerosol dry mass and composition, which complicates the comparison with aerosol models. In this study we derive aerosol water and chemical composition by a modeling approach that combines individual measurements of remotely sensed aerosol properties (e.g., optical thickness, single-scattering albedo, refractive index and size distribution) from an AERONET (Aerosol Robotic Network) Sun-sky radiometer with radiosonde measurements of relative humidity. The model simulates water uptake by aerosols based on the chemical composition (e.g., sulfates, ammonium, nitrate, organic matter and black carbon) and size distribution. A minimization method is used to calculate aerosol composition and concentration, which are then compared to in situ measurements from the Intensive Measurement Campaign At the Cabauw Tower (IMPACT, May 2008, the Netherlands). Computed concentrations show good agreement with campaign-average (i.e., 1-14 May) surface observations (mean bias is 3% for PM10 and 4-25% for the individual compounds). They follow the day-to-day (synoptic) variability in the observations and are in reasonable agreement for daily average concentrations (i.e., mean bias is 5% for PM10 and black carbon, 10% for the inorganic salts and 18% for organic matter; root-mean-squared deviations are 26% for PM10 and 35-45% for the individual compounds). The modeled water volume fraction is highly variable and strongly dependent on composition. During this campaign we find that it is >0.5 at approximately 80% relative humidity (RH) when the aerosol composition is dominated by hygroscopic inorganic salts, and <0.1 when RH is below 40%, especially when the composition is dominated by less hygroscopic compounds such as organic matter. The scattering enhancement factor (f(RH), the ratio of the scattering coefficient at 85% RH and its dry value at 676 nm) during 1-14 May is 2.6 ± 0.5. The uncertainty in AERONET (real) refractive index (0.025-0.05) is the largest source of uncertainty in the modeled aerosol composition and leads to an uncertainty of 0.1-0.25 (50-100%) in aerosol water volume fraction. Our methodology performs relatively well at Cabauw, but a better performance may be expected for regions with higher aerosol loading where the uncertainties in the AERONET inversions are smaller. © Author(s) 2014.
Generalist social bees maximize diversity intake in plant species-rich and resource-abundant environments

Numerous studies revealed a positive relationship between biodiversity and ecosystem functioning, suggesting that biodiverse environments may not only enhance ecosystem processes, but also benefit individual ecosystem members by, for example, providing a higher diversity of resources. Whether and how the number of available resources affects resource collection and subsequently consumers (e.g., through impacting functions associated with resources) have, however, been little investigated, although a better understanding of this relationship may help explain why the abundance and richness of many animal species typically decline with decreasing plant (resource) diversity. Using a social bee species as model (Tetragonula carbonaria), we investigated how plant species richness—recorded for study sites located in different habitats—and associated resource abundance affected the diversity and functionality (here defined as nutritional content and antimicrobial activity) of resources (i.e., pollen, nectar, and resin) collected by a generalist herbivorous consumer. The diversity of both pollen and resin collected strongly increased with increasing plant/tree species richness, while resource abundance was only positively correlated with resin diversity. These findings suggest that bees maximize resource diversity intake in (resource) diverse habitats. Collecting more diverse resources did, however, not increase their functionality, which appeared to be primarily driven by the surrounding (plant) source community in our study. In generalist herbivores, maximizing resource diversity intake may therefore primarily secure collection of sufficient amounts of resources across the entire foraging season, but it also ensures that the allocated resources meet all functional needs. Decreasing available resource diversity may thus impact consumers primarily by reduced resource abundance, but also by reduced resource functionality, particularly when resources of high functionality (e.g., from specific plant species) become scarce.