Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of biomass burning on upper tropospheric carbon monoxide: a study using MOCAGE global model and IAGOS airborne data

Abstract. In this paper, the fate of biomass burning emissions of carbon monoxide is studied with the global chemistry–transport model MOCAGE (MOdélisation de Chimie Atmosphérique à Grande Échelle) and IAGOS (In-Service Aircraft for a Global Observing System) airborne measurements for the year 2013. The objectives are firstly to improve their representation within the model and secondly to analyse their contribution to carbon monoxide concentrations in the upper troposphere. At first, a new implementation of biomass burning injection is developed for MOCAGE, using the latest products available in Global Fire Assimilation System (GFAS) biomass burning inventory on plume altitude and injection height. This method is validated against IAGOS observations of CO made in fire plumes, identified thanks to the SOFT-IO source attribution data. The use of these GFAS products leads to improved MOCAGE skill to simulate fire plumes originating from boreal forest wildfires. It is also shown that this new biomass burning injection method modifies the distribution of carbon monoxide in the free and upper troposphere, mostly at northern boreal latitudes. Then, MOCAGE performance is evaluated in general in the upper troposphere and lower stratosphere in comparison to the IAGOS observations and is shown to be very good, with very low bias and good correlations between the model and the observations. Finally, we analyse the contribution of biomass burning to upper tropospheric carbon monoxide concentrations. This is done by comparing simulations where biomass are toggled on and off in different source regions of the world to assess their individual influence. The two regions contributing the most to upper tropospheric CO are found to be the boreal forests and equatorial Africa, in accordance with the quantities of CO they emit each year and the fact that they undergo fast vertical transport: deep convection in the tropics and pyroconvection at high latitudes. It is also found that biomass burning contributes more than 11 % on average to the CO concentrations in the upper troposphere and up to 50 % at high latitudes during the wildfire season.
Development of Seismic Vulnerability and Exposure Models—A Case Study of Croatia

Assessing earthquake risk and building vulnerability requires an exposure model. These exposure models quantify the building stock in terms of structural characteristics, spatial location, and occupancy. The most significant exposure parameters are the structural characteristics of buildings, which must be uniformly covered by structural typologies. Structural typologies that take into account the regional specificities of design and construction provide more accurate and reliable exposure models. Despite the long history of earthquake engineering in the Republic of Croatia, the assessment of exposure and vulnerability of buildings is a rather new concept, hindered by the fact that no city in the Republic of Croatia has a database on the number, types, and characteristics of existing buildings. The article presents the creation of a building exposure model for the city of Osijek, points out the problems and concerns that the realization process brings, and details the practical solutions and strategies that have been used to achieve the set goals.
Comparison of Diabetic Macular Edema Treatment Patterns and Outcomes by European and US Retina-treating Ophthalmologists

© TOUCH MEDICAL MEDIA 2014 63 The global medical, financial, and personal toll of type 1 and 2 diabetes is well documented. In the US, the total cost of diabetes to the US healthcare system was estimated at US$174 billion (€126 billion) in 2007. The International Diabetes Federation estimates that diabetes health costs were US$105.5 billion (€82.2 billion) in the European region in 2010. As the prevalence of diabetes is expected to rise more than 50 % globally between 2000 and 2030, these costs are expected to continue to grow. While robust data regarding the impact of type 1 and 2 diabetes are readily available, information on at least one condition secondary to diabetes, specifically diabetic macular edema (DME), is lacking in publically available literature. A particular gap exists regarding the relationship between the scope of the disease and the corresponding effectiveness of long-term treatment.
Nonparametric Quantile Regression Estimation With Mixed Discrete and Continuous Data

Abstract In this article, we investigate the problem of nonparametrically estimating a conditional quantile function with mixed discrete and continuous covariates. A local linear smoothing technique combining both continuous and discrete kernel functions is introduced to estimate the conditional quantile function. We propose using a fully data-driven cross-validation approach to choose the bandwidths, and further derive the asymptotic optimality theory. In addition, we also establish the asymptotic distribution and uniform consistency (with convergence rates) for the local linear conditional quantile estimators with the data-dependent optimal bandwidths. Simulations show that the proposed approach compares well with some existing methods. Finally, an empirical application with the data taken from the IMDb website is presented to analyze the relationship between box office revenues and online rating scores. Supplementary materials for this article are available online.
Assessing Knowledge, Attitudes, and Practices towards Causal Directed Acyclic Graphs: a qualitative research project

Causal graphs provide a key tool for optimizing the validity of causal effect estimates. Although a large literature exists on the mathematical theory underlying the use of causal graphs, less literature exists to aid applied researchers in understanding how best to develop and use causal graphs in their research projects.We sought to understand why researchers do or do not regularly use DAGs by surveying practicing epidemiologists and medical researchers on their knowledge, level of interest, attitudes, and practices towards the use of causal graphs in applied epidemiology and health research. We used Twitter and the Society for Epidemiologic Research to disseminate the survey.Overall, a majority of participants reported being comfortable with using causal graphs and reported using them ‘sometimes’, ‘often’, or ‘always’ in their research. Having received training appeared to improve comprehension of the assumptions displayed in causal graphs. Many of the respondents who did not use causal graphs reported lack of knowledge as a barrier to using DAGs in their research.Causal graphs are of interest to epidemiologists and medical researchers, but there are several barriers to their uptake. Additional training and clearer guidance are needed. In addition, methodological developments regarding visualization of effect measure modification and interaction on causal graphs is needed.
Research Into Woodland Owners’ Use of Sustainable Forest Management to Inform Campaign Marketing Mix

Thirty-five percent of forestland in the United States is owned by individuals. The purpose of this research was to identify woodland owners’ barriers to harvesting trees using the advice of a forester. Harvesting trees with the advice of a forester ensures a sustainable harvest that meets the needs of the woodland owner as the forester makes recommendations depending on what the woodland owner wants to gain from their land. The research further informed the marketing mix by identifying woodland owners’ perceptions about trusted communication channels, providing a framework for segmenting the audience, and pointing to viable outreach strategies for rural interventions. Results of mail (New England) and telephone (Mississippi) surveys indicated that selling trees for income was the lowest rated land use activity reported by woodland owners. Additionally, across both regions, the surveys indicated that the primary barrier to using a forester involved some form of distrust. When comparing trusted sources of information across the two regions, forestry experts were rated similarly, but family and other woodland owners were perceived as more trustworthy in New England compared to Mississippi. Both groups preferred to receive information in written form, a preference that was almost twice as high as receiving an e-mail. This research provides the foundation for a marketing mix, improves the conservation community’s body of knowledge regarding woodland owner’s barriers to sustainable forest management actions, and provides broad recommendations for practitioners to use going forward.
Connecting actin polymer dynamics across multiple scales

Actin is an intracellular protein that constitutes a primary component of the cellular cytoskeleton and is accordingly crucial for various cell functions. Actin assembles into semi-flexible filaments that cross-link to form higher order structures within the cytoskeleton. In turn, the actin cytoskeketon regulates cell shape, and participates in cell migration and division. A variety of theoretical models have been proposed to investigate actin dynamics across distinct scales, from the stochastic nature of protein and molecular motor dynamics to the deterministic macroscopic behavior of the cytoskeleton. Yet, the relationship between molecular-level actin processes and cellular-level actin network behavior remains understudied, where prior models do not holistically bridge the two scales together. In this work, we focus on the dynamics of the formation of a branched actin structure as observed at the leading edge of motile eukaryotic cells. We construct a minimal agent-based model for the microscale branching actin dynamics, and a deterministic partial differential equation model for the macroscopic network growth and bulk diffusion. The microscale model is stochastic, as its dynamics are based on molecular level effects. The effective diffusion constant and reaction rates of the deterministic model are calculated from averaged simulations of the microscale model, using the mean displacement of the network front and characteristics of the actin network density. With this method, we design concrete metrics that connect phenomenological parameters in the reaction-diffusion system to the biochemical molecular rates typically measured experimentally. A parameter sensitivity analysis in the stochastic agent-based model shows that the effective diffusion and growth constants vary with branching parameters in a complementary way to ensure that the outward speed of the network remains fixed. These results suggest that perturbations to microscale rates can have significant consequences at the macroscopic level, and these should be taken into account when proposing continuum models of actin network dynamics.
An Integrated Histogram-Based Vision and Machine-Learning Classification Model for Industrial Emulsion Processing

Existing techniques in emulsion quality evaluation are found to be highly subjective, time-consuming, and prone to overprocessing. Other conventional droplet analysis techniques such as laser diffraction, which require dilution of samples, introduce an additional complexity to industrial processes. The possibility of developing a fully automated technique for droplet characterization during emulsification holds remarkable potential for overcoming the existing challenges. In this article, a histogram-based image segmentation technique detects droplets from emulsion micrographs. The evolution of droplet characteristics and their significance are studied by performing statistical analysis, and the significant characteristics are selected. The principal component analysis is applied to obtain a reduced set of uncorrelated components from the selected characteristics. The linear discriminant analysis classifies the micrographs into a set of quality categories called target, acceptable, marginal, and unacceptable. The model accuracy is validated using stratified five-fold cross-validation and is successful in classifying the micrographs obtained from two different manufacturing facilities with high accuracy up to 100%. The histogram-based technique is successful in detecting smaller droplets than previously reflected in the literature. The current approach is fully automated and is implemented as a soft-sensor, which supports its real-time deployment into an industrial environment. The entire approach has promising potential in the in-line prediction of emulsion quality leading to more efficient and sustainable manufacturing.
17 Respiratory and cardiovascular support

Our survival depends on the production of energy in the form of adenosine triphosphate by the process of oxidative metabolism. This in turn depends on a continual supply of substrates, particularly oxygen and glucose, to vital tissue beds such as the brain and myocardium. In a critically ill patient, the supply of oxygen may be compromised while at the same time metabolic demand is increased. Inadequate oxygen delivery may become the factor mitigating against recovery or even survival of the patient (Schumacker and Cain, 1987). In a patient with brain injury, cerebral metabolic reserve is already reduced by the primary insult and subsequent oxygen lack is a potent cause of avoidable secondary brain injury (Chesnut et al., 1993). This chapter will address fundamental physiological principles of oxygen delivery from the atmosphere to the cells, the pathophysiological effects of head injury on oxygen delivery and principles of resuscitation and the maintenance of cardiopulmonary homeostasis.
Frequency-Domain Information for Active Portfolio Management

We assess the benefits of using frequency-domain information for active portfolio management. To do so, we forecast the bond risk premium and equity risk premium using a methodology that isolates frequencies (of the predictors) with the highest predictive power. The resulting forecasts are more accurate than those of traditional forecasting methods for both asset classes. When used in the context of active portfolio management, the forecasts based on frequency-domain information lead to better portfolio performances than when using the original time series of the predictors. It produces higher information ratio (0.57 vs 0.45), higher CER gains (1.12% vs 0.81%), and lower maximum drawdown (19.1% vs 19.6%).
Does ‘heparin-induced thrombocytopenia’ hit our minds?

Abstract Unfractionated heparin is a widely used drug to prevent deep vein thrombosis and pulmonary emboli in patients at risk. With the advent of newer anticoagulants having lesser side effects, its use has diminished but not out of service. Here, we report a case of deep venous thrombosis, in a patient on prophylactic dose of heparin, which was later found to be a manifestation of heparin-induced thrombocytopenia (HIT). Thrombosis in the presence of heparin prophylaxis should be considered as HIT rather than a failure of anticoagulation.
Integrative and instrumental but low investment: The English learning motivation of Indonesian senior high school students

Considered important for global competitiveness like ASEAN Economic Society, the English proficiency of Indonesian students is unfortunately not satisfactory yet. This condition is, one of which, due to low teachers’ professionalism and students’ motivation for English learning. The motivation of students may become weak because they have not found ways to identify, drive and sustain it. Of the various studies on motivation and challenges in EFL practice in the Indonesian context, research specifically addressing how learners find motivation triggers synergized into project-based learning for sustainable and continuous English learning is still limited. This survey and interview study investigates the motivation of Senior High School (SHS) students in West Java province of Indonesia on English learning and how to drive their motivation through a collaborative project as mandated by the 2013 National Curriculum. Results of questionnaires, interviews and document analysis show that despite having integrative and instrumental motivation to learn English, the participating SHS students show low investment as indicated by low learning enthusiasm in the classroom and poor English performance. This low motivation is also related to some socioeconomic status such as school geographical location, classroom learning situation, and parental supports. The study recommends students’ involvement in a cooperative learning project which can direct and energize their English learning motivation so that they can have increased motivation, good English proficiency and become global citizens with high competitiveness.
Role of CT-Scan versus Chest X-RAY in the Diagnosis of Community-Acquired Pneumonia

"Dr. William Osler, the founder of modern me dicine, who has studied pneumonia throughout his career, called pneumonia, the captain of the men of death", due to its immeasurable havoc and burdens on humanity (Mizgerd, 2008). In 1930, before the revolution of antibiotics, pneumonia was the third cause of mortality in the US (Country Analysis Report, 2017). In 2015, 922000 children under age of five died from complicated pneumonia which constitutes 15 percent of deaths recorded among this category worldwide (Country Analysis Report, 2017). This comparison clearly shows the persistence of pneumonia as one of the major causes of International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 1 (2017) pp. 755-760 Journal homepage: http://www.ijcmas. com
Prototypes of Panaxadiol and Panaxatriol Saponins Suppress LPS-mediated iNOS/NO Production in RAW264.7 Murine Macrophage Cells

This study was performed to investigate the modulatory effects of two prototypes of Panax ginseng saponin fractions, 20(S)-protopanaxadiol saponins (PDS) and 20(S)-protopanaxatriol saponins (PTS), on the induction of inflammatory mediators in lipopolysaccharide (LPS)-treated RAW264.7 murine macrophage cells. For this purpose, RAW264.7 cells were treated with LPS (10 μg/ml) before, after, or simultaneously with PDS or PTS (150 μg/ml), and the released level of nitric oxide (NO) and expression levels of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) were evaluated. When RAW264.7 cells were treated with LPS and ginseng saponin fractions simultaneously for 24 hr, PTS, compared to PDS, more strongly attenuated the NO production induced by LPS treatment. When the cells were pretreated with LPS for 2 hr followed by PDS or PTS treatment for 24 hr, both ginseng saponins strongly reduced NO release. The pretreatment of RAW264.7 cells with PDS or PTS for 2 hr followed by LPS treatment for 24 hr significantly attenuated the LPS-induced production of NO. PTS showed stronger inhibitory potency to NO generation than PDS. Our western blot experiment showed that both PDS and PTS (150 μg/ml) also significantly down-regulated the expressions of iNOS and COX-2 induced by LPS treatment. Our results suggest that both PDS and PTS possess strong protective effects against LPS-stimulated inflammation and that their protective effects are mediated by the suppression of NO synthesis via down-regulation of pro-inflammatory enzymes, iNOS, and COX-2 in the RAW264.7 cells.
A topic‐based term frequency normalization framework to enhance probabilistic information retrieval

Many well‐known probabilistic information retrieval models have shown promise for use in document ranking, especially BM25. Nevertheless, it is observed that the control parameters in BM25 usually need to be adjusted to achieve improved performance on different data sets; additionally, the assumption in BM25 on the bag‐of‐words model prevents its direct utilization of rich information that lies at the sentence or document level. Inspired by the above challenges with respect to BM25, we first propose a new normalization method on the term frequency in BM25 (called BM25QL in this paper); in addition, the method is incorporated into CRTER2, a recent BM25‐based model, to construct CRTER2QL. Then, we incorporate topic modeling and word embedding into BM25 to relax the assumption of the bag‐of‐words model. In this direction, we propose a topic‐based retrieval model, TopTF, for BM25, which is then further incorporated into the language model (LM) and the multiple aspect term frequency (MATF) model. Furthermore, an enhanced topic‐based term frequency normalization framework, ETopTF, based on embedding is presented. Experimental studies demonstrate the great effectiveness and performance of these methods. Specifically, on all tested data sets and in terms of the mean average precision (MAP), our proposed models, BM25QL and CRTER2QL, are comparable to BM25 and CRTER2 with the best b parameter value; the TopTF models significantly outperform the baselines, and the ETopTF models could further improve the TopTF in terms of the MAP.
Market potential for Gulf of Mexico farm-raised finfish

Abstract Concerns that additional supplies of U.S. farm-raised fish may compete with domestic wild fish has contributed to resistance and litigation that has slowed aquaculture development in the U.S. We employ a contingent choice experiment to large seafood wholesalers and suppliers in the U.S. to investigate market potential of new farmed finfish species from the Gulf of Mexico. We estimate probabilities that wholesale buyers prefer a new farmed product over existing market products using a conditional logit model. The results indicate it is more probable that Gulf farmed fish will substitute for imports than for domestic wild-caught fish given U.S. wholesale buyers have a preference for domestic fish to imported fish, but no significant preference for wild-caught fish to farmed fish.
EVALUATION OF ANTICANDIDAL EFFECTS OF ESSENTIAL OILS OF COMMERCIAL LAVENDER (Lavandula angustifolia Miller) IN COMBINATION WITH KETOCONAZOLE AGAINTS SOME Candida Berkhout STRAINS

Application of combination studies with essential oils and standard antifungal drugs may reduce adverse effects of synthetic drugs and serve as alternative approach against various pathologies including candidiasis. The aim of the present study was to determine the interaction of two commercial lavender ( Lavandula angustifolia Miller) essential oils in combination with ketoconazole against clinical and standard strains of the human pathogens Candida albicans ATCC 10231, C. krusei NRRL Y-7179 and C. glabrata ATCC 66032. The chemical compositions of the investigated essential oils were confirmed both by gas chromatography/flame ionization detector (GC/FID) and gas chromatography/mass spectrometry (GC/MS) methods. Anticandidal activities of the essential oils were screened in vitro by the microdilution method. The resulting interaction of combining lavender essential oils and ketoconazole was tested using the checkerboard method. The results showed that the interaction between essential oils and ketoconazole revealed additive and indifferent effects against the tested strains. In conclusion, the effects observed by the combination of lavender essential oils and ketoconazole may be encouraging to be used against pathogenic Candida strains.