Miracle-dz/UniFAR-FTUs huggingface dataset:
CO 2-level Dependent Effects of Ocean Acidification on Squid , Doryteuthis pealeii , Early Life History Thesis by

Ocean acidification is predicted to lead to global oceanic decreases in pH of up to 0.3 units within the next 100 years. However, those levels are already being reached currently in coastal regions due to natural CO2 variability. Squid are a vital component of the pelagic ecosystem, holding a unique niche as a highly active predatory invertebrate and major prey stock for upper trophic levels. This study examined the effects of a range of ocean acidification regimes on the early life history of a coastal squid species, the Atlantic longfin squid, Doryteuthis pealeii. Eggs were raised in a flow-through ocean acidification system at CO2 levels ranging from ambient (400ppm) to 2200ppm. Time to hatching, hatching efficiency, and hatchling mantle lengths, yolk sac sizes, and statoliths were all examined to elucidate stress effects. Delays in hatching time of at least a day were seen at exposures above 1300ppm in all trials under controlled conditions. Mantle lengths were significantly reduced at exposures above 1300 ppm. Yolk sac sizes varied between CO2 treatments, but no distinct pattern emerged. Statoliths were increasingly porous and malformed as CO2 exposures increased, and were significantly reduced in surface area at exposures above 1300ppm. Doryteuthis pealeii appears to be able to withstand acidosis stress without major effects up to 1300ppm, but is strongly impacted past that threshold. Since yolk consumption did not vary among treatments, it appears that during its early life stages, D. pealeii reallocates its available energy budget away from somatic growth and system development in order to mitigate the stress of acidosis.
A 10.3 kbp segment from nprB to argJ at the 102° region of the Bacillus subtilis chromosome

The approximately 10 kbp region encompassing nprB and argJ at 102° on the Bacillus subtilis chromosome was sequenced, revealing 12 ORFs, four known genes (argJ, argC, ipi and nprB) and two genes, yitY and yitS, whose products respectively display significant homology with L-gulono-γ-lactone oxidase of rat and dihydrofolate reductase of Staphylococcus aureus. The data also indicated that nprB mapped to a different position than previously published.
A systematic review: Application of in silico models for antimalarial drug discovery

Malaria remains the global public health problem due to the reemergence of drug resistance. There is an urgent need for development of new antimalarial candidates which are effective against resistant malaria parasite. This systematic review evaluates the published research studies that applied in silico modeling during the discovery process of antimalarial drugs. Literature searches were conducted using PubMed, EBSCO, EMBASE, and Web of Science to identify the relevant articles using the search terms “Malaria” “In silico model”, “Computer-based drug design”, “Antimalarial drug”, and “Drug discovery”. Only the articles published in English between 2008 and May 2015 were included in the analysis. A total of 17 relevant articles met the search criteria. Most articles are studies specific to Plasmodium falciparum targets; 3 and 1 articles, respectively involve target for P. vivax and liver stage of Plasmodium. Both structure-based and ligand-based approaches were applied to obtain lead antimalarial candidates. Two articles also assessed absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. Confirmation of activity of the candidate leads by in vitro and/or in vivo assays were reported in some studies. Homology modelling, molecular docking, 2D- or 3D-QSAR and pharmacophore modeling are commonly applied methods. One study used de novo synthesis for lead identification and one study applied phylogenetic analysis for target identification/validation. Key words: Plasmodium, malaria, antimalarial drug, drug discovery, in silico modeling, computer-based drug design, systematic review.
Stress analysis of polycrystalline thin films and surface regions by X-ray diffraction

The components of the macroscopic mechanical stress tensor of a stressed thin film, coating, multilayer or the region near the surface of a bulk material can in principle be determined by X-ray diffraction. The various analysis methods and measurement strategies, in dependence on specimen and measurement conditions, are summarized and evaluated in this paper. First, different X-ray diffraction geometries (conventional or grazing incidence) are described. Then, the case of macroscopically elastically isotropic, untextured specimens is considered: from the simplest case of a uniaxial state of stress to the most complicated case of a triaxial state of stress. The treatment is organized according to the number of unknowns to be determined (i.e. the state of stress, principal axes known or unknown), the use of one or several values of the rotation angle φ and the tilt angle ψ of the sample, and one or multiple hkl reflections. Next, the focus is on macroscopically elastically anisotropic (e.g. textured) specimens. In this case, the use of diffraction (X-ray) elastic constants is not possible. Instead, diffraction (X-ray) stress factors have to be used. On the basis of examples, it is demonstrated that successful diffraction stress analysis is only possible if an appropriate grain-interaction model is applied.
Angular Distribution of Electrons in Photoionization of Atoms Adsorbed on a Graphene Sheet

Within the framework of a model representing the potential of a graphene sheet U(z) as an electro-neutral layer formed by smeared carbon atoms, the effect of this potential on spectral characteristics of atoms adsorbed on a graphene sheet has been studied. Since the distance between the adsorbed atom nucleus and sheet surface significantly exceeds the radii of inner atomic shells the potential U(z) makes influence on the continuum wave functions only. Their behavior in the upper semi-space (z>0) and in the lower one (z<0) where the adsorbed atom is located is defined by a jump of the logarithmic derivative of the wave function for z=0. The photoelectron angular distributions have been calculated for different mutual positions of the polarization vector e and the axis Z normal to the sheet surface. It has been shown that the existence of the electron waves reflected from the potential U(z) leads to evident asymmetry of the angular distribution relative to the plane z=0. The experimental observation of this effect is of great interest for photoelectron spectroscopy of atoms localized on graphene structures.
The ACOS CO 2 retrieval algorithm – Part 1: Description and validation against synthetic observations

Abstract. This work describes the NASA Atmospheric CO2 Observations from Space (ACOS) XCO2 retrieval algorithm, and its performance on highly realistic, simulated observations. These tests, restricted to observations over land, are used to evaluate retrieval errors in the face of realistic clouds and aerosols, polarized non-Lambertian surfaces, imperfect meteorology, and uncorrelated instrument noise. We find that post-retrieval filters are essential to eliminate the poorest retrievals, which arise primarily due to imperfect cloud screening. The remaining retrievals have RMS errors of approximately 1 ppm. Modeled instrument noise, based on the Greenhouse Gases Observing SATellite (GOSAT) in-flight performance, accounts for less than half the total error in these retrievals. A small fraction of unfiltered clouds, particularly thin cirrus, lead to a small positive bias of ~0.3 ppm. Overall, systematic errors due to imperfect characterization of clouds and aerosols dominate the error budget, while errors due to other simplifying assumptions, in particular those related to the prior meteorological fields, appear small.
Random Walk and Multiple Structural Breaks In Thai Stock Market

The Zivot and Andrews (1992) one-break and Lumsdaine and Papell (1997) two-break unit root tests are used to investigate the random walk hypothesis in Thai stock prices for the period December 1987 to December 2005. The results provide strong evidence that the Thai stock prices are characterized by a random walk, supporting this view that it is highly unlikely to make windfall profits in the Thai stock market using past price movements. Moreover, the dates of the endogenously determined structural break interestingly coincided with the Asian crisis and world recessions.
Understanding Attitudes towards Gasoline Import Demand in Viet Nam

Even with its vast reserves of oil and gas potential, the government has put this fuel resource the top of priority sectors for development, as it views as central to national economic growth as well as energy security, Viet Nam has remained a net importer of petroleum products over the past eight years. On another word, Gasoline importation has been a superior absorbability on the economy of Viet Nam, the determinants of the refined oil products imported activities analysis have been found no study yet. This paper aims to suggest the leading factors affecting import demand performances for petroleum products. The autoregressive distributed lag modelling framework (ARDL) have applied to this research; we estimated various short-run and long-run import demand models for Gasoline using time series study over the period 1995-2015. The results showed that the application of gas is stable prices in both the long and short term. Other principal operators of gas import probably are the real effective exchange rate, domestic petroleum production, and population growth. Moreover, a real economic activity found the most active and influential driver of gasoline demand accordance with the inelastic and elastic coefficients estimated in the short-run and long-run, respectively.
Young workers' overeducation and cohort effects in "P.I.G.S." countries versus the Netherlands: a pseudo-panel analysis

According to theoretical and empirical evidence young workers are more likely to be overeducated than adult ones, especially in countries where the educational attainments of young people grow quickly and the school-to-work transition is difficult and/or lengthy. Nonetheless, if overeducation were expected to disappear during working life, it would not be a crucial problem. To test the transitory nature/persistence of this phenomenon, firstly, I estimated overeducation using the competences frontiermethod and, later, I studied the “destination” of different cohorts of workers by applying a pseudo-panel technique to Eurostat data referring to European Mediterranean countries and the Netherlands.
The species–energy theory: a role for energy variability

Species-energy theory posits that energy availability regulates population sizes, extinction rates and ultimately species richness. This theory has focused mostly on total energy as a measure of energy availability. However, because energy variation can also influence population sizes and extinction rates, species-energy theory should arguably consider simultaneously both total energy and its variation. Using data on species richness of land birds and mammals, we compared the fit of three species-energy models including total energy, energy variation or both combined. We show that the combination of total energy and energy variation has greater predictive power than any of them considered separately. We also evaluate three crucial assumptions of this modified species-energy theory and show that they are supported by available data. These results illuminate the current debate on climate change, given that both average conditions and variability of climatic conditions are likely to change in the future.
Approximate Bayesian inference in semiparametric copula models

We describe a simple method for making inference on a functional of a multivariate distribution. The method is based on a copula representation of the multivariate distribution and it is based on the properties of an Approximate Bayesian Monte Carlo algorithm, where the proposed values of the functional of interest are weighed in terms of their empirical likelihood. This method is particularly useful when the "true" likelihood function associated with the working model is too costly to evaluate or when the working model is only partially specified.
NUTRITIONAL CHARACTERIZATION, BIOACTIVE COMPOUNDS AND ANTIOXIDANT ACTIVITY OF BRAZILIAN ROSES (ROSA SPP)

The aim of this study was to evaluate thirteen cultivars of roses for nutritional composition, bioactive compounds and total antioxidant activity. Attaché cultivar had the highest amounts of proteins and total fiber. Regarding color, Avalanche presented values for internal cromacity around 7 fold higher than Attaché cultivar. The results showed that the evaluated roses presented means of bioactive compounds as ascorbic acid (70.47 mg 100 g), yellow flavonoids (35.25 mg 100 g) and total anthocyanins (150.40 mg 100 g ). The evaluated roses presented relatively low content of total carotenoids (1.25 mg 100 g), and high content of total polyphenols (1565 mg 100 g) and antioxidant capacity (260 μM trolox g). Avalanche, Prima Donna, Dolce Vita, Salmone, and Elisa cultivar presented the minor Euclidean distance. The petals of the evaluated roses are excellent sources of nutritional compounds and antioxidants.
Determination of the signature of a dynamite source using source scaling; Part I, Theory

It is normally impossible to measure the source signature in land seismic data acquisition with a dynamite source, because it is normally impossible to separate the incident field from the scattered field. Nevertheless, in any serious attempt to invert the seismic data, it is essential to know the source signature; for the dynamite source this is the volume injection function. The problem can be solved by using two different shots at each shot point and relating the source signatures by the source scaling law, which follows from the invariance of the medium parameters with the size of the charge. The volume injection function of the larger shot is an amplified and stretched version of that of the smaller shot, the amplification factor being equal to the ratio of the charge masses and the time stretch factor being equal to the cube‐root of this ratio. At a given receiver, the response to one shot is a convolution of the source signature with the impulse response of the earth, plus noise. The two shots and .
WAVE IMPACTS EXCITATION ON SHIP-TYPE OFFSHORE STRUCTURES IN STEEP FRONTED WAVES

Wave impacts in steep fronted waves can induce extremely large impact pressures on the hull of moored ship-type offshore structures. As part of the SAFE-FLOW Joint Industry Project these loads were investigated with a dedicated series of model tests. Based on the results a prediction method is developed, which can be applied in the early design of the bow structure. The paper first summarizes the test philosophy and the developed prediction method. Then the practical design considerations related to bow slamming are discussed in a study focusing on the new DP-FPSO concept for a single environment.
Adjusting Complex Heterogeneity in Treatment Assignment in Observational Studies

Treatment assignment in observational studies is complex and can be inﬂuenced by many factors that include patient characteristics, physician practices, and health care systems. These inﬂuences can present heterogeneity or clustering effects in the treatment assignment. If those heterogeneity or clustering effects are not appropriately adjusted, the estimated treatment effect may be severely biased. Through a series of models that mimic various level of heterogeneity in treatment assignment in observational studies, we evaluate, through simulation study, the performance of several estimators under the impact of different types of heterogeneity. These estimators include propensity score stratiﬁcation, propensity score inverse probability weighting, propensity score regression and the partial least squares method. Our results suggest that the partial least squares method is most robust while the dummy variable adjustment method in propensity regression also performs fairly consistently. We use the proposed method to analyze a data set from the German Breast Cancer Study Group study.
Modeling inflation in Kenya: Comparison of SARIMA and Generalized Least Squares models

One desire by the policy makers in a country is to have access to reliable forecast of inflation rate. This is only achievable if the right model with high predictive accuracy is used. In this paper, seasonal auto regressive integrated moving average (SARIMA) and Generalized Least Squares regression models are developed to predict Kenya's inflation using quarterly data for the period 1981 to 2013. SARIMA (0,1,0)(0,0,1) 4 was chosen as the model with the least Akaike Information Criterion and Bayesian Information Criterion. The parameters were then estimated. The residuals were checked to find out if they follow a white noise process by using residual Q-Q and normality test plots. The Test for normality of residual was also done. Given the high p-values (0.0639237) associated with the statistics as compared to 0.05, we fail to reject the null hypothesis that an error is normally distributed in this residual series. Thus, we conclude that the model provides an adequate fit for the data. In an effort to improve this, inflation was also modeled using Generalized Least Squares regression model. The data was first checked for heteroscedasticity using the Breusch-Pagan test. Based on the p-value=0.000, which is less than alpha (of 5%), we conclude that there is substantial amount heteroscedasticity in the data. A regression model that forecasts inflation using its lags was constructed. The residuals were checked for normality using q-q plot. Additionally, the Shapiro-Wilk normality test was carried out. Its p-value was 0.08178 and since its greater than 0.05, its concluded that the residuals does not deviate from normality A comparison was made on the predictive ability of both models. SARIMA (0,1,0)(0,0,1) 4 model had the least values of MAPE, MAE and RMSE with the corresponding values given by MAPE=14.155, RMSE=0.2871and MAE=0.23692 Keywords: SARIMA, Generalized Least Squares, Akaike Information Criterion ,Bayesian Information Criterion, Shapiro-Wilk normality test and Breusch-Pagan test
Frequent aberrant DNA methylation of CDKN2A locus in capillary hemangioblastomas, pheochromocytomas and gliomas

Background. Both capillary hemangioblastoma (CHB) and pheochromocytoma (PCC) are rare, usually benign tumours occurring sporadically or as part of familial cancer syndromes. The genetic background of most of the inherited cases is well established, but the molecular causes of sporadic cases remains poorly characterized. To better understand the molecular mechanisms of CHB and PCC pathogenesis, we analysed the genetic and epigenetic alterations of the p16 and p14 genes at the CDKN2A locus. Materials and methods. Aberrant methylation of the p16 and p14 genes was analysed in 16 cases with CHB or PCC by means of methylation-specific PCR. The differential polymerase chain reaction was used to prove the occurrence of the genetic deletion of p16. For comparison, 28 cases of glioma – a highly malignant tumour of the brain – was included into the study. Results. Data of our study show that gene p16 is hypermethylated in 25% of CHBs and in 25% of PCCs, while in gliomas this alteration is more frequent (35%) and predominantly occurs in low-grade tumours (67%). Frequent hypermethylation of the p14 gene was observed in PCCs (50%) and CHBs (37.5%), but was less prevalent in gliomas (26%). When all alterations in the CDKN2A locus were considered, including hypermethylation of p16 and p14, and genetic deletion of p16, 75% of PCC, 62.5% of CHB, and 64% of gliomas had at least one alteration of this locus. Conclusions. Our study adds new data to understanding the involvement of the CDKN2A locus in the pathogenesis of CHB and PCC – two of the most common VHLrelated tumours. Furthermore, aberrant methylation in the CDKN2A locus is also frequent in gliomas.
Towards reconciling two asymptotic frameworks in spatial statistics

Two asymptotic frameworks, increasing domain asymptotics and infill asymptotics, have been advanced for obtaining limiting distributions of maximum likelihood estimators of covariance parameters in Gaussian spatial models with or without a nugget effect. These limiting distributions are known to be different in some cases. It is therefore of interest to know, for a given finite sample, which framework is more appropriate. We consider the possibility of making this choice on the basis of how well the limiting distributions obtained under each framework approximate their finite-sample counterparts. We investigate the quality of these approximations both theoretically and empirically, showing that, for certain consistently estimable parameters of exponential covariograms, approximations corresponding to the two frameworks perform about equally well. For those parameters that cannot be estimated consistently, however, the infill asymptotic approximation is preferable. Copyright 2005, Oxford University Press.
A Decoupled Feedback Structure for Covertly Appropriating Networked Control Systems

Abstract The use of communication networks for the transmission of control system signals (measurements and actuation) is becoming more widespread. If the communication (or the sensors and actuators themselves) can be modified by a malicious agent then the control of the physical plant can be covertly appropriated. A parameterised decoupling structure is introduced which allows the covert agent a wide range of control actions on the physical plant while remaining undetectable from the point of view of the original networked controller. The designer of the covert agent need only have a model of the physical plant; knowledge of the networked controller is not required. A MIMO process control example (based on the control of irrigation canals) is used to illustrate the concepts.
A Pairwise Likelihood Augmented Estimator for the Cox Model Under Left-Truncation

Survival data collected from prevalent cohorts are subject to left-truncation and the analysis is challenging. Conditional approaches for left-truncated data under the Cox model are inefficient as they typically ignore the information in the marginal likelihood of the truncation times. Length-biased sampling methods can improve the estimation efficiency but only when the stationarity assumption of the disease incidence holds, i.e., the truncation distribution is uniform; otherwise they may generate biased estimates. In this paper, we propose a semi-parametric method for the Cox model under general left-truncation, where the truncation distribution is unspecified. Our approach is to make inference based on the conditional likelihood augmented with a pairwise likelihood which eliminates the unspecified truncation distribution, yet retains the information about the regression coefficients and the baseline hazard function in the marginal likelihood. An iterative algorithm is provided to solve for the regression coefficients and the baseline hazard simultaneously. The proposed estimator is consistent and asymptotically normal with a closed-form consistent variance estimator. Simulations show a substantial efficiency gain in both the regression coefficients and the cumulative baseline hazard over the conditional approach estimator. Even when the stationarity assumption holds, our estimator results in better efficiency than some length-biased sampling estimators. An application to the analysis of a chronic kidney disease cohort study illustrates the utility of the method. A Pairwise Likelihood Augmented Estimator for the Cox Model Under Left-Truncation Fan Wu Department of Biostatistics, University of Michigan, Ann Arbor and Sehee Kim Department of Biostatistics, University of Michigan, Ann Arbor and Jing Qin Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases and Rajiv Saran Kidney Epidemiology and Cost Center, University of Michigan, Ann Arbor and Yi Li ∗ Department of Biostatistics, University of Michigan, Ann Arbor March 24, 2016 ∗E-mail: yili@umich.edu