Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of bacterial phenotypic traits in selective feeding of the heterotrophic nanoflagellate Spumella sp.

The influence of different bacterial phenotypic traits on the feeding selectivity of a bac- terivorous nanoflagellate was investigated in laboratory experiments. Twelve bacterial isolates from freshwater habitats were characterized in terms of cell size, morphology, capsule formation, surface hydrophobicity and charge, and swimming behavior. Mechanisms of differential flagellate feeding on these isolates were studied in short-term grazing experiments by high-resolution video microscopy using the nanoflagellate Spumella sp. as a model interception-feeding predator. The dif- ferentiation into distinct stages of the feeding process (contact, capture, ingestion) revealed a com- plex selection behavior illustrated by the relatively small proportion of ingested bacteria over cell contacts. We found that bacterial swimming speed increased contact rates but also decreased flagel- late capture efficiency, which had a compensating effect on overall ingestion rates. Bacterial cell size revealed no correlation with flagellate contact rates but an effective inhibition of ingestion rates when exceeding a critical size limit. Correlation analysis presented no bacterial property to account for the residual variability of flagellate ingestion efficiencies. Experiments with specifically coated artificial particles provided evidence for the relative importance of the biochemical surface composi- tion in flagellate food selection compared to physicochemical interaction forces. Only extreme charges beyond -45 mV reduced flagellate ingestion rates. Our results reinforce the idea that bacte- rial cell size strongly affects the feeding success of bacterivorous flagellates, and further implicates size-independent bacterial traits such as swimming speed and biochemical surface composition in this feeding success.
Comparison of equatorial GPS-TEC observations over an African station and an American station during the minimum and ascending phases of solar cycle 24

Abstract. GPS-TEC data were observed at the same local time at two equatorial stations on both longitudes: Lagos (6.52° N, 3.4° E, 3.04° S magnetic latitude), Nigeria; and Pucallpa (8.38° S, 74.57° W, 4.25° N magnetic latitude), Peru during the minimum (2009, 2010) and ascending (2011) phases of solar cycle 24. These data were grouped into daily, seasonal and solar activity sets. The day-to-day variations in vertical TEC (VTEC) recorded the maximum during 14:00–16:00 LT and minimum during 04:00–06:00 LT at both longitudes. Seasonally, during solar minimum, maximum VTEC values were observed during March equinox and minimum during solstices. However, during the ascending phase of the solar activity, the maximum values were recorded during the December solstice and minimum during the June solstice. VTEC also increased with solar activity at both longitudes. On longitude by longitude comparison, the African GPS station generally recorded higher VTEC values than the American GPS station. Furthermore, harmonic analysis technique was used to extract the annual and semi-annual components of the amplitudes of the TEC series at both stations. The semi-annual variations dominated the TEC series over the African equatorial station, while the annual variations dominated those over the American equatorial station. The GPS-TEC-derived averages for non-storm days were compared with the corresponding values derived by the IRI-2007 with the NeQuick topside option. The NeQuick option of IRI-2007 showed better performance at the American sector than the African sector, but generally underestimating TEC during the early morning hours at both longitudes.
Aerosol optical properties in the southeastern United States in summer – Part 2: Sensitivity of aerosol optical depth to relative humidity and aerosol parameters

Abstract. Aircraft observations of meteorological, trace gas, and aerosol properties were made between May and September 2013 in the southeastern United States (US). Regionally representative aggregate vertical profiles of median and interdecile ranges of the measured parameters were constructed from 37 individual aircraft profiles made in the afternoon when a well-mixed boundary layer with typical fair-weather cumulus was present (Wagner et al., 2015). We use these 0–4 km aggregate profiles and a simple model to calculate the sensitivity of aerosol optical depth (AOD) to changes in dry aerosol mass, relative humidity, mixed-layer height, the central diameter and width of the particle size distribution, hygroscopicity, and dry and wet refractive index, while holding the other parameters constant. The calculated sensitivity is a result of both the intrinsic sensitivity and the observed range of variation in these parameters. These observationally based sensitivity studies indicate that the relationship between AOD and dry aerosol mass in these conditions in the southeastern US can be highly variable and is especially sensitive to relative humidity (RH). For example, calculated AOD ranged from 0.137 to 0.305 as the RH was varied between the 10th and 90th percentile profiles with dry aerosol mass held constant. Calculated AOD was somewhat less sensitive to aerosol hygroscopicity, mean size, and geometric standard deviation, σg. However, some chemistry–climate models prescribe values of σg substantially larger than we or others observe, leading to potential high biases in model-calculated AOD of ∼ 25 %. Finally, AOD was least sensitive to observed variations in dry and wet aerosol refractive index and to changes in the height of the well-mixed surface layer. We expect these findings to be applicable to other moderately polluted and background continental air masses in which an accumulation mode between 0.1–0.5 µm diameter dominates aerosol extinction.
Three-Dimensional Double Layers

E double layers are ubiquitous; they will inevitably emerge, given mobile charge carriers and an interface. They play a decisive role in well-known problems such as electrochemical reactions, electrokinetics, and colloidal stability and thus have been studied extensively since the very concept of the double layer was postulated by Helmholtz. Some classical textbooks relate those issues in the title: “Double layer and electrode kinetics”. The recent renaissance of research on double layers is driven by the development of new materials and technologies. In particular, the development of roomtemperature ionic liquids (RTILs) and their applications in electrochemical energy storage, electrode kinetics, and controlled friction have triggered a new wave of research on double layers at electrified interfaces and in nanoconfinement. The development of the theory has refined and diversified pictures of the double layers: from the compact ionic layer originally postulated by Helmholtz, to the compact plus diffuse layer structure of Gouy−Chapman taught in textbooks with discreteness of charge modifications, and finally to the alternating counterion and co-ion layers in highly concentrated ionic systems, revealed most recently. However, if not counting the lateral two-dimensional (2D) structure of the first layer of specifically absorbed ions or counterions condensed on highly charged surfaces, both of which might break the translational invariance in lateral directions and thus endow 2D features to the double layers, the theory mainly focused on onedimensional (1D) ion distributions resolved in the direction normal to the interface. Such a picture, though, is currently being revised on several fronts. In particular, for double layers in concentrated systems such as room temperature ionic liquids (RTILs), the transitions between different lateral arrangements of ions adsorbed on open electrodes have been reported experimentally and revealed in simulations. Furthermore, the transition between different lateral arrangements of counterand co-ions during electrification of narrow pores has been observed in simulations and shown to greatly affect both the capacitance and dynamics of the double layers. These relatively new issues and developments all point to new challenges in understanding the three-dimensional (3D) structures of the double layers controlled by the electrification of surfaces. The article by Merlet et al. comprises an important step in this direction. Although it did not come out of the blue (cf. Figure 1), it moves the story of the double layer to the next round, and it has triggered us to write these notes.
Knowledge, Internal, and Environmental Factors on Environmental Care Behaviour among Aboriginal Students in Malaysia.

This study determined the contribution of predictor factors (i.e. knowledge about the environment as well as internal and environmental factors) on environmental care behaviour among aboriginal students. The knowledge about the environment that was investigated in this research includes environmental knowledge and environmental action knowledge. The internal factors include elements of attitude, personal responsibility, and beliefs, while the elements of environment factors are social influences, information resources, and environmental management facilities. In addition, this study used an environmental knowledge test and questionnaire as research instruments. A total of 445 aboriginal students from the Malaysian state of Pahang were involved in this research. The research data were analysed using Structural Equation Modelling (SEM). The research findings showed that the predictor factors (knowledge, attitude, personal responsibility, beliefs, social influences, information resources, and environmental management facilities) contributed 44% towards environmental care behaviour. In fact, the factors that contributed most to environmental behaviour were social influences and beliefs, followed by environmental management facilities, attitude, and personal responsibility. Nonetheless, knowledge concerning the environment did not contribute towards behaviour, but it influenced attitude, which in turn affected behaviour. Hence, the factors that have been identified to contribute to environmental care behaviour should be considered in planning educational development for the aboriginal community in order to achieve environmental sustainability.
Frequency effects on memory : A resource-limited theory

We present a review of frequency effects in memory, accompanied by a theory of memory, according to which the storage of new information in long-term memory (LTM) depletes a limited pool of working memory (WM) resources as an inverse function of item strength. We support the theory by showing that items with stronger representations in LTM (e.g. high frequency items) are easier to store, bind to context, and bind to one another; that WM resources are involved in storage and retrieval from LTM; that WM capacity is greater for stronger, more familiar stimuli. We present a novel analysis of preceding item strength, in which we show from eight existing studies that memory for an item is higher if during study it was preceded by a stronger item (e.g. a high frequency word; HF). This effect is cumulative (the more prior items are HF, the better), continuous (memory proportional to word frequency of preceding item), interacts with current item strength (larger for weaker items) and interacts with lag (decreases as the lag between the current and prior study item increases). A computational model that implements the theory is presented, which accounts for these effects. We discuss related phenomena that the model/theory can explain.
Rethinking the global secondary organic aerosol (SOA) budget: stronger production, faster removal, shorter lifetime

Abstract. Recent laboratory studies suggest that secondary organic aerosol (SOA) formation rates are higher than assumed in current models. There is also evidence that SOA removal by dry and wet deposition occurs more efficiently than some current models suggest and that photolysis and heterogeneous oxidation may be important (but currently ignored) SOA sinks. Here, we have updated the global GEOS-Chem model to include this new information on formation (i.e., wall-corrected yields and emissions of semi-volatile and intermediate volatility organic compounds) and on removal processes (photolysis and heterogeneous oxidation). We compare simulated SOA from various model configurations against ground, aircraft and satellite measurements to assess the extent to which these improved representations of SOA formation and removal processes are consistent with observed characteristics of the SOA distribution. The updated model presents a more dynamic picture of the life cycle of atmospheric SOA, with production rates 3.9 times higher and sinks a factor of 3.6 more efficient than in the base model. In particular, the updated model predicts larger SOA concentrations in the boundary layer and lower concentrations in the upper troposphere, leading to better agreement with surface and aircraft measurements of organic aerosol compared to the base model. Our analysis thus suggests that the long-standing discrepancy in model predictions of the vertical SOA distribution can now be resolved, at least in part, by a stronger source and stronger sinks leading to a shorter lifetime. The predicted global SOA burden in the updated model is 0.88 Tg and the corresponding direct radiative effect at top of the atmosphere is −0.33 W m−2, which is comparable to recent model estimates constrained by observations. The updated model predicts a population-weighed global mean surface SOA concentration that is a factor of 2 higher than in the base model, suggesting the need for a reanalysis of the contribution of SOA to PM pollution-related human health effects. The potential importance of our estimates highlights the need for more extensive field and laboratory studies focused on characterizing organic aerosol removal mechanisms and rates.
Informed Democracy: Voting-based Novelty Detection for Action Recognition

Novelty detection is crucial for real-life applications. While it is common in activity recognition to assume a closed-set setting, i.e. test samples are always of training categories, this assumption is impractical in a real-world scenario. Test samples can be of various categories including those never seen before during training. Thus, being able to know what we know and what we do not know is decisive for the model to avoid what can be catastrophic consequences. We present in this work a novel approach for identifying samples of activity classes that are not previously seen by the classifier. Our model employs a voting-based scheme that leverages the estimated uncertainty of the individual classifiers in their predictions to measure the novelty of a new input sample. Furthermore, the voting is privileged to a subset of informed classifiers that can best estimate whether a sample is novel or not when it is classified to a certain known category. In a thorough evaluation on UCF-101 and HMDB-51, we show that our model consistently outperforms state-of-the-art in novelty detection. Additionally, by combining our model with off-the-shelf zero-shot learning (ZSL) approaches, our model leads to a significant improvement in action classification accuracy for the generalized ZSL setting.
Kuznets meets Lucas: structural change and human capital

This paper develops a multi-sector growth model with human capital accumulation. In this model, human capital induces structural change through two channels: changes in relative prices and changes in the investment rate of physical and human capital. We show that the specifications of the model give rise to a generalized balanced growth path (GBGP). Furthermore, We show that the model is consistent with (i) the decline in agriculture, (ii) the hump-shaped of manufacturing, (iii) the rise of the services sector, and (iv) the path of human capital accumulation in the US economy during the 20th century. Given the findings, We outline that imbalances between physical and human capital contribute to explain cross-country differences in the pace of structural change.
Anti‐TNFα (Remicade®) therapy protects dystrophic skeletal muscle from necrosis

Necrosis of skeletal muscle fibers in the lethal childhood myopathy Duchenne muscular dystrophy (DMD) results from defects in the cell membrane‐associated protein dystrophin. This study tests the novel hypothesis that the initial sarcolemmal breakdown resulting from dystrophin deficiency is exacerbated by inflammatory cells and that cytokines specifically tumor necrosis factor‐α (TNFα) contribute to muscle necrosis. To block in vivo TNFα bioactivity young dystrophic mdx mice (a model for DMD) were injected weekly from 7 days of age with the anti‐TNFα antibody Remicade® before the onset of muscle necrosis and dystropathology that normally occurs at 21 days postnatally. The extent of inflammation muscle necrosis and myotube formation was measured by histological analysis from 18 to 28 days and muscle damage was also visualized by penetration of Evans blue dye into myofibers. Data from Remicade ‐treated and control mdx mice were compared with mdx/TNFα(−/−) mice that lack TNFα. Pharmacological blockade of TNFα activity with Remicade® clearly delayed and greatly reduced the breakdown of dystrophic muscle in marked contrast to the situation in mdx and mdx/ TNFα(−/−) mice. Remicade had no adverse effect on new muscle formation. Remicade is a highly specific anti‐inflammatory intervention and clinical application to muscular dystrophies is suggested by this marked protective effect against skeletal muscle breakdown. —Grounds M. D. Torrisi J. Anti‐TNFα (Remicade) therapy protects dystrophic skeletal muscle from necrosis.
Resting-State Functional Brain Connectivity Best Predicts the Personality Dimension of Openness to Experience

Abstract Personality neuroscience aims to find associations between brain measures and personality traits. Findings to date have been severely limited by a number of factors, including small sample size and omission of out-of-sample prediction. We capitalized on the recent availability of a large database, together with the emergence of specific criteria for best practices in neuroimaging studies of individual differences. We analyzed resting-state functional magnetic resonance imaging (fMRI) data from 884 young healthy adults in the Human Connectome Project database. We attempted to predict personality traits from the “Big Five,” as assessed with the Neuroticism/Extraversion/Openness Five-Factor Inventory test, using individual functional connectivity matrices. After regressing out potential confounds (such as age, sex, handedness, and fluid intelligence), we used a cross-validated framework, together with test-retest replication (across two sessions of resting-state fMRI for each subject), to quantify how well the neuroimaging data could predict each of the five personality factors. We tested three different (published) denoising strategies for the fMRI data, two intersubject alignment and brain parcellation schemes, and three different linear models for prediction. As measurement noise is known to moderate statistical relationships, we performed final prediction analyses using average connectivity across both imaging sessions (1 hr of data), with the analysis pipeline that yielded the highest predictability overall. Across all results (test/retest; three denoising strategies; two alignment schemes; three models), Openness to experience emerged as the only reliably predicted personality factor. Using the full hour of resting-state data and the best pipeline, we could predict Openness to experience (NEOFAC_O: r=.24, R 2=.024) almost as well as we could predict the score on a 24-item intelligence test (PMAT24_A_CR: r=.26, R 2=.044). Other factors (Extraversion, Neuroticism, Agreeableness, and Conscientiousness) yielded weaker predictions across results that were not statistically significant under permutation testing. We also derived two superordinate personality factors (“α” and “β”) from a principal components analysis of the Neuroticism/Extraversion/Openness Five-Factor Inventory factor scores, thereby reducing noise and enhancing the precision of these measures of personality. We could account for 5% of the variance in the β superordinate factor (r=.27, R 2=.050), which loads highly on Openness to experience. We conclude with a discussion of the potential for predicting personality from neuroimaging data and make specific recommendations for the field.
Bicyclus brakefieldi (Nymphalidae, Satyrinae), a new species of Bicyclus from the Congo River basin.

A new species of Bicyclus is described from the Democratic Republic of Congo. The species belongs to the ignobilis species-group, but has different androconial structure and slightly different wing pattern. Genitalia differences are very small as is expected within most Bicyclus species-groups. Comparison with the other known species in the ignobilis-group and discussion of biogeography of the different species are provided.
Submicron particle mass concentrations and sources in the Amazonian wet season (AMAZE-08)

Abstract. Real-time mass spectra of the non-refractory species in submicron aerosol particles were recorded in a tropical rainforest in the central Amazon Basin during the wet season from February to March 2008, as a part of the Amazonian Aerosol Characterization Experiment (AMAZE-08). Organic material accounted on average for more than 80% of the non-refractory submicron particle mass concentrations during the period of measurements. There was insufficient ammonium to neutralize sulfate. In this acidic, isoprene-rich, HO2-dominant environment, positive-matrix factorization of the time series of particle mass spectra identified four statistical factors to account for the 99% of the variance in the signal intensities of the organic constituents. The first factor was identified as associated with regional and local pollution and labeled "HOA" for its hydrocarbon-like characteristics. A second factor was associated with long-range transport and labeled "OOA-1" for its oxygenated characteristics. A third factor, labeled "OOA-2," was implicated as associated with the reactive uptake of isoprene oxidation products, especially of epoxydiols to acidic haze, fog, or cloud droplets. A fourth factor, labeled "OOA-3," was consistent with an association with the fresh production of secondary organic material (SOM) by the mechanism of gas-phase oxidation of biogenic volatile organic precursors followed by gas-to-particle conversion of the oxidation products. The suffixes 1, 2, and 3 on the OOA labels signify ordinal ranking with respect to the extent of oxidation represented by the factor. The process of aqueous-phase oxidation of water-soluble products of gas-phase photochemistry might also have been associated to some extent with the OOA-2 factor. The campaign-average factor loadings had a ratio of 1.4:1 for OOA-2 : OOA-3, suggesting the comparable importance of particle-phase compared to gas-phase pathways for the production of SOM during the study period.