Immunoglobulin G (IgG) specific responses to recombinant Qß displayed MSP3 and UB05 in plasma of asymptomatic Plasmodium falciparum-infected children living in two different agro-ecological settings of Cameroon.

Introduction: in areas with intense perennial malaria transmission, limited data is available on the impact of environmental conditions especially rainfall on naturally acquired immunity against promising malaria vaccine candidates. For this reason, we have compared IgG antibody responses specific to Plasmodium spp. derived MSP3 and UB05 vaccine candidates, in plasma of children living in two areas of Cameroon differing in rainfall conditions. Methods: data about children less than 5 years old was collected during the years 2017 and 2018. Next malaria asymptomatic P. falciparum (Pf) infected children were selected following malaria test confirmation. MSP3 and UB05 specific IgG antibody responses were measured in participant´s plasma using enzyme-linked immunosorbent assay (ELISA). Results: interestingly, IgG antibody responses specific to UB05 were significantly higher (p<0.0001) in Pf-negative children when compared to their asymptomatic Pf-infected counterparts living in monomodal rainfall areas. In contrast, a significantly higher (p<0.0001) IgG response to MSP3 was observed instead in asymptomatic Pf-infected children in the same population. In addition, IgG responses specific to UB05 remained significantly higher in bimodal when compared to monomodal rainfall areas irrespective of children´s Pf infection status (p<0.0055 for Pf-positive and p<0.0001 for negative children). On the contrary, IgG antibody responses specific to MSP3 were significantly higher in bimodal relative to monomodal rainfall areas (P<0.0001) just for Pf-negative children. Conclusion: thus IgG antibody responses specific to UBO5 are a better correlate of naturally acquired immunity against malaria in Pf-negative Cameroonian children especially in monomodal rainfall areas.

Number size distribution of bacterial aerosols in terrestrial and marine airflows at a coastal site of Japan.

Size-differentiated concentration of bacterial aerosols is essential for investigating their dissemination via the atmosphere. In this study, the number size distribution of bacterial aerosols was measured at a coastal site in southwestern Japan (32.324°N, 129.993°E) using a size-segregated eight-stage (>11, 7.0-11, 4.7-7.0, 3.3-4.7, 2.1-3.3, 1.1-2.1, 0.65-1.1, and 0.43-0.65µm) sampler. The results showed that the distribution differed according to the source areas: terrestrial air, oceanic air, or a combination of the two. The distribution in the long-distance transported terrestrial air from the Asian continent was monomodal, with a peak of 3.3-4.7 µm. The distribution in local land breeze air was bimodal, with the peaks at 0.43-1.1 and 3.3-4.7 µm. A similar bimodal distribution was encountered when the local island air and long-distance transported terrestrial air mixed. In contrast, the size distribution did not show clear peaks in the air from either nearby or remote marine areas. According to the air mass backward trajectories, the further the distance the air moved in the 72 h before arriving at the site, the lower the concentration of total bacterial aerosols. The estimation of dry deposition fluxes of bacterial cells showed that the deposition was dominated by cells larger than 1.1 µm with a relative contribution from 70.5 % to 93.7 %, except for the local land breeze cases, where the contributions in the size ranges larger and smaller than 1.1 µm were similar. These results show the distinctive number size distributions and removal processes of bacterial aerosols in different types of air. In addition, they indicate that size-dependent characteristics of airborne bacteria should be considered when studying their activities and roles in the atmospheric environment.

Road and Railway Smart Mobility: A High-Definition Ground Truth Hybrid Dataset.

A robust visual understanding of complex urban environments using passive optical sensors is an onerous and essential task for autonomous navigation. The problem is heavily characterized by the quality of the available dataset and the number of instances it includes. Regardless of the benchmark results of perception algorithms, a model would only be reliable and capable of enhanced decision making if the dataset covers the exact domain of the end-use case. For this purpose, in order to improve the level of instances in datasets used for the training and validation of Autonomous Vehicles (AV), Advanced Driver Assistance Systems (ADAS), and autonomous driving, and to reduce the void due to the no-existence of any datasets in the context of railway smart mobility, we introduce our multimodal hybrid dataset called ESRORAD. ESRORAD is comprised of 34 videos, 2.7 k virtual images, and 100 k real images for both road and railway scenes collected in two Normandy towns, Rouen and Le Havre. All the images are annotated with 3D bounding boxes showing at least three different classes of persons, cars, and bicycles. Crucially, our dataset is the first of its kind with uncompromised efforts on being the best in terms of large volume, abundance in annotation, and diversity in scenes. Our escorting study provides an in-depth analysis of the dataset's characteristics as well as a performance evaluation with various state-of-the-art models trained under other popular datasets, namely, KITTI and NUScenes. Some examples of image annotations and the prediction results of our 3D object detection lightweight algorithms are available in ESRORAD dataset. Finally, the dataset is available online. This repository consists of 52 datasets with their respective annotations performed.

Dual Coding or Cognitive Load? Exploring the Effect of Multimodal Input on English as a Foreign Language Learners' Vocabulary Learning.

In the era of eLearning 4.0, many researchers have suggested that multimodal input helps to enhance second language (L2) vocabulary learning. However, previous studies on the effects of multimodal teaching have failed to yield definitive conclusions. Furthermore, only few studies on the multimodal input of vocabulary learning have aimed at junior high school students and have focused on explicit vocabulary instruction in class. To explore the effects of multimodal input on English as a foreign language (EFL) learners' vocabulary learning and summarize effective methods, this study adopts a mixed-method approach. Based on dual coding theory and cognitive load theory, the teaching materials in this study were designed using the resources provided by the multimodal corpus iWeb and other websites. A total of 60 junior high school students who learned EFL and had a similar English proficiency level were divided into an experimental group (EG) and a control group (CG). Target words were selected through questionnaire I. During the experiment, the CG learned from monomodal materials while the EG received multimodal input, and an immediate post-test was delivered to the two groups. Questionnaire II was distributed in the EG, and five students of the EG were randomly selected for an interview. One week later, a delayed post-test was conducted on the EG and CG. The results showed that the EG performed better in the post-test but did worse than the CG in the delayed post-test. The results of the questionnaire and the interview suggest that students held both positive and negative attitudes toward the multimodal input approach in vocabulary learning. The study concludes with some implications for choosing a multimodal input approach in vocabulary learning, along with a number of suggestions on how to optimize its positive influence and minimize its negative effects.

Multistage Forward Path Regenerative Genetic Algorithm for Brain Magnetic Resonant Imaging Registration.

In image registration, the search space used to compute the optimal transformation between the images depends on the group of pixels in the vicinity. Favorable results can be achieved by significantly increasing the number of neighboring pixels in the search space; however, this strategy increases the computational load, thus making it challenging to realize the most desirable solution in a reasonable amount of time. To address the mentioned problem, the genetic algorithm is used to find the optimum solution and the solution lies in finding the best chromosomes. In rigid image registration problem, chromosomes contain a set of three parameters, x-translation, y-translation, and rotation. The genetic algorithm iteratively improves chromosomes from generation to generation and selects the best one having the best fittest value. Chromosomes with high fitness value are the ones with an optimal solution where the template image best aligns reference image. Fitness function in the genetic algorithm for image registration problem uses similarity measure index measure to find the amount of similarity between two images. The best fittest value is the one with a high similarity measure that shows the best-aligned template and reference image. Here we used the structural similarity index measure in fitness function that helps in evaluating the best chromosome, even for the compressed images with low quality, intensity nonuniformity (INU), and noise degradation. Building on the genetic algorithm, we propose a novel approach called multistage forward path regenerative genetic algorithm (MFRGA), abbreviated as MFRGA, with reducing search space at each stage. Compared with the single stage of genetic algorithm, our approach proved to be more reliable and accurate in terms of finding true rigid image transformation for alignment. At each increasing stage of MFRGA, results are computed with decreasing search space and increasing precision levels. Moreover, to prove the robustness of our algorithm, we utilized compressed images of brain magnetic resonant imaging that vary in compression qualities ranging from 10 to 100. Furthermore, we added noise levels of 1%, 3%, 5%, 7%, and 9% with an INU of 20% and 40%, respectively, provided by the online BrainWeb simulator. We achieved the monomodal rigid image registration that proves to be successful using MFRGA, even when the noise is critical, the compression quality is the least, and the intensity is nonuniform.

Metaphor processing is supramodal semantic processing: The role of the bilateral lateral temporal regions in multimodal communication.

This paper presents an fMRI study on healthy adult understanding of metaphors in multimodal communication. We investigated metaphors expressed either only in coverbal gestures ("monomodal metaphors") or in speech with accompanying gestures ("multimodal metaphors"). Monomodal metaphoric gestures convey metaphoric information not expressed in the accompanying speech (e.g. saying the non-metaphoric utterance, "She felt bad" while dropping down the hand with palm facing up; here, the gesture alone indicates metaphoricity), whereas coverbal gestures in multimodal metaphors indicate metaphoricity redundant to the speech (e.g. saying the metaphoric utterance, "Her spirits fell" while dropping the hand with palm facing up). In other words, in monomodal metaphors, gestures add information not spoken, whereas the gestures in multimodal metaphors can be redundant to the spoken content. Understanding and integrating the information in each modality, here spoken and visual, is important in multimodal communication, but most prior studies have only considered multimodal metaphors where the gesture is redundant to what is spoken. Our participants watched audiovisual clips of an actor speaking while gesturing. We found that abstract metaphor comprehension recruited the lateral superior/middle temporal cortices, regardless of the modality in which the conceptual metaphor is expressed. These results suggest that abstract metaphors, regardless of modality, involve resources implicated in general semantic processing and are consistent with the role of these areas in supramodal semantic processing as well as the theory of embodied cognition.

The Size Dependence of Phytoplankton Growth Rates: A Trade-Off between Nutrient Uptake and Metabolism.

Rates of metabolism and population growth are often assumed to decrease universally with increasing organism size. Recent observations have shown, however, that maximum population growth rates among phytoplankton smaller than ∼6 µm in diameter tend to increase with organism size. Here we bring together observations and theory to demonstrate that the observed change in slope is attributable to a trade-off between nutrient uptake and the potential rate of internal metabolism. Specifically, we apply an established model of phytoplankton growth to explore a trade-off between the ability of cells to replenish their internal quota (which increases with size) and their ability to synthesize new biomass (which decreases with size). Contrary to the metabolic theory of ecology, these results demonstrate that rates of resource acquisition (rather than metabolism) provide the primary physiological constraint on the growth rates of some of the smallest and most numerically abundant photosynthetic organisms on Earth.

Obtaining of Ni/NiO nanopowder from aqua solutions of Ni(CH3COO)2 ammonia complexes.

Ni/NiO nanopowders have been prepared by using thermal decomposition of aqua solutions of nickel acetate ammine complexes in air at the annealing temperature range of 300°C to 500°C, time of decomposition from 30 to 180 min, and ammonia content in initial complex 3.6 to 9.55 mol/mol Ni(2+). Chemical composition of obtained powders has been characterized by chemical and thermal analysis. Phase analysis and particle size of powders have been investigated by X-ray diffraction method, transmission electron microscopy (TEM), and scanning electron microscopy (SEM). The powders' pore structure has been determinated by low-temperature nitrogen adsorption method. Products of decomposition were represented as agglomerates of nanoparticles of Ni, NiO, and hydroxy-containing precursors. Mean agglomerate size depended on ammonia content in initial complex, annealing temperature, and duration and has grown from 30 to 40 to 400 to 520 nm. Mean nanoparticle size of hydroxy-containing precursors was invariable with ammonia concentration in initial complex, annealing temperature, and duration and has grown 5 nm. Mean nanoparticle size of Ni depended on annealing temperature and has grown from 40 to 60 to 40 to 70 nm at temperatures 400°Ð¡ and 500°Ð¡, respectively. Mean nanoparticle size of NiO increased with temperature rising from 5 nm at 350°Ð¡ to 20 to 25 nm at 500°Ð¡.