25 research outputs found
Astrophysics from data analysis of spherical gravitational wave detectors
The direct detection of gravitational waves will provide valuable
astrophysical information about many celestial objects. Also, it will be an
important test to general relativity and other theories of gravitation. The
gravitational wave detector SCHENBERG has recently undergone its first test
run. It is expected to have its first scientific run soon. In this work the
data analysis system of this spherical, resonant mass detector is tested
through the simulation of the detection of gravitational waves generated during
the inspiralling phase of a binary system. It is shown from the simulated data
that it is not necessary to have all six transducers operational in order to
determine the source's direction and the wave's amplitudes.Comment: 8 pages and 3 figure
Can lightning be a noise source for a spherical gravitational wave antenna?
The detection of gravitational waves is a very active research field at the
moment. In Brazil the gravitational wave detector is called Mario SCHENBERG.
Due to its high sensitivity it is necessary to model mathematically all known
noise sources so that digital filters can be developed that maximize the
signal-to-noise ratio. One of the noise sources that must be considered are the
disturbances caused by electromagnetic pulses due to lightning close to the
experiment. Such disturbances may influence the vibrations of the antenna's
normal modes and mask possible gravitational wave signals. In this work we
model the interaction between lightning and SCHENBERG antenna and calculate the
intensity of the noise due to a close lightning stroke in the detected signal.
We find that the noise generated does not disturb the experiment significantly.Comment: 5 pages, 6 figure
Protein methyltransferase 7 deficiency in Leishmania major increases neutrophil associated pathology in murine model
Leishmania major is the main causative agent of cutaneous leishmaniasis in the Old World. In Leishmania parasites, the lack of transcriptional control is mostly compensated by post-transcriptional mechanisms. Methylation of arginine is a conserved post-translational modification executed by Protein Arginine Methyltransferase (PRMTs). The genome from L. major encodes five PRMT homologs, including the cytosolic protein associated with several RNA-binding proteins, LmjPRMT7. It has been previously reported that LmjPRMT7 could impact parasite infectivity. In addition, a more recent work has clearly shown the importance of LmjPRMT7 in RNA-binding capacity and protein stability of methylation targets, demonstrating the role of this enzyme as an important epigenetic regulator of mRNA metabolism. In this study, we unveil the impact of PRMT7-mediated methylation on parasite development and virulence. Our data reveals that higher levels of LmjPRMT7 can impair parasite pathogenicity, and that deletion of this enzyme rescues the pathogenic phenotype of an attenuated strain of L. major. Interestingly, lesion formation caused by LmjPRMT7 knockout parasites is associated with an exacerbated inflammatory reaction in the tissue correlated with an excessive neutrophil recruitment. Moreover, the absence of LmjPRMT7 also impairs parasite development within the sand fly vector Phlebotomus duboscqi. Finally, a transcriptome analysis shed light onto possible genes affected by depletion of this enzyme. Taken together, this study highlights how post-transcriptional regulation can affect different aspects of the parasite biology
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Constrained pre-equalization accounting for multi-path fading emulated using large RC networks: applications to wireless and photonics communications
Multi-path propagation is modelled assuming a multi-layer RC network with randomly allocated resistors and capacitors to represent the transmission medium. Due to frequency-selective attenuation, the waveforms associated with each propagation path incur path-dependent distortion. A pre-equalization procedure that takes into account the capabilities of the transmission source as well as the transmission properties of the medium is developed. The problem is cast within a Mixed Integer Linear Programming optimization framework that uses the developed nominal RC network model, with the excitation waveform customized to optimize signal fidelity from the transmitter to the receiver. The objective is to match a Gaussian pulse input accounting for frequency regions where there would be pronounced fading. Simulations are carried out with different network realizations in order to evaluate the sensitivity of the solution with respect to changes in the transmission medium mimicking the multi-path propagation. The proposed approach is of relevance where equalization techniques are difficult to implement. Applications are discussed within the context of emergent communication modalities across the EM spectrum such as light percolation as well as emergent indoor communications assuming various modulation protocols or UWB schemes as well as within the context of space division multiplexing
Mapping Integrated Crop–Livestock Systems Using Fused Sentinel-2 and PlanetScope Time Series and Deep Learning
Integrated crop–livestock systems (ICLS) are among the main viable strategies for sustainable agricultural production. Mapping these systems is crucial for monitoring land use changes in Brazil, playing a significant role in promoting sustainable agricultural production. Due to the highly dynamic nature of ICLS management, mapping them is a challenging task. The main objective of this research was to develop a method for mapping ICLS using deep learning algorithms applied on Satellite Image Time Series (SITS) data cubes, which consist of Sentinel-2 (S2) and PlanetScope (PS) satellite images, as well as data fused (DF) from both sensors. This study focused on two Brazilian states with varying landscapes and field sizes. Targeting ICLS, field data were combined with S2 and PS data to build land use and land cover classification models for three sequential agricultural years (2018/2019, 2019/2020, and 2020/2021). We tested three experimental settings to assess the classification performance using S2, PS, and DF data cubes. The test classification algorithms included Random Forest (RF), Temporal Convolutional Neural Network (TempCNN), Residual Network (ResNet), and a Lightweight Temporal Attention Encoder (L-TAE), with the latter incorporating an attention-based model, fusing S2 and PS within the temporal encoders. Experimental results did not show statistically significant differences between the three data sources for both study areas. Nevertheless, the TempCNN outperformed the other classifiers with an overall accuracy above 90% and an F1-Score of 86.6% for the ICLS class. By selecting the best models, we generated annual ICLS maps, including their surrounding landscapes. This study demonstrated the potential of deep learning algorithms and SITS to successfully map dynamic agricultural systems
Correction: Antigenicity and Protective Efficacy of a Leishmania Amastigote-specific Protein, Member of the Super-oxygenase Family, against Visceral Leishmaniasis.
[This corrects the article on p. e2148 in vol. 7.]
Antigenicity and protective efficacy of a Leishmania amastigote-specific protein, member of the super-oxygenase family, against visceral leishmaniasis.
BackgroundThe present study aimed to evaluate a hypothetical Leishmania amastigote-specific protein (LiHyp1), previously identified by an immunoproteomic approach performed in Leishmania infantum, which showed homology to the super-oxygenase gene family, attempting to select a new candidate antigen for specific serodiagnosis, as well as to compose a vaccine against VL.Methodology/principal findingsThe LiHyp1 DNA sequence was cloned; the recombinant protein (rLiHyp1) was purified and evaluated for its antigenicity and immunogenicity. The rLiHyp1 protein was recognized by antibodies from sera of asymptomatic and symptomatic animals with canine visceral leishmaniasis (CVL), but presented no cross-reactivity with sera of dogs vaccinated with Leish-Tec, a Brazilian commercial vaccine; with Chagas' disease or healthy animals. In addition, the immunogenicity and protective efficacy of rLiHyp1 plus saponin was evaluated in BALB/c mice challenged subcutaneously with virulent L. infantum promastigotes. rLiHyp1 plus saponin vaccinated mice showed a high and specific production of IFN-γ, IL-12, and GM-CSF after in vitro stimulation with the recombinant protein. Immunized and infected mice, as compared to the control groups (saline and saponin), showed significant reductions in the number of parasites found in the liver, spleen, bone marrow, and in the paws' draining lymph nodes. Protection was associated with an IL-12-dependent production of IFN-γ, produced mainly by CD4 T cells. In these mice, a decrease in the parasite-mediated IL-4 and IL-10 response could also be observed.Conclusions/significanceThe present study showed that this Leishmania oxygenase amastigote-specific protein can be used for a more sensitive and specific serodiagnosis of asymptomatic and symptomatic CVL and, when combined with a Th1-type adjuvant, can also be employ as a candidate antigen to develop vaccines against VL
Identification of differentially expressed proteins from Leishmania amazonensis associated with the loss of virulence of the parasites.
BACKGROUND: The present study analyzed whether or not the in vitro cultivation for long periods of time of pre-isolated Leishmania amazonensis from lesions of chronically infected BALB/c mice was able to interfere in the parasites' infectivity using in vivo and in vitro experiments. In addition, the proteins that presented a significant decrease or increase in their protein expression content were identified applying a proteomic approach. METHODOLOGY/PRINCIPAL FINDINGS: Parasites were cultured in vitro for 150 days. Aliquots were collected on the day 0 of culture (R0), as well as after ten (R10; 50 days of culture), twenty (R20; 100 days of culture), and thirty (R30; 150 days of culture) passages, and were used to analyze the parasites' in vitro and in vivo infectivity, as well as to perform the proteomic approach. Approximately 837, 967, 935, and 872 spots were found in 2-DE gels prepared from R0, R10, R20, and R30 samples, respectively. A total of 37 spots presented a significant decrease in their intensity of expression, whereas a significant increase in protein content during cultivation could be observed for 19 proteins (both cases >2.0 folds). Some of these identified proteins can be described, such as diagnosis and/or vaccine candidates, while others are involved in the infectivity of Leishmania. It is interesting to note that six proteins, considered hypothetical in Leishmania, showed a significant decrease in their expression and were also identified. CONCLUSIONS/SIGNIFICANCE: The present study contributes to the understanding that the cultivation of parasites over long periods of time may well be related to the possible loss of infectivity of L. amazonensis. The identified proteins that presented a significant decrease in their expression during cultivation, including the hypothetical, may also be related to this loss of parasites' infectivity, and applied in future studies, including vaccine candidates and/or immunotherapeutic targets against leishmaniasis