1,659 research outputs found
VNI-Net: Vector Neurons-based Rotation-Invariant Descriptor for LiDAR Place Recognition
LiDAR-based place recognition plays a crucial role in Simultaneous
Localization and Mapping (SLAM) and LiDAR localization.
Despite the emergence of various deep learning-based and hand-crafting-based
methods, rotation-induced place recognition failure remains a critical
challenge.
Existing studies address this limitation through specific training strategies
or network structures.
However, the former does not produce satisfactory results, while the latter
focuses mainly on the reduced problem of SO(2) rotation invariance. Methods
targeting SO(3) rotation invariance suffer from limitations in discrimination
capability.
In this paper, we propose a new method that employs Vector Neurons Network
(VNN) to achieve SO(3) rotation invariance.
We first extract rotation-equivariant features from neighboring points and
map low-dimensional features to a high-dimensional space through VNN.
Afterwards, we calculate the Euclidean and Cosine distance in the
rotation-equivariant feature space as rotation-invariant feature descriptors.
Finally, we aggregate the features using GeM pooling to obtain global
descriptors.
To address the significant information loss when formulating
rotation-invariant descriptors, we propose computing distances between features
at different layers within the Euclidean space neighborhood.
This greatly improves the discriminability of the point cloud descriptors
while ensuring computational efficiency.
Experimental results on public datasets show that our approach significantly
outperforms other baseline methods implementing rotation invariance, while
achieving comparable results with current state-of-the-art place recognition
methods that do not consider rotation issues
Learning Sequence Descriptor based on Spatiotemporal Attention for Visual Place Recognition
Sequence-based visual place recognition (sVPR) aims to match frame sequences
with frames stored in a reference map for localization. Existing methods
include sequence matching and sequence descriptor-based retrieval. The former
is based on the assumption of constant velocity, which is difficult to hold in
real scenarios and does not get rid of the intrinsic single frame descriptor
mismatch. The latter solves this problem by extracting a descriptor for the
whole sequence, but current sequence descriptors are only constructed by
feature aggregation of multi-frames, with no temporal information interaction.
In this paper, we propose a sequential descriptor extraction method to fuse
spatiotemporal information effectively and generate discriminative descriptors.
Specifically, similar features on the same frame focu on each other and learn
space structure, and the same local regions of different frames learn local
feature changes over time. And we use sliding windows to control the temporal
self-attention range and adpot relative position encoding to construct the
positional relationships between different features, which allows our
descriptor to capture the inherent dynamics in the frame sequence and local
feature motion
Integrated Analysis of Transcriptome and Metabolome Reveals the Mechanism of Chlorine Dioxide Repressed Potato (Solanum tuberosum L.) Tuber Sprouting
Sprouting is an irreversible deterioration of potato quality, which not only causes loss in their commercial value but also produces harmful toxins. As a popular disinfectant, ClO2 can inhibit the sprouting of potato tubers. Using transcriptomic and metabolomic approaches to understand the repressive mechanism of ClO2 in potato sprouting is yet to be reported. Sequencing the transcriptome and metabolome of potatoes treated with ClO2 in this study revealed a total of 3,119 differentially expressed genes, with 1,247 and 1,872 genes showing down- and upregulated expression, respectively. The majority of the downregulated genes were associated with plant hormone signal transduction, whereas upregulated differential genes were associated primarily with biological processes, such as phenylpropanoid biosynthesis and the mitogen-activated protein kinase (MAPK) signaling pathway. Metabonomic assays identified a total of 932 metabolites, with 33 and 52 metabolites being down- and upregulated, respectively. Downregulated metabolites were mostly alkaloids, amino acids, and their derivatives, whereas upregulated metabolites were composed mainly of flavonoids and coumarins. Integrated transcriptomic and metabolomic analyses showed that many different metabolites were regulated by several different genes, forming a complex regulatory network. These results provide new insights for understanding the mechanism of ClO2-mediated repression of potato sprouting
Role of apamin sensitive small conductance calcium-activated potassium currents in long term cardiac memory in rabbits
Background
Apamin-sensitive small conductance calcium-activated K current (IKAS) is upregulated during ventricular pacing and masks short-term cardiac memory (CM).
Objective
– To determine the role of IKAS in long-term CM.
Methods
– CM was created with 3-5 weeks of ventricular pacing and defined by a flat or inverted T-wave off pacing. Epicardial optical mapping was performed in both paced and normal ventricles. Action potential duration (APD80) was determined during RA pacing. Ventricular stability was tested before and after IKAS blockade. Four paced hearts and 4 normal hearts were used for western blotting and histology.
Results
– There were no significant differences in either the echocardiographic parameters or in fibrosis levels between groups. Apamin induced more APD80 prolongation in CM than in normal ventricles (9.6% [8.8%-10.5%] vs 3.1% [1.9%-4.3%], p<0.001). Apamin significantly lengthend the APD80 in the CM model at late activation sites, indicating significant IKAS upregulation at those sites. The CM model also had altered Ca2+ handling as the 50% Ca2+ transient duration and amplitude were increased at distal sites compared to a proximal site (near the pacing site). After apamin, the CM model had increased VF inducibility (paced vs control, 33/40 (82.5%) vs 7/20 (35%) P<0.001), and longer VF durations (124 vs 26 seconds, P<0.001).
Conclusions
Chronic ventricular pacing increases Ca2+ transients at late activation sites which activates IKAS to maintain repolarization reserve. IKAS blockade increases VF vulnerability in chronically paced rabbit ventricles
A novel recombinase polymerase amplification (RPA) assay for the rapid isothermal detection of Neospora caninum in aborted bovine fetuses
The development of a method to rapidly diagnose Neospora caninum infection is highly desirable. Recombinase polymerase amplification (RPA), combined with lateral flow (LF) strips, is a novel approach to rapidly amplify and visualize DNA. We have developed a prototype LF-RPA assay, using primers and a probe that targeted a specific sequence in the N. caninum NC-5 gene. The N. caninum-specific LF-RPA assay was first tested on purified DNA from oocysts and amplified N. caninum DNA to detectable levels in 10 min, at a constant temperature and without the need for an expensive thermocycler. The designed RPA primers and probe displayed 100% specificity for detecting N. caninum without any cross-reaction with DNA from nine related protozoan spp. (eg Toxoplasma gondii, Sarcocystis gigantean, Sarcocystis zuoi, Hammondia hammondi, Hammondia heydorni, Eimeria cylindrica, Plasmodium falciparum, Theileria annulata and Babesia bigemina). Although, LF-RPA assay detected amounts as low as 50 fg of N. caninum DNA, it was nearly 5-fold less sensitive than previously published qPCR and nested PCR assays. We tested the diagnostic performance of the LF-RPA assay for the detection of N. caninum DNA in aborted bovine fetal tissue samples, and compared the results with those obtained from nested PCR. Out of the 75 samples examined, 18 (24%) and 17 (22.6%) tested positive using LF-RPA and nested PCR, respectively. Our results indicate that LF-RPA is a suitable assay for the rapid and reliable detection of N. caninum
Theoretical Aspects of Gravitational Lensing in TeVeS
Since Bekenstein's (2004) creation of his Tensor-Vector-Scalar theory
(TeVeS), the Modified Newtonian dynamics (MOND) paradigm has been redeemed from
the embarrassment of lacking a relativistic version. One primary success of
TeVeS is that it provides an enhancement of gravitational lensing, which could
not be achieved by other MONDian theories. Following Bekenstein's work, we
investigate the phenomena of gravitational lensing including deflection angles,
lens equations and time delay. We find that the deflection angle would maintain
its value while the distance of closest approach vary in the MOND regime, this
coincides with the conclusion of Mortlock and Turner's (2001) intuitional
approach. Moreover, the scalar field, which is introduced to enhance the
deflection angle in TeVeS, contributes a negative effect on the potential time
delay. Unfortunately this phenomenon is unmeasurable in lensing systems where
we can only observe the time delay between two images for a given source.
However, this measurable time delay offers another constraint on the mass ratio
of the DM and MOND scenarios, which in general differs from that given by the
deflection angle. In other words, for a lensing system, if two masses, m_gN and
m_gM, are mutually alternatives for the deflection angles in their own
paradigm, regarding the time delay they are in general in an exclusive
relation.Comment: 15 pages, 7 figure
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