99 research outputs found
Multiangle social network recommendation algorithms and similarity network evaluation
Multiangle social network recommendation algorithms (MSN) and a new assessmentmethod, called similarity network evaluation (SNE), are both proposed. From the viewpoint of six dimensions, the MSN are classified into six algorithms, including user-based algorithmfromresource point (UBR), user-based algorithmfromtag point (UBT), resource-based algorithm fromtag point (RBT), resource-based algorithm from user point (RBU), tag-based algorithm from resource point (TBR), and tag-based algorithm from user point (TBU). Compared with the traditional recall/precision (RP) method, the SNE is more simple, effective, and visualized. The simulation results show that TBR and UBR are the best algorithms, RBU and TBU are the worst ones, and UBT and RBT are in the medium levels
Reconstructing Three-decade Global Fine-Grained Nighttime Light Observations by a New Super-Resolution Framework
Satellite-collected nighttime light provides a unique perspective on human
activities, including urbanization, population growth, and epidemics. Yet,
long-term and fine-grained nighttime light observations are lacking, leaving
the analysis and applications of decades of light changes in urban facilities
undeveloped. To fill this gap, we developed an innovative framework and used it
to design a new super-resolution model that reconstructs low-resolution
nighttime light data into high resolution. The validation of one billion data
points shows that the correlation coefficient of our model at the global scale
reaches 0.873, which is significantly higher than that of other existing models
(maximum = 0.713). Our model also outperforms existing models at the national
and urban scales. Furthermore, through an inspection of airports and roads,
only our model's image details can reveal the historical development of these
facilities. We provide the long-term and fine-grained nighttime light
observations to promote research on human activities. The dataset is available
at \url{https://doi.org/10.5281/zenodo.7859205}
RD-VIO: Robust Visual-Inertial Odometry for Mobile Augmented Reality in Dynamic Environments
It is typically challenging for visual or visual-inertial odometry systems to
handle the problems of dynamic scenes and pure rotation. In this work, we
design a novel visual-inertial odometry (VIO) system called RD-VIO to handle
both of these two problems. Firstly, we propose an IMU-PARSAC algorithm which
can robustly detect and match keypoints in a two-stage process. In the first
state, landmarks are matched with new keypoints using visual and IMU
measurements. We collect statistical information from the matching and then
guide the intra-keypoint matching in the second stage. Secondly, to handle the
problem of pure rotation, we detect the motion type and adapt the
deferred-triangulation technique during the data-association process. We make
the pure-rotational frames into the special subframes. When solving the
visual-inertial bundle adjustment, they provide additional constraints to the
pure-rotational motion. We evaluate the proposed VIO system on public datasets.
Experiments show the proposed RD-VIO has obvious advantages over other methods
in dynamic environments
Thyroid dysfunction and risk of cutaneous malignant melanoma: a bidirectional two-sample Mendelian randomization study
BackgroundEpidemiologic and observational data have found a risk association between thyroid dysfunction and cutaneous malignant melanoma (CMM), however, the cause and direction of these effects are yet unknown. By using a bidirectional two-sample Mendelian randomization (MR) methodology, we hoped to further investigate the causal link between thyroid dysfunction and CMM in this work.MethodsA genome-wide association study (GWAS) of 9,851,867 single nucleotide polymorphisms (SNPs) in a European population was used to develop genetic tools for thyroid dysfunction. Hypothyroidism was linked to 22,687 cases and 440,246 controls. For hyperthyroidism, there were 3545 cases and 459,388 controls. A total of 3751 cases and 372016 controls were included in the genetic data for CMM from UK Biobank (http://www.nealelab.is/uk-biobank) (the Dataset: ieu - b - 4969). Among them, inverse variance weighting (IVW) is the main MR Analysis method for causality assessment. MR-Egger method, MR Pleiotropic residual and outlier test (MR-PRESSO), and simple and weighted median (VM) were used to supplement the IVW method. Sensitivity analyses, mainly Cochran’s Q test, leave-one-out analysis, and MR Egger intercept test were performed to assess the robustness of the outcomes.ResultsThe two-sample MR Analysis results revealed a negative correlation between genetically predicted hypothyroidism and the probability of CMM (OR=0.987, 95%CI =0.075-0.999, p=0.041). The supplemental MR Analysis did not reveal any statistically significant differences, although the direction of the effect sizes for the other approaches was consistent with the IVW effect sizes. The results of the causal analysis were relatively robust, according to a sensitivity analysis. The risk of CMM was unaffected by hyperthyroidism (p>0.05). No correlation between CMM and thyroid dysfunction was seen in the reverse MR analysis.ConclusionAlthough the magnitude of the causal association is weak and further investigation of the mechanism of this putative causal relationship is required, our findings imply that hypothyroidism may be a protective factor for CMM
Elevation of YKL-40 in the CSF of Anti-NMDAR Encephalitis Patients Is Associated With Poor Prognosis
Objective: Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis predominantly affects children and young women; the disease can have a multistage presentation and exhibit a wide variety of neuropsychiatric features. This study aimed to investigate the profile of YKL-40 (Chitinase 3-like 1) in anti-NMDAR encephalitis patients and evaluate its association with modified Rankin Scale (mRS) scores and expression of inflammatory cytokines.Methods: A total of 66 patients were enrolled in this study, 33 with anti-NMDAR encephalitis, 13 with viral meningitis and 20 with non-inflammatory neurological disease. Patients were evaluated to determine mRS scores at disease onset and at the 3 month follow-up; cerebrospinal fluid (CSF) samples were collected in the meantime. CSF levels of YKL-40 and cytokines (TNF-α, IL-6, IL-10) were measured by enzyme-linked immunosorbent assay.Results: CSF levels of YKL-40 and inflammatory cytokines (TNF-α, IL-6, IL-10) were all more highly elevated in patients with anti-NMDAR encephalitis at the acute stage of disease compared with the controls. Levels of CSF YKL-40 were correlated with levels of IL-6 both at disease onset and at the 3 month follow-up. Changes in YKL-40 levels were significantly correlated with improved mRS scores in patients with anti-NMDAR encephalitis.Conclusion: Our study suggests that CSF levels of YKL-40 in patients with anti-NMDAR encephalitis were increased and correlated with clinical mRS scores. This may be reflective of the underlying neuroinflammatory process. YKL-40 demonstrates potential as a possible biomarker for the prognosis of anti-NMDAR encephalitis
Highly-stable, flexible delivery of microjoule-level ultrafast pulses in vacuumized anti-resonant hollow-core fibers for active synchronization
We demonstrate the stable and flexible light delivery of multi-{\mu}J,
sub-200-fs pulses over a ~10-m-long vacuumized anti-resonant hollow-core fiber
(AR-HCF), which was successfully used for high-performance pulse
synchronization. Compared with the pulse train launched into the AR-HCF, the
transmitted pulse train out of the fiber exhibits excellent stabilities in
pulse power and spectrum, with pointing stability largely improved. The
walk-off between the fiber-delivery and the other free-space-propagation pulse
trains, in an open loop, was measured to be <6 fs root-mean-square (RMS) over
90 minutes, corresponding to a relative optical-path variation of <2x10-7. This
walk-off can be further suppressed to ~2 fs RMS simply using an active control
loop, highlighting the great application potentials of this AR-HCF set-up in
large-scale laser and accelerator facilities
Association of Psychological Characteristics and Functional Dyspepsia Treatment Outcome: A Case-Control Study
This study was to investigate the association of psychological characteristics and functional dyspepsia treatment outcome. 109 patients who met the criteria for FD were enrolled. Eysenck Personality Questionnaire (EPQ), Symptom Checklist 90 (SCL90), and the Pittsburgh Sleep Quality Index (PSQI) were used to measure personality, psychological symptoms, and sleep quality in our patients. Leeds Dyspepsia Questionnaire (LDQ) was used to assess dyspeptic symptoms at baseline and after eight weeks of treatment. The LDQ scores change after therapy, and the degraded rate of LDQ was used to assess the prognosis of patients. Logistic regression model was used to assess the effect of the personality, psychological symptoms, and sleep quality on the prognosis of patients. Our result revealed that poor sleep quality (OR=7.68, 95% CI 1.83–32.25) and bad marriage status (OR=1.22, 95% CI 1.10–1.36) had the negative effect on the prognosis of FD, while extroversion in personality traits (OR=0.86, 95% CI 0.76–0.96) had positive effect on the prognosis of FD. We should pay attention to the sleep quality, the personality, and the marriage status of FD patients; psychological intervention may have benefit in refractory FD
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