179 research outputs found
Self-Powered Gesture Recognition with Ambient Light
We present a self-powered module for gesture recognition that utilizes small, low-cost photodiodes for both energy harvesting and gesture sensing. Operating in the photovoltaic mode, photodiodes harvest energy from ambient light. In the meantime, the instantaneously harvested power from individual photodiodes is monitored and exploited as a clue for sensing finger gestures in proximity. Harvested power from all photodiodes are aggregated to drive the whole gesture-recognition module including a micro-controller running the recognition algorithm. We design robust, lightweight algorithm to recognize finger gestures in the presence of ambient light fluctuations. We fabricate two prototypes to facilitate user’s interaction with smart glasses and smart watches. Results show 99.7%/98.3% overall precision/recall in recognizing five gestures on glasses and 99.2%/97.5% precision/recall in recognizing seven gestures on the watch. The system consumes 34.6 µW/74.3 µW for the glasses/watch and thus can be powered by the energy harvested from ambient light. We also test system’s robustness under various light intensities, light directions, and ambient light fluctuations. The system maintains high recognition accuracy (\u3e 96%) in all tested settings
SRIBO: An Efficient and Resilient Single-Range and Inertia Based Odometry for Flying Robots
Positioning with one inertial measurement unit and one ranging sensor is
commonly thought to be feasible only when trajectories are in certain patterns
ensuring observability. For this reason, to pursue observable patterns, it is
required either exciting the trajectory or searching key nodes in a long
interval, which is commonly highly nonlinear and may also lack resilience.
Therefore, such a positioning approach is still not widely accepted in
real-world applications. To address this issue, this work first investigates
the dissipative nature of flying robots considering aerial drag effects and
re-formulates the corresponding positioning problem, which guarantees
observability almost surely. On this basis, a dimension-reduced wriggling
estimator is proposed accordingly. This estimator slides the estimation horizon
in a stepping manner, and output matrices can be approximately evaluated based
on the historical estimation sequence. The computational complexity is then
further reduced via a dimension-reduction approach using polynomial fittings.
In this way, the states of robots can be estimated via linear programming in a
sufficiently long interval, and the degree of observability is thereby further
enhanced because an adequate redundancy of measurements is available for each
estimation. Subsequently, the estimator's convergence and numerical stability
are proven theoretically. Finally, both indoor and outdoor experiments verify
that the proposed estimator can achieve decimeter-level precision at hundreds
of hertz per second, and it is resilient to sensors' failures. Hopefully, this
study can provide a new practical approach for self-localization as well as
relative positioning of cooperative agents with low-cost and lightweight
sensors
Colloidal assembly of polydisperse particle blends during drying
In this work, we synthesize a polydisperse aqueous colloidal system composed of small and large zwitterionic particles, as well as medium sized standard acrylic particles. By assembling these dispersions into films by drying, we show using atomic force microscopy (AFM) how their top surfaces can be mostly covered by zwitterionic groups for a wide range of evaporation rates. We probe underneath the top film surface using Fourier-transform infrared (FTIR) spectroscopy – attenuated total reflection (ATR), observing that the content in zwitterionic particles of the film upper layer increases for faster evaporation rates. We show how polydisperse systems hold great potential to overcome the evaporation rate dependence of size segregation processes in drying colloidal blends, and we provide further insights into the assembly mechanisms involved. Polydisperse blends enhance the robustness of such processes for application in coatings and other soft products where evaporation rate can not be tuned.</p
PTPRO-related CD8<sup>+</sup> T-cell signatures predict prognosis and immunotherapy response in patients with breast cancer
Background: Poor immunogenicity and extensive immunosuppressive T-cell infiltration in the tumor immune microenvironment (TIME) have been identified as potential barriers to immunotherapy success in “immune-cold” breast cancers. Thus, it is crucial to identify biomarkers that can predict immunotherapy efficacy. Protein tyrosine phosphatase receptor type O (PTPRO) regulates multiple kinases and pathways and has been implied to play a regulatory role in immune cell infiltration in various cancers. Methods: ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) were performed to uncover the TIME landscape. The correlation analysis of PTPRO and immune infiltration was performed to characterize the immune features of PTPRO. Univariate and multivariate Cox analyses were applied to determine the prognostic value of various variables and construct the PTPRO-related CD8+ T-cell signatures (PTSs). The Kaplan–Meier curve and the receiver operating characteristic (ROC) curve were used to estimate the performance of PTS in assessing prognosis and immunotherapy response in multiple validation datasets. Results: High PTPRO expression was related to high infiltration levels of CD8+ T cells, as well as macrophages, activated dendritic cells (aDCs), tumor-infiltrating lymphocytes (TILs), and Th1 cells. Given the critical role of CD8+ T cells in the TIME, we focused on the impact of PTPRO expression on CD8+ T-cell infiltration. The prognostic PTS was then constructed using the TCGA training dataset. Further analysis showed that the PTS exhibited favorable prognostic performance in multiple validation datasets. Of note, the PTS could accurately predict the response to immune checkpoint inhibitors (ICIs). Conclusion: PTPRO significantly impacts CD8+ T-cell infiltration in breast cancer, suggesting a potential role of immunomodulation. PTPRO-based PTS provides a new immune cell paradigm for prognosis, which is valuable for immunotherapy decisions in cancer patients
CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations
The long runtime of high-fidelity partial differential equation (PDE) solvers
makes them unsuitable for time-critical applications. We propose to accelerate
PDE solvers using reduced-order modeling (ROM). Whereas prior ROM approaches
reduce the dimensionality of discretized vector fields, our continuous
reduced-order modeling (CROM) approach builds a smooth, low-dimensional
manifold of the continuous vector fields themselves, not their discretization.
We represent this reduced manifold using continuously differentiable neural
fields, which may train on any and all available numerical solutions of the
continuous system, even when they are obtained using diverse methods or
discretizations. We validate our approach on an extensive range of PDEs with
training data from voxel grids, meshes, and point clouds. Compared to prior
discretization-dependent ROM methods, such as linear subspace proper orthogonal
decomposition (POD) and nonlinear manifold neural-network-based autoencoders,
CROM features higher accuracy, lower memory consumption, dynamically adaptive
resolutions, and applicability to any discretization. For equal latent space
dimension, CROM exhibits 79 and 49 better accuracy, and
39 and 132 smaller memory footprint, than POD and autoencoder
methods, respectively. Experiments demonstrate 109 and 89
wall-clock speedups over unreduced models on CPUs and GPUs, respectively
Coexistence of multiuser entanglement distribution and classical light in optical fiber network with a semiconductor chip
Building communication links among multiple users in a scalable and robust
way is a key objective in achieving large-scale quantum networks. In realistic
scenario, noise from the coexisting classical light is inevitable and can
ultimately disrupt the entanglement. The previous significant fully connected
multiuser entanglement distribution experiments are conducted using dark fiber
links and there is no explicit relation between the entanglement degradations
induced by classical noise and its error rate. Here we fabricate a
semiconductor chip with a high figure-of-merit modal overlap to directly
generate broadband polarization entanglement. Our monolithic source maintains
polarization entanglement fidelity above 96% for 42 nm bandwidth with a
brightness of 1.2*10^7 Hz/mW. We perform a continuously working quantum
entanglement distribution among three users coexisting with classical light.
Under finite-key analysis, we establish secure keys and enable images
encryption as well as quantum secret sharing between users. Our work paves the
way for practical multiparty quantum communication with integrated photonic
architecture compatible with real-world fiber optical communication network
Male Patients With Dilated Cardiomyopathy Exhibiting a Higher Heart Rate Acceleration Capacity or a Lower Deceleration Capacity Are at Higher Risk of Cardiac Death
The effects of dilated cardiomyopathy (DCM) on cardiac autonomic regulation and electrophysiology, and the consequences of such changes, remain unclear. We evaluated the associations between heart rate acceleration capacity (AC) and deceleration capacity (DC), heart structural and functional changes, and cardiac death in 202 healthy controls and 100 DCM patients. The DC was lower and the AC was higher in DCM patients (both males and females). Multivariable, linear, logistic regression analyses revealed that in males, age was positively associated with AC in healthy controls (N = 85); the left atrial diameter (LAD) was positively and the left ventricular ejection fraction (LVEF) was negatively associated with AC in DCM patients (N = 65); age was negatively associated with DC in healthy controls (N = 85); and the LAD was negatively and the LVEF was positively associated with DC in DCM patients (N = 65). In females, only age was associated with either AC or DC in healthy controls (N = 117). Kaplan–Meier analysis revealed that male DCM patients with greater LADs (≥46.5 mm) (long-rank chi-squared value = 11.1, P = 0.001), an elevated AC (≥-4.75 ms) (log-rank chi-squared value = 6.8, P = 0.009), and a lower DC (≤4.72 ms) (log-rank chi-squared value = 9.1, P = 0.003) were at higher risk of cardiac death within 60 months of follow-up. In conclusion, in males, DCM significantly affected both the AC and DC; a higher AC or a lower DC increased the risk of cardiac death
Novel ceRNA network construction associated with programmed cell death in acute rejection of heart allograft in mice
BackgroundT cell-mediated acute rejection(AR) after heart transplantation(HT) ultimately results in graft failure and is a common indication for secondary transplantation. It’s a serious threat to heart transplant recipients. This study aimed to explore the novel lncRNA-miRNA-mRNA networks that contributed to AR in a mouse heart transplantation model.MethodsThe donor heart from Babl/C mice was transplanted to C57BL/6 mice with heterotopic implantation to the abdominal cavity. The control group was syngeneic heart transplantation with the same kind of mice donor. The whole-transcriptome sequencing was performed to obtain differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs) and lncRNAs (DElncRNAs) in mouse heart allograft. The biological functions of ceRNA networks was analyzed by GO and KEGG enrichment. Differentially expressed ceRNA involved in programmed cell death were further verified with qRT-PCR testing.ResultsLots of DEmRNAs, DEmiRNAs and DElncRNAs were identified in acute rejection and control after heart transplantation, including up-regulated 4754 DEmRNAs, 1634 DElncRNAs, 182 DEmiRNAs, and down-regulated 4365 DEmRNAs, 1761 DElncRNAs, 132 DEmiRNAs. Based on the ceRNA theory, lncRNA-miRNA-mRNA regulatory networks were constructed in allograft acute rejection response. The functional enrichment analysis indicate that the down-regulated mRNAs are mainly involved in cardiac muscle cell contraction, potassium channel activity, etc. and the up-regulated mRNAs are mainly involved in T cell differentiation and mononuclear cell migration, etc. The KEGG pathway enrichment analysis showed that the down-regulated DEmRNAs were mainly enriched in adrenergic signaling, axon guidance, calcium signaling pathway, etc. The up-regulated DEmRNAs were enriched in the adhesion function, chemokine signaling pathway, apoptosis, etc. Four lncRNA-mediated ceRNA regulatory pathways, Pvt1/miR-30c-5p/Pdgfc, 1700071M16Rik/miR-145a-3p/Pdgfc, 1700071M16Rik/miR-145a-3p/Tox, 1700071M16Rik/miR-145a-3p/Themis2, were finally validated. In addition, increased expression of PVT1, 1700071M16Rik, Tox and Themis2 may be considered as potential diagnostic gene biomarkers in AR.ConclusionWe speculated that Pvt1/miR-30c-5p/Pdgfc, 1700071M16Rik/miR-145a-3p/Pdgfc, 1700071M16Rik/miR-145a-3p/Tox and 1700071M16Rik/miR-145a-3p/Themis2 interaction pairs may serve as potential biomarkers in AR after HT
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