55 research outputs found
Microstrip Triplexer using a common triple-mode resonator
An all-resonator based triplexer is presented using a double-stub-loaded resonator (DSLR) that acts as a common resonator at the junction of the three channels. The open stub DSLR has been analysed using even and odd-mode method to reveal the relationship between the three resonant modes. The design offers flexibility of frequency selection. The DSLR resonator is coupled with three sets of hairpin resonators to form the triplexer at 1.8, 2.1, and 2.6 GHz for mobile communication applications. The measurement results are in very good agreement with the simulations
DiffGAN-F2S: Symmetric and Efficient Denoising Diffusion GANs for Structural Connectivity Prediction from Brain fMRI
Mapping from functional connectivity (FC) to structural connectivity (SC) can
facilitate multimodal brain network fusion and discover potential biomarkers
for clinical implications. However, it is challenging to directly bridge the
reliable non-linear mapping relations between SC and functional magnetic
resonance imaging (fMRI). In this paper, a novel diffusision generative
adversarial network-based fMRI-to-SC (DiffGAN-F2S) model is proposed to predict
SC from brain fMRI in an end-to-end manner. To be specific, the proposed
DiffGAN-F2S leverages denoising diffusion probabilistic models (DDPMs) and
adversarial learning to efficiently generate high-fidelity SC through a few
steps from fMRI. By designing the dual-channel multi-head spatial attention
(DMSA) and graph convolutional modules, the symmetric graph generator first
captures global relations among direct and indirect connected brain regions,
then models the local brain region interactions. It can uncover the complex
mapping relations between fMRI and structural connectivity. Furthermore, the
spatially connected consistency loss is devised to constrain the generator to
preserve global-local topological information for accurate intrinsic SC
prediction. Testing on the public Alzheimer's Disease Neuroimaging Initiative
(ADNI) dataset, the proposed model can effectively generate empirical
SC-preserved connectivity from four-dimensional imaging data and shows superior
performance in SC prediction compared with other related models. Furthermore,
the proposed model can identify the vast majority of important brain regions
and connections derived from the empirical method, providing an alternative way
to fuse multimodal brain networks and analyze clinical disease.Comment: 12 page
Model-enhanced Vector Index
Embedding-based retrieval methods construct vector indices to search for
document representations that are most similar to the query representations.
They are widely used in document retrieval due to low latency and decent recall
performance. Recent research indicates that deep retrieval solutions offer
better model quality, but are hindered by unacceptable serving latency and the
inability to support document updates. In this paper, we aim to enhance the
vector index with end-to-end deep generative models, leveraging the
differentiable advantages of deep retrieval models while maintaining desirable
serving efficiency. We propose Model-enhanced Vector Index (MEVI), a
differentiable model-enhanced index empowered by a twin-tower representation
model. MEVI leverages a Residual Quantization (RQ) codebook to bridge the
sequence-to-sequence deep retrieval and embedding-based models. To
substantially reduce the inference time, instead of decoding the unique
document ids in long sequential steps, we first generate some semantic virtual
cluster ids of candidate documents in a small number of steps, and then
leverage the well-adapted embedding vectors to further perform a fine-grained
search for the relevant documents in the candidate virtual clusters. We
empirically show that our model achieves better performance on the commonly
used academic benchmarks MSMARCO Passage and Natural Questions, with comparable
serving latency to dense retrieval solutions
Systematic investigation of single walled nanotubes production in mesoporous catalytic templates
The main goal of the project was to optimize the synthesis conditions for mesoporous materials like MCM-41 and SBA-15 in order to achieve their emerging applications in catalysis, reaction engineering, separation. By optimizing these parameters, it was expected to attain a specific and thorough understanding of the synthesis conditions of the mesoporous materials, with the prospect of industrial application in the near future.MASTER OF ENGINEERING (SCBE
Recommended from our members
Stability analysis of the amplifier with negative impedance compensation
A novel amplifier design technique based on negative impedance compensation has been proposed in our recent paper. In this paper, we investigate the stability of this amplifier system. The parameter space approach has been used to determine system parameters in the negative impedance circuit such that the stability of the amplifier system can be guaranteed in a certain region represented by those parameters. The simulation results have demonstrated that stable circuit behavior for the amplifier can be achieve
Joint Direction of Arrival-Polarization Parameter Tracking Algorithm Based on Multi-Target Multi-Bernoulli Filter
This paper presents a tracking algorithm for joint estimation of direction of arrival (DOA) and polarization parameters, which exhibit dynamic behavior due to the movement of signal source carriers. The proposed algorithm addresses the challenge of real-time estimation in multi-target scenarios with an unknown number. This algorithm is built upon the Multi-target Multi-Bernoulli (MeMBer) filter algorithm, which makes use of a sensor array called Circular Orthogonal Double-Dipole (CODD). The algorithm begins by constructing a Minimum Description Length (MDL) principle, taking advantage of the characteristics of the polarization-sensitive array. This allows for adaptive estimation of the number of signal sources and facilitates the separation of the noise subspace. Subsequently, the joint parameter Multiple Signal Classification (MUSIC) spatial spectrum function is employed as the pseudo-likelihood function, overcoming the limitations imposed by unknown prior information constraints. To approximate the posterior distribution of MeMBer filters, Sequential Monte Carlo (SMC) method is utilized. The simulation results demonstrate that the proposed algorithm achieves excellent tracking accuracy in joint DOA-polarization parameter estimation, whether in scenarios with known or unknown numbers of signal sources. Moreover, the algorithm demonstrates robust tracking convergence even under low Signal-to-Noise Ratio (SNR) conditions
Investigation on natural resources and species conservation of Ophiocordyceps sinensis, the famous medicinal fungus endemic to the Tibetan Plateau
Pulmonary lymphangioleimyomatosis and systemic lupus erythematosus in a menopausal woman
Abstract Background Pulmonary lymphangioleimyomatosis (PLAM) is a rare disease involving lung. PLAM primarily affects young women, a characteristic it shares with systemic lupus erythematosus (SLE). Estrogen has long been assumed to play an important role both in PLAM and SLE. We report a menopausal woman, who was found to have PLAM 1 year after she was diagnosed with SLE. Her chest radiograph was normal in the early phase of SLE. Case presentation A 52-year-old Chinese woman was referred to our hospital in August 2014 because of swelling in both legs. She also reported a malar rash and intermittent generalized arthralgia. Laboratory examination showed leukopenia. Her serum albumin level was 23 g/L; 24-h urinary protein excretion was 5.3 g. She tested positive for anti-Smith (Sm) antibody and anti-SS-A antibody. Renal biopsy indicated Class V + IV(G)-A lupus nephritis (LN). The condition of SLE and LN improved on a regime of tapering prednisolone and intermittent intravenous cyclophosphamide therapy until 1 year later when she developed exertional dyspnea accompanied with frequent cough. Thoracic computed tomography revealed numerous well-defined cysts and the diagnosis of PLAM was confirmed by lung biopsy. In the follow-up period, the patient continued to be on prednisolone and mycophenolate mofetil for the treatment of SLE, but only agreed to receive symptomatic treatment for PLAM. One year after the diagnosis of PLAM, during which time the SLE was stable, she died of respiratory failure and cor pulmonale. Conclusion We report a patient with coexisting SLE and PLAM, who was treated with immunosuppressive therapy. SLE was stable but PLAM was not improved. Although the coexistence of SLE and PLAM might be a coincidence, the occurrence of these two diseases in a menopausal woman may warrant further mechanistic exploration
Study on Water-Driving Law and Remaining Oil Distribution Pattern in Ultra-low Permeability Reservoir
The water-cut rises quickly and the remaining oil distribution is complex when the ultra-low permeability reservoir enters the high water cut stage. The comprehensive use of reservoir engineering, dynamic monitoring, numerical simulation, core experiments and other methods, this paper systematically summarizes three types of water-driving law and distribution characteristics of remaining oil, which are pore-fracture flow, pore-fracture flow and fracture flow. It is considered that the horizontal water drive is mainly controlled by material source, well pattern and fracture, while the vertical water drive is mainly controlled by reservoir heterogeneity, water line distance, injection-production well distance, etc. , the patterns of residual oil formed by different types of percolation are different, in this paper, 7 macroscopic patterns of remaining oil distribution, such as well pattern control, heterogeneity control, single sand body connected control, longitudinal interference, injection-production non-correspondence and non-main reservoir unutilized, are summarized, in the light of different remaining oil patterns, the paper puts forward the adjustment direction of tapping potential, such as optimizing injection-production structure, optimizing injection-production mode
- …