Predicting the epidemic threshold of the susceptible-infected-recovered model

Researchers have developed several theoretical methods for predicting epidemic thresholds, including the mean-field like (MFL) method, the quenched mean-field (QMF) method, and the dynamical message passing (DMP) method. When these methods are applied to predict epidemic threshold they often produce differing results and their relative levels of accuracy are still unknown. We systematically analyze these two issues---relationships among differing results and levels of accuracy---by studying the susceptible-infected-recovered (SIR) model on uncorrelated configuration networks and a group of 56 real-world networks. In uncorrelated configuration networks the MFL and DMP methods yield identical predictions that are larger and more accurate than the prediction generated by the QMF method. When compared to the 56 real-world networks, the epidemic threshold obtained by the DMP method is closer to the actual epidemic threshold because it incorporates full network topology information and some dynamical correlations. We find that in some scenarios---such as networks with positive degree-degree correlations, with an eigenvector localized on the high $k$-core nodes, or with a high level of clustering---the epidemic threshold predicted by the MFL method, which uses the degree distribution as the only input parameter, performs better than the other two methods. We also find that the performances of the three predictions are irregular versus modularity

Plasmoid ejection and secondary current sheet generation from magnetic reconnection in laser-plasma interaction

Reconnection of the self-generated magnetic fields in laser-plasma interaction was first investigated experimentally by Nilson {\it et al.} [Phys. Rev. Lett. 97, 255001 (2006)] by shining two laser pulses a distance apart on a solid target layer. An elongated current sheet (CS) was observed in the plasma between the two laser spots. In order to more closely model magnetotail reconnection, here two side-by-side thin target layers, instead of a single one, are used. It is found that at one end of the elongated CS a fan-like electron outflow region including three well-collimated electron jets appears. The ($>1$ MeV) tail of the jet energy distribution exhibits a power-law scaling. The enhanced electron acceleration is attributed to the intense inductive electric field in the narrow electron dominated reconnection region, as well as additional acceleration as they are trapped inside the rapidly moving plasmoid formed in and ejected from the CS. The ejection also induces a secondary CS

Protein tyrosine kinase 6 is associated with nasopharyngeal carcinoma poor prognosis and metastasis

BACKGROUND: The aim of this study was to analyze the expression of protein tyrosine kinase 6 (PTK6) in nasopharyngeal carcinoma (NPC) samples, and to identify whether PTK6 can serve as a biomarker for the diagnosis and prognosis of NPC. METHODS: We used quantitative RT-PCR and Western blotting analysis to detect mRNA and protein expression of PTK6 in NPC cell lines and immortalized nasopharyngeal epithelial cell lines. 31 NPC and 16 non-tumorous nasopharyngeal mucosa biopsies were collected to detect the difference in the expression of mRNA level of PTK6 by quantitative RT-PCR. We also collected 178 NPC and 10 normal nasopharyngeal epithelial cases with clinical follow-up data to investigate the expression of PTK6 by immunohistochemistry staining (IHC). PTK6 overexpression on cell growth and colony formation ability were measured by the method of cell proliferation assay and colony formation assay. RESULTS: The expression of PTK6 was higher in most of NPC cell lines at both mRNA and protein levels than in immortalized nasopharyngeal epithelial cell lines (NPECs) induced by Bmi-1 (Bmi-1/NPEC1, and Bmi-1/NPEC2). The mRNA level of PTK6 was high in NPC biopsies compared to non-tumorous nasopharyngeal mucosa biopsies. IHC results showed the expression of PTK6 was significantly correlated to tumor size (P<0.001), clinical stage (P<0.001), and metastasis (P=0.016). The patients with high-expression of PTK6 had a significantly poor prognosis compared to those of low-expression (47.8% versus 80.0%, P<0.001), especially in the patients at the advanced stages (42.2% versus 79.1%, P<0.001). Multivariate analysis indicated that the level of PTK6 expression was an independent prognostic factor for the overall survival of patients with NPC (P <0.001). Overexpression of PTK6 in HNE1 cells enhanced the ability of cell proliferation and colony formation. CONCLUSIONS: Our results suggest that high-expression of PTK6 is an independent factor for NPC patients and it might serve as a potential prognostic biomarker for patients with NPC

MelHuBERT: A simplified HuBERT on Mel spectrograms

Self-supervised models have had great success in learning speech representations that can generalize to various downstream tasks. However, most self-supervised models require a large amount of compute and multiple GPUs to train, significantly hampering the development of self-supervised learning. In an attempt to reduce the computation of training, we revisit the training of HuBERT, a highly successful self-supervised model. We improve and simplify several key components, including the loss function, input representation, and training in multiple stages. Our model, MelHuBERT, is able to achieve favorable performance on phone recognition, speaker identification, and automatic speech recognition against HuBERT, while saving 31.2% of the pre-training time, or equivalently 33.5% MACs per one second speech. The code and pre-trained models are available in https://github.com/nervjack2/MelHuBERT.Comment: ASRU 202

Storage of multiple single-photon pulses emitted from a quantum dot in a solid-state quantum memory

Quantum repeaters are critical components for distributing entanglement over long distances in presence of unavoidable optical losses during transmission. Stimulated by Duan-Lukin-Cirac-Zoller protocol, many improved quantum-repeater protocols based on quantum memories have been proposed, which commonly focus on the entanglement-distribution rate. Among these protocols, the elimination of multi-photons (multi-photon-pairs) and the use of multimode quantum memory are demonstrated to have the ability to greatly improve the entanglement-distribution rate. Here, we demonstrate the storage of deterministic single photons emitted from a quantum dot in a polarization-maintaining solid-state quantum memory; in addition, multi-temporal-mode memory with $1$, $20$ and $100$ narrow single-photon pulses is also demonstrated. Multi-photons are eliminated, and only one photon at most is contained in each pulse. Moreover, the solid-state properties of both sub-systems make this configuration more stable and easier to be scalable. Our work will be helpful in the construction of efficient quantum repeaters based on all-solid-state devicesComment: Published version, including supplementary materia

Application of the indirect fluorescent antibody assay in the study of malaria infection in the Yangtze River Three Gorges Reservoir, China

<p>Abstract</p> <p>Background</p> <p>China Yangtze Three Gorges Project (TGP) is one of the biggest construction projects in the world. The areas around the Three Gorge Dam has a history of tertian malaria and subtertian malaria epidemic, but there are no overall data about malaria epidemics before the completion of the project. The objective of this study was to get a reliable baseline on malaria infection in the Yangtze River Three Gorges reservoir area and to provide reference data for future studies about the impact of the project on malaria epidemics.</p> <p>Methods</p> <p>Two surveys of malaria infection were carried out in area, at six-month intervals in May and October 2008. About 3,600 dual specimens blood film samples for parasite diagnosis and filter paper blood spots for serology (using the immunofluorescence antibody test) were collected from the general population, including school populations, whenever possible.</p> <p>Results</p> <p>The overall percentage of positive response of the same population during post-transmission periods was about twice (1.40/0.72) of that in pre-transmission. Positive individuals under 15 years of age were detected in all the localities.</p> <p>Conclusion</p> <p>A certain extent of malaria infection existed in this area. Additional studies are needed to determine the length of malaria experience, and chemotherapeutic intervention as well as the distribution of main vectors for transmission in this area.</p

INFLUENCE OF TRANSGLUTAMINASE-INDUCED CROSS-LINKING ON IN VITRO DIGESTIBILITY OF SOY PROTEIN ISOLATE

ABSTRAC

DAISY: Data Adaptive Self-Supervised Early Exit for Speech Representation Models

Self-supervised speech models have shown to be useful for various tasks, but their large size limits the use in devices with low computing power and memory. In this work, we explore early exit, an approach for reducing latency by exiting the forward process of a network early. Most approaches of early exit need a separate early exit model for each task, with some even requiring fine-tuning of the entire pretrained model. We introduce Data Adaptive Self-Supervised Early Exit (DAISY), an approach that decides when to exit based on the self-supervised loss, eliminating the need for multiple round of training and fine-tuning. DAISY matches the performance of HuBERT on the MiniSUPERB benchmark, but with much faster inference times. Our analysis on the adaptivity of DAISY shows that the model exits early (using fewer layers) on clean data while exits late (using more layers) on noisy data, dynamically adjusting the computational cost of inference based on the noise level of each sample.Accepted by Interspeech 202