2,802 research outputs found
Convolutional Recurrent Neural Network for Dynamic Functional MRI Analysis and Brain Disease Identification
Dynamic functional connectivity (dFC) networks derived from resting-state functional magnetic resonance imaging (rs-fMRI) help us understand fundamental dynamic characteristics of human brains, thereby providing an efficient solution for automated identification of brain diseases, such as Alzheimer's disease (AD) and its prodromal stage. Existing studies have applied deep learning methods to dFC network analysis and achieved good performance compared with traditional machine learning methods. However, they seldom take advantage of sequential information conveyed in dFC networks that could be informative to improve the diagnosis performance. In this paper, we propose a convolutional recurrent neural network (CRNN) for automated brain disease classification with rs-fMRI data. Specifically, we first construct dFC networks from rs-fMRI data using a sliding window strategy. Then, we employ three convolutional layers and long short-term memory (LSTM) layer to extract high-level features of dFC networks and also preserve the sequential information of extracted features, followed by three fully connected layers for brain disease classification. Experimental results on 174 subjects with 563 rs-fMRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) demonstrate the effectiveness of our proposed method in binary and multi-category classification tasks
Distributions and Physical Properties of Molecular Clouds in the Third Galactic Quadrant: = [219.75, 229.75] and = [-5.25, 5.25]
We present the results of an unbiased CO/CO/CO ( =
1-0) survey in a portion of the third Galactic quadrant (TGQ): = [219.75,
229.75] and = [-5.25, 5.25]. The high-resolution and
high-sensitivity data sets help to unravel the distributions and physical
properties of the molecular clouds (MCs) in the mapped area. In the LSR
velocity range from -1 to 85 km/s, the molecular material successfully traces
the Local, Perseus, and Outer arms. In the TGQ, the Outer arm appears to be
more prominent than that in the second Galactic quadrant (SGQ), but the Perseus
arm is not as conspicuous as that in the SGQ. A total of 1,502 CO, 570
CO, and 53 CO molecular structures are identified, spanning over
and orders of magnitude in size and mass, respectively. Tight
mass-radius correlations and virial parameter-mass anticorrelations are
observable. Yet, it seems that no clear correlations between velocity
dispersion and effective radius can be found over the full dynamic range. The
vertical distribution of the MCs renders evident pictures of the Galactic warp
and flare.Comment: 22 pages, 13 figures, 7 tables (with machine-readable versions),
published in ApJ
Influence of Ethnicity on the Accuracy of Non-Invasive Scores Predicting Non-Alcoholic Fatty Liver Disease
Objectives Presence of non-alcoholic fatty liver disease (NAFLD) can predict risks for diabetes, cardiovascular disease and advanced liver disease in the general population. We aimed to establish a non-invasive score for prediction of NAFLD in Han Chinese, the largest ethnic group in the world, and detect whether ethnicity influences the accuracy of such a score. Methods Liver fat content (LFAT) was measured by quantitative ultrasound in 3548 subjects in the Shanghai Changfeng Community and a Chinese score was created using multivariate logistic regression analyses. This new score was internally validated in Chinese and externally in Finns. Its diagnostic performance was compared to the NAFLD liver fat score, fatty liver index (FLI) and hepatic steatosis index (HSI) developed in Finns, Italians and Koreans. We also analyzed how obesity related to LFAT measured by H-1-MRS in 79 Finns and 118 Chinese with type 2 diabetes (T2D). Results The metabolic syndrome and T2D, fasting serum insulin, body mass index (BMI) and AST/ALT ratio were independent predictors of NAFLD in Chinese. The AUROC in the Chinese validation cohort was 0.76 (0.73-0.78) and in Finns 0.73 (0.68-0.78) (p Conclusion The predictors of NAFLD in Han Chinese are as in Europids but the Chinese have more LFAT for any given degree of obesity than Europids. Ethnicity needs to be considered when NAFLD is predicted using risk scores.Peer reviewe
A simulation study on the measurement of D0-D0bar mixing parameter y at BES-III
We established a method on measuring the \dzdzb mixing parameter for
BESIII experiment at the BEPCII collider. In this method, the doubly
tagged events, with one decays to
CP-eigenstates and the other decays semileptonically, are used to
reconstruct the signals. Since this analysis requires good separation,
a likelihood approach, which combines the , time of flight and the
electromagnetic shower detectors information, is used for particle
identification. We estimate the sensitivity of the measurement of to be
0.007 based on a fully simulated MC sample.Comment: 6 pages, 7 figure
Evasion of anti-growth signaling: a key step in tumorigenesis and potential target for treatment and prophylaxis by natural compounds
The evasion of anti-growth signaling is an important characteristic of cancer cells. In order to continue to proliferate, cancer cells must somehow uncouple themselves from the many signals that exist to slow down cell growth. Here, we define the anti-growth signaling process, and review several important pathways involved in growth signaling: p53, phosphatase and tensin homolog (PTEN), retinoblastoma protein (Rb), Hippo, growth differentiation factor 15 (GDF15), AT-rich interactive domain 1A (ARID1A), Notch, insulin-like growth factor (IGF), and Krüppel-like factor 5 (KLF5) pathways. Aberrations in these processes in cancer cells involve mutations and thus the suppression of genes that prevent growth, as well as mutation and activation of genes involved in driving cell growth. Using these pathways as examples, we prioritize molecular targets that might be leveraged to promote anti-growth signaling in cancer cells. Interestingly, naturally-occurring phytochemicals found in human diets (either singly or as mixtures) may promote anti-growth signaling, and do so without the potentially adverse effects associated with synthetic chemicals. We review examples of naturally-occurring phytochemicals that may be applied to prevent cancer by antagonizing growth signaling, and propose one phytochemical for each pathway. These are: epigallocatechin-3-gallate (EGCG) for the Rb pathway, luteolin for p53, curcumin for PTEN, porphyrins for Hippo, genistein for GDF15, resveratrol for ARID1A, withaferin A for Notch and diguelin for the IGF1-receptor pathway. The coordination of anti-growth signaling and natural compound studies will provide insight into the future application of these compounds in the clinical setting
Baichuan 2: Open Large-scale Language Models
Large language models (LLMs) have demonstrated remarkable performance on a
variety of natural language tasks based on just a few examples of natural
language instructions, reducing the need for extensive feature engineering.
However, most powerful LLMs are closed-source or limited in their capability
for languages other than English. In this technical report, we present Baichuan
2, a series of large-scale multilingual language models containing 7 billion
and 13 billion parameters, trained from scratch, on 2.6 trillion tokens.
Baichuan 2 matches or outperforms other open-source models of similar size on
public benchmarks like MMLU, CMMLU, GSM8K, and HumanEval. Furthermore, Baichuan
2 excels in vertical domains such as medicine and law. We will release all
pre-training model checkpoints to benefit the research community in better
understanding the training dynamics of Baichuan 2.Comment: Baichuan 2 technical report. Github:
https://github.com/baichuan-inc/Baichuan
Epidemiology of Schistosomiasis in the People’s Republic of China, 2004
Although the number of human infections decreased, human prevalence increased from 4.9% in 1995 to 5.1% in 2004
Measurement of azimuthal asymmetries in inclusive charged dipion production in annihilations at = 3.65 GeV
We present a measurement of the azimuthal asymmetries of two charged pions in
the inclusive process based on a data set of 62
at the center-of-mass energy GeV collected with
the BESIII detector. These asymmetries can be attributed to the Collins
fragmentation function. We observe a nonzero asymmetry, which increases with
increasing pion momentum. As our energy scale is close to that of the existing
semi-inclusive deep inelastic scattering experimental data, the measured
asymmetries are important inputs for the global analysis of extracting the
quark transversity distribution inside the nucleon and are valuable to explore
the energy evolution of the spin-dependent fragmentation function.Comment: 7 pages, 5 figure
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