202 research outputs found
Biological Factor Regulatory Neural Network
Genes are fundamental for analyzing biological systems and many recent works
proposed to utilize gene expression for various biological tasks by deep
learning models. Despite their promising performance, it is hard for deep
neural networks to provide biological insights for humans due to their
black-box nature. Recently, some works integrated biological knowledge with
neural networks to improve the transparency and performance of their models.
However, these methods can only incorporate partial biological knowledge,
leading to suboptimal performance. In this paper, we propose the Biological
Factor Regulatory Neural Network (BFReg-NN), a generic framework to model
relations among biological factors in cell systems. BFReg-NN starts from gene
expression data and is capable of merging most existing biological knowledge
into the model, including the regulatory relations among genes or proteins
(e.g., gene regulatory networks (GRN), protein-protein interaction networks
(PPI)) and the hierarchical relations among genes, proteins and pathways (e.g.,
several genes/proteins are contained in a pathway). Moreover, BFReg-NN also has
the ability to provide new biologically meaningful insights because of its
white-box characteristics. Experimental results on different gene
expression-based tasks verify the superiority of BFReg-NN compared with
baselines. Our case studies also show that the key insights found by BFReg-NN
are consistent with the biological literature
Top-Down Structure and Device Fabrication using \u3ci\u3eIn Situ\u3c/i\u3e Nanomachining
We demonstrate the potential of an alternative tool for the fabrication of nanoscale structures and devices. A nanoindenter integrated with an atomic force microscope is shown to be a powerful machine tool for cutting precise length nanowires or nanobelts and for manipulating the shortened wires. We also demonstrate its utility in cutting grooves and fabricating dents (or periodic arrays of dents) in ZnSnanobelts. This approach permits the direct mechanical machining of nanodevices that are supported on a substrate without the inherent complications of e beam or photolithography
Effect of Tensile Offset Angles on Micro/Nanoscale Tensile Testing
For one-dimensional (1D) structures such as tubes, wires, and beams, tensile testing is a simple and reliable methodology for measuring their mechanical properties. The tensile offset angle effect on mechanical property measurement has long been ignored. In this study, theoretical and finite-element analysis(FEA) models for analyzing the tensile offset angle effect have been established. It is found that longitudinal stress decreases with increasing offset angles. The theoretically calculated elastic modulus relative errors reach 4.45% at the offset angle of 10°, whereas the experimentally measured elastic modulus relative errors are 45.4% at the offset angle of 15°. The difference in elastic modulus relative errors between the theoreticalanalysis and the experimental results is discussed with reference to the sensing system in the experimental instrumentation. To accurately measure the mechanical properties using the tensile testing technique, perfect alignment with a zero or small offset angle less than 5° is needed. A calibration methodology for aligning specimens has been developed
Learn from Yesterday: A Semi-Supervised Continual Learning Method for Supervision-Limited Text-to-SQL Task Streams
Conventional text-to-SQL studies are limited to a single task with a
fixed-size training and test set. When confronted with a stream of tasks common
in real-world applications, existing methods struggle with the problems of
insufficient supervised data and high retraining costs. The former tends to
cause overfitting on unseen databases for the new task, while the latter makes
a full review of instances from past tasks impractical for the model, resulting
in forgetting of learned SQL structures and database schemas. To address the
problems, this paper proposes integrating semi-supervised learning (SSL) and
continual learning (CL) in a stream of text-to-SQL tasks and offers two
promising solutions in turn. The first solution Vanilla is to perform
self-training, augmenting the supervised training data with predicted
pseudo-labeled instances of the current task, while replacing the full volume
retraining with episodic memory replay to balance the training efficiency with
the performance of previous tasks. The improved solution SFNet takes advantage
of the intrinsic connection between CL and SSL. It uses in-memory past
information to help current SSL, while adding high-quality pseudo instances in
memory to improve future replay. The experiments on two datasets shows that
SFNet outperforms the widely-used SSL-only and CL-only baselines on multiple
metrics.Comment: Accepted by AAAI-202
Tobacco Mosaic Virus Templated Synthesis of One Dimensional Inorganic–Polymer Hybrid Fibres
Inorganic–polymer hybrid nanofibres were prepared by using a rod-like tobacco mosaic virus (TMV) as a template. With tetraethylorthosilicate (TEOS) as a precursor, long silica-coated TMVfibres were formed via a head-to-tail assembly, which showed a substantial increase of the elastic modulus. Furthermore, homogenous titania–TMV hybrid fibres could be prepared using polyaniline-coated TMV fibres as a template, which were used to form a composite film that was able to sense liquefied petroleum gases
Tobacco Mosaic Virus Templated Synthesis of One Dimensional Inorganic-Polymer Hybrid Fibres
Inorganic–polymer hybrid nanofibres were prepared by using a rod-like tobacco mosaic virus (TMV) as a template. With tetraethylorthosilicate (TEOS) as a precursor, long silica-coated TMVfibres were formed via a head-to-tail assembly, which showed a substantial increase of the elastic modulus. Furthermore, homogenous titania–TMV hybrid fibres could be prepared using polyaniline-coated TMV fibres as a template, which were used to form a composite film that was able to sense liquefied petroleum gases
On-line detection of spherical sensor for inrush current detection
With the exploration and demand for the field of marine, underwater vehicles are used in deep water widely, however, there is a lack of research about underwater vehicles which are applied in shallow wary water. When underwater vehicles working in shallow wary water, they will be affected by the inrush current effect of shallow waters, so the research of underwater vehicles about anti current control becomes a meaningful item. But due to the high cost of underwater work, simulation and analysis to the inrush current online detection mechanism first, to determine the effects of surge phenomenon of underwater vehicles. Electromotor drives propeller to generate the flow, the detection mechanism is subjected to the impact of all directions. For some mechanical analysis of the inrush current online detection mechanism and analyzing the influence on the water inrush current when it moved in this paper, so we can reduce the effects of water inrush current on underwater vehicles in the subsequent experiments
The Relationship between Chinese High School Students' Test Anxiety and Academic Performance during the National College Entrance Examination
Under China's exam-oriented educational system, high school students are under high pressure, especially before they undertake the National College Entrance Examination. In China, the National College Entrance Examination is also given the meaning of the top priority in the life of most parents. This study focuses on the influence of Chinese high school students' test anxiety on their National College Entrance Examination results. The results show that the more anxious the examinees are, the less satisfactory their scores are. On the contrary, the less anxious they are, the better their scores are. Exam anxiety is negatively related to the scores of the National College Entrance Examination. This study has important research value for the field of high school education and psychological distress in China. It fills the gap in the research on the impact of college entrance examination anxiety on the scores of senior high school students, provides a reference for the follow-up research on the mechanism of intervention in high school students' anxiety, and also makes the society and school parents pay attention to the problem of high school students' exam anxiety
Field Scanner Design for MUSTANG of the Green Bank Telescope
MUSTANG is a bolometer camera for the Green Bank Telescope (GBT) working at a
frequency of 90 GHz. The detector has a field of view of 40 arcseconds. To
cancel out random emission change from atmosphere and other sources, requires a
fast scanning reflecting system with a few arcminute ranges. In this paper, the
aberrations of an off-axis system are reviewed. The condition for an optimized
system is provided. In an optimized system, as additional image transfer
mirrors are introduced, new aberrations of the off-axis system may be
reintroduced, resulting in a limited field of view. In this paper, different
scanning mirror arrangements for the GBT system are analyzed through the ray
tracing analysis. These include using the subreflector as the scanning mirror,
chopping a flat mirror and transferring image with an ellipse mirror, and
chopping a flat mirror and transferring image with a pair of face-to-face
paraboloid mirrors. The system analysis shows that chopping a flat mirror and
using a well aligned pair of paraboloids can generate the required field of
view for the MUSTUNG detector system, while other systems all suffer from
larger off-axis aberrations added by the system modification. The spot diagrams
of the well aligned pair of paraboloids produced is only about one Airy disk
size within a scanning angle of about 3 arcmin.Comment: 7 pages, 9 figure
Urinary biomarkers associated with podocyte injury in lupus nephritis
The most prevalent and devastating form of organ damage in systemic lupus erythematosus (SLE) is lupus nephritis (LN). LN is characterized by glomerular injury, inflammation, cell proliferation, and necrosis, leading to podocyte injury and tubular epithelial cell damage. Assays for urine biomarkers have demonstrated significant promise in the early detection of LN, evaluation of disease activity, and tracking of reaction to therapy. This is because they are non-invasive, allow for frequent monitoring and easy self-collection, transport and storage. Podocyte injury is believed to be a essential factor in LN. The extent and type of podocyte injury could be connected to the severity of proteinuria, making podocyte-derived cellular debris and injury-related urinary proteins potential markers for the diagnosis and monitoring of LN. This article focuses on studies examining urinary biomarkers associated with podocyte injury in LN, offering fresh perspectives on the application of biomarkers in the early detection and management of LN
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