379 research outputs found
DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences.
Modeling the properties and functions of DNA sequences is an important, but challenging task in the broad field of genomics. This task is particularly difficult for non-coding DNA, the vast majority of which is still poorly understood in terms of function. A powerful predictive model for the function of non-coding DNA can have enormous benefit for both basic science and translational research because over 98% of the human genome is non-coding and 93% of disease-associated variants lie in these regions. To address this need, we propose DanQ, a novel hybrid convolutional and bi-directional long short-term memory recurrent neural network framework for predicting non-coding function de novo from sequence. In the DanQ model, the convolution layer captures regulatory motifs, while the recurrent layer captures long-term dependencies between the motifs in order to learn a regulatory 'grammar' to improve predictions. DanQ improves considerably upon other models across several metrics. For some regulatory markers, DanQ can achieve over a 50% relative improvement in the area under the precision-recall curve metric compared to related models. We have made the source code available at the github repository http://github.com/uci-cbcl/DanQ
District-level Spatial Analysis of Migration Flows in Ghana: Determinants and Implications for Policy
The present study investigates the determinants of inter-district migration flows over the 1995-2000 period in Ghana. A combination of socio-economic, natural and spatial ‘district-level’ attributes are considered as potential variables explaining the direction of migration flows. In addition to the ‘net’ migration model, ‘in’ and ‘out’ migration models are also employed within the context of the gravity model. Results in the three models consistently show that people move out of districts with less employment and choose districts with high employment rate as destinations. While shorter distance to roads encourages out-migration, districts with better water access seem to attract migrants. Generally, people move out of predominantly agrarian districts to relatively more urbanized districts.Gross migration, Net migration, Inter-district migration flows, spatial analysis, Ghana, Africa, Community/Rural/Urban Development, Labor and Human Capital,
Solar-Powered Handheld Bioinstrumentation
This project expands on a previous MQP with the objective of developing a low-cost, handheld bioinstrumentation demonstration board while meeting significantly stricter power, size and cost constraints than the previous project. The device must operate using only power provided by a solar panel in indoor lighting conditions and be contained on a board the size of a standard business card. We designed and built a functional prototype that measures electrocardiogram (ECG) signals taken from the fingertips and displays the user\u27s heart rate on a liquid crystal display panel. Recommendations for future work include implementation of an alternative method we investigated using photoplethysmography (PPG), which we were not able to fully implement because of time and power constraints
Joint Modeling of Radial Velocities and Photometry with a Gaussian Process Framework
Developments in the stability of modern spectrographs have led to extremely
precise instrumental radial velocity (RV) measurements. For most stars, the
detection limit of planetary companions with these instruments is expected to
be dominated by astrophysical noise sources such as starspots. Correlated
signals caused by rotationally-modulated starspots can obscure or mimic the
Doppler shifts induced by even the closest, most massive planets. This is
especially true for young, magnetically active stars where stellar activity can
cause fluctuation amplitudes of 0.1 mag in brightness and 100
m s in RV semi-amplitudes. Techniques that can mitigate these effects
and increase our sensitivity to young planets are critical to improving our
understanding of the evolution of planetary systems. Gaussian processes (GPs)
have been successfully employed to model and constrain activity signals in
individual cases. However, a principled approach of this technique,
specifically for the joint modeling of photometry and RVs, has not yet been
developed. In this work, we present a GP framework to simultaneously model
stellar activity signals in photometry and RVs that can be used to investigate
the relationship between both time series. Our method, inspired by the
framework of (Aigrain et al. 2012), models spot-driven
activity signals as the linear combinations of two independent latent GPs and
their time derivatives. We also simulate time series affected by starspots by
extending the software (Luger et al. 2019) to incorporate
time evolution of stellar features. Using these synthetic datasets, we show
that our method can predict spot-driven RV variations with greater accuracy
than other GP approaches.Comment: 19 pages, 10 figure
An advanced hardware-in-the-loop battery simulation platform for the experimental testing of battery management system
Extensive testing of a battery management system (BMS) on real battery storage system (BSS) requires lots of efforts in setting up and configuring the hardware as well as protecting the system from unpredictable faults during the test. To overcome this complexity, a hardware-in-the-loop (HIL) simulation tool is employed and integrated to the BMS test system. By using this tool, it allows to push the tested system up to the operational limits, where may incur potential faults or accidents, to examine all possible test cases within the simulation environment. In this paper, an advanced HIL-based virtual battery module (VBM), consists of one “live” cell connected in series with fifteen simulated cells, is introduced for the purposes of testing the BMS components. First, the complete cell model is built and validated using real world driving cycle while the HIL-based VBM is then exercised under an Urban Dynamometer Driving Schedule (UDDS) driving cycle to ensure it is fully working and ready for the BMS testing in real-time. Finally, commissioning of the whole system is performed to guarantee the stable operation of the system for the BMS evaluation
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