102,993 research outputs found
Resonant Tunneling through double-bended Graphene Nanoribbons
We investigate theoretically resonant tunneling through double-bended
graphene nanoribbon structures, i.e., armchair-edged graphene nanoribbons
(AGNRs) in between two semi-infinite zigzag graphene nanoribbon (ZGNR) leads.
Our numerical results demonstrate that the resonant tunneling can be tuned
dramatically by the Fermi energy and the length and/or widths of the AGNR for
both the metallic and semiconductor-like AGNRs. The structure can also be use
to control the valley polarization of the tunneling currents and could be
useful for potential application in valleytronics devices.Comment: 4 pages, 4 figure
Using probe electrospray ionization mass spectrometry and machine learning for detecting pancreatic cancer with high performance
A rapid blood-based diagnostic modality to detect pancreatic ductal adenocarcinoma (PDAC) with high accuracy is an unmet medical need. The study aimed to validate a unique diagnosis system using Probe Electrospray Ionization Mass Spectrometry (PESI-MS) and Machine Learning to the diagnosis of PDAC. Peripheral blood samples were collected from a total of 322 consecutive PDAC patients and 265 controls with a family history of PDAC. Five µl of serum samples were analyzed using PESI-MS system. The mass spectra from each specimen were then fed into machine learning algorithms to discriminate between control and cancer cases. A total of 587 serum samples were analyzed. The sensitivity of the machine learning algorithm using PESI-MS profiles to identify PDAC is 90.8% with specificity of 91.7% (95% CI 83.9%-97.4% and 82.8%-97.7% respectively). Combined PESI-MS profiles with age and CA19-9 as predictors, the accuracy for stage 1 or 2 of PDAC is 92.9% and for stage 3 or 4 is 93% (95% CI 86.3-98.2; 87.9-97.4 respectively). The accuracy and simplicity of the PESI-MS profiles combined with machine learning provide an opportunity to detect PDAC at an early stage and must be applicable to the examination of at-risk populations. [Abstract copyright: AJTR Copyright © 2020.
Quantum pumping in graphene nanoribbons at resonant transmission
Adiabatic quantum charge pumping in graphene nanoribbon double barrier
structures with armchair and zigzag edges in the resonant transmission regime
is analyzed. Using recursive Green's function method we numerically calculate
the pumped charge for pumping contours encircling a resonance. We find that for
armchair ribbons the whole resonance line contributes to the pumping of a
single electron (ignoring double spin degeneracy) per cycle through the device.
The case of zigzag ribbons is more interesting due to zero-conductance
resonances. These resonances separate the whole resonance line into several
parts, each of which corresponds to the pumping of a single electron through
the device. Moreover, in contrast to armchair ribbons, one electron can be
pumped from the left lead to the right one or backwards. The current direction
depends on the particular part of the resonance line encircled by the pumping
contour.Comment: 6 pages, 5 figures. This is an author-created, un-copyedited version
of an article accepted for publication in EPL. IOP Publishing Ltd is not
responsible for any errors or omissions in this version of the manuscript or
any version derived from it. The definitive publisher authenticated version
is available online at 10.1209/0295-5075/92/4701
The Determinants of Foreign-Direct-Investment (FDI) Inflows in Nigeria
Due to the importance of foreign direct investment (FDI), scholars are always keen to explore FDI determinants and analyze their implications. Nevertheless scholars have proposed mixed viewpoints of FDI and interpreted its determinants differently, which do not contribute to the knowledge advancement and amalgamation of FDI literatures. The current research, therefore, aims to advance the knowledge of FDI determinants in Nigeria through a new investigation on the key determinant factors affecting Nigeria’s inward FDI. Data were collected from UNCTAD (1970-2014) and analyzed by auto-regressive distributed lag tests (ARDL). A comprehensive theory-based model was developed accounting for many variables, such as the interest rate, external debt, oil rents, the Gross Domestic Product (GDP) growth rate, trade and exchange rate volatility. The analysis of FDI determinants in the Nigerian economy yielded reliable, robust, and economically meaningful results thereby offering an insight into the driving factors of inward FDI. Findings indicate that the interest rate, external debt, oil rents, and GDP growth are all important determinants, possessing a long-run effect on FDI. Different from the literature, however, trade and exchange rate volatility are barely important to FDI. Several policy implications flow from the findings. From a policy point of view, regarding the GDP growth rate, there should be concerted efforts to boost the performance of the non-oil sector in Nigeria through more investments in the agricultural and industrial sectors making the growth of the economy spread across other sectors and, in turn, encouraging inward FDI in such areas. Countries such as Nigeria, endowed with natural resources, should pursue policies targeted at full deregulation (privatisation) of their natural resource sector to better utilize the abundance of their natural resources thereby attracting additional FDI. Nigeria should also pursue better debt management practices. When debts are acquired, they should be targeted towards future consumption and longer-term investments. Most importantly, as an import-dependent economy, the Nigerian government should also formulate export-driven and appropriate fiscal policies that will stabilize Nigeria’s trade relationship with other world economies. The Nigerian government should create the necessary environment that will regulate macroeconomic and specifically monetary policy (interest rate) which is essential for the attraction of FDI inflows into the economy. Finally, Nigeria should ensure that the quality of exportable commodities is improved to enhance international competitiveness
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