1,024 research outputs found
Breaking the challenge of signal integrity using time-domain spoof surface plasmon polaritons
In modern integrated circuits and wireless communication systems/devices,
three key features need to be solved simultaneously to reach higher performance
and more compact size: signal integrity, interference suppression, and
miniaturization. However, the above-mentioned requests are almost contradictory
using the traditional techniques. To overcome this challenge, here we propose
time-domain spoof surface plasmon polaritons (SPPs) as the carrier of signals.
By designing a special plasmonic waveguide constructed by printing two narrow
corrugated metallic strips on the top and bottom surfaces of a dielectric
substrate with mirror symmetry, we show that spoof SPPs are supported from very
low frequency to the cutoff frequency with strong subwavelength effects, which
can be converted to the time-domain SPPs. When two such plasmonic waveguides
are tightly packed with deep-subwavelength separation, which commonly happens
in the integrated circuits and wireless communications due to limited space, we
demonstrate theoretically and experimentally that SPP signals on such two
plasmonic waveguides have better propagation performance and much less mutual
coupling than the conventional signals on two traditional microstrip lines with
the same size and separation. Hence the proposed method can achieve significant
interference suppression in very compact space, providing a potential solution
to break the challenge of signal integrity
System Dynamics Based Simulation Study On Storage and Distribution Integration of Electronic Commerce Enterprise
With the strong advocacy of national policies and the rapid development of electronic commerce, offline logistics operation has become the key to efficient and fast e-commerce. This paper will use the system dynamic method to build an integrated warehousing and distribution system of e-commerce, applying the computer simulation to analyze the change of each parameter after the target inventory and delay time have changed. Suggestions will be put forward at last: building of an info-sharing mechanism, reducing the delay time via active coordination, predicting the target inventory of distribution center on time. Through these to reduce the average cost and the possibility of short supply at distribution center, and thus guarantee the delivery quality and speed, optimize buyers’ shopping experience, form a virtuous circle and enhance the overall competence of the supply chain
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NAD tagSeq reveals that NAD+-capped RNAs are mostly produced from a large number of protein-coding genes in Arabidopsis.
The 5' end of a eukaryotic mRNA transcript generally has a 7-methylguanosine (m7G) cap that protects mRNA from degradation and mediates almost all other aspects of gene expression. Some RNAs in Escherichia coli, yeast, and mammals were recently found to contain an NAD+ cap. Here, we report the development of the method NAD tagSeq for transcriptome-wide identification and quantification of NAD+-capped RNAs (NAD-RNAs). The method uses an enzymatic reaction and then a click chemistry reaction to label NAD-RNAs with a synthetic RNA tag. The tagged RNA molecules can be enriched and directly sequenced using the Oxford Nanopore sequencing technology. NAD tagSeq can allow more accurate identification and quantification of NAD-RNAs, as well as reveal the sequences of whole NAD-RNA transcripts using single-molecule RNA sequencing. Using NAD tagSeq, we found that NAD-RNAs in Arabidopsis were produced by at least several thousand genes, most of which are protein-coding genes, with the majority of these transcripts coming from <200 genes. For some Arabidopsis genes, over 5% of their transcripts were NAD capped. Gene ontology terms overrepresented in the 2,000 genes that produced the highest numbers of NAD-RNAs are related to photosynthesis, protein synthesis, and responses to cytokinin and stresses. The NAD-RNAs in Arabidopsis generally have the same overall sequence structures as the canonical m7G-capped mRNAs, although most of them appear to have a shorter 5' untranslated region (5' UTR). The identification and quantification of NAD-RNAs and revelation of their sequence features can provide essential steps toward understanding the functions of NAD-RNAs
Travel Demand Forecasting: A Fair AI Approach
Artificial Intelligence (AI) and machine learning have been increasingly
adopted for travel demand forecasting. The AI-based travel demand forecasting
models, though generate accurate predictions, may produce prediction biases and
raise fairness issues. Using such biased models for decision-making may lead to
transportation policies that exacerbate social inequalities. However, limited
studies have been focused on addressing the fairness issues of these models.
Therefore, in this study, we propose a novel methodology to develop
fairness-aware, highly-accurate travel demand forecasting models. Particularly,
the proposed methodology can enhance the fairness of AI models for multiple
protected attributes (such as race and income) simultaneously. Specifically, we
introduce a new fairness regularization term, which is explicitly designed to
measure the correlation between prediction accuracy and multiple protected
attributes, into the loss function of the travel demand forecasting model. We
conduct two case studies to evaluate the performance of the proposed
methodology using real-world ridesourcing-trip data in Chicago, IL and Austin,
TX, respectively. Results highlight that our proposed methodology can
effectively enhance fairness for multiple protected attributes while preserving
prediction accuracy. Additionally, we have compared our methodology with three
state-of-the-art methods that adopt the regularization term approach, and the
results demonstrate that our approach significantly outperforms them in both
preserving prediction accuracy and enhancing fairness. This study can provide
transportation professionals with a new tool to achieve fair and accurate
travel demand forecasting.Comment: improved the methodology; updated new content
Effects of Gene Methylation Reprogramming in Cloned Calves Derived from In Vitro-Transfected Somatic Cells
AbstractIn vitro transfection of cultured cells combined with nuclear transfer currently is the most effective procedure to produce transgenic livestock. In the present study, bovine primary fetal fibroblasts were transfected with a green fluorescent protein (GFP) reporter transgene and used as nuclear donor cells in oocyte reconstructions. To examine the role of host cytoplasm on transgene expression and developmental outcome, GFP-expressing fibroblasts were fused to oocytes reconstructed either metaphase or telophase activation, and PCR technology was also employed. The results showed that GFP became detectable at the 8- to 16-cell stage, approximately 80h after reconstruction, and remained positive at all later stages. Embryonic development to the blastocyst stage was not significantly different among metaphase and telophase groups. Therefore, GFP transgene technology can be used to select embryoes derived from transgenic animals
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