Critical Neurons: optimized visual recognition in a neuronal network

In the past few decades, there have been intense debates whether the brain operates at a critical state. To verify the criticality hypothesis in the neuronal networks is challenging and the accumulating experimental and theoretical results remain controversial at this point. Here we simulate how visual information of a nature image is processed by the finite Kinouchi-Copelli neuronal network, extracting the trends of the mutual information (how sensible the neuronal network is), the dynamical range (how sensitive the network responds to external stimuli) and the statistical fluctuations (how criticality is defined in conventional statistical physics). It is rather remarkable that the optimized state for visual recognition, although close to, does not coincide with the critical state where the statistical fluctuations reach the maximum. Different images and/or network sizes of course lead to differences in details but the trend of the information optimization remains the same. Our findings pave the first step to investigate how the information processing is optimized in different neuronal networks and suggest that the criticality hypothesis may not be necessary to explain why a neuronal network can process information smartly.Comment: 11 pages, 4 figures in the main text and 3 figures in the Supplementary Informatio

Compact Dual-Band Dipole Antenna with Asymmetric Arms for WLAN Applications

A dual-band dipole antenna that consists of a horn- and a C-shaped metallic arm is presented. Depending on the asymmetric arms, the antenna provides two −10 dB impedance bandwidths of 225 MHz (about 9.2% at 2.45 GHz) and 1190 MHz (about 21.6% at 5.5 GHz), respectively. This feature enables it to cover the required bandwidths for wireless local area network (WLAN) operation at the 2.4 GHz band and 5.2/5.8 GHz bands for IEEE 802.11 a/b/g standards. More importantly, the compact size (7 mm × 24 mm) and good radiating performance of the antenna are profitable to be integrated with wireless communication devices on restricted RF-elements spaces

Data preprocessing for artificial neural network applications in prioritizing railroad projects â a practical experience in Taiwan

[[abstract]]Financial constraints necessitate the tradeoff among proposed railroad projects, so that the project priorities for implementation and budget allocation need to be determined by the ranking mechanisms in the government. At present, the Taiwan central government prioritizes funding allocations primarily using the analytic hierarchy process (AHP), a methodology that permits the synthesizing of subjective judgments systematically and logically into objective consensus. However, due to the coopetition and heterogeneity of railway projects, the proper priorities of railroad projects could not be always evaluated by the AHP. The decision makers prefer subjective judgments to referring to the AHP evaluation re- sults. This circumstance not only decreased the AHP advantages, but also raised the risk of the policies. A method to con- sider both objective measures and subjective judgments of project attributes can help reduce this problem. Accordingly, combining the AHP with the artificial neural network (ANN) methodologies would theoretically be a proper solution to bring a ranking predication model by creating the obscure relations between objective measures by the AHP and subjec- tive judgments. However, the inconsistency between the AHP evaluation and subjective judgments resulted in the inferior soundness of the AHP/ANN ranking forecast model. To overcome this problem, this study proposes the data prepro- cessing method (DPM) to calculate the correlation coefficient value using the subjective and objective ranking incidence matrixes; according to the correlation coefficient value, the consistency between the AHP rankings and subjective judg- ments of railroad projects can be evaluated and improved, so that the forecast accuracy of the AHP/ANN ranking forecast model can also be enhanced. Based on this concept, a practical railroad project ranking experience derived from the Insti- tute of Transportation of Taiwan is illustrated in this paper to reveal the feasibility of applying the DPM to the AHP/ANN ranking prediction model.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]SCI[[ispeerreviewed]]Y[[booktype]]電子版[[countrycodes]]LT

The Impact of Product innovation on Performance: The Influence of Uncertainty and Managerial Accounting Information Systems

This paper reports on a survey of Taiwanese high-tech firms, using a path analysis to examine the effects of managerial accounting information systems (MAIS) on the relationship between product innovation and organizational performance. Two of the major characteristics suggested by Chenhall and Morris (1986), broad scope and timeliness, are systematically related to the subject matter of this study, thus, employing these two characteristics to explore the connection between MAIS, product innovation and organizational performance. We find that product innovation has a positive effect on organizational performance through the use of MAIS, and find the extent of this positive effect is more significant in business environments marked by high levels of uncertainty. This study provides evidence to understand whether product innovation requires more extensive use of MAIS in highly uncertain environments and whether the use of MAIS can improve organizational performance. The results also help practicing managers realize the importance of MAIS in modern organizations and the benefits of using MAIS to the organization. Finally, we remind managers engaging in product innovation practices that they should place importance on the use of MAIS, because traditional cost control systems no longer help in solving the problems that are specific to the current, modern business environment

Terminal proteins of Streptomyces chromosome can target DNA into eukaryotic nuclei

Streptomyces species are highly abundant soil bacteria that possess linear chromosomes (and linear plasmids). The 5′ ends of these molecules are covalently bound by terminal proteins (TPs), that are important for integrity and replication of the telomeres. There are at least two types of TPs, both of which contain a DNA-binding domain and a classical eukaryotic nuclear localization signal (NLS). Here we show that the NLS motifs on these TPs are highly efficient in targeting the proteins along with covalently bound plasmid DNA into the nuclei of human cells. The TP-mediated nuclear targeting resembles the inter-kingdom gene transfer mediated by Ti plasmids of Agrobacterium tumefaciens, in which a piece of the Ti plasmid DNA is targeted to the plant nuclei by a covalently bound NLS-containing protein. The discovery of the nuclear localization functions of the Streptomyces TPs not only suggests possible inter-kingdom gene exchanges between Streptomyces and eukaryotes in soil but also provides a novel strategy for gene delivery in humans and other eukaryotes

Maintaining the structural integrity of thebamboo mosaic virus 3′ untranslated region isnecessary for retaining the catalytic constant forminus-strand RNA synthesis

Background: Bamboo mosaic virus (BaMV) and the Potato virus X (PVX) are members of the genus Potexvirus andhave a single-stranded positive-sense RNA genome. The 3′-untranslated region (UTR) of the BaMV RNA genomewas mapped structurally into ABC (a cloverleaf-like), D (a stem-loop), and E (pseudoknot) domains. The BaMVreplicase complex that was isolated from the infected plants was able to recognize the 3′ UTR of PVX RNA toinitiate minus-strand RNA synthesis in vitro.Results: To investigate whether the 3′ UTR of PVX RNA is also compatible with BaMV replicase in vivo, weconstructed chimera mutants using a BaMV backbone containing the PVX 3′ UTR, which was inserted in or used toreplace the various domains in the 3′ UTR of BaMV. None of the mutants, except for the mutant with the PVX3′ UTR inserted upstream of the BaMV 3′ UTR, exhibited a detectable accumulation of viral RNA in Nicotianabenthamiana plants. The in vitro BaMV RdRp replication assay demonstrated that the RNA products were generatedby the short RNA transcripts, which were derived from the chimera mutants to various extents. Furthermore, theVmax/KM of the BaMV 3′ UTR (rABCDE) was approximately three fold higher than rABCP, rP, and rDE in minus-strandRNA synthesis. These mutants failed to accumulate viral products in protoplasts and plants, but were adequatelyreplicated in vitro.Conclusions: Among the various studied BaMV/PVX chimera mutants, the BaMV-S/PABCDE that containednon-interrupted BaMV 3′ UTR was the only mutant that exhibited a wild-type level of viral product accumulation inprotoplasts and plants. These results indicate that the continuity of the domains in the 3′ UTR of BaMV RNA wasnot interrupted and the domains were not replaced with the 3′ UTR of PVX RNA in vivo

Genome-Wide Gene-Environment Interaction Analysis Using Set-Based Association Tests

The identification of gene-environment interactions (G × E) may eventually guide health-related choices and medical interventions for complex diseases. More powerful methods must be developed to identify G × E. The “adaptive combination of Bayes factors method” (ADABF) has been proposed as a powerful genome-wide polygenic approach to detect G × E. In this work, we evaluate its performance when serving as a gene-based G × E test. We compare ADABF with six tests including the “Set-Based gene-EnviRonment InterAction test” (SBERIA), “gene-environment set association test” (GESAT), etc. With extensive simulations, SBERIA and ADABF are found to be more powerful than other G × E tests. However, SBERIA suffers from a power loss when 50% SNP main effects are in the same direction with the SNP × E interaction effects while 50% are in the opposite direction. We further applied these seven G × E methods to the Taiwan Biobank data to explore gene× alcohol interactions on blood pressure levels. The ADAMTS7P1 gene at chromosome 15q25.2 was detected to interact with alcohol consumption on diastolic blood pressure (p = 9.5 × 10−7, according to the GESAT test). At this gene, the P-values provided by other six tests all reached the suggestive significance level (p < 5 × 10−5). Regarding the computation time required for a genome-wide G × E analysis, SBERIA is the fastest method, followed by ADABF. Considering the validity, power performance, robustness, and computation time, ADABF is recommended for genome-wide G × E analyses