Lowest common ancestor interconnection networks

Lowest Common Ancestor (LCA) networks are built using switches capable of connecting u + d inputs/outputs in a permutation pattern. For n source nodes and I stages of switches, n/d switches are used in stage l - n/d - u/d in stage l - 2, and in general , n-u^l-i-l/d^l-i switches in stage i. The resulting hierarchical structure possesses interesting connectivity and permutational properties. A full characterization of LCA networks is presented together with a permutation routing algorithm for a family of LCA networks. The algorithm uses the network itself to collect and disseminate information about the permutation. A schedule of O(dp log_d/u n) passes is obtained with a switch set-up cost factor of O(log_d/u n) (p is the minimum number of passes that an algorithm with global knowledge schedules)

The Different Attribute of Online Store- An Industrial Perspective

Online stores are dramatically increasing and becoming popular, in a way that enterprisers invest tremendous resource and effort to meet customer requirements. However, the failure rate resulting from improper operation has been increasing year by year. By investigating the main cause, the operators cannot grasp the online store websites’ industry type and attribute category. Therefore, they fail to effectively use resource, show website image of the stores and information quality, to further meet customers’ demand and obtain the expected operational efficiency. Therefore, this research (1) grasps the website attribute of online stores by reviewing the literature; (2) sets up “online store website attributes structure” through qualitative method, serving as a basis for enterprisers to improve the operation/service mechanism; (3) sets up “industry breadth and depth graph”, so as to find the website content equilibrium degree of various industries’ online store and further obtain improvement strategy. It is believed that this research result, as said by the professors and scholars being interviewed, not only assists enterprisers to clearly grasp advantage/disadvantage and strategy of online store website attribute, but also promotes the effectiveness in resource utilization and the probability of success. Meanwhile, this research result can also effectively link practical application and academic value and provide researchers with new direction and scope.DOR : 98.1000/1726-8125.2015.0.27.0.0.84.10

Self‐potential ambient noise and spectral relationship with urbanization, seismicity, and strain rate revealed via the Taiwan Geoelectric Monitoring Network

AbstractGeoelectric self‐potential (SP) signals are sensitive to natural and anthropogenic factors. The SP spectral characteristics under the different factors in Taiwan were investigated, and the SP spectral scalings were correlated with urbanization level, seismicity, and crustal deformation. The ambient SP noise models were first established by estimating the probability density functions of the spectrograms at each frequency. The effects of the natural and anthropogenic factors on the SP signals are understood by comparing the SP noise models under various conditions, such as precipitation, urbanization, and electric trains. Results show that the SP signals in areas of high industrialization and human activity and areas close to train stations behave as white noises and exhibit a distinct spectral ripple at frequencies around 1 Hz. On the other hand, the SP spectral power law parameters, Gutenberg‐Richter b values, and dilation strain rates were estimated by using the SP, earthquake catalog, and GPS data, respectively, during 2012–2017. By investigating the correlations of the SP spectral parameters with the Gutenberg‐Richter b value, dilation strain rates, and urbanization level, the SP optimal frequency band is found between 0.006 and 1 Hz due to the high correlation between the SP and seismicity data and between the SP and dilation data and the low correlation between the SP and urbanization data. Hence, this study may help the filtering and screening of the SP data and facilitate the understanding of the mechano‐electric behavior in the crust

Computational modeling with forward and reverse engineering links signaling network and genomic regulatory responses: NF-κB signaling-induced gene expression responses in inflammation

<p>Abstract</p> <p>Background</p> <p>Signal transduction is the major mechanism through which cells transmit external stimuli to evoke intracellular biochemical responses. Diverse cellular stimuli create a wide variety of transcription factor activities through signal transduction pathways, resulting in different gene expression patterns. Understanding the relationship between external stimuli and the corresponding cellular responses, as well as the subsequent effects on downstream genes, is a major challenge in systems biology. Thus, a systematic approach is needed to integrate experimental data and theoretical hypotheses to identify the physiological consequences of environmental stimuli.</p> <p>Results</p> <p>We proposed a systematic approach that combines forward and reverse engineering to link the signal transduction cascade with the gene responses. To demonstrate the feasibility of our strategy, we focused on linking the NF-κB signaling pathway with the inflammatory gene regulatory responses because NF-κB has long been recognized to play a crucial role in inflammation. We first utilized forward engineering (Hybrid Functional Petri Nets) to construct the NF-κB signaling pathway and reverse engineering (Network Components Analysis) to build a gene regulatory network (GRN). Then, we demonstrated that the corresponding IKK profiles can be identified in the GRN and are consistent with the experimental validation of the IKK kinase assay. We found that the time-lapse gene expression of several cytokines and chemokines (TNF-α, IL-1, IL-6, CXCL1, CXCL2 and CCL3) is concordant with the NF-κB activity profile, and these genes have stronger influence strength within the GRN. Such regulatory effects have highlighted the crucial roles of NF-κB signaling in the acute inflammatory response and enhance our understanding of the systemic inflammatory response syndrome.</p> <p>Conclusion</p> <p>We successfully identified and distinguished the corresponding signaling profiles among three microarray datasets with different stimuli strengths. In our model, the crucial genes of the NF-κB regulatory network were also identified to reflect the biological consequences of inflammation. With the experimental validation, our strategy is thus an effective solution to decipher cross-talk effects when attempting to integrate new kinetic parameters from other signal transduction pathways. The strategy also provides new insight for systems biology modeling to link any signal transduction pathways with the responses of downstream genes of interest.</p

Functional roles of arginine residues in mung bean vacuolar H+-pyrophosphatase

AbstractPlant vacuolar H+-translocating inorganic pyrophosphatase (V-PPase EC 3.6.1.1) utilizes inorganic pyrophosphate (PPi) as an energy source to generate a H+ gradient potential for the secondary transport of ions and metabolites across the vacuole membrane. In this study, functional roles of arginine residues in mung bean V-PPase were determined by site-directed mutagenesis. Alignment of amino-acid sequence of K+-dependent V-PPases from several organisms showed that 11 of all 15 arginine residues were highly conserved. Arginine residues were individually substituted by alanine residues to produce R→A-substituted V-PPases, which were then heterologously expressed in yeast. The characteristics of mutant variants were subsequently scrutinized. As a result, most R→A-substituted V-PPases exhibited similar enzymatic activities to the wild-type with exception that R242A, R523A, and R609A mutants markedly lost their abilities of PPi hydrolysis and associated H+-translocation. Moreover, mutation on these three arginines altered the optimal pH and significantly reduced K+-stimulation for enzymatic activities, implying a conformational change or a modification in enzymatic reaction upon substitution. In particular, R242A performed striking resistance to specific arginine-modifiers, 2,3-butanedione and phenylglyoxal, revealing that Arg242 is most likely the primary target residue for these two reagents. The mutation at Arg242 also removed F− inhibition that is presumably derived from the interfering in the formation of substrate complex Mg2+–PPi. Our results suggest accordingly that active pocket of V-PPase probably contains the essential Arg242 which is embedded in a more hydrophobic environment

Preclinical Evaluation on the Tumor Suppression Efficiency and Combination Drug Effects of Fermented Wheat Germ Extract in Human Ovarian Carcinoma Cells

Fermented wheat germ extract (FWGE) is a nutrient supplement and a potential antitumor ingredient for developing an integrated chemotherapy with standard chemotherapeutic drugs for treating ovarian cancer patients. In this study, we evaluated the tumor suppression efficiency of FWGE in human ovarian carcinoma cells, SKOV-3 and ES-2, and found the half-maximal inhibitory concentrations (IC50s) to be 643.76 μg/mL and 246.11 μg/mL after 48 h of FWGE treatment. FWGE treatment also induced programmed cell death by activating the caspase-7 cleavage in both SKOV-3 and ES-2 cells, but only caspase-3 and poly(adenosine diphosphate-ribose) polymerase cleavages were activated in SKOV-3 cells. Moreover, FWGE exhibited combination drug effects with cisplatin and docetaxel in SKOV-3 and ES-2 cells by enhancing the cytotoxicity of both drugs. In conclusion, we found that FWGE not only suppressed cell growth but also induced caspase-3-related and caspase-7-related cell death in human ovarian carcinoma cells. FWGE treatment further enhanced the cytotoxicity of cisplatin and docetaxel, suggesting that FWGE is a potential ingredient in the development of adjuvant chemotherapy with cisplatin or docetaxel for treating ovarian cancer patients