Fault tolerant packet-switched network design and Its sensitivity

Reliability and performance for telecommunication networks have traditionally been investigated separately in spite of their close relation. A design method integrating them for a reliable packet switched network, called a proofing method, is presented. Two heuristic design approaches (max-average, max-delay-link) for optimizing network cost in the proofing method are described. To verify their effectiveness and applicability, they are compared numerically for three example network topologies. The sensitivity of these two methods is examined with respect to changes in traffic demand and in link reliability. The design sensitivity to variation of input data is examined by changing the predicted probability of link failure, and by increasing the network traffic over the predicted value. The resulting analysis shows relative insensitivity of solutions generated by the two design methods to input data</p

Stomagen positively regulates stomatal density in Arabidopsis.

葉の気孔の数を増加させる因子の発見～CO2削減や食糧増産へ向けて～. 京都大学プレスリリース. 2009-12-10.Stomata in the epidermal tissues of leaves are valves through which passes CO(2), and as such they influence the global carbon cycle. The two-dimensional pattern and density of stomata in the leaf epidermis are genetically and environmentally regulated to optimize gas exchange. Two putative intercellular signalling factors, EPF1 and EPF2, function as negative regulators of stomatal development in Arabidopsis, possibly by interacting with the receptor-like protein TMM. One or more positive intercellular signalling factors are assumed to be involved in stomatal development, but their identities are unknown. Here we show that a novel secretory peptide, which we designate as stomagen, is a positive intercellular signalling factor that is conserved among vascular plants. Stomagen is a 45-amino--rich peptide that is generated from a 102-amino-acid precursor protein designated as STOMAGEN. Both an in planta analysis and a semi-in-vitro analysis with recombinant and chemically synthesized stomagen peptides showed that stomagen has stomata-inducing activity in a dose-dependent manner. A genetic analysis showed that TMM is epistatic to STOMAGEN (At4g12970), suggesting that stomatal development is finely regulated by competitive binding of positive and negative regulators to the same receptor. Notably, STOMAGEN is expressed in inner tissues (the mesophyll) of immature leaves but not in the epidermal tissues where stomata develop. This study provides evidence of a mesophyll-derived positive regulator of stomatal density. Our findings provide a conceptual advancement in understanding stomatal development: inner photosynthetic tissues optimize their function by regulating stomatal density in the epidermis for efficient uptake of CO(2)

Performance Analysis of Signaling Delay for Wireless Cellular Networks

In wireless cellular networks, signaling traffic such as location update, paging and handoff due to the user\u27s mobility takes a considerable portion of the total traffic load. In addition, the maximum allowable delays may be different among the signaling packets. In this paper, we present an analytical model for evaluating a total processing delay of signaling packets of wireless cellular networks, which integrates the delays of the radio channel and the processing delay at the wired portion. Through numerical examples, we show that priority processing is effective for reducing the handoff processing delays. We also evaluate the delay difference among cells according to their position within the location area, and the influence of number of terminals upon the processing delays

Energy-Efficient Receiver-Driven Wireless Mesh Sensor Networks

A major challenge in wireless sensor networks research is energy efficiency. In the intermittent receiver-driven data transmission (IRDT) protocol, which aims at saving energy, communication between two nodes commences when multiple receiver nodes transmit their own IDs and the sender nodes receive them. This protocol can be used to construct a mesh network which is robust against node failure and wireless channel fluctuations. In our work, we improve this protocol by implementing a collision avoidance method for control packets. First, we refer to the probability of control packet collision as a function of the intermittent interval. We then introduce procedures to determine the interval which decreases or minimizes this probability. Afterwards, we include a data aggregation mechanism into IRDT to reduce data transmission frequency and the occurrence of control packet collisions. Through computer simulation, we show that IRDT can offer greater reduction of the average energy consumption compared with RI-MAC and X-MAC, especially at small loads, and we also demonstrate that IRDT with collision avoidance for control packets can attain higher performance than the original IRDT. This method ensures a packet collection ratio of more than 99% and an average energy consumption 38% lower than that of EA-ALPL and 90% lower than that of the original IRDT

Hybrid Representation-Enhanced Sampling for Bayesian Active Learning in Musculoskeletal Segmentation of Lower Extremities

Purpose: Manual annotations for training deep learning (DL) models in auto-segmentation are time-intensive. This study introduces a hybrid representation-enhanced sampling strategy that integrates both density and diversity criteria within an uncertainty-based Bayesian active learning (BAL) framework to reduce annotation efforts by selecting the most informative training samples. Methods: The experiments are performed on two lower extremity (LE) datasets of MRI and CT images, focusing on the segmentation of the femur, pelvis, sacrum, quadriceps femoris, hamstrings, adductors, sartorius, and iliopsoas, utilizing a U-net-based BAL framework. Our method selects uncertain samples with high density and diversity for manual revision, optimizing for maximal similarity to unlabeled instances and minimal similarity to existing training data. We assess the accuracy and efficiency using Dice and a proposed metric called reduced annotation cost (RAC), respectively. We further evaluate the impact of various acquisition rules on BAL performance and design an ablation study for effectiveness estimation. Results: In MRI and CT datasets, our method was superior or comparable to existing ones, achieving a 0.8\% Dice and 1.0\% RAC increase in CT (statistically significant), and a 0.8\% Dice and 1.1\% RAC increase in MRI (not statistically significant) in volume-wise acquisition. Our ablation study indicates that combining density and diversity criteria enhances the efficiency of BAL in musculoskeletal segmentation compared to using either criterion alone. Conclusion: Our sampling method is proven efficient in reducing annotation costs in image segmentation tasks. The combination of the proposed method and our BAL framework provides a semi-automatic way for efficient annotation of medical image datasets.Comment: 15 pages, 5 figure

Microarray-Based Transcriptional Profiling of Renieramycin M and Jorunnamycin C, Isolated from Thai Marine Organisms

Renieramycin M and jorunnamycin C, two isoquinolinequinone compounds differing only at the C-22 ester side chain, were evaluated for their cytotoxic effects on human colon (HCT116) and breast (MDA-MB-435) cancer cell lines. These two compounds displayed potent cancer cell growth inhibition, their IC50 values reaching nanomolar order. To examine their effects on transcription, we carried out oligonucleotide microarray analysis with focus on the similarities and differences between the two compounds in terms of transcriptional profiles. We found that the down-regulation of PTPRK (protein tyrosine phosphatase receptor type K) can be considered as a biomarker responsive to the cytotoxic effects of this class of antitumor marine natural products