ハブ カイヒ ルーティング ニ ヨル フクソウ セイギョ

多様化した消費者ニーズに呼応してプロダクトの差異化が進展している。しかし、競合プロダクトの台頭に伴いコモディティ化が進んで同質的になり、差異化による比較優位性の訴求が難しくなる。このため、顧客価値の送達がプロダクト・プランニングにおいて課題として検討されており、QFDの手法を織り込んだデフレームのコンセプトをベースとしている。分析の結果、代替品の性能向上で市場が縮小する場合でも、デジタルカメラ市場では差異化戦略が有効で、プロダクトの特性が訴求できるカテゴリーの形成や上方へのカテゴリー・シフトが起きている事態が明らかになった。To control congestion in information networks, we performed TCP/IP like traffic simulations using the hub avoidance routing which incorporates the number of adjacent nodes as costs. In these simulations three sample networks were adopted: Scale-Free network(SFN) which has the similar structural properties to those of the Internet, Random Network(RN) as a homogeneous structure network, and Random Geometric Networks(RGN) as a structural model for wireless ad-hoc network. In comparison with the case of the shortest path routing, the hub avoidance routing was found to be more effective on a traffic congestion control, and had higher packet reachability for destination nodes. In the case of RGN, however, this method had not any congestion suppression effect at all because the cause of congestion in RGN is not on hub nodes but on bridge nodes that connect small network islands

ハブ回避ルーティングによる輻輳抑制

E(その他)現実ネットワークでの輻輳抑制のため、隣接ノードのリンク数をコストとして組み込んだハブ回避ルーティングで IP 通信を模した通信シミュレーションを行った。ネットワークには、インターネットに似た構造を持つスケールフリーネットワークの１つ Barabási-Albert モデル（BA）、比較対象としてランダムネットワーク（RN）、無線アドホックネットワークの構造モデルであるランダムジオメトリックネットワーク（RGN）を使用した。その結果、最短経路と比べ BA、RN に関してはリンク数をコストとするとハブ回避ルーティングの方が輻輳を抑制でき到達率も高くなることがわかった。特に BA に対してこの効果は顕著であった。一方、RGN では輻輳抑制効果が全くなかった。これは RGN での輻輳発生原因がリンク数の多いハブノードではなく、ネットワークとネットワークを繋ぐ間のノードで起きているためだと考えられる。To control congestion in information networks, we performed TCP/IP like traffic simulations using the hub avoidance routing which incorporates the number of adjacent nodes as costs. In these simulations three sample networks were adopted: Scale-Free network(SFN) which has the similar structural properties to those of the Internet, Random Network(RN) as a homogeneous structure network, and Random Geometric Networks(RGN) as a structural model for wireless ad-hoc network. In comparison with the case of the shortest path routing, the hub avoidance routing was found to be more effective on a traffic congestion control, and had higher packet reachability for destination nodes. In the case of RGN, however, this method had not any congestion suppression effect at all because the cause of congestion in RGN is not on hub nodes but on bridge nodes that connect small network islands

Performance of plasma Aβ42/40, measured using a fully automated immunoassay, across a broad patient population in identifying amyloid status

Abstract Background Plasma biomarkers have emerged as promising screening tools for Alzheimer’s disease (AD) because of their potential to detect amyloid β (Aβ) accumulation in the brain. One such candidate is the plasma Aβ42/40 ratio (Aβ42/40). Unlike previous research that used traditional immunoassay, recent studies that measured plasma Aβ42/40 using fully automated platforms reported promising results. However, its utility should be confirmed using a broader patient population, focusing on the potential for early detection. Methods We recruited 174 participants, including healthy controls (HC) and patients with clinical diagnoses of AD, frontotemporal lobar degeneration, dementia with Lewy bodies/Parkinson’s disease, mild cognitive impairment (MCI), and others, from a university memory clinic. We examined the performance of plasma Aβ42/40, measured using the fully automated high-sensitivity chemiluminescence enzyme (HISCL) immunoassay, in detecting amyloid-positron emission tomography (PET)-derived Aβ pathology. We also compared its performance with that of Simoa-based plasma phosphorylated tau at residue 181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL). Results Using the best cut-off derived from the Youden Index, plasma Aβ42/40 yielded an area under the receiver operating characteristic curve (AUC) of 0.949 in distinguishing visually assessed 18F-Florbetaben amyloid PET positivity. The plasma Aβ42/40 had a significantly superior AUC than p-tau181, GFAP, and NfL in the 167 participants with measurements for all four biomarkers. Next, we analyzed 99 participants, including only the HC and those with MCI, and discovered that plasma Aβ42/40 outperformed the other plasma biomarkers, suggesting its ability to detect early amyloid accumulation. Using the Centiloid scale (CL), Spearman’s rank correlation coefficient between plasma Aβ42/40 and CL was -0.767. Among the 15 participants falling within the CL values indicative of potential future amyloid accumulation (CL between 13.5 and 35.7), plasma Aβ42/40 categorized 61.5% (8/13) as Aβ-positive, whereas visual assessment of amyloid PET identified 20% (3/15) as positive. Conclusion Plasma Aβ42/40 measured using the fully automated HISCL platform showed excellent performance in identifying Aβ accumulation in the brain in a well-characterized cohort. This equipment may be useful for screening amyloid pathology because it has the potential to detect early amyloid pathology and is readily applied in clinical settings