Planning Review: Application of Vertical Greening for Landscape Beautification in Taipei

For the improvement of city landscape, vertical greening by plantation is one of the effective approaches. In the past few years, vertical greening has gained significant progress in both technological development and practical application. Thanks to the 2010 Flora Expo, vertical greening has made significant contribution to the landscape beautification in Taipei. Among various applications, temporary greening of fences surrounding construction sites has developed a unique landscape for Taipei city. In this paper, potential environmental benefits and application experience of vertical greening in Taipei city will be reviewed and discussed

Association algorithm to mine the rules that govern enzyme definition and to classify protein sequences

BACKGROUND: The number of sequences compiled in many genome projects is growing exponentially, but most of them have not been characterized experimentally. An automatic annotation scheme must be in an urgent need to reduce the gap between the amount of new sequences produced and reliable functional annotation. This work proposes rules for automatically classifying the fungus genes. The approach involves elucidating the enzyme classifying rule that is hidden in UniProt protein knowledgebase and then applying it for classification. The association algorithm, Apriori, is utilized to mine the relationship between the enzyme class and significant InterPro entries. The candidate rules are evaluated for their classificatory capacity. RESULTS: There were five datasets collected from the Swiss-Prot for establishing the annotation rules. These were treated as the training sets. The TrEMBL entries were treated as the testing set. A correct enzyme classification rate of 70% was obtained for the prokaryote datasets and a similar rate of about 80% was obtained for the eukaryote datasets. The fungus training dataset which lacks an enzyme class description was also used to evaluate the fungus candidate rules. A total of 88 out of 5085 test entries were matched with the fungus rule set. These were otherwise poorly annotated using their functional descriptions. CONCLUSION: The feasibility of using the method presented here to classify enzyme classes based on the enzyme domain rules is evident. The rules may be also employed by the protein annotators in manual annotation or implemented in an automatic annotation flowchart

Three-Tier Capacity and Traffic Allocation for Core, Edges, and Devices for Mobile Edge Computing

In order to satisfy the 5G requirements of ultra-low latency, mobile edge computing (MEC)-based architecture, composed of three-tier nodes, core, edges, and devices, is proposed. In MEC-based architecture, previous studies focused on the controlplane issue, i.e., how to allocate traffic to be processed at different nodes to meet this ultra-low latency requirement. Also important is how to allocate the capacity to different nodes in the management plane so as to establish a minimal-capacity network. The objectives of this paper is to solve two problems: 1) to allocate the capacity of all nodes in MEC-based architecture so as to provide a minimal-capacity network and 2) to allocate the traffic to satisfy the latency percentage constraint, i.e., at least a percentage of traffic satisfying the latency constraint. In order to achieve these objectives, a two-phase iterative optimization (TPIO) method is proposed to try to optimize capacity and traffic allocation in MEC-based architecture. TPIO iteratively uses two phases to adjust capacity and traffic allocation respectively because they are tightly coupled. In the first phase, using queuing theory calculates the optimal traffic allocation under fixed allocated capacity, while in the second phase, allocated capacity is further reduced under fixed traffic allocation to satisfy the latency percentage constraint. Simulation results show that MEC-based architecture can save about 20.7% of capacity of two-tier architecture. Further, an extra 12.2% capacity must be forfeited when the percentage of satisfying latency is 90%, compared to 50%.This work was supported in part by H2020 collaborative Europe/Taiwan research project 5G-CORAL (grant number 761586), and Ministry of Science and Technology, Taiwan for financially supporting this research under Contract No. MOST 106-2218-E-009-018

Variable selection based on entropic criterion and its application to the debris-flow triggering

We propose a new data analyzing scheme, the method of minimum entropy analysis (MEA), in this paper. New MEA provides a quantitative criterion to select relevant variables for modeling the physical system interested. Such method can be easily extended to various geophysical/geological data analysis, where many relevant or irrelevant available measurements may obscure the understanding of the highly complicated physical system like the triggering of debris-flows. After demonstrating and testing the MEA method, we apply this method to a dataset of debris-flow occurrences in Taiwan and successfully find out three relevant variables, i.e. the hydrological form factor, numbers and areas of landslides, to the triggering of observed debris-flow events due to the 1996 Typhoon Herb.Comment: 9 pages and 4 table

Human mobility increased with vaccine coverage and attenuated the protection of COVID-19 vaccination: a longitudinal study of 107 countries

Background: The World Health Organization has raised concerns that vaccinated people may reduce physical and social distancing more than necessary. With imperfect vaccine protection and the lifting of mobility restrictions, understanding how human mobility responded to vaccination and its potential consequence is critical. We estimated vaccination-induced mobility (VM) and examined whether it attenuates the effect of COVID-19 vaccination on controlling case growth. Methods: We collected a longitudinal data set of 107 countries between 15 February 2020 and 6 February 2022 from Google COVID-19 Community Mobility Reports, the Oxford COVID-19 Government Response Tracker, Our World in Data, and World Development Indicators. We measured mobility in four categories of location: retail and recreational places, transit stations, grocery stores and pharmacies, and workplaces. We applied panel data models to address unobserved country characteristics and used Gelbach decomposition to evaluate the extent to which VM has offset vaccination effectiveness. Results: Across locations, a 10-percentage-point (pp) increase in vaccine coverage was associated with a 1.4-4.3 pp increase in mobility (P < 0.001). VM was greater in lower-income countries (up to 7.9 pps; 95% confidence interval (CI) = 5.3 to 10.5, P < 0.001) and in earlier stages of vaccine rollouts (up to 19.2 pps; 95% CI = 15.1 to 23.2%, P < 0.001). VM decreased the effectiveness of vaccines in controlling case growth by 33.4% in retail and recreation places (P < 0.001), 26.4% in transit stations (P < 0.001), and 15.4% in grocery stores and pharmacies (P = 0.002). Conclusions: VM provides support for the Peltzman effect; it attenuates but does not completely counter vaccine effectiveness. Our study findings suggest strategies for mitigating the unintended consequences of VM, including reducing short-term mobility responses after vaccination, prioritizing mobility in grocery-type places and workplaces, and accelerating rollouts at earlier stages of vaccination, especially in lower-income countries