Constructed wetlands: Prediction of performance with case-based reasoning (part B)

The aim of this research was to assess the treatment efficiencies for gully pot liquor of experimental vertical- flow constructed wetland filters containing Phragmites australis (Cav.) Trin. ex Steud. (common reed) and filter media of different adsorption capacities. Six out of 12 filters received inflow water spiked with metals. For 2 years, hydrated nickel and copper nitrate were added to sieved gully pot liquor to simulate contaminated primary treated storm runoff. The findings were analyzed and discussed in a previous paper (Part A). Case-based reasoning (CBR) methods were applied to predict 5 days at 20°C N-Allylthiourea biochemical oxygen demand (BOD) and suspended solids (SS), and to demonstrate an alternative method of analyzing water quality performance indicators. The CBR method was successful in predicting if outflow concentrations were either above or below the thresholds set for water-quality variables. Relatively small case bases of approximately 60 entries are sufficient to yield relatively high predictions of compliance of at least 90% for BOD. Biochemical oxygen demand and SS are expensive to estimate, and can be cost-effectively controlled by applying CBR with the input variables turbidity and conductivity

Barriers to better care for people with AIDS in developing countries

Access to good quality antiretroviral treatment has transformed the prognosis for people with AIDS in the developed world. Although it is feasible and desirable to deliver antiretroviral drugs in resource poor settings,few of the 95% of people with HIV and AIDS who live in developing countries receive them. The World Health Organization has launched a programme to deliver antiretroviral drugs to three million people with AIDS in the developing world by 2005, the “3 by 5” initiative. We identify some of the challenges faced by the initiative, focusing on delivery of care

The Mill By The Sea

https://digitalcommons.library.umaine.edu/mmb-vp/2114/thumbnail.jp

Bells of Saint Mary\u27s

The bells of St. Marry\u27s at sweet eventide,Shall call me beloved, to come to your side,And out in the valley in south of the sea, I know you\u27ll be waiting, yes waiting for me. RefrainThe Bells of St. Mary\u27s,Ah! hear they are callingThe young loves-- true lovesWho come from the sea,And so my beloved,When red leaves are falling,The Love-bells shall ring out- ring outFor you and me.The Bells of St. Mary\u27s, Ah! hear they are callingThe young loves- the true lovesWho come from the sea,And so, my beloved,When red leaves are falling,The love-bells shall ring out- ring outFor you and me. At the porch of St. Mary\u27s I\u27ll wait there with youIn your soft wedding dress with its ribbons of blue,in the church of St. Mary\u27s sweet voices shall sing,For you and me dearest the wedding bells ring.(to Refrain

Torts

Covers cases on limitation of actions in malpractice suits, on the extent of liability for ultrahazardous activities (Furber), and on defenses available to the tortfeasor in wrongful death actions (Dixon)

Meeting the design challenges of nano-CMOS electronics: an introduction to an upcoming EPSRC pilot project

The years of ‘happy scaling’ are over and the fundamental challenges that the semiconductor industry faces, at both technology and device level, will impinge deeply upon the design of future integrated circuits and systems. This paper provides an introduction to these challenges and gives an overview of the Grid infrastructure that will be developed as part of a recently funded EPSRC pilot project to address them, and we hope, which will revolutionise the electronics design industry

A GPS-Less Localization and Mobility Modelling (LMM) System for Wildlife Tracking

Existing wildlife tracking solutions typically use sensor nodes with specialised facilities, such as long-range radio, solar array of cells and Global Positioning System (GPS). This introduces additional manufacturing cost, increased energy and memory consumptions and increased sensor node weight. This paper proposes a novel Localization and Mobility Modelling (LMM) system, that can carry out wildlife tracking by merely using low-cost, lightweight sensor nodes and using short-range peer-to-peer communication facilities only, i.e. without the need for any specialised facilities. This is done by using two computationally simple operations, which are: (i) aggregated data collections from sensor nodes via peer-to-peer communications in a distributed manner, and (ii) estimation of sensor nodes' movement traces using trilateration. The computational load placed on each sensor node is just that of data collection and aggregation, whereas movement traces estimation is carried out on a backend server, separated from the sensor nodes. In the design of the LMM system, we have: (i) carried out an empirical evaluation of different parameter value settings for data collection to develop a Multi-Zone Multi-Hierarchy (MZMH) communication structure, (ii) demonstrated a novel use of an Aggregation based Topology Learning (ATL) protocol for collecting sensor nodes' topology data using peer-to-peer multi-hop communications, and (iii) used a novel Location Estimation (LE) method for estimating sensor nodes' movement traces from the collected topology data. The evaluation results show that the LMM system can accurately estimate sensor nodes' movement traces but with significantly less energy and memory costs, demonstrating its cost-efficiency as compared to the related wildlife tracking solutions. © 2020 IEEE

The Bells of St. Mary\u27s

https://digitalcommons.library.umaine.edu/mmb-vp/1093/thumbnail.jp

The Bells of St. Mary\u27s

https://digitalcommons.library.umaine.edu/mmb-vp/1094/thumbnail.jp

Live Demonstration: Multiplexing AER Asynchronous Channels over LVDS Links with Flow-Control and Clock- Correction for Scalable Neuromorphic Systems

In this live demonstration we exploit the use of a serial link for fast asynchronous communication in massively parallel processing platforms connected to a DVS for realtime implementation of bio-inspired vision processing on spiking neural networks