Design and implementation of the embedded capacitance layers for decoupling of wireless sensor nodes

In this paper, the embedded capacitance material (ECM) is fabricated between the power and ground layers of the wireless sensor nodes, forming an integrated capacitance to replace the large amount of decoupling capacitors on the board. The ECM material, whose dielectric constant is 16, has the same size of the wireless sensor nodes of 3cm*3cm, with a thickness of only 14μm. Though the capacitance of a single ECM layer being only around 8nF, there are two reasons the ECM layers can still replace the high frequency decoupling capacitors (100nF in our case) on the board. The first reason is: the parasitic inductance of the ECM layer is much lower than the surface mount capacitors'. A smaller capacitance value of the ECM layer could achieve the same resonant frequency of the surface mount decoupling capacitors. Simulation and measurement fit this assumption well. The second reason is: more than one layer of ECM material are utilized during the design step to get a parallel connection of the several ECM capacitance layers, finally leading to a larger value of the capacitance and smaller value of parasitic. Characterization of the ECM is carried out by the LCR meter. To evaluate the behaviors of the ECM layer, time and frequency domain measurements are performed on the power-bus decoupling of the wireless sensor nodes. Comparison with the measurements of bare PCB board and decoupling capacitors solution are provided to show the improvement of the ECM layer. Measurements show that the implementation of the ECM layer can not only save the space of the surface mount decoupling capacitors, but also provide better power-bus decoupling to the nodes.

The GrEAT pack: generic electronic assistive technology environmental control system - information booklet

This is a user manual for your electronic assistive technology environmental control system trial pack or in simple words – a few bits of technology that can let you control some household appliances. This information is intended for you, your family and carers.

Adult orthodontics: internet information and a national survey

Aims: 1. To investigate the reliability and readability of information on the Internet on adult orthodontics. 2. To evaluate the profile and treatment of adults by specialist orthodontists in the Republic of Ireland (ROI). Materials and methods: 1. An Internet search was conducted in May 2015 using three search engines (Google, Yahoo and Bing), with two search terms (“adult orthodontics” and “adult braces”). The first 50 websites from each engine were screened and exclusion criteria applied. Included websites were then assessed for reliability using the JAMA benchmarks, the DISCERN and LIDA tools and the presence of the HON seal. Readability was assessed using the FRES. 2. A pilot-tested questionnaire about adult orthodontics was distributed to 122 eligible specialist orthodontists in the ROI. Questions addressed general and treatment information about adult orthodontic patients, methods of information provision and respondent demographics. Results: 1. Thirteen websites met the inclusion criteria. Three websites contained all JAMA benchmarks and one displayed the HON Seal. The mean overall score for DISCERN was 3.9/5 and the mean total LIDA score was 115/120. The average FRES score was 63.1. 2. The questionnaire yielded a response rate of 83%. The typical demographic profile of adult orthodontic patients was professional females between 25-35 years. The most common incisor relationship and skeletal base was Class II, division 1 (51%) and Class II (61%) respectively. Aesthetic upper brackets and metal lower brackets were the most frequently used appliances. Only 30% of orthodontists advise their adult patients to find extra information on the Internet. Conclusions: 1. The reliability and readability of information on the Internet on adult orthodontics is of moderate quality. 2. The provision of adult orthodontic treatment is common among specialist orthodontists in the Republic of Ireland.

Adhesives for fixed orthodontic bands

Background: Orthodontic treatment involves using fixed or removable appliances (dental braces) to correct the positions of teeth. It has been shown that the quality of treatment result obtained with fixed appliances is much better than with removable appliances. Fixed appliances are, therefore, favoured by most orthodontists for treatment. The success of a fixed orthodontic appliance depends on the metal attachments (brackets and bands) being attached securely to the teeth so that they do not become loose during treatment. Brackets are usually attached to the front and side teeth, whereas bands (metal rings that go round the teeth) are more commonly used on the back teeth (molars). A number of adhesives are available to attach bands to teeth and it is important to understand which group of adhesives bond most reliably, as well as reducing or preventing dental decay during the treatment period. :Objectives: To evaluate the effectiveness of the adhesives used to attach bands to teeth during fixed appliance treatment, in terms of: (1) how often the bands come off during treatment; and (2) whether they protect the banded teeth against decay during fixed appliance treatment. Search methods: The following electronic databases were searched: Cochrane Oral Health's Trials Register (searched 2 June 2016), Cochrane Central Register of Controlled Trials (CENTRAL; 2016, Issue 5) in the Cochrane Library (searched 2 June 2016), MEDLINE Ovid (1946 to 2 June 2016) and EMBASE Ovid (1980 to 2 June 2016). We searched ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform for ongoing trials. No restrictions were placed on the language or date of publication when searching the electronic databases. Selection criteria: Randomised and controlled clinical trials (RCTs and CCTs) (including split-mouth studies) of adhesives used to attach orthodontic bands to molar teeth were selected. Patients with full arch fixed orthodontic appliance(s) who had bands attached to molars were included. Data collection and analysis: All review authors were involved in study selection, validity assessment and data extraction without blinding to the authors, adhesives used or results obtained. All disagreements were resolved by discussion. Main results: Five RCTs and three CCTs were identified as meeting the review's inclusion criteria. All the included trials were of split-mouth design. Four trials compared chemically cured zinc phosphate and chemically cured glass ionomer; three trials compared chemically cured glass ionomer cement with light cured compomer; one trial compared chemically cured glass ionomer with a chemically cured glass phosphonate. Data analysis was often inappropriate within the studies meeting the inclusion criteria. Authors' conclusions: There is insufficient high quality evidence with regard to the most effective adhesive for attaching orthodontic bands to molar teeth. Further RCTs are required.

User interaction monitoring and analysis framework

An overview is given of a user interaction monitoring and analysis framework called BaranC. Monitoring and analysing human-digital interaction is an essential part of developing a user model as the basis for investigating user experience. The primary human-digital interaction, such as on a laptop or smartphone, is best understood and modelled in the wider context of the user and their environment. The BaranC framework provides monitoring and analysis capabilities that not only records all user interaction with a digital device (e.g. smartphone), but also collects all available context data (such as from sensors in the digital device itself, a fitness band or a smart appliances). The data collected by BaranC is recorded as a User Digital Imprint (UDI) which is, in effect, the user model and provides the basis for data analysis. BaranC provides functionality that is useful for user experience studies, user interface design evaluation, and providing user assistance services. An important concern for personal data is privacy, and the framework gives the user full control over the monitoring, storing and sharing of their data.

A service-oriented user interaction analysis framework supporting adaptive applications

A comprehensive user model, built by monitoring a user's current use of applications, can be an excellent starting point for building adaptive user-centred applications. The BaranC framework monitors all user interaction with a digital device (e.g. smartphone), and also collects all available context data (such as from sensors in the digital device itself, in a smart watch, or in smart appliances) in order to build a full model of user application behaviour. The model built from the collected data, called the UDI (User Digital Imprint), is further augmented by analysis services, for example, a service to produce activity profiles from smartphone sensor data. The enhanced UDI model can then be the basis for building an appropriate adaptive application that is user-centred as it is based on an individual user model. As BaranC supports continuous user monitoring, an application can be dynamically adaptive in real-time to the current context (e.g. time, location or activity). Furthermore, since BaranC is continuously augmenting the user model with more monitored data, over time the user model changes, and the adaptive application can adapt gradually over time to changing user behaviour patterns. BaranC has been implemented as a service-oriented framework where the collection of data for the UDI and all sharing of the UDI data are kept strictly under the user's control. In addition, being service-oriented allows (with the user's permission) its monitoring and analysis services to be easily used by 3rd parties in order to provide 3rd party adaptive assistant services. An example 3rd party service demonstrator, built on top of BaranC, proactively assists a user by dynamic predication, based on the current context, what apps and contacts the user is likely to need. BaranC introduces an innovative user-controlled unified service model of monitoring and use of personal digital activity data in order to provide adaptive user-centred applications. This aims to improve on the current situation where the diversity of adaptive applications results in a proliferation of applications monitoring and using personal data, resulting in a lack of clarity, a dispersal of data, and a diminution of user control.