Evaluation of forensic evidence in DNA mixture using RMNE

Invited Paper Sessions (IPS) 21: Statistical reasoning in lawTo establish the link between an arrested suspect and a crime case based on a DNA mixture, one of the two main statistical tools used by forensic scientists is the random man not excluded (RMNE) probability. The tradi- tional RMNE approach omits any knowledge on the number of contributors and is commonly regarded as being less powerful than the likelihood (LR) approach. In view of the simplicity of interpretation of RMNE, which is the major advantage of using it to present DNA evidences in court, we present a new concept for the interpretation and calculation of the RMNE proba- bility. A new approach for determining the non-exclusion of a random man is proposed, upon which a general formula for the calculation of RMNE probability is developed. By taking account of the number of contributors, the new RMNE probability can be much more powerful for evaluating the evidentiary value of non excluded suspects, compared to the traditional RMNE approach. As illustrated by an example based on a real rape case, our approach can be easily implemented and can shorten the gap between the two approaches by utilizing more information of the case.published_or_final_versio

Load forecasting by fuzzy neural network in Box-Jenkins models

In this paper, the use of FNN to identify appropriate Box-Jenkins models for the electricity load forecasting in Hong Kong is presented. FNN is found to be suitable to identify the Box-Jenkin model. By such model, we can forecast the load accurately.published_or_final_versio

Longitudinal predictors of Chinese word reading and spelling among elementary grade students.

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The core components of reading instruction in Chinese

The present study aimed at identifying core components of reading instruction in Chinese within the framework of the tiered intervention model. A curriculum with four teaching components of cognitive-linguistic skills was implemented in a Program school for 3 years since Grade 1. The findings showed that the Tier 1 intervention was effective in enhancing the literacy and cognitive-linguistic skills of children in the Program school. The positive effects were maintained at the end of Grade 2. Progress in both word-level and text-level cognitive-linguistic skills predicted significantly progress in reading comprehension. Based on the present findings, the four core reading components in Chinese were proposed-oral language, morphological awareness, orthographic skills, and syntactic skills. Comparing the Big Five in English and the four core components in Chinese reflects different cognitive demands for reading diverse orthographies. © 2011 Springer Science+Business Media B.V.postprin

Reliability and validity of alternate step test times in subjects with chronic stroke

OBJECTIVE: (i) To investigate the intra-rater, inter-rater and test-retest reliability and minimal detectable change of the Alternate Step Test (AST) when assessing people with chronic stroke. (ii) To quantify the correlation between AST times and stroke-specific impairments. DESIGN: Cross-sectional study. SETTING: University-based rehabilitation centre. PARTICIPANTS: A convenience sample of 86 participants: 45 with chronic stroke, and 41 healthy elderly subjects. METHODS: The AST was administered along with the Fugl-Meyer Lower Extremity Assessment (FMA-LE), the Five Times Sit-To-Stand Test (FTSTS), limits of stability (LOS) measurements, Berg Balance Scale (BBS) scores, Chinese-translated Activities-specific Balance Confidence Scale (ABC-C) ratings, and the Timed “Up and Go” test (TUG). RESULTS: Excellent intra-rater, inter-rater and test-retest reliability were found, with a minimal detectable change of 3.26 s. AST times were significantly associated with FMA-LE assessment, FTSTS times, LOS in the forward and backward directions and to the affected side, BBS ratings and TUG times. CONCLUSION: AST time is a reliable assessment tool that correlates with different stroke-specific impairments in people with chronic stroke.published_or_final_versio

Lifestyle-modified mortality associated with air pollution: a time-series study

Health Services Research Fund & Health Care and Promotion Fund: Research Dissemination Reports (Series 9)published_or_final_versio

Atomic Layer Deposition of Ni Thin Films and Application to Area-Selective Deposition

Ni thin films were deposited by atomic layer deposition (ALD) using bis(dimethylamino-2-methyl-2-butoxo)nickel [Ni(dmamb)(2)] as a precursor and NH3 gas as a reactant. The growth characteristics and film properties of ALD Ni were investigated. Low-resistivity films were deposited on Si and SiO2 substrates, producing high-purity Ni films with a small amount of oxygen and negligible amounts of nitrogen and carbon. Additionally, ALD Ni showed excellent conformality in nanoscale via holes. Utilizing this conformality, Ni/Si core/shell nanowires with uniform diameters were fabricated. By combining ALD Ni with octadecyltrichlorosilane (OTS) self-assembled monolayer as a blocking layer, area-selective ALD was conducted for selective deposition of Ni films. When performed on the prepatterned OTS substrate, the Ni films were selectively coated only on OTS-free regions, building up Ni line patterns with 3 mu m width. Electrical measurement results showed that all of the Ni lines were electrically isolated, also indicating the selective Ni deposition. (C) 2010 The Electrochemical Society. [DOI: 10.1149/1.3504196] All rights reserved.ope

IoT-Based Wireless Polysomnography Intelligent System for Sleep Monitoring

© 2013 IEEE. Polysomnography (PSG) is considered the gold standard in the diagnosis of obstructive sleep apnea (OSA). The diagnosis of OSA requires an overnight sleep experiment in a laboratory. However, due to limitations in relation to the number of labs and beds available, patients often need to wait a long time before being diagnosed and eventually treated. In addition, the unfamiliar environment and restricted mobility when a patient is being tested with a polysomnogram may disturb their sleep, resulting in an incomplete or corrupted test. Therefore, it is posed that a PSG conducted in the patient's home would be more reliable and convenient. The Internet of Things (IoT) plays a vital role in the e-Health system. In this paper, we implement an IoT-based wireless polysomnography system for sleep monitoring, which utilizes a battery-powered, miniature, wireless, portable, and multipurpose recorder. A Java-based PSG recording program in the personal computer is designed to save several bio-signals and transfer them into the European data format. These PSG records can be used to determine a patient's sleep stages and diagnose OSA. This system is portable, lightweight, and has low power-consumption. To demonstrate the feasibility of the proposed PSG system, a comparison was made between the standard PSG-Alice 5 Diagnostic Sleep System and the proposed system. Several healthy volunteer patients participated in the PSG experiment and were monitored by both the standard PSG-Alice 5 Diagnostic Sleep System and the proposed system simultaneously, under the supervision of specialists at the Sleep Laboratory in Taipei Veteran General Hospital. A comparison of the results of the time-domain waveform and sleep stage of the two systems shows that the proposed system is reliable and can be applied in practice. The proposed system can facilitate the long-Term tracing and research of personal sleep monitoring at home

Whole-Genome Array CGH Evaluation for Replacing Prenatal Karyotyping in Hong Kong

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