Pulsed laser deposition of Ga-La-S chalcogenide glass thin film optical waveguides

Thin film optical waveguides of the chalcogenide glass Ga-La-S have been deposited on substrates of CaF2 and microscope glass by the technique of pulsed laser deposition. The chalcogenide properties of photobleaching, photodoping, and photoinduced refractive index changes have been observed and preliminary experiments carried out. The refractive index and thickness of the layer were verified using a waveguide "dark mode" analysis technique

Evaluating cutpoints for the MHI-5 and MCS using the GHQ-12: a comparison of five different methods

Background The Mental Health Inventory (MHI-5) and the Mental Health Component Summary score (MCS) derived from the Short Form 36 (SF-36) instrument are well validated and reliable scales. A drawback of their construction is that neither has a clinically validated cutpoint to define a case of common mental disorder (CMD). This paper aims to produce cutpoints for the MHI-5 and MCS by comparison with the General Health Questionnaire (GHQ-12). Methods Data were analysed from wave 9 of the British Household Panel Survey (2000), providing a sample size of 14,669 individuals. Receiver Operating Characteristic (ROC) curves were used to compare the scales and define cutpoints for the MHI-5 and MCS, using the following optimisation criteria: the Youden Index, the point closest to (0,1) on the ROC curve, minimising the misclassification rate, the minimax method, and prevalence matching. Results For the MHI-5, the Youden Index and the (0,1) methods both gave a cutpoint of 76, minimising the misclassification rate gave a cutpoint of 60 and the minimax method and prevalence matching gave a cutpoint of 68. For the MCS, the Youden Index and the (0,1) methods gave cutpoints of 51.7 and 52.1 respectively, minimising the error rate gave a cutpoint of 44.8 and both the minimax method and prevalence matching gave a cutpoint of 48.9. The correlation between the MHI-5 and the MCS was 0.88. Conclusion The Youden Index and (0,1) methods are most suitable for determining a cutpoint for the MHI-5, since they are least dependent on population prevalence. The choice of method is dependent on the intended application. The MHI-5 performs remarkably well against the longer MCS

RNAstrand: reading direction of structured RNAs in multiple sequence alignments

<p>Abstract</p> <p>Motivation</p> <p>Genome-wide screens for structured ncRNA genes in mammals, urochordates, and nematodes have predicted thousands of putative ncRNA genes and other structured RNA motifs. A prerequisite for their functional annotation is to determine the reading direction with high precision.</p> <p>Results</p> <p>While folding energies of an RNA and its reverse complement are similar, the differences are sufficient at least in conjunction with substitution patterns to discriminate between structured RNAs and their complements. We present here a support vector machine that reliably classifies the reading direction of a structured RNA from a multiple sequence alignment and provides a considerable improvement in classification accuracy over previous approaches.</p> <p>Software</p> <p>RNAstrand is freely available as a stand-alone tool from <url>http://www.bioinf.uni-leipzig.de/Software/RNAstrand</url> and is also included in the latest release of RNAz, a part of the Vienna RNA Package.</p

Detection of unsafety in families with parental and/or child developmental problems at the start of family support

Background Risk assessment is crucial in preventing child maltreatment as it can identify high-risk cases in need of child protection intervention. Despite this importance, there have been no validated risk assessment instruments available in the Netherlands for assessing the risk of child maltreatment. Therefore, the predictive validity of the California Family Risk Assessment (CFRA) was examined in Dutch families who received family support. In addition, the added value of a number of experimental items was examined. Finally, it was examined whether the predictive value of the instrument could be improved by modifying the scoring procedure. Methods Dutch families who experienced parenting and/or child developmental problems and were referred by the Centres for Youth and Family for family support between July 2009 and March 2011 were included. This led to a sample of 491 families. The predictive validity of the CFRA and the added value of the experimental items were examined by calculating AUC values. A CHAID analysis was performed to examine whether the scoring procedure could be improved. Results About half of the individual CFRA items were not related to future reports of child maltreatment. The predictive validity of the CFRA in predicting future reports of child maltreatment was found to be modest (AUC = .693). The addition of some of the experimental items and the modification of the scoring procedure by including only items that were significantly associated with future maltreatment reports resulted in a ‘high’ predictive validity (AUC = .795). Conclusions This new set of items might be a valuable instrument that also saves time because only variables that uniquely contribute to the prediction of future reports of child maltreatment are included. Furthermore, items that are perceived as difficult to assess by professionals, such as parental mental health problems or parents’ history of abuse/neglect, could be omitted without compromising predictive validity. However, it is important to examine the psychometric properties of this new set of items in a new dataset

Validity of the Falls Risk for Older People in the Community (FROP‑Com) tool to predict falls and fall injuries for older people presenting to the emergency department after falling

The aims of this study were to (1) externally validate the accuracy of the Falls Risk for Older People in the Community (FROP-Com) falls risk assessment tool in predicting falls and (2) undertake initial validation of the accuracy of the FROPCom to predict injurious falls (requiring medical attention) in people aged ≥ 60 years presenting to emergency departments (EDs) after falling. Two hundred and thirteen participants (mean age = 72.4 years; 59.2% women) were recruited (control group of a randomised controlled trial). A FROP-Com assessment was completed at a home visit within 2 weeks of ED discharge. Data on falls and injurious falls requiring medical attention were collected via monthly falls calendars for the next 12 months. Predictive accuracy was evaluated using sensitivity and specificity of a high-risk FROP-Com classification (score ≥ 19) in predicting a fall and injurious falls requiring medical attention. Fifty per cent of participants fell, with 60.4% of falls requiring medical attention. Thirty-two per cent were classified as high, 49% as moderate and 19% low falls risk. Low sensitivity was achieved for the FROP-Com high-risk classification for predicting falls (43.4%) and injurious falls (34.4%), although specificity was high (79.4% and 78.6%, respectively). Despite the FROP-Com’s low predictive accuracy, the high fall rate and high falls risk of the sample suggest that older people who fall, present to ED and are discharged home are at high risk of future falls. In high-falls-risk populations such as in this study, the FROP-Com is not a valid tool for classifying risk of falls or injurious falls. Its potential value may instead be in identifying risk factors for falling to direct tailoring of falls prevention interventions to reduce future falls