The independent effects of attention and lead stimulus properties on the acoustic blink reflex

The effects of attention to a lead stimulus and of its sensory properties on modulation of the acoustic blink reflex were investigated. Participants performed a reaction time task cued by an acoustic or a visual lead stimulus. In Experiment 1, half the participants were presented with sustained lead stimuli. For the remainder, the lead stimulus was discrete and consisted of two brief presentations that marked the onset and offset of a stimulus-free interval. In Experiment 2, sustained lead stimuli were presented at a low or high intensity. The attentional demands of the task enhanced blink latency and magnitude modulation during acoustic and visual lead stimuli, with blink modulation being largest at a late point during the lead stimulus. Independent of the attentional effects, blink latency and magnitude modulation were larger during sustained than during discrete acoustic lead stimuli, whereas there was no difference for visual lead stimuli. Increases in the intensity of the lead stimulus enhanced blink modulation regardless of lead stimulus modality. Attention to a lead stimulus and the properties of the lead stimulus appear to have independent effects on blink reflex modulation.

Lead sulfide nanocrystal: conducting polymer solar cells

In this paper, we report photovoltaic devices fabricated from lead sulfide nanocrystals and the conducting polymer poly(2-methoxy-5-(2'-ethyl-hexyloxy)-p-phenylene vinylene). This composite material was produced via a new single-pot synthesis which solves many of the issues associated with existing methods. Our devices have white light power conversion efficiencies under AM 1.5 illumination of 0.7% and single wavelength conversion efficiencies of 1.1%. Additionally, they exhibit remarkably good ideality factors (n = 1.15). Our measurements show that these composites have significant potential as soft optoelectronic materials.

Rainfall variability at decadal and longer time scales: signal or noise?

Rainfall variability occurs over a wide range of temporal scales. Knowledge and understanding of such variability can lead to improved risk management practices in agricultural and other industries. Analyses of temporal patterns in 100 yr of observed monthly global sea surface temperature and sea level pressure data show that the single most important cause of explainable, terrestrial rainfall variability resides within the El Nino-Southern Oscillation (ENSO) frequency domain (2.5-8.0 yr), followed by a slightly weaker but highly significant decadal signal (9-13 yr), with some evidence of lesser but significant rainfall variability at interclecadal time scales (15-18 yr). Most of the rainfall variability significantly linked to frequencies tower than ENSO occurs in the Australasian region, with smaller effects in North and South America, central and southern Africa, and western Europe. While low-frequency (LF) signals at a decadal frequency are dominant, the variability evident was ENSO-like in all the frequency domains considered. The extent to which such LF variability is (i) predictable and (ii) either part of the overall ENSO variability or caused by independent processes remains an as yet unanswered question. Further progress can only be made through mechanistic studies using a variety of models.

Zero-non-zero patterned vector error correction modeling for I(2) cointegrated time series with applications in testing PPP and stock market relationships

Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

Time-evolution of highly localized positive-energy states of the free Dirac electron

Highly localized positive-energy states of the free Dirac electron are constructed and shown to evolve in a simple way under the action of Dirac's equation. When the initial uncertainty in position is small on the scale of the Compton wavelength, there is an associated uncertainty in the mean energy that is large compared with the rest mass of the electron. However, this does not lead to any breakdown of the one-particle description, associated with the possibility of pair-production, but rather leads to a rapid expansion of the probability density outwards from the point of localization, at speeds close to the speed of light.

Procedures and parameters in the real-time program refinement calculus

The real-time refinement calculus is a formal method for the systematic derivation of real-time programs from real-time specifications in a style similar to the non-real-time refinement calculi of Back and Morgan. In this paper we extend the real-time refinement calculus with procedures and provide refinement rules for refining real-time specifications to procedure calls. A real-time specification can include constraints on, not only what outputs are produced, but also when they are produced. The derived programs can also include time constraints oil when certain points in the program must be reached; these are expressed in the form of deadline commands. Such programs are machine independent. An important consequence of the approach taken is that, not only are the specifications machine independent, but the whole refinement process is machine independent. To implement the machine independent code on a target machine one has a separate task of showing that the compiled machine code will reach all its deadlines before they expire. For real-time programs, externally observable input and output variables are essential. These differ from local variables in that their values are observable over the duration of the execution of the program. Hence procedures require input and output parameter mechanisms that are references to the actual parameters so that changes to external inputs are observable within the procedure and changes to output parameters are externally observable. In addition, we allow value and result parameters. These may be auxiliary parameters, which are used for reasoning about the correctness of real-time programs as well as in the expression of timing deadlines, but do not lead to any code being generated for them by a compiler. (c) 2006 Elsevier B.V. All rights reserved.

Specific detection of enterovirus 71 directly from clinical specimens using real-time RT-PCR hybridization probe assay

Enterovirus 71 (EV71) is one of the main causative agents of hand, foot and mouth disease (HFMD) in young children. Infections caused by EV71 could lead to many complications, ranging from brainstem encephalitis to pulmonary oedema, resulting in high mortality. Thus, rapid detection of the virus is required to enable measures to be implemented in preventing widespread transmission. Based on primers and probes targeting at the VP1 region, a real-time reverse-transcriptase polymerase chain reaction (RT-PCR) hybridization probe assay was developed for specific detection of EV71 from clinical specimens. Quantitative analysis showed that the assay was able to detect as low as 5 EV71 viral copies and EV71 was detected from 46 of the 55 clinical specimens obtained from pediatric patients suffering from HFMD during the period from 2000 to 2003 in Singapore. This study showed that the single tube real-time RT-PCR assay developed in this study can be applied as a rapid and sensitive method for specific detection of EV71 directly from clinical specimens. (c) 2005 Elsevier Ltd. All rights reserved.

Does naltrexone treatment lead to depression? Findings from a randomized controlled trial in subjects with opioid dependence

Objective: Dysphoria and depression have been cited as side effects of the opioid antagonist naltrexone. We aimed to assess whether depressive symptoms are a clinically relevant side effect in a population receiving naltrexone as a treatment for opioid dependence. Methods: We carried out a randomized controlled, open-label trial comparing rapid opiate detoxification under anesthesia and naltrexone treatment with continued methadone maintenance at the Alcohol and Drug Service, Royal Brisbane and Women's Hospital, Brisbane, Australia. The study subjects were patients stabilized on methadone maintenance treatment for heroin dependence who wished to transfer to naltrexone treatment. The Beck Depression Inventory, State-Trait Anxiety Inventory and Opiate Treatment Index subscales for heroin use and social functioning were used at baseline and follow-up assessments at 1, 2, 3 and 6 months. Results: Forty-two participants were allocated to receive naltrexone treatment, whereas 38 continued methadone maintenance as the control condition. Participants who received naltrexone did not exhibit worsening of depressive symptoms. In participants attending all follow-up assessments, there was a trend for those receiving naltrexone to exhibit an improvement in depression over time compared with the control group. Participants who were adherent to naltrexone treatment exhibited fewer depressive symptoms than those who were nonadherent. Conclusions: These results suggest that depression need not be considered a common adverse effect of naltrexone treatment or a treatment contraindication and that engaging with or adhering to naltrexone treatment may be associated with fewer depressive symptoms.

Rapid detection of a chromosomally mediated penicillin resistance-associated ponA mutation in Neisseria gonorrhoeae using a real-time PCR assay

The recent emergence of a decreased susceptibility of Neisseria gonorrhoeae strains to penicillin in New Caledonia has lead clinicians to operate a change in the treatment strategy. In addition, this important health issue has emphasized the need for a rapid means of detecting penicillin resistance in N. gonorrhoeae in order to select an effective treatment and limit the spread of resistant strains. In recent years, the use of fluorescence resonance energy transfer on the LightCycler has proven to be a valuable tool for the screening of mutations occurring in the genome of various microorganisms. In this study, we developed a real-time PCR assay coupled with a fluorometric hybridization probes system to detect a penicillin resistance-associated mutation on the N. gonorrhoeae ponA gene. Following an extensive evaluation involving 136 isolates, melting curve analysis correctly evidenced a 5 degrees C T-m shift in all N. gonorrhoeae strains possessing this mutation, as determined by conventional sequencing analysis. Moreover, the mutation profiles obtained with the real-time PCR showed good correlation with the pattern of penicillin susceptibility generated with classical antibiograms. Overall, our molecular assay allowed an accurate and reproducible determination of the susceptibility to penicillin corresponding to a mutation present in all chromosomally mediated resistant strains of N. gonorrhoeae.

Three-factor models versus time series models:quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data

Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant.

The valuation of travel time savings in least developed countries:theoretical and empirical challenges and results from a field study

In developed countries travel time savings can account for as much as 80% of the overall benefits arising from transport infrastructure and service improvements. In developing countries they are generally ignored in transport project appraisals, notwithstanding their importance. One of the reasons for ignoring these benefits in the developing countries is that there is insufficient empirical evidence to support the conventional models for valuing travel time where work patterns, particularly of the poor, are diverse and it is difficult to distinguish between work and non-work activities. The exclusion of time saving benefits may lead to a bias against investment decisions that benefit the poor and understate the poverty reduction potential of transport investments in Least Developed Countries (LDCs). This is because the poor undertake most travel and transport by walking and headloading on local roads, tracks and paths and improvements of local infrastructure and services bring large time saving benefits for them through modal shifts. The paper reports on an empirical study to develop a methodology for valuing rural travel time savings in the LDCs. Apart from identifying the theoretical and empirical issues in valuing travel time savings in the LDCs, the paper presents and discusses the results of an analysis of data from Bangladesh. Some of the study findings challenge the conventional wisdom concerning the time saving values. The Bangladesh study suggests that the western concept of dividing travel time savings into working and non-working time savings is broadly valid in the developing country context. The study validates the use of preference methods in valuing non-working time saving values. However, stated preference (SP) method is more appropriate than revealed preference (RP) method.

Does nuclear tissue infected with bacteria following disc herniations lead to Modic changes in the adjacent vertebrae?

Purpose To investigate the prevalence of infected herniated nucleus material in lumbar disc herniations and to determine if patients with an anaerobic infected disc are more likely to develop Modic change (MC) (bone oedema) in the adjacent vertebrae after the disc herniation. MCs (bone oedema) in vertebrae are observed in 6 % of the general population and in 35-40 % of people with low back pain. These changes are strongly associated with low back pain. There are probably a mechanical cause and an infective cause that causes MC. Several studies on nuclear tissue from herniated discs have demonstrated the presence of low virulent anaerobic microorganisms, predominantly Propionibacterium acnes, in 7-53 % of patients. At the time of a herniation these low virulent anaerobic bacteria may enter the disc and give rise to an insidious infection. Local inflammation in the adjacent bone may be a secondary effect due to cytokine and propionic acid production. Methods Patients undergoing primary surgery at a single spinal level for lumbar disc herniation with an MRI-confirmed lumbar disc herniation, where the annular fibres were penetrated by visible nuclear tissue, had the nucleus material removed. Stringent antiseptic sterile protocols were followed. Results Sixty-one patients were included, mean age 46.4 years (SD 9.7), 27 % female. All patients were immunocompetent. No patient had received a previous epidural steroid injection or undergone previous back surgery. In total, microbiological cultures were positive in 28 (46 %) patients. Anaerobic cultures were positive in 26 (43 %) patients, and of these 4 (7 %) had dual microbial infections, containing both one aerobic and one anaerobic culture. No tissue specimens had more than two types of bacteria identified. Two (3 %) cultures only had aerobic bacteria isolated. In the discs with a nucleus with anaerobic bacteria, 80 % developed new MC in the vertebrae adjacent to the previous disc herniation. In contrast, none of those with aerobic bacteria and only 44 % of patients with negative cultures developed new MC. The association between an anaerobic culture and new MCs is highly statistically significant (P = 0.0038), with an odds ratio of 5.60 (95 % CI 1.51-21.95). Conclusion These findings support the theory that the occurrence of MCs Type 1 in the vertebrae adjacent to a previously herniated disc may be due to oedema surrounding an infected disc. The discs infected with anaerobic bacteria were more likely (P<0.0038) to develop MCs in the adjacent vertebrae than those in which no bacteria were found or those in which aerobic bacteria were found. © Springer-Verlag Berlin Heidelberg 2013.

Time scale analysis for fluidized bed melt granulation I: granule-granule and granule-droplet collision rates

Fluidized bed spray granulators (FBMG) are widely used in the process industry for particle size growth; a desirable feature in many products, such as granulated food and medical tablets. In this paper, the first in a series of four discussing the rate of various microscopic events occurring in FBMG, theoretical analysis coupled with CFD simulations have been used to predict granule–granule and droplet–granule collision time scales. The granule–granule collision time scale was derived from principles of kinetic theory of granular flow (KTGF). For the droplet–granule collisions, two limiting models were derived; one is for the case of fast droplet velocity, where the granule velocity is considerable lower than that of the droplet (ballistic model) and another for the case where the droplet is traveling with a velocity similar to the velocity of the granules. The hydrodynamic parameters used in the solution of the above models were obtained from the CFD predictions for a typical spray fluidized bed system. The granule–granule collision rate within an identified spray zone was found to fall approximately within the range of 10-2–10-3 s, while the droplet–granule collision was found to be much faster, however, slowing rapidly (exponentially) when moving away from the spray nozzle tip. Such information, together with the time scale analysis of droplet solidification and spreading, discussed in part II and III of this study, are useful for probability analysis of the various event occurring during a granulation process, which then lead to be better qualitative and, in part IV, quantitative prediction of the aggregation rate.

Does reviewing lead to better learning and decision making? Answers from a randomized stock market experiment

Background - The literature is not univocal about the effects of Peer Review (PR) within the context of constructivist learning. Due to the predominant focus on using PR as an assessment tool, rather than a constructivist learning activity, and because most studies implicitly assume that the benefits of PR are limited to the reviewee, little is known about the effects upon students who are required to review their peers. Much of the theoretical debate in the literature is focused on explaining how and why constructivist learning is beneficial. At the same time these discussions are marked by an underlying presupposition of a causal relationship between reviewing and deep learning. Objectives - The purpose of the study is to investigate whether the writing of PR feedback causes students to benefit in terms of: perceived utility about statistics, actual use of statistics, better understanding of statistical concepts and associated methods, changed attitudes towards market risks, and outcomes of decisions that were made. Methods - We conducted a randomized experiment, assigning students randomly to receive PR or non–PR treatments and used two cohorts with a different time span. The paper discusses the experimental design and all the software components that we used to support the learning process: Reproducible Computing technology which allows students to reproduce or re–use statistical results from peers, Collaborative PR, and an AI–enhanced Stock Market Engine. Results - The results establish that the writing of PR feedback messages causes students to experience benefits in terms of Behavior, Non–Rote Learning, and Attitudes, provided the sequence of PR activities are maintained for a period that is sufficiently long.

Analysis and Data Mining of Lead-Zinc Ore Data

This paper presents the results of our data mining study of Pb-Zn (lead-zinc) ore assay records from a mine enterprise in Bulgaria. We examined the dataset, cleaned outliers, visualized the data, and created dataset statistics. A Pb-Zn cluster data mining model was created for segmentation and prediction of Pb-Zn ore assay data. The Pb-Zn cluster data model consists of five clusters and DMX queries. We analyzed the Pb-Zn cluster content, size, structure, and characteristics. The set of the DMX queries allows for browsing and managing the clusters, as well as predicting ore assay records. A testing and validation of the Pb-Zn cluster data mining model was developed in order to show its reasonable accuracy before beingused in a production environment. The Pb-Zn cluster data mining model can be used for changes of the mine grinding and floatation processing parameters in almost real-time, which is important for the efficiency of the Pb-Zn ore beneficiation process. ACM Computing Classification System (1998): H.2.8, H.3.3.