Predicting organic acid concentration from UV/vis spectrometry measurements - A comparison of machine learning techniques

The concentration of organic acids in anaerobic digesters is one of the most critical parameters for monitoring and advanced control of anaerobic digestion processes. Thus, a reliable online-measurement system is absolutely necessary. A novel approach to obtaining these measurements indirectly and online using UV/vis spectroscopic probes, in conjunction with powerful pattern recognition methods, is presented in this paper. An UV/vis spectroscopic probe from S::CAN is used in combination with a custom-built dilution system to monitor the absorption of fully fermented sludge at a spectrum from 200 to 750 nm. Advanced pattern recognition methods are then used to map the non-linear relationship between measured absorption spectra to laboratory measurements of organic acid concentrations. Linear discriminant analysis, generalized discriminant analysis (GerDA), support vector machines (SVM), relevance vector machines, random forest and neural networks are investigated for this purpose and their performance compared. To validate the approach, online measurements have been taken at a full-scale 1.3-MW industrial biogas plant. Results show that whereas some of the methods considered do not yield satisfactory results, accurate prediction of organic acid concentration ranges can be obtained with both GerDA and SVM-based classifiers, with classification rates in excess of 87% achieved on test data.

Dual-processes in learning and judgment:Evidence from the multiple cue probability learning paradigm

Multiple cue probability learning (MCPL) involves learning to predict a criterion based on a set of novel cues when feedback is provided in response to each judgment made. But to what extent does MCPL require controlled attention and explicit hypothesis testing? The results of two experiments show that this depends on cue polarity. Learning about cues that predict positively is aided by automatic cognitive processes, whereas learning about cues that predict negatively is especially demanding on controlled attention and hypothesis testing processes. In the studies reported here, negative, but not positive cue learning related to individual differences in working memory capacity both on measures of overall judgment performance and modelling of the implicit learning process. However, the introduction of a novel method to monitor participants' explicit beliefs about a set of cues on a trial-by-trial basis revealed that participants were engaged in explicit hypothesis testing about positive and negative cues, and explicit beliefs about both types of cues were linked to working memory capacity. Taken together, our results indicate that while people are engaged in explicit hypothesis testing during cue learning, explicit beliefs are applied to judgment only when cues are negative. © 2012 Elsevier Inc.

Cooperative Learning in Science: Follow-up from primary to high school

This paper reports a two-year longitudinal study of the effects of cooperative learning on science attainment, attitudes towards science, and social connectedness during transition from primary to high school. A previous project on cooperative learning in primary schools observed gains in science understanding and in social aspects of school life. This project followed 204 children involved in the previous project and 440 comparison children who were not as they undertook transition from 24 primary schools to 16 high schools. Cognitive, affective, and social gains observed in the original project survived transition. The implications improving the effectiveness of school transition by using cooperative learning initiatives are explored. Possibilities for future research and the implications for practice and policy are discussed.

Improving parameter learning of Bayesian nets from incomplete data

This paper addresses the estimation of parameters of a Bayesian network from incomplete data. The task is usually tackled by running the Expectation-Maximization (EM) algorithm several times in order to obtain a high log-likelihood estimate. We argue that choosing the maximum log-likelihood estimate (as well as the maximum penalized log-likelihood and the maximum a posteriori estimate) has severe drawbacks, being affected both by overfitting and model uncertainty. Two ideas are discussed to overcome these issues: a maximum entropy approach and a Bayesian model averaging approach. Both ideas can be easily applied on top of EM, while the entropy idea can be also implemented in a more sophisticated way, through a dedicated non-linear solver. A vast set of experiments shows that these ideas produce significantly better estimates and inferences than the traditional and widely used maximum (penalized) log-likelihood and maximum a posteriori estimates. In particular, if EM is adopted as optimization engine, the model averaging approach is the best performing one; its performance is matched by the entropy approach when implemented using the non-linear solver. The results suggest that the applicability of these ideas is immediate (they are easy to implement and to integrate in currently available inference engines) and that they constitute a better way to learn Bayesian network parameters.

Patience, Persistence and Pragmatism: Experiences and Lessons Learnt from the Implementation of Clinically Integrated Teaching and Learning of Evidence-Based Health Care - A Qualitative Study

Background

Clinically integrated teaching and learning are regarded as the best options for improving evidence-based healthcare (EBHC) knowledge, skills and attitudes. To inform implementation of such strategies, we assessed experiences and opinions on lessons learnt of those involved in such programmes.

Methods and Findings

We conducted semi-structured interviews with 24 EBHC programme coordinators from around the world, selected through purposive sampling. Following data transcription, a multidisciplinary group of investigators carried out analysis and data interpretation, using thematic content analysis. Successful implementation of clinically integrated teaching and learning of EBHC takes much time. Student learning needs to start in pre-clinical years with consolidation, application and assessment following in clinical years. Learning is supported through partnerships between various types of staff including the core EBHC team, clinical lecturers and clinicians working in the clinical setting. While full integration of EBHC learning into all clinical rotations is considered necessary, this was not always achieved. Critical success factors were pragmatism and readiness to use opportunities for engagement and including EBHC learning in the curriculum; patience; and a critical mass of the right teachers who have EBHC knowledge and skills and are confident in facilitating learning. Role modelling of EBHC within the clinical setting emerged as an important facilitator. The institutional context exerts an important influence; with faculty buy-in, endorsement by institutional leaders, and an EBHC-friendly culture, together with a supportive community of practice, all acting as key enablers. The most common challenges identified were lack of teaching time within the clinical curriculum, misconceptions about EBHC, resistance of staff, lack of confidence of tutors, lack of time, and negative role modelling.

Conclusions

Implementing clinically integrated EBHC curricula requires institutional support, a critical mass of the right teachers and role models in the clinical setting combined with patience, persistence and pragmatism on the part of teachers.

Failure-Free Survival and Radiotherapy in Patients With Newly Diagnosed Nonmetastatic Prostate Cancer: Data From Patients in the Control Arm of the STAMPEDE Trial

Importance: The natural history of patients with newly diagnosed high-risk nonmetastatic (M0) prostate cancer receiving hormone therapy (HT) either alone or with standard-of-care radiotherapy (RT) is not well documented. Furthermore, no clinical trial has assessed the role of RT in patients with node-positive (N+) M0 disease. The STAMPEDE Trial includes such individuals, allowing an exploratory multivariate analysis of the impact of radical RT.

Objective: To describe survival and the impact on failure-free survival of RT by nodal involvement in these patients.

Design, Setting, and Participants: Cohort study using data collected for patients allocated to the control arm (standard-of-care only) of the STAMPEDE Trial between October 5, 2005, and May 1, 2014. Outcomes are presented as hazard ratios (HRs) with 95% CIs derived from adjusted Cox models; survival estimates are reported at 2 and 5 years. Participants were high-risk, hormone-naive patients with newly diagnosed M0 prostate cancer starting long-term HT for the first time. Radiotherapy is encouraged in this group, but mandated for patients with node-negative (N0) M0 disease only since November 2011.

Exposures: Long-term HT either alone or with RT, as per local standard. Planned RT use was recorded at entry.

Main Outcomes and Measures: Failure-free survival (FFS) and overall survival.

Results: A total of 721 men with newly diagnosed M0 disease were included: median age at entry, 66 (interquartile range [IQR], 61-72) years, median (IQR) prostate-specific antigen level of 43 (18-88) ng/mL. There were 40 deaths (31 owing to prostate cancer) with 17 months' median follow-up. Two-year survival was 96% (95% CI, 93%-97%) and 2-year FFS, 77% (95% CI, 73%-81%). Median (IQR) FFS was 63 (26 to not reached) months. Time to FFS was worse in patients with N+ disease (HR, 2.02 [95% CI, 1.46-2.81]) than in those with N0 disease. Failure-free survival outcomes favored planned use of RT for patients with both N0M0 (HR, 0.33 [95% CI, 0.18-0.61]) and N+M0 disease (HR, 0.48 [95% CI, 0.29-0.79]).

Conclusions and Relevance: Survival for men entering the cohort with high-risk M0 disease was higher than anticipated at study inception. These nonrandomized data were consistent with previous trials that support routine use of RT with HT in patients with N0M0 disease. Additionally, the data suggest that the benefits of RT extend to men with N+M0 disease.

Trial Registration: clinicaltrials.gov Identifier: NCT00268476; ISRCTN78818544.

Do challenge, task experience or computer familiarity influence the learning of historical chronology from virtual environments in 8–9 year old children?

Studies examined the potential use of Virtual Environments (VEs) in teaching historical chronology to 127 children of primary school age (8–9 years). The use of passive fly-through VEs had been found, in an earlier study, to be disadvantageous with this age group when tested for their subsequent ability to place displayed sequential events in correct chronological order. All VEs in the present studies included active challenge, previously shown to enhance learning in older participants. Primary school children in the UK (all frequent computer users) were tested using UK historical materials, but no significant effect was found between three conditions (Paper, PowerPoint and VE) with minimal pre-training. However, excellent (error free) learning occurred when children were allowed greater exploration prior to training in the VE. In Ukraine, with children having much less computer familiarity, training in a VE (depicting Ukrainian history) produced better learning compared to PowerPoint, but no better than in a Paper condition. The results confirmed the benefit of using challenge in a VE with primary age children, but only with adequate prior familiarisation with the medium. Familiarity may reduce working memory load and increase children’s spatial memory capacity for acquiring sequential temporal-spatial information from virtual displays. Keywords: timeline, chronographics