Practical application and statistical analysis of titrimetric monitoring of water and sludge samples

Titrimetry offers the possibility of simultaneous measurement at low cost of several (buffering) components. A first step in the study towards practical application of the titrimetric technique was the titrimetric analysis by up- or down-titration of standard solutions, standard mixtures, solids digester samples and water samples coming from autotrophic nitrogen-removal reactors. The resulting raw data were further processed with an Excel-based program. This program first converts the raw data into a buffer curve upon which a linear buffer capacity model is fitted to the experimental data by estimating the (buffer) concentrations and corresponding pKa values. As such the type of component and the concentration can be determined. As a second step the resulting calculated concentrations were analysed statistically to assess the accuracy and precision of the titrimetric technique. For this purpose, the data were paired, i.e. the difference between the concentration obtained with titrimetry and the concentration obtained with another technique such as colorimetry or gas chromatography was calculated. First the normality of the paired data was assessed. Then, a paired t-test (normal data) or a paired Wilcoxon test (normal data) was used to statistically compare the results obtained with the titrimetric technique to either the stock solution concentration or measurements with another method (colorimetry or gas chromatography). The statistical tests showed that, depending on the titrant concentration, concentrations from 50 mg/. to 3 000 mg/. could adequately be measured with the titrimetric technique

Identifying brain changes related to cognitive aging using VBM and visual rating scales

Aging is often associated with changes in brain structures as well as in cognitive functions. Structural changes can be visualized with Magnetic Resonance Imaging (MRI) using voxel-based grey matter morphometry (VBM) and visual rating scales to assess atrophy level. Several MRI studies have shown that possible neural correlates of cognitive changes can be seen in normal aging. It is still not fully understood how cognitive function as measured by tests and demographic factors are related to brain changes in the MRI. We recruited 55 healthy elderly subjects aged 50–79 years. A battery of cognitive tests was administered to all subjects prior to MRI scanning. Our aim was to assess correlations between age, sex, education, cognitive test performance, and the said two MRI-based measures. Our results show significant differences in VBM grey matter volume for education level (≤ 12 vs. > 12 years), with a smaller amount of grey matter volume in subjects with lower educational levels, and for age in interaction with education, indicating larger grey matter volume for young, higher educated adults. Also, grey matter volume was found to be correlated with working memory function (Digit Span Backward). Furthermore, significant positive correlations were found between visual ratings and both age and education, showing larger atrophy levels with increasing age and decreasing level of education. These findings provide supportive evidence that MRI-VBM detects structural differences for education level, and correlates with educational level and age, and working memory task performance.</p

White matter connectome correlates of auditory over-responsivity: edge density imaging and machine-learning classifiers

Sensory over-responsivity (SOR) commonly involves auditory and/or tactile domains, and can affect children with or without additional neurodevelopmental challenges. In this study, we examined white matter microstructural and connectome correlates of auditory over-responsivity (AOR), analyzing prospectively collected data from 39 boys, aged 8–12 years. In addition to conventional diffusion tensor imaging (DTI) maps – including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD); we used DTI and high-resolution T1 scans to develop connectome Edge Density (ED) maps. The tract-based spatial statistics was used for voxel-wise comparison of diffusion and ED maps. Then, stepwise penalized logistic regression was applied to identify independent variable (s) predicting AOR, as potential imaging biomarker (s) for AOR. Finally, we compared different combinations of machine learning algorithms (i.e., naïve Bayes, random forest, and support vector machine (SVM) and tract-based DTI/connectome metrics for classification of children with AOR. In direct sensory phenotype assessment, 15 (out of 39) boys exhibited AOR (with or without neurodevelopmental concerns). Voxel-wise analysis demonstrates extensive impairment of white matter microstructural integrity in children with AOR on DTI maps – evidenced by lower FA and higher MD and RD; moreover, there was lower connectome ED in anterior-superior corona radiata, genu and body of corpus callosum. In stepwise logistic regression, the average FA of left superior longitudinal fasciculus (SLF) was the single independent variable distinguishing children with AOR (p = 0.007). Subsequently, the left SLF average FA yielded an area under the curve of 0.756 in receiver operating characteristic analysis for prediction of AOR (p = 0.008) as a region-of-interest (ROI)-based imaging biomarker. In comparative study of different combinations of machine-learning models and DTI/ED metrics, random forest algorithms using ED had higher accuracy for AOR classification. Our results demonstrate extensive white matter microstructural impairment in children with AOR, with specifically lower connectomic ED in anterior-superior tracts and associated commissural pathways. Also, average FA of left SLF can be applied as ROI-based imaging biomarker for prediction of SOR. Finally, machine-learning models can provide accurate and objective image-based classifiers for identification of children with AOR based on white matter tracts connectome ED

For a Migrant Art: Samuel Beckett and Cultural Nationalism

This essay charts Samuel Beckett’s linguistic migration from English to French at the end of the Second World War, locating this within the context of other twentieth-century literary migrations. It then proceeds to identify some of the principal ways in which Beckett seeks to resist forms of cultural nationalism (Irish, French and German). The distance that Beckett takes from these European forms of cultural nationalism is reflected not only in the migrant status of his characters, but also in the way in which he deploys national-cultural references. The essay argues that Beckett’s aim in this respect bears comparison with that of the ‘good European’ as defined by Nietzsche. An important difference, however, is that in Beckett’s case the emphasis falls not upon cosmopolitanism but rather upon a perpetual migrancy that is captured above all in his movement between languages

Process evaluation of appreciative inquiry to translate pain management evidence into pediatric nursing practice

Background Appreciative inquiry (AI) is an innovative knowledge translation (KT) intervention that is compatible with the Promoting Action on Research in Health Services (PARiHS) framework. This study explored the innovative use of AI as a theoretically based KT intervention applied to a clinical issue in an inpatient pediatric care setting. The implementation of AI was explored in terms of its acceptability, fidelity, and feasibility as a KT intervention in pain management. Methods A mixed-methods case study design was used. The case was a surgical unit in a pediatric academic-affiliated hospital. The sample consisted of nurses in leadership positions and staff nurses interested in the study. Data on the AI intervention implementation were collected by digitally recording the AI sessions, maintaining logs, and conducting individual semistructured interviews. Data were analysed using qualitative and quantitative content analyses and descriptive statistics. Findings were triangulated in the discussion. Results Three nurse leaders and nine staff members participated in the study. Participants were generally satisfied with the intervention, which consisted of four 3-hour, interactive AI sessions delivered over two weeks to promote change based on positive examples of pain management in the unit and staff implementation of an action plan. The AI sessions were delivered with high fidelity and 11 of 12 participants attended all four sessions, where they developed an action plan to enhance evidence-based pain assessment documentation. Participants labeled AI a 'refreshing approach to change' because it was positive, democratic, and built on existing practices. Several barriers affected their implementation of the action plan, including a context of change overload, logistics, busyness, and a lack of organised follow-up. Conclusions Results of this case study supported the acceptability, fidelity, and feasibility of AI as a KT intervention in pain management. The AI intervention requires minor refinements (e.g., incorporating continued follow-up meetings) to enhance its clinical utility and sustainability. The implementation process and effectiveness of the modified AI intervention require evaluation in a larger multisite study

Attention wins over sensory attenuation in a sound detection task

'Sensory attenuation', i.e., reduced neural responses to self-induced compared to externally generated stimuli, is a well-established phenomenon. However, very few studies directly compared sensory attenuation with attention effect, which leads to increased neural responses. In this study, we brought sensory attenuation and attention together in a behavioural auditory detection task, where both effects were quantitatively measured and compared. The classic auditory attention effect of facilitating detection performance was replicated. When attention and sensory attenuation were both present, attentional facilitation decreased but remained significant. The results are discussed in the light of current theories of sensory attenuation

A Two-stage Flow-based Intrusion Detection Model ForNext-generation Networks

The next-generation network provides state-of-the-art access-independent services over converged mobile and fixed networks. Security in the converged network environment is a major challenge. Traditional packet and protocol-based intrusion detection techniques cannot be used in next-generation networks due to slow throughput, low accuracy and their inability to inspect encrypted payload. An alternative solution for protection of next-generation networks is to use network flow records for detection of malicious activity in the network traffic. The network flow records are independent of access networks and user applications. In this paper, we propose a two-stage flow-based intrusion detection system for next-generation networks. The first stage uses an enhanced unsupervised one-class support vector machine which separates malicious flows from normal network traffic. The second stage uses a self-organizing map which automatically groups malicious flows into different alert clusters. We validated the proposed approach on two flow-based datasets and obtained promising results

Study protocol: adjuvant holmium-166 radioembolization after radiofrequency ablation in early-stage hepatocellular carcinoma patients-a dose-finding study (HORA EST HCC Trial)

Purpose To investigate the biodistribution of holmium-166 microspheres (Ho-166-MS) when administered after radiofrequency ablation (RFA) of early-stage hepatocellular carcinoma (HCC). The aim is to establish a perfused liver administration dose that results in a tumoricidal dose of holmium-166 on the hyperaemic zone around the ablation necrosis (i.e. target volume). Materials and Methods This is a multicentre, prospective, dose-escalation study in HCC patients with a solitary lesion 2-5 cm, or a maximum of 3 lesions of = 120 Gy has been reached on the target volume in 9/10 patients of a cohort. Secondary endpoints include toxicity, local recurrence, disease-free and overall survival. Discussion This study aims to find the optimal administration dose of adjuvant radioembolization with Ho-166-MS after RFA. Ultimately, the goal is to bring the efficacy of thermal ablation up to par with surgical resection for early-stage HCC patients.Cellular mechanisms in basic and clinical gastroenterology and hepatolog