Fully Adaptive Newton--Galerkin Methods for Semilinear Elliptic Partial Differential Equations

In this paper we develop an adaptive procedure for the numerical solution of general, semilinear elliptic problems with possible singular perturbations. Our approach combines both prediction-type adaptive Newton methods and a linear adaptive finite element discretization (based on a robust a posteriori error analysis), thereby leading to a fully adaptive Newton–Galerkin scheme. Numerical experiments underline the robustness and reliability of the proposed approach for various examples

Rapid parallel adaptive radiations from a single hybridogenic ancestral population

The Alpine lake whitefish (Coregonus lavaretus) species complex is a classic example of a recent radiation, associated with colonization of the Alpine lakes following the glacial retreat (less than 15 kyr BP). They have formed a unique array of endemic lake flocks, each with one to six described sympatric species differing in morphology, diet and reproductive ecology. Here, we present a genomic investigation of the relationships between and within the lake flocks. Comparing the signal between over 1000 AFLP loci and mitochondrial control region sequence data, we use phylogenetic tree-based and population genetic methods to reconstruct the phylogenetic history of the group and to delineate the principal centres of genetic diversity within the radiation. We find significant cytonuclear discordance showing that the genomically monophyletic Alpine whitefish clade arose from a hybrid swarm of at least two glacial refugial lineages. Within this radiation, we find seven extant genetic clusters centred on seven lake systems. Most interestingly, we find evidence of sympatric speciation within and parallel evolution of equivalent phenotypes among these lake systems. However, we also find the genetic signature of human-mediated gene flow and diversity loss within many lakes, highlighting the fragility of recent radiations.

[Arterial-adaptive dilatation and Doppler velocimetry in normal fetuses with a single umbilical artery]

PURPOSE: In this study we examined the arterial-adaptive dilatation and Doppler velocimetry, especially RI values, in normal fetuses with a single umbilical artery (SUA). MATERIALS AND METHODS: We studied 195 fetuses from 18 to 39 weeks of gestational age with a prenatally identified SUA retrospectively. They were enrolled in this study if the following information applied: > 18 weeks of gestational age, no structural or chromosomal abnormalities, and histopathological confirmation of SUA. Sonographic examination included evaluation of the umbilical artery resistance and the cross-sectional area of the umbilical cord, and its vessels were measured in all cases. Small for gestational age (SGA) was diagnosed when the birth weight was below the 10th percentile for gestational age. Fetuses with intrauterine growth restriction were defined as those with biometric data below the 5th percentile. RESULTS: There were 119 cases of prenatally identified SUA which met the inclusion criteria. RI values were below the 10th percentile in 33/119 (27.33) and below the 50th percentile in 73/119 (61.33). RI values below the 10th percentile were significantly more likely to be in the normal collective than in the growth restricted collective [31/87 (35.63%) vs. 2/32 (6.25%); p = 0.001]. Even more significant differences became apparent when comparing the RI values below the 50th percentile of both groups. An umbilical artery diameter over the 90th percentile was found in 49 (41.9%) of cases and was significantly more likely to be present in normal growing fetuses than in the growth restricted group. CONCLUSION: Normal fetuses with SUA are at higher risk to be born as SGA. With our study results we can confirm the hypothesis that Doppler flow measurements and arterial diameter in SUA are different from those found in normal fetal umbilical arteries. RI values over the 50th percentile or a cross-sectional area of the artery below 95th percentile after 26th week of gestation significantly increases the risk of SGA.

Coronary artery stents: influence of adaptive statistical iterative reconstruction on image quality using 64-HDCT

OBJECTIVE: The assessment of coronary stents with present-generation 64-detector row computed tomography (HDCT) scanners is limited by image noise and blooming artefacts. We evaluated the performance of adaptive statistical iterative reconstruction (ASIR) for noise reduction in coronary stent imaging with HDCT. METHODS AND RESULTS: In 50 stents of 28 patients (mean age 64 ± 10 years) undergoing coronary CT angiography (CCTA) on an HDCT scanner the mean in-stent luminal diameter, stent length, image quality, in-stent contrast attenuation, and image noise were assessed. Studies were reconstructed using filtered back projection (FBP) and ASIR-FBP composites. ASIR resulted in reduced image noise vs. FBP (P < 0.0001). Two readers graded the CCTA stent image quality on a 4-point Likert scale and determined the proportion of interpretable stent segments. The best image quality for all clinical images was obtained with 40 and 60% ASIR with significantly larger luminal area visualization compared with FBP (+42.1 ± 5.4% with 100% ASIR vs. FBP alone; P < 0.0001) while the stent length was decreased (-4.7 ± 0.9%,

Locomotor velocity and striatal adaptive gene expression changes of the direct and indirect pathways in Parkinsonian rats

BACKGROUND In Parkinson's disease (PD), bradykinesia, or slowness of movement, only appears after a large striatal dopamine depletion. Compensatory mechanisms probably play a role in this delayed appearance of symptoms. OBJECTIVE Our hypothesis is that the striatal direct and indirect pathways participate in these compensatory mechanisms. METHODS We used the unilateral 6-hydroxydopamine (6-OHDA) rat model of PD and control animals. Four weeks after the lesion, the spontaneous locomotor activity of the rats was measured and then the animals were killed and their brain extracted. We quantified the mRNA expression of markers of the striatal direct and indirect pathways as well as the nigral expression of dopamine transporter (DAT) and tyrosine hydroxylase (TH) mRNA. We also carried out an immunohistochemistry for the striatal TH protein expression. RESULTS As expected, the unilateral 6-OHDA rats presented a tendency to an ipsilateral head turning and a low locomotor velocity. In 6-OHDA rats only, we observed a significant and positive correlation between locomotor velocity and both D1-class dopamine receptor (D1R) (direct pathway) and enkephalin (ENK) (indirect pathway) mRNA in the lesioned striatum, as well as between D1R and ENK mRNA. CONCLUSIONS Our results demonstrate a strong relationship between both direct and indirect pathways and spontaneous locomotor activity in the parkinsonian rat model. We suggest a synergy between both pathways which could play a role in compensatory mechanisms and may contribute to the delayed appearance of bradykinesia in PD.

An Early-Warning System for Hypo-/Hyperglycemic Events Based on Fusion of Adaptive Prediction Models

Introduction: Early warning of future hypoglycemic and hyperglycemic events can improve the safety of type 1 diabetes mellitus (T1DM) patients. The aim of this study is to design and evaluate a hypoglycemia / hyperglycemia early warning system (EWS) for T1DM patients under sensor-augmented pump (SAP) therapy. Methods: The EWS is based on the combination of data-driven online adaptive prediction models and a warning algorithm. Three modeling approaches have been investigated: (i) autoregressive (ARX) models, (ii) auto-regressive with an output correction module (cARX) models, and (iii) recurrent neural network (RNN) models. The warning algorithm performs postprocessing of the models′ outputs and issues alerts if upcoming hypoglycemic/hyperglycemic events are detected. Fusion of the cARX and RNN models, due to their complementary prediction performances, resulted in the hybrid autoregressive with an output correction module/recurrent neural network (cARN)-based EWS. Results: The EWS was evaluated on 23 T1DM patients under SAP therapy. The ARX-based system achieved hypoglycemic (hyperglycemic) event prediction with median values of accuracy of 100.0% (100.0%), detection time of 10.0 (8.0) min, and daily false alarms of 0.7 (0.5). The respective values for the cARX-based system were 100.0% (100.0%), 17.5 (14.8) min, and 1.5 (1.3) and, for the RNN-based system, were 100.0% (92.0%), 8.4 (7.0) min, and 0.1 (0.2). The hybrid cARN-based EWS presented outperforming results with 100.0% (100.0%) prediction accuracy, detection 16.7 (14.7) min in advance, and 0.8 (0.8) daily false alarms. Conclusion: Combined use of cARX and RNN models for the development of an EWS outperformed the single use of each model, achieving accurate and prompt event prediction with few false alarms, thus providing increased safety and comfort.

Adaptive Algorithms for Personalized Diabetes Treatment

Dynamic systems, especially in real-life applications, are often determined by inter-/intra-variability, uncertainties and time-varying components. Physiological systems are probably the most representative example in which population variability, vital signal measurement noise and uncertain dynamics render their explicit representation and optimization a rather difficult task. Systems characterized by such challenges often require the use of adaptive algorithmic solutions able to perform an iterative structural and/or parametrical update process towards optimized behavior. Adaptive optimization presents the advantages of (i) individualization through learning of basic system characteristics, (ii) ability to follow time-varying dynamics and (iii) low computational cost. In this chapter, the use of online adaptive algorithms is investigated in two basic research areas related to diabetes management: (i) real-time glucose regulation and (ii) real-time prediction of hypo-/hyperglycemia. The applicability of these methods is illustrated through the design and development of an adaptive glucose control algorithm based on reinforcement learning and optimal control and an adaptive, personalized early-warning system for the recognition and alarm generation against hypo- and hyperglycemic events.

Adaptive servo-ventilation as treatment of persistent central sleep apnea in post-acute ischemic stroke patients.

BACKGROUND Adaptive servo-ventilation (ASV) is a well-established treatment of central sleep apnea (CSA) related to congestive heart failure (CHF). Few studies have evaluated the effectiveness and adherence in patients with CSA of other etiologies, and even less is known about treatment of CSA in patients of post ischemic stroke. METHODS A single-centre retrospective analysis of ASV treatment for CSA in post-acute ischemic stroke patients without concomitant CHF was performed. Demographics, clinical data, sleep studies, ventilator settings, and adherence data were evaluated. RESULTS Out of 154 patients on ASV, 15 patients had CSA related to ischemic stroke and were started on ASV a median of 11 months after the acute cerebrovascular event. Thirteen out of the 15 patients were initially treated with continuous positive airway pressure (11/15) and bilevel positive airway pressure (2/15) therapy with unsatisfactory control of CSA. ASV significantly improved AHI (46.7 ± 24.3 vs 8.5 ± 12/h, P = 0.001) and reduced ESS (8.7 ± 5.7 vs 5.6 ± 2.5, P = 0.08) with a mean nightly use of ASV of 5.4 ± 2.4 h at 3 months after the initiation of treatment. Results were maintained at 6 months. CONCLUSION ASV was well tolerated and clinically effective in this group of patients with persistent CSA after ischemic stroke.

Addition of docetaxel, zoledronic acid, or both to first-line long-term hormone therapy in prostate cancer (STAMPEDE): survival results from an adaptive, multiarm, multistage, platform randomised controlled trial

BACKGROUND Long-term hormone therapy has been the standard of care for advanced prostate cancer since the 1940s. STAMPEDE is a randomised controlled trial using a multiarm, multistage platform design. It recruits men with high-risk, locally advanced, metastatic or recurrent prostate cancer who are starting first-line long-term hormone therapy. We report primary survival results for three research comparisons testing the addition of zoledronic acid, docetaxel, or their combination to standard of care versus standard of care alone. METHODS Standard of care was hormone therapy for at least 2 years; radiotherapy was encouraged for men with N0M0 disease to November, 2011, then mandated; radiotherapy was optional for men with node-positive non-metastatic (N+M0) disease. Stratified randomisation (via minimisation) allocated men 2:1:1:1 to standard of care only (SOC-only; control), standard of care plus zoledronic acid (SOC + ZA), standard of care plus docetaxel (SOC + Doc), or standard of care with both zoledronic acid and docetaxel (SOC + ZA + Doc). Zoledronic acid (4 mg) was given for six 3-weekly cycles, then 4-weekly until 2 years, and docetaxel (75 mg/m(2)) for six 3-weekly cycles with prednisolone 10 mg daily. There was no blinding to treatment allocation. The primary outcome measure was overall survival. Pairwise comparisons of research versus control had 90% power at 2·5% one-sided α for hazard ratio (HR) 0·75, requiring roughly 400 control arm deaths. Statistical analyses were undertaken with standard log-rank-type methods for time-to-event data, with hazard ratios (HRs) and 95% CIs derived from adjusted Cox models. This trial is registered at ClinicalTrials.gov (NCT00268476) and ControlledTrials.com (ISRCTN78818544). FINDINGS 2962 men were randomly assigned to four groups between Oct 5, 2005, and March 31, 2013. Median age was 65 years (IQR 60-71). 1817 (61%) men had M+ disease, 448 (15%) had N+/X M0, and 697 (24%) had N0M0. 165 (6%) men were previously treated with local therapy, and median prostate-specific antigen was 65 ng/mL (IQR 23-184). Median follow-up was 43 months (IQR 30-60). There were 415 deaths in the control group (347 [84%] prostate cancer). Median overall survival was 71 months (IQR 32 to not reached) for SOC-only, not reached (32 to not reached) for SOC + ZA (HR 0·94, 95% CI 0·79-1·11; p=0·450), 81 months (41 to not reached) for SOC + Doc (0·78, 0·66-0·93; p=0·006), and 76 months (39 to not reached) for SOC + ZA + Doc (0·82, 0·69-0·97; p=0·022). There was no evidence of heterogeneity in treatment effect (for any of the treatments) across prespecified subsets. Grade 3-5 adverse events were reported for 399 (32%) patients receiving SOC, 197 (32%) receiving SOC + ZA, 288 (52%) receiving SOC + Doc, and 269 (52%) receiving SOC + ZA + Doc. INTERPRETATION Zoledronic acid showed no evidence of survival improvement and should not be part of standard of care for this population. Docetaxel chemotherapy, given at the time of long-term hormone therapy initiation, showed evidence of improved survival accompanied by an increase in adverse events. Docetaxel treatment should become part of standard of care for adequately fit men commencing long-term hormone therapy. FUNDING Cancer Research UK, Medical Research Council, Novartis, Sanofi-Aventis, Pfizer, Janssen, Astellas, NIHR Clinical Research Network, Swiss Group for Clinical Cancer Research.

More adaptive versus less maladaptive coping: What is more predictive of symptom severity? Development of a new scale to investigate coping profiles across different psychopathological syndromes

BACKGROUND: Lack of adaptive and enhanced maladaptive coping with stress and negative emotions are implicated in many psychopathological disorders. We describe the development of a new scale to investigate the relative contribution of different coping styles to psychopathology in a large population sample. We hypothesized that the magnitude of the supposed positive correlation between maladaptive coping and psychopathology would be stronger than the supposed negative correlation between adaptive coping and psychopathology. We also examined whether distinct coping style patterns emerge for different psychopathological syndromes. METHODS: A total of 2200 individuals from the general population participated in an online survey. The Patient Health Questionnaire-9 (PHQ-9), the Obsessive-Compulsive Inventory revised (OCI-R) and the Paranoia Checklist were administered along with a novel instrument called Maladaptive and Adaptive Coping Styles (MAX) questionnaire. Participants were reassessed six months later. RESULTS: MAX consists of three dimensions representing adaptive coping, maladaptive coping and avoidance. Across all psychopathological syndromes, similar response patterns emerged. Maladaptive coping was more strongly related to psychopathology than adaptive coping both cross-sectionally and longitudinally. The overall number of coping styles adopted by an individual predicted greater psychopathology. Mediation analysis suggests that a mild positive relationship between adaptive and certain maladaptive styles (emotional suppression) partially accounts for the attenuated relationship between adaptive coping and depressive symptoms. LIMITATIONS: Results should be replicated in a clinical population. CONCLUSIONS: Results suggest that maladaptive and adaptive coping styles are not reciprocal. Reducing maladaptive coping seems to be more important for outcome than enhancing adaptive coping. The study supports transdiagnostic approaches advocating that maladaptive coping is a common factor across different psychopathologies.

Recent Advances in Adaptive Sampling and Reconstruction for Monte Carlo Rendering

Monte Carlo integration is firmly established as the basis for most practical realistic image synthesis algorithms because of its flexibility and generality. However, the visual quality of rendered images often suffers from estimator variance, which appears as visually distracting noise. Adaptive sampling and reconstruction algorithms reduce variance by controlling the sampling density and aggregating samples in a reconstruction step, possibly over large image regions. In this paper we survey recent advances in this area. We distinguish between “a priori” methods that analyze the light transport equations and derive sampling rates and reconstruction filters from this analysis, and “a posteriori” methods that apply statistical techniques to sets of samples to drive the adaptive sampling and reconstruction process. They typically estimate the errors of several reconstruction filters, and select the best filter locally to minimize error. We discuss advantages and disadvantages of recent state-of-the-art techniques, and provide visual and quantitative comparisons. Some of these techniques are proving useful in real-world applications, and we aim to provide an overview for practitioners and researchers to assess these approaches. In addition, we discuss directions for potential further improvements.

Denoising Your Monte Carlo Renders: Recent Advances in Image Space-Adaptive Sampling and Reconstruction

With the ongoing shift in the computer graphics industry toward Monte Carlo rendering, there is a need for effective, practical noise-reduction techniques that are applicable to a wide range of rendering effects and easily integrated into existing production pipelines. This course surveys recent advances in image-space adaptive sampling and reconstruction algorithms for noise reduction, which have proven very effective at reducing the computational cost of Monte Carlo techniques in practice. These approaches leverage advanced image-filtering techniques with statistical methods for error estimation. They are attractive because they can be integrated easily into conventional Monte Carlo rendering frameworks, they are applicable to most rendering effects, and their computational overhead is modest.