Bayesian Analysis of Femtosecond Pump-Probe Photoelectron-Photoion Coincidence Spectra with Fluctuating Laser Intensities

This paper employs Bayesian probability theory for analyzing data generated in femtosecond pump-probe photoelectron-photoion coincidence (PEPICO) experiments. These experiments allow investigating ultrafast dynamical processes in photoexcited molecules. Bayesian probability theory is consistently applied to data analysis problems occurring in these types of experiments such as background subtraction and false coincidences. We previously demonstrated that the Bayesian formalism has many advantages, amongst which are compensation of false coincidences, no overestimation of pump-only contributions, significantly increased signal-to-noise ratio, and applicability to any experimental situation and noise statistics. Most importantly, by accounting for false coincidences, our approach allows running experiments at higher ionization rates, resulting in an appreciable reduction of data acquisition times. In addition to our previous paper, we include fluctuating laser intensities, of which the straightforward implementation highlights yet another advantage of the Bayesian formalism. Our method is thoroughly scrutinized by challenging mock data, where we find a minor impact of laser fluctuations on false coincidences, yet a noteworthy influence on background subtraction. We apply our algorithm to data obtained in experiments and discuss the impact of laser fluctuations on the data analysis

Reinforcement learning for safety-critical control of an automated vehicle

We present our approach for the development, validation and deployment of a data-driven decision-making function for the automated control of a vehicle. The decisionmaking function, based on an artificial neural network is trained to steer the mobile robot SPIDER towards a predefined, static path to a target point while avoiding collisions with obstacles along the path. The training is conducted by means of proximal policy optimisation (PPO), a state of the art algorithm from the field of reinforcement learning. The resulting controller is validated using KPIs quantifying its capability to follow a given path and its reactivity on perceived obstacles along the path. The corresponding tests are carried out in the training environment. Additionally, the tests shall be performed as well in the robotics situation Gazebo and in real world scenarios. For the latter the controller is deployed on a FPGA-based development platform, the FRACTAL platform, and integrated into the SPIDER software stack

Birch pollen induces toll-like receptor 4-dependent dendritic cell activation favoring t cell responses

Seasonal exposure to birch pollen (BP) is a major cause of pollinosis. The specific role of Toll-like receptor 4 (TLR4) in BP-induced allergic inflammation and the identification of key factors in birch pollen extracts (BPE) initiating this process remain to be explored. This study aimed to examine (i) the importance of TLR4 for dendritic cell (DC) activation by BPE, (ii) the extent of the contribution of BPE-derived lipopolysaccharide (LPS) and other potential TLR4 adjuvant(s) in BPE, and (iii) the relevance of the TLR4-dependent activation of BPE-stimulated DCs in the initiation of an adaptive immune response. In vitro, activation of murine bone marrow-derived DCs (BMDCs) and human monocyte-derived DCs by BPE or the equivalent LPS (nLPS) was analyzed by flow cytometry. Polymyxin B (PMB), a TLR4 antagonist and TLR4-deficient BMDCs were used to investigate the TLR4 signaling in DC activation. The immunostimulatory activity of BPE was compared to protein-/lipid-depleted BPE-fractions. In co-cultures of BPE-pulsed BMDCs and Bet v 1-specific hybridoma T cells, the influence of the TLR4-dependent DC activation on T cell activation was analyzed. In vivo immunization of IL-4 reporter mice was conducted to study BPE-induced Th2 polarization upon PMB pre-treatment. Murine and human DC activation induced by either BPE or nLPS was inhibited by the TLR4 antagonist or by PMB, and abrogated in TLR4-deficient BMDCs compared to wild-type BMDCs. The lipid-free but not the protein-free fraction showed a reduced capacity to activate the TLR4 signaling and murine DCs. In human DCs, nLPS only partially reproduced the BPE-induced activation intensity. BPE-primed BMDCs efficiently stimulated T cell activation, which was repressed by the TLR4 antagonist or PMB, and the addition of nLPS to Bet v 1 did not reproduce the effect of BPE. In vivo, immunization with BPE induced a significant Th2 polarization, whereas administration of BPE pre-incubated with PMB showed a decreased tendency. These findings suggest that TLR4 is a major pathway by which BPE triggers DC activation that is involved in the initiation of adaptive immune responses. Further characterization of these BP-derived TLR4 adjuvants could provide new candidates for therapeutic strategies targeting specific mechanisms in BP-induced allergic inflammation

Fundamental challenges in designing a collaborative travel app

The growing capabilities of smartphones have opened up new opportunities for travel coordination and transport is a fertile area for app development. One stream of development is apps that enable collaborative travel, either in the form of lift sharing or collaborative shopping, but despite growing interest from governmental agencies, there is little evidence of the efficacy of such apps. Based on trials of purpose built travel collaboration apps, deployed in tourism, urban and rural residential communities, and logistics, this paper analyses the fundamental challenges facing users adopting such travel apps. The findings suggest that transport practitioners, policy makers and app developers need to better understand the challenges associated with attracting users, the use of incentives and the types of communities most appropriate to implement collaborative travel concepts using such approaches. Also, how the users’ sense of time pressure and the issues around reciprocal exchange can impact on their long-term success and wider adoption

Prognostic Value of [18F]-Fluoro-Deoxy-Glucose PET/CT, S100 or MIA for Assessment of Cancer-Associated Mortality in Patients with High Risk Melanoma

PURPOSE: To assess the prognostic value of FDG PET/CT compared to the tumor markers S100B and melanoma inhibitory activity (MIA) in patients with high risk melanoma. METHODS: Retrospective study in 125 consecutive patients with high risk melanoma that underwent FDG PET/CT for re-staging. Diagnostic accuracy and prognostic value was determined for FDG PET/CT as well as for S100B and MIA. As standard of reference, cytological, histological, PET/CT or MRI follow-up findings as well as clinical follow-up were used. RESULTS: Of 125 patients, FDG PET/CT was positive in 62 patients. 37 (29.6%) patients had elevated S100B (>100 pg/ml) and 24 (20.2%) had elevated MIA (>10 pg/ml) values. Overall specificities for FDG PET/CT, S100B and MIA were 96.8% (95% CI, 89.1% to 99.1%), 85.7% (75.0% to 92.3%), and 95.2% (86.9% to 98.4%), corresponding sensitivities were 96.8% (89.0% to 99.1%), 45.2% (33.4% to 55.5%), and 36.1% (25.2% to 48.6%), respectively. The negative predictive values (NPV) for PET/CT, S100B, and MIA were 96.8% (89.1% to 99.1%), 61.4% (50.9% to 70.9%), and 60.6% (50.8% to 69.7%). The positive predictive values (PPV) were 96.7% (89.0% to 99.1%), 75.7% (59.9% to 86.6%), and 88.0% (70.0% to 95.8%). Patients with elevated S100B- or MIA values or PET/CT positive findings showed a significantly (p<0.001 each, univariate Cox regression models) higher risk of melanoma associated death which was increased 4.2-, 6.5- or 17.2-fold, respectively. CONCLUSION: PET/CT has a higher prognostic power in the assessment of cancer-associated mortality in melanoma patients compared with S100 and MIA

Prior Stroke in PFO Patients Is Associated With Both PFO-Related and -Unrelated Factors.

Background and Purpose: To identify factors associated with prior stroke at presentation in patients with cryptogenic stroke (CS) and patent foramen ovale (PFO). Methods: We studied cross-sectional data from the International PFO Consortium Study (NCT00859885). Patients with first-ever stroke and those with prior stroke at baseline were analyzed for an association with PFO-related (right-to-left shunt at rest, atrial septal aneurysm, deep venous thrombosis, pulmonary embolism, and Valsalva maneuver) and PFO-unrelated factors (age, gender, BMI, hypertension, diabetes mellitus, hypercholesterolemia, smoking, migraine, coronary artery disease, aortic plaque). A multivariable analysis was used to adjust effect estimation for confounding, e.g., owing to the age-dependent definition of study groups in this cross-sectional study design. Results: We identified 635 patients with first-ever and 53 patients with prior stroke. Age, BMI, hypertension, diabetes mellitus, hypercholesterolemia, coronary artery disease, and right-to-left shunt (RLS) at rest were significantly associated with prior stroke. Using a pre-specified multivariable logistic regression model, age (Odds Ratio 1.06), BMI (OR 1.06), hypercholesterolemia (OR 1.90) and RLS at rest (OR 1.88) were strongly associated with prior stroke.Based on these factors, we developed a nomogram to illustrate the strength of the relation of individual factors to prior stroke. Conclusion: In patients with CS and PFO, the likelihood of prior stroke is associated with both, PFO-related and PFO-unrelated factors