Autothermal reforming of palm empty fruit bunch bio-oil: thermodynamic modelling

This work focuses on thermodynamic analysis of the autothermal reforming of palm empty fruit bunch (PEFB) bio-oil for the production of hydrogen and syngas. PEFB bio-oil composition was simulated using bio-oil surrogates generated from a mixture of acetic acid, phenol, levoglucosan, palmitic acid and furfural. A sensitivity analysis revealed that the hydrogen and syngas yields were not sensitive to actual bio-oil composition, but were determined by a good match of molar elemental composition between real bio-oil and surrogate mixture. The maximum hydrogen yield obtained under constant reaction enthalpy and pressure was about 12 wt% at S/C = 1 and increased to about 18 wt% at S/C = 4; both yields occurring at equivalence ratio Φ of 0.31. The possibility of generating syngas with varying H2 and CO content using autothermal reforming was analysed and application of this process to fuel cells and Fischer-Tropsch synthesis is discussed. Using a novel simple modelling methodology, reaction mechanisms were proposed which were able to account for equilibrium product distribution. It was evident that different combinations of reactions could be used to obtain the same equilibrium product concentrations. One proposed reaction mechanism, referred to as the ‘partial oxidation based mechanism’ involved the partial oxidation reaction of the bio-oil to produce hydrogen, with the extent of steam reforming and water gas shift reactions varying depending on the amount of oxygen used. Another proposed mechanism, referred to as the ‘complete oxidation based mechanism’ was represented by thermal decomposition of about 30% of bio-oil and hydrogen production obtained by decomposition, steam reforming, water gas shift and carbon gasification reactions. The importance of these mechanisms in assisting in the eventual choice of catalyst to be used in a real ATR of PEFB bio-oil process was discussed

Surrogates of immunologic cell death (ICD) and chemoradiotherapy outcomes in head and neck squamous cell carcinoma (HNSCC)

Objectives: Chemoradiation can induce immunogenic (ICD) or tolerogenic cell death. ICD relies on the generation of damage-associated molecular patterns which can stimulate toll-like receptors (TLRs). We sought to determine whether we can predict responses to chemoradiation by measuring surrogate biomarkers of ICD in a cohort of patients with locally advanced (LA) head and neck squamous cell carcinoma (HNSCC). Materials and Methods: In a cohort of 113 LA HNSCC pts we evaluated expression of TLR4, TLR7 and TLR9 in the EpCAM + circulating tumor cell (CTC) fraction at baseline and after cisplatin chemoradiation. We also quantified changes in chemokines CXCL10, CXCL16 and IL-2R in the serum. Results: Seventy three patients had evaluable specimens. Among cases with biomarker assessment at baseline and post treatment, 36.8% had an increase in CXCL10 levels (p = 0.022), 73.7% had an increase in CXCL16 levels (p = 0.002) and 63.8% had an increase in IL2Ra levels (p = 0.032) with treatment. 52.0% of evaluable cases at baseline and post-treatment had an increase in TLR4 levels (p = 0.996), 42.9% had an increase in TLR7 levels (p = 0.042) and 27.7% had increase in TLR9 levels (p = 0.011) with treatment. CXCL10 levels at baseline were significantly associated with PFS and OS (p = 0.010 and p = 0.032, respectively). Conclusions: Our results suggest that chemoradiation leads to quantifiable effects in surrogate markers of ICD. These effects may inform trials combining chemoradiation with immune checkpoint inhibitors. In addition, CXCL10 has prognostic effect in pts treated with chemoradiation. © 201

Pseudomonas aeruginosa bacteraemia in patients with hematologic malignancies: risk factors, treatment and outcome

Our aims were to identify factors associated with Pseudomonas aeruginosa (PA) bloodstream infection (BSI) in patients with hematological malignancies and evaluate the outcome of the affected patients. Consecutive patients with hematological malignancies who developed PA BSI were identified. Subsequently, two case–control studies were performed to evaluate the risk factors (i) for PA BSI and (ii) for carbapenem resistant (CR) PA BSI. Patients' outcome was evaluated at 28 days after the onset of bacteraemia. A total of 64 patients with PA BSI (45 caused by CS and 19 by CR organisms) and 128 without PA BSI were enrolled. Patients with rapidly fatal disease, steroid use, neutropenia or prior surgery were more likely to develop PA BSI, whereas patients with previous hospitalization and prior use of fluoroquinolones were more likely to develop CR PA BSI. The 28-day mortality rate was 35.9%. Severity of sepsis was the only independent predictor of adverse outcome. © 2017 Elsevier Inc

From Human Automation Interactions to Social Human Autonomy Machine Teaming in Maritime Transportation

Part 1: Information Technology and Disaster ManagementInternational audienceRecent technological advances in the field of Artificial intelligence (AI) and machine learning led to the creation of smart AI-enabled automation systems that are drastically changing maritime transportation. We developed a systematic literature review to understand how automation, based on Information Technologies (IT), has tackled the challenges related to human and machine interactions. We notably discuss the conceptual evolution from Human-Automation Interaction (HAI) to Human Autonomy Teaming (HAT) and present the risks of high levels of automation and the importance of teamwork in safety critical systems. Our results lie on a map of five clusters that highlight the importance of trust in the interactions between humans and machines, the risks related to automation, the human errors that are arising from these interactions, the effects of automation on situational awareness and the social norms in human-computer interactions. This literature show that human-machines interactions have mainly been studied from the computer/information systems’ (IS) point of view, hence neglecting the social dimensions of humans. Building on the difference between the concepts of automation and autonomy, we suggest the development of the concept of Social Human Autonomy Machine Teaming (SHAMT) to better consider the social dimensions of humans in these new interactions. Future research should focus on the right equilibrium between social needs, social interactions among humans and with autonomous machines with AI to optimize the global autonomy of the human-machine teammates in a whole ecosystem