From bench scale to pilot plant: A 150x scaled-up configuration of a microwave-driven structured reactor for methane dehydroaromatization

Microwave-assisted gas-phase conversion on structured catalysts is emerging as a promising process intensifi-cation technology in the field of heterogeneous catalysis. The combination of selective heating and structured catalytic materials induces a temperature difference between the heated catalytic sample and the surrounding void regions to avoid non-selective gas-phase reactions. This operational principle allowed inhibiting thermal cracking in alkane dehydrogenation processes as well as retarding catalyst deactivation by coking in methane dehydroaromatization (MDA) processes. However, its effectiveness has not been reported so far out of the lab-oratory scale conditions. This work addresses the scaling of the microwave-assisted MDA process from lab scale experiments to a scaled-up configuration capable of stable operation with a 150-fold higher feeding rate. The scaling-up potential and main obstacles to overcome for this technology are critically discussed. In addition, a techno-economic assessment of the MW-MDA process is presented. The catalytic activity was kept for seven consecutive reaction cycles, i.e. 35 h MW-MDA, prior to a progressive decay due to permanent deactivation caused by zeolite dealumination and active metal loss. The scaled set-up operated for up to 295 consecutive hours under unmanned operation conducting 4 -h MDA-regeneration cycles on Mo/ZSM-5@SiC monoliths and resulting in 125-fold increase of converted methane and a 450-fold increase of benzene (0.17 LC6H6/h) in comparison with the laboratory scale tests. Scaled set-up experiments were run using only a 6-fold microwave input power, thus, highlighting the non-linearity between energy consumption and scaling factor for this tech-nology and the importance of microwave cavity design

Overcoming stability problems in microwave-assisted heterogeneous catalytic processes affected by catalyst coking

Microwave-assisted heterogeneous catalysis (MHC) is gaining attention due to its exciting prospects related to selective catalyst heating, enhanced energy-efficiency, and partial inhibition of detrimental side gas-phase reactions. The induced temperature difference between the catalyst and the comparatively colder surrounding reactive atmosphere is pointed as the main factor of the process selectivity enhancement towards the products of interest in a number of hydrocarbon conversion processes. However, MHC is traditionally restricted to catalytic reactions in the absence of catalyst coking. As excellent MW-susceptors, carbon deposits represent an enormous drawback of the MHC technology, being main responsible of long-term process malfunctions. This work addresses the potentials and limitations of MHC for such processes affected by coking (MHCC). It also intends to evaluate the use of different catalyst and reactor configurations to overcome heating stability problems derived from the undesired coke deposits. The concept of long-term MHCC operation has been experimentally tested/applied to for the methane non-oxidative coupling reaction at 700¿C on Mo/ZSM-5@SiC structured catalysts. Preliminary process scalability tests suggest that a 6-fold power input increases the processing of methane flow by 150 times under the same controlled temperature and spatial velocity conditions. This finding paves the way for the implementation of high-capacity MHCC processes at up-scaled facilities

Noise Can Reduce Disorder in Chaotic Dynamics

We evoke the idea of representation of the chaotic attractor by the set of unstable periodic orbits and disclose a novel noise-induced ordering phenomenon. For long unstable periodic orbits forming the strange attractor the weights (or natural measure) is generally highly inhomogeneous over the set, either diminishing or enhancing the contribution of these orbits into system dynamics. We show analytically and numerically a weak noise to reduce this inhomogeneity and, additionally to obvious perturbing impact, make a regularizing influence on the chaotic dynamics. This universal effect is rooted into the nature of deterministic chaos.Comment: 11 pages, 5 figure

Allelic variants of melanocortin 3 receptor gene (MC3R) and weight loss in obesity: a randomised trial of hypo-energetic high- versus low-fat diets

INTRODUCTION: The melanocortin system plays an important role in energy homeostasis. Mice genetically deficient in the melanocortin-3 receptor gene have a normal body weight with increased body fat, mild hypophagia compared to wild-type mice. In humans, Thr6Lys and Val81Ile variants of the melanocortin-3 receptor gene (MC3R) have been associated with childhood obesity, higher BMI Z-score and elevated body fat percentage compared to non-carriers. The aim of this study is to assess the association in adults between allelic variants of MC3R with weight loss induced by energy-restricted diets. SUBJECTS AND METHODS: This research is based on the NUGENOB study, a trial conducted to assess weight loss during a 10-week dietary intervention involving two different hypo-energetic (high-fat and low-fat) diets. A total of 760 obese patients were genotyped for 10 single nucleotide polymorphisms covering the single exon of MC3R gene and its flanking regions, including the missense variants Thr6Lys and Val81Ile. Linear mixed models and haplotype-based analysis were carried out to assess the potential association between genetic polymorphisms and differential weight loss, fat mass loss, waist change and resting energy expenditure changes. RESULTS: No differences in drop-out rate were found by MC3R genotypes. The rs6014646 polymorphism was significantly associated with weight loss using co-dominant (p = 0.04) and dominant models (p = 0.03). These p-values were not statistically significant after strict control for multiple testing. Haplotype-based multivariate analysis using permutations showed that rs3827103-rs1543873 (p = 0.06), rs6014646-rs6024730 (p = 0.05) and rs3746619-rs3827103 (p = 0.10) displayed near-statistical significant results in relation to weight loss. No other significant associations or gene*diet interactions were detected for weight loss, fat mass loss, waist change and resting energy expenditure changes. CONCLUSION: The study provided overall sufficient evidence to support that there is no major effect of genetic variants of MC3R and differential weight loss after a 10-week dietary intervention with hypo-energetic diets in obese Europeans

Negative cancer beliefs, recognition of cancer symptoms and anticipated times to help-seeking: an international cancer benchmarking partnership (ICBP) study

Background: Understanding what influences people to seek help can inform interventions to promote earlier diagnosis of cancer, and ultimately better cancer survival. We aimed to examine relationships between negative cancer beliefs, recognition of cancer symptoms and how long people think they would take to go to the doctor with possible cancer symptoms (anticipated patient intervals). Methods: Telephone interviews of 20,814 individuals (50+) in the United Kingdom, Australia, Canada, Denmark, Norway and Sweden were carried out using the Awareness and Beliefs about Cancer Measure (ABC). ABC included items on cancer beliefs, recognition of cancer symptoms and anticipated time to help-seeking for cough and rectal bleeding. The anticipated time to help-seeking was dichotomised as over one month for persistent cough and over one week for rectal bleeding. Results: Not recognising persistent cough/hoarseness and unexplained bleeding as cancer symptoms increased the likelihood of a longer anticipated patient interval for persistent cough (OR=1.66; 95%CI=1.47-1.87) and rectal bleeding (OR=1.90; 95%CI=1.58-2.30), respectively. Endorsing four or more out of six negative beliefs about cancer increased the likelihood of longer anticipated patient intervals for persistent cough and rectal bleeding (OR=2.18; 95%CI=1.71-2.78 and OR=1.97; 95%CI=1.51-2.57). Many negative beliefs about cancer moderated the relationship between not recognising unexplained bleeding as a cancer symptom and longer anticipated patient interval for rectal bleeding (p=0.005). CONCLUSIONS: Intervention studies should address both negative beliefs about cancer and knowledge of symptoms to optimise the effect

Anthropogenic Space Weather

Anthropogenic effects on the space environment started in the late 19th century and reached their peak in the 1960s when high-altitude nuclear explosions were carried out by the USA and the Soviet Union. These explosions created artificial radiation belts near Earth that resulted in major damages to several satellites. Another, unexpected impact of the high-altitude nuclear tests was the electromagnetic pulse (EMP) that can have devastating effects over a large geographic area (as large as the continental United States). Other anthropogenic impacts on the space environment include chemical release ex- periments, high-frequency wave heating of the ionosphere and the interaction of VLF waves with the radiation belts. This paper reviews the fundamental physical process behind these phenomena and discusses the observations of their impacts.Comment: 71 pages, 35 figure

Rules extraction from neural networks applied to the prediction and recognition of prokaryotic promoters

Promoters are DNA sequences located upstream of the gene region and play a central role in gene expression. Computational techniques show good accuracy in gene prediction but are less successful in predicting promoters, primarily because of the high number of false positives that reflect characteristics of the promoter sequences. Many machine learning methods have been used to address this issue. Neural Networks (NN) have been successfully used in this field because of their ability to recognize imprecise and incomplete patterns characteristic of promoter sequences. In this paper, NN was used to predict and recognize promoter sequences in two data sets: (i) one based on nucleotide sequence information and (ii) another based on stability sequence information. The accuracy was approximately 80% for simulation (i) and 68% for simulation (ii). In the rules extracted, biological consensus motifs were important parts of the NN learning process in both simulations