Properties Analysis of Spent Commercial Residue Hydrotreating Catalyst: Surface Property Changes of Spent Catalysts in Commercial Residue Hydrotreating Unit

In this study, the changes of the surface properties of 14 spent catalysts, which were sampled from a commercial residue hydrotreating unit at the end of an operation cycle, were analyzed and compared with the corresponding fresh catalysts. It was found that the changes in the surface properties do not have change laws along the bed height. Furthermore, the pore size, pore volume and surface area of most of the catalysts decreased after reaction and the number of micropores of the spent catalysts increased, due to the fact that the coke and metals deposited in the catalyst to alter the pore distribution. But some catalysts with high coke content, the pore size and pore volume decreased with the increase of surface area, which was a result of the forming of massive micro/mesopores (the pore size is mainly ranged from 3 to 10 nm), when partial soft coke desorbed under the action of the deposited active metals and micro/mesopores were formed in macropores or large mesopores. The surface properties of the spent catalysts were not only related to the deposition amounts, but also to the deposition configurations of the coke and metals on the catalysts

Properties Analysis of Spent Catalyst for Fixed-Bed Residue Hydrotreating Unit: Composition of Deposited Elements Along Catalyst Bed

Element compositions of spent catalyst from a commercial fixed-bed residue hydrotreating unit of Petro-China were analyzed in order to investigate the reasons for the catalyst deactivation. The spent catalysts were sampled from different axial position of the reactor. Depositions of C, H, S, N, Ni and V on the spent catalysts were studied. No necessary relation was observed for the contents of various deposited elements along the bed at the end of a run. The deposition amount of elements was mainly related to local reaction conditions and catalyst loading states in the fixed-bed. The catalysts with high metal depositions have low contents of coke, high contents of sulfur and high H/C, which indicates that residue hydrotreating is an autocatalytic process. Metal sulfides deposited on catalysts have a hydrogenation activity in residue hydrotreating. The coke on residue hydrotreating catalysts mainly comes from some specific condensed ring structures containing nitrogen existed in asphaltene which is difficult to hydrotreat.Key words: Spent catalyst; Residue hydrotreating; Deposited elements; Compositio

Properties Analysis of Spent Catalyst for Fixed-Bed Residue Hydrotreating Unit: Radial Distribution of Deposited Elements in Spent Catalyst Particles

14 spent catalysts, which were sampled from a commercial residue hydrotreating unit at the end of an operation cycle, were analyzed by SEM to describe elements distributions along the radial direction of particles. Different from laboratory equipment, on the whole, V, Ni and S showed U-shaped pattern along the radial direction of spent catalysts. The catalyst bed has been penetrated by deposited metals and deposited massive metals on catalyst, so the pore size of catalyst decreased, diffusion resistance increased and reactants entered internal of the catalysts more difficultly. Most of the organometallic compounds hydrotreated and deposited on outside of the catalyst particles. It is showed that metals deposited on catalyst in forms of metal sulfides because the points of high metal content also have high sulfur contents unexceptionally. The structure of high metal deposition catalyst was destroyed obviously or massive irregular material has deposited on the external surface. It is verified by SEM that there is no any distribution law for deposited elements along the bed height. The change laws of deposited elements along the bed height and radial direction of particles were influenced by various factors in commercial residue hydrotrating.Key words: Residue hydrotreating unit; Spent catalyst; SE

MEDNC: Multi-ensemble deep neural network for COVID-19 diagnosis

Coronavirus disease 2019 (COVID-19) has spread all over the world for three years, but medical facilities in many areas still aren't adequate. There is a need for rapid COVID-19 diagnosis to identify high-risk patients and maximize the use of limited medical resources. Motivated by this fact, we proposed the deep learning framework MEDNC for automatic prediction and diagnosis of COVID-19 using computed tomography (CT) images. Our model was trained using two publicly available sets of COVID-19 data. And it was built with the inspiration of transfer learning. Results indicated that the MEDNC greatly enhanced the detection of COVID-19 infections, reaching an accuracy of 98.79% and 99.82% respectively. We tested MEDNC on a brain tumor and a blood cell dataset to show that our model applies to a wide range of problems. The outcomes demonstrated that our proposed models attained an accuracy of 99.39% and 99.28%, respectively. This COVID-19 recognition tool could help optimize healthcare resources and reduce clinicians' workload when screening for the virus

Spikeformer: A Novel Architecture for Training High-Performance Low-Latency Spiking Neural Network

Spiking neural networks (SNNs) have made great progress on both performance and efficiency over the last few years,but their unique working pattern makes it hard to train a high-performance low-latency SNN.Thus the development of SNNs still lags behind traditional artificial neural networks (ANNs).To compensate this gap,many extraordinary works have been proposed.Nevertheless,these works are mainly based on the same kind of network structure (i.e.CNN) and their performance is worse than their ANN counterparts,which limits the applications of SNNs.To this end,we propose a novel Transformer-based SNN,termed "Spikeformer",which outperforms its ANN counterpart on both static dataset and neuromorphic dataset and may be an alternative architecture to CNN for training high-performance SNNs.First,to deal with the problem of "data hungry" and the unstable training period exhibited in the vanilla model,we design the Convolutional Tokenizer (CT) module,which improves the accuracy of the original model on DVS-Gesture by more than 16%.Besides,in order to better incorporate the attention mechanism inside Transformer and the spatio-temporal information inherent to SNN,we adopt spatio-temporal attention (STA) instead of spatial-wise or temporal-wise attention.With our proposed method,we achieve competitive or state-of-the-art (SOTA) SNN performance on DVS-CIFAR10,DVS-Gesture,and ImageNet datasets with the least simulation time steps (i.e.low latency).Remarkably,our Spikeformer outperforms other SNNs on ImageNet by a large margin (i.e.more than 5%) and even outperforms its ANN counterpart by 3.1% and 2.2% on DVS-Gesture and ImageNet respectively,indicating that Spikeformer is a promising architecture for training large-scale SNNs and may be more suitable for SNNs compared to CNN.We believe that this work shall keep the development of SNNs in step with ANNs as much as possible.Code will be available

Association of Lumican Gene with Susceptibility to Pathological Myopia in the Northern Han Ethnic Chinese

Pathological myopia is a severe hereditary ocular disease leading to blindness. It is urgent and very important to find the pathogenesis and therapy for this disease. The purpose of the study is to analyze sequences of lumican and decorin genes with pathological myopia(PM) and control subjects to verify the relationship between lumican, decorin genes and PM in Northern Han Chinese. We collected and analyzed the blood samples of 94 adults (including 12 pedigree cases and 82 sporadic cases) with PM and 90 controls in the northern Han ethnic Chinese. Genotyping was performed by direct sequencing after polymerase chain reaction(PCR) amplification and allele frequencies were tested for Hardy-Weinberg equilibrium. Univariate analysis revealed significant differences between two groups for three SNPs: rs3759223 (C → T) and rs17853500 (T → C) of the lumican gene and rs74419 (T → C) of decorin gene with (P < .05) for all their genotype distribution and allele frequency. There is no significant difference for incidence of these mutations between pedigree and sporadic group (P > .05). The results suggested that the sequence variants in 5′-regulatory region of lumican gene and 3'UTR of decorin gene were associated significantly with PM in Northern Han Chinese. Further studies are needed to confirm finally whether the two genes are the virulence genes of PM