Selective fructose dehydration to 5-hydroxymethylfurfural from a fructose-glucose mixture over a sulfuric acid catalyst in a biphasic system: Experimental study and kinetic modelling

A two-step process combining the (equilibrium) glucose isomerization to fructose with selective dehydration of fructose in the obtained sugar mixture to 5-hydroxymethylfurfural (HMF), where glucose is largely unconverted and recycled, represents an attractive concept to increase the overall efficiency for HMF synthesis. This work presents experimental and modelling studies on the conversion of such fructose-glucose mixture to HMF using the sulfuric acid catalyst in a water-methyl isobutyl ketone biphasic system under a wide range of conditions (e.g., temperature, catalyst and sugar concentrations). Through detailed product analyses and ESI-MS spectroscopy, the excess formation of formic acid (together with humins) by the direct sugar/HMF degradation was confirmed and included in the reaction network (neglected in most literatures). The kinetic modelling based on batch experiments in monophasic water well describes the measurements thereof, whereas distinct deviations were found in the prediction of typical literature kinetic models. The incorporation of HMF equilibrium extraction into the developed kinetic model, with consideration of phase volume change as a function of temperature and partial phase miscibility, enables to predict reaction results in the biphasic system in batch. This kinetic model allows to optimize conditions for HMF synthesis that are favored in continuous reactors with minimized back mixing. Based on the model implications, the biphasic system was optimized with slug flow microreactors to better address process intensification and scale-up aspects. Using a simulated fructose-glucose mixture feedstock to represent commercially available high fructose corn syrups, a maximum HMF yield of 81% was obtained at 155 °C over 0.05 M H2SO4 at a residence time of 16 min in the microreactor, with 96% fructose conversion and over 95% of glucose remaining unconverted

Fast-ParC: Position Aware Global Kernel for ConvNets and ViTs

Transformer models have made tremendous progress in various fields in recent years. In the field of computer vision, vision transformers (ViTs) also become strong alternatives to convolutional neural networks (ConvNets), yet they have not been able to replace ConvNets since both have their own merits. For instance, ViTs are good at extracting global features with attention mechanisms while ConvNets are more efficient in modeling local relationships due to their strong inductive bias. A natural idea that arises is to combine the strengths of both ConvNets and ViTs to design new structures. In this paper, we propose a new basic neural network operator named position-aware circular convolution (ParC) and its accelerated version Fast-ParC. The ParC operator can capture global features by using a global kernel and circular convolution while keeping location sensitiveness by employing position embeddings. Our Fast-ParC further reduces the O(n2) time complexity of ParC to O(n log n) using Fast Fourier Transform. This acceleration makes it possible to use global convolution in the early stages of models with large feature maps, yet still maintains the overall computational cost comparable with using 3x3 or 7x7 kernels. The proposed operation can be used in a plug-and-play manner to 1) convert ViTs to pure-ConvNet architecture to enjoy wider hardware support and achieve higher inference speed; 2) replacing traditional convolutions in the deep stage of ConvNets to improve accuracy by enlarging the effective receptive field. Experiment results show that our ParC op can effectively enlarge the receptive field of traditional ConvNets, and adopting the proposed op benefits both ViTs and ConvNet models on all three popular vision tasks, image classification, objectComment: 19 pages, 8 figures, 11 tables. A preliminary version of this paper has been published in ECCV 2022 and it can be find in arXiv:2203.0395

Impact of serum SP-A and SP-D levels on comparison and prognosis of idiopathic pulmonary fibrosis: A systematic review and meta-analysis.

Background and objective: Idiopathic pulmonary fibrosis (IPF) has a poor prognosis in general; however, it is heterogeneous to detect relative biomarkers for predicting the disease progression. Serum biomarkers can be conveniently collected to detect and help to differentially diagnose IPF and predict IPF prognosis. This meta-analysis aimed to evaluate the use of serum surfactant proteins A and D (SP-A and SP-D) for differential diagnosis and prognosis of IPF. Methods: Relevant articles were searched in PubMed, Embase, and Chinese National Knowledge Infrastructuredatabases and reviewed by 2 independent readers. Standard mean difference (SMD) and 95% confidence interval (CI) were calculated to assess the difference in serum levels of SP-A/D among patients with IPF, when compared to patients with non-IPF interstitial lung disease (ILD), pulmonary infection, and healthy control. Hazard ratio (HR) and 95% CI were used to compare the relative risk of mortality. Results: Twenty-one articles (totalling 1289 IPF patients) were included in final meta-analysis. Serum SP-A levels were significantly higher in patients with IPF than in patients with non-IPF ILD (SMD: 1.108 [0.584, 1.632], P \u3c .001), or pulmonary infection (SMD: 1.320 [0.999, 1.640], P \u3c .001) and healthy controls (SMD: 2.802 [1.901, 3.702], P \u3c .001). There was no significant difference in serum SP-D levels between patients with IPF and those with non-IPF ILD patients (SMD: 0.459 [−0.000, 0.919], P = .050). Serum SP-D levels were significantly higher in patients with IPF than in patients with pulmonary infection (SMD: 1.308 [0.813, 1.803], P \u3c .001) and healthy controls (SMD: 2.235 [1.739, 2.731], P \u3c .001). Risk of death in patients with IPF and elevated serum SP-A was increased 39% compared to patients with low SP-A groups. Elevated SP-D increased risk by 111% when compared to low SP-D. In acute exacerbation of IPF, serum SP-A/D were higher than those in stable stage. The comparisons and prognosis might be different in Asian and Caucasian patients. Conclusions: Serum SP-A/D detection might be useful for differential diagnosis and prediction of survival in patients with IPF

Hot Compression Test and Microstructure Evolution in LZ50 Axle Steel

True strain-true stress curves of the LZ50 axle steel were obtained after hot compression tests had been performed on a Gleeble-3800 thermal simulator at strain rates of 0.01, 0.1, 1 and 5 s^(-1) and at deformation temperatures from 850 to 1,150 ℃. Following the data processing, the relationship between the flow stress and the deformation temperature of the material under different true strain conditions was analysed. On this basis and according to the influence of deformation factors, the constitutive equation of the Johnson-Cook flow stress model is established, and the model is modified according to the defects of the model, so that the improved model can effectively predict the mechanical behaviour in the range of high strain rates and temperatures. The dynamic material model (DMM) was used to generate the hot working diagram of the material. Through calculation and analysis, the optimum process area in terms of temperature was found to be in the range from 1,050 to 1,150 ℃ and in terms of strain rate in the rage from 1 to 5 s^(-1). Finally, the microstructure evolution of the compressed specimens under different strain rates and temperatures was studied in the metallographic analysis, which provided a theoretical basis and reference value for later damage

Effect of Ultrasound on Graphite Flotation of Different Stages of Luobei

This is an article in the field of mineral processing engineering. In order to explore the influence of ultrasonic pretreatment on the graphite flotation process of different stages, tests on the effects of different ultrasonic time on the roughing and cleaning of graphite were carried out. The research results show that when the ore contains muddy minerals, ultrasonic pretreatment can’t improve the effect of graphite roughing. Compared with the conventional flotation, the flotation effect of ultrasonic pretreatment for ultrasonic treatment cleaning stage 2, 4 and 6 is gradually improved with the increase of the ultrasonic pretreatment time. When the ultrasonic pretreatment time is 2.5 min, the graphite selection effect is the best. In the test of stage by stage ultrasonic cleaning, the effect of ultrasonic pretreatment for 0.5 min on 1～4 stages is not obvious, but it has a certain effect on 5 and 6 stages. When the ultrasonic pretreatment time is 2.5 min, the effect of each fine section is obvious. The order of the cleaning effect of ultrasonic pretreatment is ultrasonic treatment cleaning stage 5>stage 6>stage 4>stage 3>stage 2>stage 1. The research shows that the flotation effect of ultrasonic pretreatment in the rear section of graphite cleaning is better than that in the front one

Rank-Aware Negative Training for Semi-Supervised Text Classification

Semi-supervised text classification-based paradigms (SSTC) typically employ the spirit of self-training. The key idea is to train a deep classifier on limited labeled texts and then iteratively predict the unlabeled texts as their pseudo-labels for further training. However, the performance is largely affected by the accuracy of pseudo-labels, which may not be significant in real-world scenarios. This paper presents a Rank-aware Negative Training (RNT) framework to address SSTC in learning with noisy label manner. To alleviate the noisy information, we adapt a reasoning with uncertainty-based approach to rank the unlabeled texts based on the evidential support received from the labeled texts. Moreover, we propose the use of negative training to train RNT based on the concept that ``the input instance does not belong to the complementary label''. A complementary label is randomly selected from all labels except the label on-target. Intuitively, the probability of a true label serving as a complementary label is low and thus provides less noisy information during the training, resulting in better performance on the test data. Finally, we evaluate the proposed solution on various text classification benchmark datasets. Our extensive experiments show that it consistently overcomes the state-of-the-art alternatives in most scenarios and achieves competitive performance in the others. The code of RNT is publicly available at:https://github.com/amurtadha/RNT.Comment: TACL 202

Variation in epibiotic bacteria on two squat lobster species of Munidopsidae

The relationships between epibiotic bacteria on deep-sea hosts and host lifestyle factors are of particular interest in the field of deep-sea chemoautotrophic environmental adaptations. The squat lobsters Shinkaia crosnieri and Munidopsis verrilli are both dominant species in cold-seep ecosystems, and they have different distributions and feeding behaviors. These species may have evolved to have distinct epibiotic microbiota. Here, we compared the epibiotic bacterial communities on the M. verrilli carapace (MVcarapace), S. crosnieri carapace (SCcarapace), and S. crosnieri ventral plumose setae (SCsetae). The epibiotic bacteria on SCsetae were dense and diverse and had a multi-layer configuration, while those on MVcarapace and SCcarapace were sparse and had a monolayer configuration. Chemoautotrophic bacteria had the highest relative abundance in all epibiotic bacterial communities. The relative abundance of amplicon sequence variant 3 (ASV3; unknown species in order Thiotrichales), which is associated with sulfide oxidation, was significantly higher in SCsetae than MVcarapace and SCcarapace. Thiotrichales species seemed to be specifically enriched on SCsetae, potentially due to the synthetic substrate supply, adhesion preference, and host behaviors. We hypothesize that the S. crosnieri episymbionts use chemical fluxes near cold seeps more efficiently, thereby supporting the host’s nutrient strategies, resulting in a different distribution of the two species of squat lobster

OphGLM: Training an Ophthalmology Large Language-and-Vision Assistant based on Instructions and Dialogue

Large multimodal language models (LMMs) have achieved significant success in general domains. However, due to the significant differences between medical images and text and general web content, the performance of LMMs in medical scenarios is limited. In ophthalmology, clinical diagnosis relies on multiple modalities of medical images, but unfortunately, multimodal ophthalmic large language models have not been explored to date. In this paper, we study and construct an ophthalmic large multimodal model. Firstly, we use fundus images as an entry point to build a disease assessment and diagnosis pipeline to achieve common ophthalmic disease diagnosis and lesion segmentation. Then, we establish a new ophthalmic multimodal instruction-following and dialogue fine-tuning dataset based on disease-related knowledge data and publicly available real-world medical dialogue. We introduce visual ability into the large language model to complete the ophthalmic large language and vision assistant (OphGLM). Our experimental results demonstrate that the OphGLM model performs exceptionally well, and it has the potential to revolutionize clinical applications in ophthalmology. The dataset, code, and models will be made publicly available at https://github.com/ML-AILab/OphGLM.Comment: OphGLM:The first ophthalmology large language-and-vision assistant based on instructions and dialogu

Newly-discovered ring-moat dome structures in the lunar maria:possible origins and implications

We report on a newly discovered morphological feature on the lunar surface, here named Ring-Moat Dome Structure (RMDS). These low domes (a few meters to ~20 m height with slopes <5°) are typically surrounded by narrow annular depressions or moats. We mapped about 2,600 RMDSs in the lunar maria with diameters ranging from tens to hundreds of meters. Four candidate hypotheses for their origin involving volcanism are considered. We currently favor a mechanism for the formation of the RMDS related to modification of the initial lava flows through inflated flow squeeze-ups and/or extrusion of magmatic foams below a cooling lava flow surface. These newly discovered features provide new insights into the nature of emplacement of lunar lava flows, suggesting that in the waning stages of a dike emplacement event, magmatic foams can be produced, extrude to the surface as the dike closes, and break through the upper lava flow thermal boundary layer (crust) to form foam mounds and surrounding moats

Effects of gold and copper mining on the structure and diversity of the surrounding plant communities in Northeast Tiger and Leopard National Park

IntroductionNortheast China Tiger and Leopard National Park is home to the largest and only breeding family of wild tigers and leopards in China. The mining of open-pit gold and copper mines in the core zone might affect the surrounding forest ecosystem and the survival activities of wild tigers and leopards.MethodsIn order to understand the impacts of gold and copper mining on the structure and diversities of the surrounding plant communities, the vegetation of the forest layer, shrub layer and herb layer of the forest community in the original forest area, mining area, tailings area and restoration area of the Northeast China Tiger and Leopard National Park were investigated, and the influence of plant community structure on species diversity was also evaluated.ResultsThis study concluded that there are 25 species belonging to 11 families, 16 genera of trees, 43 species belonging to 22 families, 35 genera of shrubs, and 57 species belonging to 23 families, 46 genera of herb in the sampling sites. There were no significant differences in the community structure characteristics and species diversities of the tree layer and the shrub layer in different operational areas. However, in herb layer, the heights, the coverage and the species diversity index were higher in the restoration area. Additionally, the community structure was one of the major factors that influence the diversity indices, which might be an important way for mining to impact plant diversity.DiscussionTherefore, mining had some impacts on the structure and diversity of the surrounding plant communities, but the impacts did not reach a significant level. These results could provide scientific support for the management of the forest ecosystems around the mining area of Northeast Tiger and Leopard Park