281 research outputs found
Redox-mediated reactions of vinylferrocene: Toward redox auxiliaries
Chemical redox reactions have been exploited to transform unreactive vinylferrocene into a powerful dienophile for the Diels–Alder reaction and reactive substrate for thiol addition reactions upon conversion to its ferrocenium state. We have further investigated the ability of these reactions to facilitate redox-auxiliary-like reactivity by further hydrogenolyisis of the Diels–Alder adduct to the corresponding cyclopentane derivative
Research on the Architecture Model of Volatile Data Forensics
AbstractThis paper proposed a new architecture model of volatile data forensic. The model applied to all the volatile data sources is a general model. It can rebuild the evidence data fragment to chains of evidence which contains the behavior characteristics, so as to assist investigators to do case analysis. With the accumulated experience, the model can help judicial officers to intelligently analyze the same type of computer crimes, and based on currently available information to predict the impending crimes
Knowledge Graph Transfer Network for Few-Shot Recognition
Few-shot learning aims to learn novel categories from very few samples given
some base categories with sufficient training samples. The main challenge of
this task is the novel categories are prone to dominated by color, texture,
shape of the object or background context (namely specificity), which are
distinct for the given few training samples but not common for the
corresponding categories (see Figure 1). Fortunately, we find that transferring
information of the correlated based categories can help learn the novel
concepts and thus avoid the novel concept being dominated by the specificity.
Besides, incorporating semantic correlations among different categories can
effectively regularize this information transfer. In this work, we represent
the semantic correlations in the form of structured knowledge graph and
integrate this graph into deep neural networks to promote few-shot learning by
a novel Knowledge Graph Transfer Network (KGTN). Specifically, by initializing
each node with the classifier weight of the corresponding category, a
propagation mechanism is learned to adaptively propagate node message through
the graph to explore node interaction and transfer classifier information of
the base categories to those of the novel ones. Extensive experiments on the
ImageNet dataset show significant performance improvement compared with current
leading competitors. Furthermore, we construct an ImageNet-6K dataset that
covers larger scale categories, i.e, 6,000 categories, and experiments on this
dataset further demonstrate the effectiveness of our proposed model.Comment: accepted by AAAI 2020 as oral pape
Study on Spinnability of PP/PU Blends and Preparation of PP/PU Bi-component Melt Blown Nonwovens
Melt blown polymer blends offers a good way to combine two polymers in the same fiber generating nonwovens with new and novel properties. In this study, polypropylene (PP) and polyurethane (PU) were blended to prepare PP/PU bicomponent melt blown nonwovens. The spinnability of PP/PU composites was investigated and PP/PU bi-component nonwovens with compositions of 95/5, 90/10, 80/20 and 70/30 were prepared by using the melt blowing technique. The melt blown fibers exhibited a ‘sea-island’ structure with PP as the continuous phase and PU as the dispersed phase. When the content of PU in the blend was above 40 %, PP/PU melt blown nonwovens could not be produced due to fiber breaking. For PP/PU (90/10) nonwovens, it was found that the average fiber diameter decreased with increasing die to collector (DCD) and elevated hot air pressure
Rethinking Memory and Communication Cost for Efficient Large Language Model Training
Recently, various distributed strategies for large language model training
have been proposed. However, these methods provided limited solutions for the
trade-off between memory consumption and communication cost. In this paper, we
rethink the impact of memory consumption and communication costs on the
training speed of large language models, and propose a memory-communication
balanced strategy set Partial Redundancy Optimizer (PaRO). PaRO provides
comprehensive options which reduces the amount and frequency of inter-group
communication with minor memory redundancy by fine-grained sharding strategy,
thereby improving the training efficiency in various training scenarios.
Additionally, we propose a Hierarchical Overlapping Ring (HO-Ring)
communication topology to enhance communication efficiency between nodes or
across switches in large language model training. Our experiments demonstrate
that PaRO significantly improves training throughput by 1.19x-2.50x compared to
the SOTA method and achieves a near-linear scalability. The HO-Ring algorithm
improves communication efficiency by 36.5% compared to the traditional Ring
algorithm
Development of fermented sea buckthorn (Hippophae rhamnoides L.) juice and investigation of its antioxidant and antimicrobial activity
Sea buckthorn (Hippophae rhamnoides L.) is an edible and medicinal plant species. However, due to its sour taste, it is not readily accepted by consumers. To overcome this, fermentation can be used to change its flavor profile. In this study, we used response surface methodology (RSM) to determine the best process for producing fermented sea buckthorn juice (FSBJ) using probiotics. The biological enzyme activity and total flavonoid content (TFC) of sea buckthorn juice (SBJ) increased after fermentation. When the number of bacteria inoculated was 4.08 × 106 CFU/mL and the inoculation ratio was 30% Z. mobilis, 5% L. casei, 13.75% L. plantarum, 31.25% P. acidilactici, 12.5% L. animalis, and 7.5% P. pentosaceus, the amount of sugar was 2.98% (w/v) after 20 h of fermentation at 37°C, and the superoxide dismutase (SOD) activity reached 725.44 U/mL, and the TFC reached 2.38 mg/mL. FSBJ demonstrated strong antimicrobial activity against Escherichia coli, Staphylococcus aureus and Botrytis cinerea. Then, to investigate the antioxidant capacity of FSBJ, we used H2O2 to induce oxidative stress in C2C12 cells and assessed the protection conferred by FSBJ to damaged cells. It was discovered that after 24 h of treatment with FSBJ, not only was there an increase in the activities of intracellular SOD and glutathione peroxidase (GSH-Px), but also a reduction in reactive oxygen species (ROS) content, catalase (CAT) activity, and malondialdehyde (MDA) content. This research lays the theoretical groundwork and provides reference materials for the improved fermentation of sea buckthorn and demonstrates its resulting antioxidant effect
Preparation of sea buckthorn (Hippophae rhamnoides L.) seed meal peptide by mixed fermentation and its effect on volatile compounds and hypoglycemia
This study employed mixed bacterial strains to ferment seabuckthorn seed meal into peptides, and conducted a comprehensive evaluation of the growth adaptive conditions, molecular weight distribution, volatile compounds, and in vitro hypoglycemic activity required for fermentation. Results showed that when the amount of maltose was 1.1% and MgSO4·7H2O was added at 0.15 g/L, the peptide yield reached 43.85% with a mixed fermentation of Lactobacillus fermentum, Bacillus subtilis, Lactobacillus casei, Lactobacillus rhamnosus, and Lactobacillus acidophilus. Components with a molecular weight below 1 kDa were found to be more effective in inhibiting the activity of α-amylase and α-glucosidase, with the identified sequence being FYLPKM. Finally, SPME/GC–MS results showed that 86 volatile components were detected during the fermentation of seabuckthorn seed meal, including 22 alcohols, 9 acids, 7 ketones, 14 alkanes, 20 esters, and 14 other compounds. With prolonged fermentation time, the content of acids and esters increased significantly
Case Report: Cancer spectrum and genetic characteristics of a de novo germline POLD1 p.L606M variant-induced polyposis syndrome
Germline variations in the DNA polymerase genes, POLE and POLD1, can lead to a hereditary cancer syndrome that is characterized by frequent gastrointestinal polyposis and multiple primary malignant tumors. However, because of its rare occurrence, this disorder has not been extensively studied. In this report, we present the case of a 22-year-old female patient who had been diagnosed with gastrointestinal polyposis, breast fibroadenoma, multiple primary colorectal cancers, and glioblastoma (grade IV) within a span of 4 years. Next-generation sequencing analysis revealed a germline variant in POLD1 (c.1816C>A; p.L606M). In silico analysis using protein functional predicting software, including SIFT, Polyphen, GERP++, and CADD, further confirmed the pathogenicity of POLD1 p.L606M (classified as ACMG grade Class 4). In line with polymerase deficiency, both rectal cancer and glioblastoma tissues exhibited a high tumor mutation burden, with 16.9 muts/Mb and 347.1 muts/Mb, respectively. Interestingly, the patient has no family history of cancer, and gene examination of both parents confirms that this is a de novo germline variant. Therefore, molecular screening for POLD1 may be necessary for patients with such a cancer spectrum, regardless of their family history
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