An Effective Surface Defect Classification Method Based on RepVGG with CBAM Attention Mechanism (RepVGG-CBAM) for Aluminum Profiles

The automatic classification of aluminum profile surface defects is of great significance in improving the surface quality of aluminum profiles in practical production. This classification is influenced by the small and unbalanced number of samples and lack of uniformity in the size and spatial distribution of aluminum profile surface defects. It is difficult to achieve high classification accuracy by directly using the current advanced classification algorithms. In this paper, digital image processing methods such as rotation, flipping, contrast, and luminance transformation were used to augment the number of samples and imitate the complex imaging environment in actual practice. A RepVGG with CBAM attention mechanism (RepVGG-CBAM) model was proposed and applied to classify ten types of aluminum profile surface defects. The classification accuracy reached 99.41%, in particular, the proposed method can perfectly classify six types of defects: concave line (cl), exposed bottom (eb), exposed corner bottom (ecb), mixed color (mc), non-conductivity (nc) and orange peel (op), with 100% precision, recall, and F1. Compared with the existing advanced classification algorithms VGG16, VGG19, ResNet34, ResNet50, ShuffleNet_v2, and basic RepVGG, our model is the best in terms of accuracy, macro precision, macro recall and macro F1, and the accuracy was improved by 4.85% over basic RepVGG. Finally, an ablation experiment proved that the classification ability was strongest when the CBAM attention mechanism was added following Stage 1 to Stage 4 of RepVGG. Overall, the method we proposed in this paper has a significant reference value for classifying aluminum profile surface defects

Rheb1 mediates DISC1-dependent regulation of new neuron development in the adult hippocampus

Acknowledgments: We thank D. Weinberger, D. St. Clair and D. Valle for discussion, Jaden Shin for gene expression analyses, members of Ming and Song Laboratories for help and critical comments, L. Liu, Y. Cai, Q. Hussaini, and M. Jardine-Alborz for technical support. Funding: This work was supported by NIH (NS048271, MH105128), NARSAD, and MSCRF to G-l.M., by NIH (NS047344 and NS093772) and MSCRF to H.S., by NARSAD and NIH (NS093772) to K.C., and by NARSAD to E.K.Peer reviewedPublisher PD

Investigating the Short-Term Effects of Cold Stress on Metabolite Responses and Metabolic Pathways in Inner-Mongolia Sanhe Cattle

Inner-Mongolia Sanhe cattle are well-adapted to low-temperature conditions, but the metabolic mechanisms underlying their climatic resilience are still unknown. Based on the 1H Nuclear Magnetic Resonance platform, 41 metabolites were identified and quantified in the serum of 10 heifers under thermal neutrality (5 °C), and subsequent exposure to hyper-cold temperature (−32 °C) for 3 h. Subsequently, 28 metabolites were pre-filtrated, and they provided better performance in multivariate analysis than that of using 41 metabolites. This indicated the need for pre-filtering of the metabolome data in a paired experimental design. In response to the cold exposure challenge, 19 metabolites associated with cold stress response were identified, mainly enriched in “aminoacyl-tRNA biosynthesis” and “valine, leucine, and isoleucine degradation”. A further integration of metabolome and gene expression highlighted the functional roles of the DLD(dihydrolipoamide dehydrogenase), WARS (tryptophanyl-tRNA synthetase), and RARS(arginyl-tRNA synthetase) genes in metabolic pathways of valine and leucine. Furthermore, the essential regulations of SLC30A6 (solute carrier family 30 (zinc transporter), member 6) in metabolic transportation for propionate, acetate, valine, and leucine under severe cold exposure were observed. Our findings presented a comprehensive characterization of the serum metabolome of Inner-Mongolia Sanhe cattle, and contributed to a better understanding of the crucial roles of regulations in metabolites and metabolic pathways during cold stress events in cattle

Brain-specific Crmp2 deletion leads to neuronal development deficits and behavioural impairments in mice

Acknowledgements: This work was supported by grants from NSF (31430037/31271156/ 31270826) and MOST (2014CB942801/2012CB517904/2012YQ03026006) to Z.X.; from NIH (NS048271, MH105128) to G.-l.M., from NIH (NS047344) to H.S., and from NRASAD to E.K. and K.M.C. Author notes: Hongsheng Zhang, Eunchai Kang and Yaqing Wang: These authors contributed equally to this work.Peer reviewedPublisher PD

Vasopressors in septic shock: a systematic review and network meta-analysis

Objective: Vasopressor agents are often prescribed in septic shock. However, their effects remain controversial. We conducted a systematic review and Bayesian network meta-analysis to compare the effects among different types of vasopressor agents. Data sources We searched for relevant studies in PubMed, Embase, and the Cochrane Library databases from database inception until December 2014. Study selection Randomized controlled trials in adults with septic shock that evaluated different vasopressor agents were selected. Data extraction Two authors independently selected studies and extracted data on study characteristics, methods, and outcomes. Data synthesis Twenty-one trials (n=3,819) met inclusion criteria, which compared eleven vasopressor agents or vasopressor combinations (norepinephrine [NE], dopamine [DA], vasopressin [VP], epinephrine [EN], terlipressin [TP], phenylephrine [PE], TP+NE, TP + dobutamine [DB], NE+DB, NE+EN, and NE + dopexamine [DX]). Except for the superiority of NE over DA, the mortality of patients treated with any vasopressor agent or vasopressor combination was not significantly different. Compared to DA, NE was found to be associated with decreased cardiac adverse events, heart rate (standardized mean difference [SMD]: −2.10; 95% confidence interval [CI]: −3.95, −0.25; P=0.03), and cardiac index (SMD: −0.73; 95% CI: −1.14, −0.03; P=0.004) and increased systemic vascular resistance index (SVRI) (SMD: 1.03; 95% CI: 0.61, 1.45; P<0.0001). This Bayesian meta-analysis revealed a possible rank of probability of mortality among the eleven vasopressor agents or vasopressor combinations; from lowest to highest, they are NE+DB, EN, TP, NE+EN, TP+NE, VP, TP+DB, NE, PE, NE+DX, and DA. Conclusion: In terms of survival, NE may be superior to DA. Otherwise, there is insufficient evidence to suggest that any other vasopressor agent or vasopressor combination is superior to another. When compared to DA, NE is associated with decreased heart rate, cardiac index, and cardiovascular adverse events, as well as increased SVRI. The effects of vasopressor agents or vasopressor combinations on mortality in patients with septic shock require further investigation