Canjun Wang
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View article: Modeling and Experimental Investigation of Ultrasonic Vibration-Assisted Drilling Force for Titanium Alloy
Modeling and Experimental Investigation of Ultrasonic Vibration-Assisted Drilling Force for Titanium Alloy Open
To overcome the issues of excessive cutting force, poor chip segmentation, and premature tool wear during the drilling of Ti-6Al-4V titanium alloy. This study established the cutting edge motion trajectory function and instantaneous dynami…
View article: Investigation of Basic Assumption for Contact Between Spheric Asperities in Rough Surface
Investigation of Basic Assumption for Contact Between Spheric Asperities in Rough Surface Open
Accurate analyses of contact problems for rough surfaces are important but complicated. Some assumptions, namely that all asperities can be approximated by a hemisphere with the same radius and assuming a Gaussian distribution of the asper…
View article: Experimental Investigation and Modeling of Surface Roughness in BTA Deep Hole Drilling with Vibration Assisted
Experimental Investigation and Modeling of Surface Roughness in BTA Deep Hole Drilling with Vibration Assisted Open
The surface roughness of hole machining greatly influences the mechanical properties of parts, such as early fatigue failure and corrosion resistance. The boring and trepanning association (BTA) deep hole drilling with axial vibration assi…
View article: Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm
Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm Open
Background The prevalence of Alzheimer's disease (AD) varies based on gender. Due to the lack of early stage biomarkers, most of them are diagnosed at the terminal stage. This study aimed to explore sex-specific signaling pathways and iden…
View article: Additional file 5 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm
Additional file 5 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm Open
Additional file 5: Supplementary Data 5. Significantly enriched GO entries and KEGG pathways in males.
View article: Additional file 7 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm
Additional file 7 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm Open
Additional file 7: Supplementary Data 7. GSEA in males.
View article: Additional file 1 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm
Additional file 1 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm Open
Additional file 1: Supplementary Data 1. List of DEGs in females.
View article: Additional file 3 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm
Additional file 3 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm Open
Additional file 3: Supplementary Data 3. Intersected DEGs lists of males and females.
View article: Additional file 2 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm
Additional file 2 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm Open
Additional file 2: Supplementary Data 2. List of DEGs in males.
View article: Additional file 9 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm
Additional file 9 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm Open
Additional file 9: Supplementary Data 9. Degree, MNC, Radiality, Stress and Closeness were used to screen 8 overlapping hub genes in males.
View article: Additional file 6 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm
Additional file 6 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm Open
Additional file 6: Supplementary Data 6. GSEA in females.
View article: Additional file 8 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm
Additional file 8 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm Open
Additional file 8: Supplementary Data 8. Degree, MNC, Radiality, Stress and Closeness were used to screen 11 overlapping hub genes in females.
View article: Additional file 4 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm
Additional file 4 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm Open
Additional file 4: Supplementary Data 4. Significantly enriched GO entries and KEGG pathways in females.
View article: Additional file 10 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm
Additional file 10 of Bioinformatics analysis of diagnostic biomarkers for Alzheimer's disease in peripheral blood based on sex differences and support vector machine algorithm Open
Additional file 10: Supplementary Data 10. A statistical analysis of immune checkpoint genes and 13 hub genes.
View article: Subthreshold Periodic Signal Detection by Bounded Noise‐Induced Resonance in the FitzHugh–Nagumo Neuron
Subthreshold Periodic Signal Detection by Bounded Noise‐Induced Resonance in the FitzHugh–Nagumo Neuron Open
Neurons can detect weak target signals from complex background signals through stochastic resonance (SR) and vibrational resonance (VR) mechanisms. However, random phase variation of rapidly fluctuating background signals is generally igno…
View article: Exploring the Mechanical Anisotropy and Ideal Strengths of Tetragonal B4CO4
Exploring the Mechanical Anisotropy and Ideal Strengths of Tetragonal B4CO4 Open
First-principles calculations were employed to study the mechanical properties for the recently proposed tetragonal B4CO4 (t-B4CO4). The calculated structural parameters and elastic constants of t-B4CO4 are in excellent agreement with the …
View article: Enhancing Stability of Thin-Walled Short Steel Channel Using CFRP under Eccentric Compression
Enhancing Stability of Thin-Walled Short Steel Channel Using CFRP under Eccentric Compression Open
This paper presents the experimental and analytical results of eccentrically loaded short cold-formed thin-wall steel channels strengthened with transversely oriented carbon fiber reinforced polymer (CFRP) strips around their web and flang…