Issues and Path Selection of Artificial Intelligence Design Talents Training in applied Undergraduate Universities in Smart City

The widespread popularity and application of artificial intelligence technology requires technological innovation, of which talent training is an important content. The lack of professional talents has greatly restricted the development of the artificial intelligence industry to some extent. How to train industrial design talents with comprehensive qualities of artificial intelligence design talents in universities has now become the most important topic. Carry out university teacher training based on the industrial design profession, carry out the collaborative education innovation model based on university-enterprise-government , innovative ability and awareness training curriculum system, and use artificial intelligence talent training goals and curriculum system for the construction and practice of goals. Analyze the current plight of artificial intelligence design talent training in applied general universities, clarify the current types and status quo of artificial intelligence design talents, and propose specific ways to solve the current artificial intelligence design talent training. There are few relevant talents for artificial intelligence design professionals who can combine their ideas and technology in actual production. The lack of design talents has greatly limited the development of their industries to some extent. The current application-oriented undergraduates Colleges and universities should explore specific paths for the training of artificial intelligence design talents, and the construction and practice of related curriculum systems should also be gradually revised during practical exploration, so as to realize innovative education through educational innovation

Mean-variance hybrid portfolio optimization with quantile-based risk measure

This paper addresses the importance of incorporating various risk measures in portfolio management and proposes a dynamic hybrid portfolio optimization model that combines the spectral risk measure and the Value-at-Risk in the mean-variance formulation. By utilizing the quantile optimization technique and martingale representation, we offer a solution framework for these issues and also develop a closed-form portfolio policy when all market parameters are deterministic. Our hybrid model outperforms the classical continuous-time mean-variance portfolio policy by allocating a higher position of the risky asset in favorable market states and a less risky asset in unfavorable market states. This desirable property leads to promising numerical experiment results, including improved Sortino ratio and reduced downside risk compared to the benchmark models

An Exploratory Study on CLU, CR1 and PICALM and Parkinson Disease

Recent GWAS and subsequent confirmation studies reported several single-nucleotide polymorphisms (SNPs) at the CLU, CR1 and PICALM loci in association with late-onset Alzheimer's disease (AD). Parkinson disease (PD) shares several clinical and pathologic characteristics with AD; we therefore explored whether these SNPs were also associated with PD risk.791 non-Hispanic Whites cases and 1,580 matched controls were included in the study. Odds ratios (OR) and 95% confidence intervals (CI) were obtained from logistic regression models. rs11136000 at the CLU locus was associated with PD risk under the recessive model (comparing TT versus CC+CT: OR = 0.71, 95% CI: 0.55-0.92, p = 0.008) after adjusting for year of birth, gender, smoking, and caffeine intake. Further adjustment for family history of PD and ApoE ε4 status did not change the result. In addition, we did not find evidence for effect modification by ApoE or known PD risk factors. The association, however, appeared to be stronger for PD with dementia (OR = 0.49, 95% CI: 0.27-0.91) than for PD without dementia (OR = 0.81, 95% CI: 0.61-1.06). The two other SNPs, rs6656401 from CR1, and rs3851179 from PICALM region were not associated with PD (p>0.05).Our exploratory analysis suggests an association of CLU with PD. This exploratory finding and the role of dementia in explaining this finding needs further investigation