An alternating peak-optimization method for optimal trajectory generation of quadrotor drones

In this paper, we propose an alternating optimization method to address a time-optimal trajectory generation problem. Different from the existing solutions, our approach introduces a new formulation that minimizes the overall trajectory running time while maintaining the polynomial smoothness constraints and incorporating hard limits on motion derivatives to ensure feasibility. To address this problem, an alternating peak-optimization method is developed, which splits the optimization process into two sub-optimizations: the first sub-optimization optimizes polynomial coefficients for smoothness, and the second sub-optimization adjusts the time allocated to each trajectory segment. These are alternated until a feasible minimum-time solution is found. We offer a comprehensive set of simulations and experiments to showcase the superior performance of our approach in comparison to existing methods. A collection of demonstration videos with real drone flying experiments can be accessed at https://www.youtube.com/playlist?list=PLQGtPFK17zUYkwFT-fr0a8E49R8Uq712l

TaxAI: A Dynamic Economic Simulator and Benchmark for Multi-Agent Reinforcement Learning

Taxation and government spending are crucial tools for governments to promote economic growth and maintain social equity. However, the difficulty in accurately predicting the dynamic strategies of diverse self-interested households presents a challenge for governments to implement effective tax policies. Given its proficiency in modeling other agents in partially observable environments and adaptively learning to find optimal policies, Multi-Agent Reinforcement Learning (MARL) is highly suitable for solving dynamic games between the government and numerous households. Although MARL shows more potential than traditional methods such as the genetic algorithm and dynamic programming, there is a lack of large-scale multi-agent reinforcement learning economic simulators. Therefore, we propose a MARL environment, named \textbf{TaxAI}, for dynamic games involving $N$ households, government, firms, and financial intermediaries based on the Bewley-Aiyagari economic model. Our study benchmarks 2 traditional economic methods with 7 MARL methods on TaxAI, demonstrating the effectiveness and superiority of MARL algorithms. Moreover, TaxAI's scalability in simulating dynamic interactions between the government and 10,000 households, coupled with real-data calibration, grants it a substantial improvement in scale and reality over existing simulators. Therefore, TaxAI is the most realistic economic simulator, which aims to generate feasible recommendations for governments and individuals.Comment: 26 pages, 8 figures, 12 table

Freezing of gait in Parkinson’s disease with glucocerebrosidase mutations: prevalence, clinical correlates and effect on quality of life

ObjectivesMutations in glucocerebrosidase (GBA1) can change the clinical phenotype of Parkinson’s disease (PD). This study aimed to explore the clinical characteristics of freezing of gait (FOG) in PD patients with GBA1 mutations.MethodsA whole-exome sequencing analysis was used to identify the GBA1 mutations (pathogenic or likely pathogenic) and exclude other PD-related gene mutations. A forward binary logistic regression model was conducted to identify the associated factors of FOG. The stepwise multiple linear regression analysis models were used to explore the effect of FOG on quality of life.ResultsThe prevalence of FOG in patients with GBA1 mutations (30/95, 31.6%) was significantly higher than those in patients without GBA1 mutations (152/760, 20%) (p = 0.009). A higher (i.e., worse) Unified PD Rating Scale part III score (OR = 1.126, 95%CI = 1.061–1.194, p < 0.001) and a lower (i.e., worse) Montreal Cognitive Assessment score (OR = 0.830, 95%CI = 0.713–0.967, p = 0.017) were significantly associated with FOG in PD patients with GBA1 mutations. The presence of FOG was significantly associated with the decreased (i.e., worse) score of PD Questionnaire 39 after adjustment for sex, age, disease duration, motor score, and non-motor score (B = 14.981, p = 0.001).ConclusionFOG is a relatively common disabling symptom in PD patients with GBA1 mutations, which is affected by motor disability and cognitive decline. Quality of life is reduced in patients with FOG and GBA1 mutations

THEORETICAL AND EXPERIMENTAL STUDIES OF THE STABILITY IN CVD Nb3Sn SUPERCONDUCTING COMPOSITE TAPES

La stabilité dynamique de rubans composites de Nb3Sn a été étudiée. En considérant la limite d'élasticité des matériaux et un modèle à deux dimensions, un critère de stabilité a été déterminé théoriquement. En utilisant ce critère, on peut montrer qu'il existe une épaisseur optimale pour la couche de cuivre, épaisseur pour laquelle un maximum de densité de courant critique peut être obtenu. Les résultats théoriques sont en bon accord avec les expériences faites avec des bobines maquettes et avec les résultats publiés. En se basant sur la stabilité dynamique, l'unification des critères de stabilité cryostatique, dynamique et adiabatique est discuté.The dynamic stabi1ity of CVD Nb3Sn superconducting composite tapes has been studied. Considering plastic yield of the materials and based on a two-dimensional model, the stability criterion has been obtained theoretically. Using the above criterion, one can show that there exists an optimum thickness of the copper cladding, at which a maximum of the overall critical current density can be reached. The theoretical results are in good agreement with our experiments with simulation coils or with the reported results. Based on the theory of the dynamic stability, the unification of the cryostatic, dynamic and adiabatic stability has been discussed

Meta-analysis of the rs231775 locus polymorphism in the CTLA-4 gene and the susceptibility to Graves’ disease in children

The aim of this study was to systematically evaluate the correlation between the rs231775 locus polymorphism in the cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) gene and genetic susceptibility to Graves’ disease (GD) in children. Some studies found that the CTLA-4 gene polymorphism was associated with GD in children. The data up to February 2022 were retrieved from the databases. Stata 15.0 software was used for meta-analysis. A total of seven studies were included in our research. The results of the meta-analysis showed that the rs231775 locus polymorphism in the CTLA-4 gene in general and Asian populations was correlated with children’s susceptibility to GD (A vs G: OR = 0.75, 95% CI (0.660–0.86); GG vs AA: OR = 1.34, 95% CI (1.04–1.73); AG vs AA: OR = 1.32, 95% CI (1.02–1.10); AG + GG vs AA: OR = 3.81, 95% CI (2.17–6.70); GG vs AA + AG: OR = 1.23, 95% CI (1.05–1.45)). In summary, the rs231775 locus polymorphism in the CLTA-4 gene may be a risk factor for GD in Asian children. The G allele may be a susceptibility factor, while the allele A may be a protective factor against GD in Asian children. In the future, more large-scale studies may be needed to verify our results

Stage 1 Hypertension and the 10‐Year and Lifetime Risk of Cardiovascular Disease: A Prospective Real‐World Study

Background The 10‐year and lifetime cardiovascular disease risk in the population with stage 1 hypertension and the effects of recovery from and progression of stage 1 hypertension remain undetermined. Methods and Results This prospective cohort study included 96 268 individuals with blood pressure measurements obtained in 2006 and again in 2010. The 10‐year cardiovascular disease risk was estimated using the multivariable Cox proportional hazards model, and the lifetime risk was calculated using a modified survival analysis that accounted for the competing risk of death. Stage 1 hypertension was detected in 30.83% of the cohort. The 10‐year cardiovascular disease risk was 2.80%, and the lifetime risk was 16.61%. Compared with the normal blood pressure group, the stage 1 hypertension group had a 35% higher 10‐year risk (hazard ratio [HR], 1.35 [95% CI, 1.19–1.52]) and a 36% higher lifetime risk (HR, 1.36 [95% CI, 1.25–1.49]). By 2010, 12.57% of the participants with stage 1 hypertension had progressed to stage 2, with a significant 156% increase in 10‐year risk (HR, 2.56 [95% CI, 2.11–3.11]) and an increased lifetime risk of 129% (HR, 2.29 [95% CI, 1.89–2.77]). There was no appreciable change in risk in those with stage 1 hypertension whose blood pressure returned to the normal‐elevated range. Conclusions Stage 1 hypertension was associated with a significant increase in 10‐year and lifetime cardiovascular disease risk. Progression to stage 2 hypertension was associated with a marked increase in lifetime risk. The current guidelines require revision to promote early detection and appropriate management of blood pressure

Experimental Study on YOLO-Based Leather Surface Defect Detection

Accurate, reliable, and fast intelligent detection of leather surface defects has become an important subject in industrial inspection, which aims at improving production efficiency and increasing automation levels. This work focuses on the rapid defect recognition and localization of leather surface defects for industrious applications, which is based on the state-of-the-art real-time detection model YOLO. Three experimental Schemes with different challenges were designed to find the optimal YOLO-based leather surface defect detection scheme. Typical tanned leather surface defect images from the factory were collected, which are comprised of eight types of defects, namely rotten surface, hole, scratch, crease, healed injury, bacterial injury, growth line, and pinhole, which exhibit variations in shapes, sizes, and colors, reflecting the various characteristics found in tanned leather defects. A comprehensive and in-depth review of the YOLO series of models is presented, including YOLOv1 to YOLOv8. The systematic and extensive experiments were conducted,which indicate that the YOLO models can simultaneously detect multiple types of defects present in each leather image. The multi-defect detection task achieved a maximum of 52.3% mean average precision (mAP), 58.2% precision, and 68.7% recall. For single-class detection tasks, the highest performance reached 85.1% mAP, 90.9% precision, and 81.8% recall. These works provide feasible intelligent solutions for surface defects in the leather industry, laying a solid foundation for the design and development of new solutions for leather defect detection