Cerebrovascular risk factors impact brain phenotypes and cognitive function in healthy population

Cognitive decline is a major characteristic of ageing. Studies show that cardiovascular risk factors (CVR) are associated with cognitive declines and brain phenotypes, but the causality between CVR and cognitive function needs further understanding. In this study, we seek to investigate the causalities between CVR, brain phenotypes and cognitive function. We first generate a general factor (gCVR) representing common CVR and a score representing the polygenic risk (PRS). We then identify phenotypes of brain and cognitive functions associated with gCVR and PRS. Moreover, we conduct causal mediation analysis to evaluate the indirect effect of PRS through CVR, which infers the causality of gCVR on brain phenotypes and cognition. Further, we test the mediation effect of gCVR on the total effect of brain phenotypes on cognitive function. Finally, the causality between CVR and brain phenotypes is cross validated using Mendelian randomization (MR) with genetic instruments. The results show that CVR mediates the effect of PRS on brain phenotypes and cognitive function, and CVR also mediates the effect of brain phenotypes on cognitive changes. Additionally, we validate that the variation in a few brain phenotypes., e.g., volume of grey matter, are caused by CVR

Cerebrovascular risk factors impact brain phenotypes and cognitive function in healthy population

Cognitive decline is a major characteristic of ageing. Studies show that cardiovascular risk factors (CVR) are associated with cognitive declines and brain phenotypes, but the causality between CVR and cognitive function needs further understanding. In this study, we seek to investigate the causalities between CVR, brain phenotypes and cognitive function. We first generate a general factor (gCVR) representing common CVR and a score representing the polygenic risk (PRS). We then identify phenotypes of brain and cognitive functions associated with gCVR and PRS. Moreover, we conduct causal mediation analysis to evaluate the indirect effect of PRS through CVR, which infers the causality of gCVR on brain phenotypes and cognition. Further, we test the mediation effect of gCVR on the total effect of brain phenotypes on cognitive function. Finally, the causality between CVR and brain phenotypes is cross validated using Mendelian randomization (MR) with genetic instruments. The results show that CVR mediates the effect of PRS on brain phenotypes and cognitive function, and CVR also mediates the effect of brain phenotypes on cognitive changes. Additionally, we validate that the variation in a few brain phenotypes., e.g., volume of grey matter, are caused by CVR

Online Adaptive Error Compensation SVM-Based Sliding Mode Control of an Unmanned Aerial Vehicle

Unmanned Aerial Vehicle (UAV) is a nonlinear dynamic system with uncertainties and noises. Therefore, an appropriate control system has an obligation to ensure the stabilization and navigation of UAV. This paper mainly discusses the control problem of quad-rotor UAV system, which is influenced by unknown parameters and noises. Besides, a sliding mode control based on online adaptive error compensation support vector machine (SVM) is proposed for stabilizing quad-rotor UAV system. Sliding mode controller is established through analyzing quad-rotor dynamics model in which the unknown parameters are computed by offline SVM. During this process, the online adaptive error compensation SVM method is applied in this paper. As modeling errors and noises both exist in the process of flight, the offline SVM one-time mode cannot predict the uncertainties and noises accurately. The control law is adjusted in real-time by introducing new training sample data to online adaptive SVM in the control process, so that the stability and robustness of flight are ensured. It can be demonstrated through the simulation experiments that the UAV that joined online adaptive SVM can track the changing path faster according to its dynamic model. Consequently, the proposed method that is proved has the better control effect in the UAV system

Online Adaptive Error Compensation SVM-Based Sliding Mode Control of an Unmanned Aerial Vehicle

Unmanned Aerial Vehicle (UAV) is a nonlinear dynamic system with uncertainties and noises. Therefore, an appropriate control system has an obligation to ensure the stabilization and navigation of UAV. This paper mainly discusses the control problem of quad-rotor UAV system, which is influenced by unknown parameters and noises. Besides, a sliding mode control based on online adaptive error compensation support vector machine (SVM) is proposed for stabilizing quad-rotor UAV system. Sliding mode controller is established through analyzing quad-rotor dynamics model in which the unknown parameters are computed by offline SVM. During this process, the online adaptive error compensation SVM method is applied in this paper. As modeling errors and noises both exist in the process of flight, the offline SVM one-time mode cannot predict the uncertainties and noises accurately. The control law is adjusted in real-time by introducing new training sample data to online adaptive SVM in the control process, so that the stability and robustness of flight are ensured. It can be demonstrated through the simulation experiments that the UAV that joined online adaptive SVM can track the changing path faster according to its dynamic model. Consequently, the proposed method that is proved has the better control effect in the UAV system. Document type: Articl

Comparison of a solvent mixture assisted dilute acid and alkali pretreatment in sugar production from hybrid Pennisetum

Abstract(#br)The effects of an acetone-butanol-ethanol (ABE) mixture on dilute H 2 SO 4 and NaOH pretreatment for enzymatic saccharification of hybrid Pennisetum (HP) were investigated. The results showed that ABE assisted the removal of xylan and lignin during H 2 SO 4 and NaOH pretreatment, respectively. The glucose yield of HP increased from 33.6% to 52.9% with the assistance of a relatively higher concentration of ABE mixture (ABE4) during H 2 SO 4 pretreatment, and during NaOH pretreatment, a lower concentration of ABE (ABE2) increased the glucose yield from 64.6% to 80.2%. The hydrolysis yield increases were related to the compositional change and surface characteristics of the pretreated materials. As observed by X-ray photoelectron spectroscopy, ABE4 resulted in a greater lignin content on the surface of materials than that produced by ABE2 during NaOH pretreatment, which possibly increased the non-productive adsorption of cellulase, thus decreasing the hydrolysis yield. The results suggested that an ABE mixture could be used as an auxiliary agent for further increasing of the digestibility of acid- and alkali-pretreated lignocellulosic materials. However, the digestibility was different depending on the concentrations of ABE during acid and alkali pretreatments

Characterizations of (Jordan) derivation on Banach algebra with local actions

Let $\mathcal{A}$ be a unital Banach $*$-algebra and $\mathcal{M}$ be a unital $*$-$\mathcal{A}$-bimodule. If $W$ is a left separating point of $\mathcal{M}$, we show that every $*$-derivable mapping at $W$ is a Jordan derivation, and every $*$-left derivable mapping at $W$ is a Jordan left derivation under the condition $W \mathcal{A}=\mathcal{A}W$. Moreover we give a complete description of linear mappings $\delta$ and $\tau$ from $\mathcal{A}$ into $\mathcal{M}$ satisfying $\delta(A)B^*+A\tau(B)^*=0$ for any $A, B\in \mathcal{A}$ with $AB^*=0$ or $\delta(A)\circ B^*+A\circ\tau(B)^*=0$ for any $A, B\in \mathcal{A}$ with $A\circ B^*=0$, where $A\circ B=AB+BA$ is the Jordan product

Study on the Interaction between the Reduction and Remediation of Dredged Sediments from Tai Lake Based on Vacuum Electro-Osmosis

The treatment of metal-contaminated sediment generated in environmental dredging projects often requires both reduction and remediation, and the electric field has good application prospects in the integration of reduction and remediation. In this study, based on the electro-osmosis, vacuum, and vacuum electro-osmosis methods, a detachable test system was made. Experiments of the three methods were carried out independently on the reduction and remediation of dredged sediment from Tai Lake under pollution-free and Cu-contaminated conditions. The results show that copper contamination weakens the effect of reduction, and the production of copper precipitates makes the soil more prone to cracking and blocking drainage channels, which has the greatest impact on the electro-osmosis method. In terms of copper concentration, vacuum electro-osmosis achieves the transport and discharge of contaminants, and has the best remediation effect. The removal rates at the anode and cathode are 45.1% and 50.0%, respectively. A correlation model based on electrical conductivity, moisture content, and contaminant concentration was established to facilitate the determination of contaminant concentrations in actual projects. Electro-migration plays a dominant role in the remediation process, and the reduction affects the electric field distribution and, thus, the migration efficiency

Online Adaptive Error Compensation SVM-Based Sliding Mode Control of an Unmanned Aerial Vehicle

Unmanned Aerial Vehicle (UAV) is a nonlinear dynamic system with uncertainties and noises. Therefore, an appropriate control system has an obligation to ensure the stabilization and navigation of UAV. This paper mainly discusses the control problem of quad-rotor UAV system, which is influenced by unknown parameters and noises. Besides, a sliding mode control based on online adaptive error compensation support vector machine (SVM) is proposed for stabilizing quad-rotor UAV system. Sliding mode controller is established through analyzing quad-rotor dynamics model in which the unknown parameters are computed by offline SVM. During this process, the online adaptive error compensation SVM method is applied in this paper. As modeling errors and noises both exist in the process of flight, the offline SVM one-time mode cannot predict the uncertainties and noises accurately. The control law is adjusted in real-time by introducing new training sample data to online adaptive SVM in the control process, so that the stability and robustness of flight are ensured. It can be demonstrated through the simulation experiments that the UAV that joined online adaptive SVM can track the changing path faster according to its dynamic model. Consequently, the proposed method that is proved has the better control effect in the UAV system

Techniques of Frameless Robot-Assisted Deep Brain Stimulation and Accuracy Compared with the Frame-Based Technique

Background: Frameless robot-assisted deep brain stimulation (DBS) is an innovative technique for leads implantation. This study aimed to evaluate the accuracy and precision of this technique using the Sinovation SR1 robot. Methods: 35 patients with Parkinson’s disease who accepted conventional frame-based DBS surgery (n = 18) and frameless robot-assisted DBS surgery (n = 17) by the same group of neurosurgeons were analyzed. The coordinate of the tip of the intended trajectory was recorded as xi, yi, and zi. The actual position of lead implantation was recorded as xa, ya, and za. The vector error was calculated by the formula of √(xi − xa)2 + (yi − ya)2 + (zi − za)2 to evaluate the accuracy. Results: The vector error was 1.52 ± 0.53 mm (range: 0.20–2.39 mm) in the robot-assisted group and was 1.77 ± 0.67 mm (0.59–2.98 mm) in the frame-based group with no significant difference between two groups (p = 0.1301). In 10.7% (n = 3) frameless robot-assisted implanted leads, the vector error was greater than 2.00 mm with a maximum offset of 2.39 mm, and in 35.5% (n = 11) frame-based implanted leads, the vector error was larger than 2.00 mm with a maximum offset of 2.98 mm. Leads were more posterior than planned trajectories in the robot-assisted group and more medial and posterior in the conventional frame-based group. Conclusions: Awake frameless robot-assisted DBS surgery was comparable to the conventional frame-based technique in the accuracy and precision for leads implantation