A SLAM Algorithm Based on Adaptive Cubature Kalman Filter

We need to predict mathematical model of the system and a priori knowledge of the noise statistics when traditional simultaneous localization and mapping (SLAM) solutions are used. However, in many practical applications, prior statistics of the noise are unknown or time-varying, which will lead to large estimation errors or even cause divergence. In order to solve the above problem, an innovative cubature Kalman filter-based SLAM (CKF-SLAM) algorithm based on an adaptive cubature Kalman filter (ACKF) was established in this paper. The novel algorithm estimates the statistical parameters of the unknown system noise by introducing the Sage-Husa noise statistic estimator. Combining the advantages of the CKF-SLAM and the adaptive estimator, the new ACKF-SLAM algorithm can reduce the state estimated error significantly and improve the navigation accuracy of the SLAM system effectively. The performance of this new algorithm has been examined through numerical simulations in different scenarios. The results have shown that the position error can be effectively reduced with the new adaptive CKF-SLAM algorithm. Compared with other traditional SLAM methods, the accuracy of the nonlinear SLAM system is significantly improved. It verifies that the proposed ACKF-SLAM algorithm is valid and feasible

Flow simulation considering adsorption boundary layer based on digital rock and finite element method

Due to the low permeability of tight reservoirs, throats play a significant role in controlling fluid flow. Although many studies have been conducted to investigate fluid flow in throats in the microscale domain, comparatively fewer works have been devoted to study the effect of adsorption boundary layer (ABL) in throats based on the digital rock method. By considering an ABL, we investigate its effects on fluid flow. We build digital rock model based on computed tomography technology. Then, microscopic pore structures are extracted with watershed segmentation and pore geometries are meshed through Delaunay triangulation approach. Finally, using the meshed digital simulation model and finite element method, we investigate the effects of viscosity and thickness of ABL on microscale flow. Our results demonstrate that viscosity and thickness of ABL are major factors that significantly hinder fluid flow in throats

Case report: Microwave ablation is a safe and effective method for primary hyperparathyroidism in pregnancy

Primary hyperparathyroidism (PHPT) is a rare disease in pregnancy and endangers the health of both pregnant women and fetuses. However, the treatments are very limited for PHPT and most of them are unsatisfactory because of the peculiar state in pregnancy. The only curable method is parathyroidectomy which can be safely performed in the second trimester of pregnancy. In this case, we reported a pregnant woman with primary parathyroid adenoma presenting hypercalcemia and severe vomit at the end of first trimester. Finally, she got cured by microwave ablation at the end of first trimester and gave birth to a healthy baby boy

Association of sleep characteristics with cardiovascular disease risk in adults over 40 years of age: a cross-sectional survey

BackgroundThe relationship between sleep characteristics and cardiovascular disease (CVD) risk has yet to reach a consistent conclusion, and more research needs to be carried out. This study aimed to explore the relationship between snoring, daytime sleepiness, bedtime, sleep duration, and high-risk sleep patterns with CVD risk.MethodsData from the National Health and Nutrition Examination Survey (NHANES) 2015–2018 were collected and analyzed. Multivariable logistic regression was used to evaluate the relationship between snoring, daytime sleepiness, bedtime, sleep duration, high-risk sleep patterns, and CVD risk. Stratified analysis and interaction tests were carried out according to hypertension, diabetes and age.ResultsThe final analysis contained 6,830 participants, including 1,001 with CVD. Multivariable logistic regression suggested that the relationship between snoring [OR = 7.37,95%CI = (6.06,8.96)], daytime sleepiness [OR = 11.21,95%CI = (9.60,13.08)], sleep duration shorter than 7 h [OR = 9.50,95%CI = (7.65,11.79)] or longer than 8 h [OR = 6.61,95%CI = (5.33,8.19)], bedtime after 0:00 [OR = 13.20,95%CI = (9.78,17.80)] compared to 22:00–22:59, high-risk sleep patterns [OR = 47.73,95%CI = (36.73,62.04)] and CVD risk were statistically significant. Hypertension and diabetes interacted with high-risk sleep patterns, but age did not.ConclusionsSnoring, daytime sleepiness, excessive or short sleep duration, inappropriate bedtime, and high-risk sleep patterns composed of these factors are associated with the CVD risk. High-risk sleep patterns have a more significant impact on patients with hypertension and diabetes

The Relationship Between Cognitive Dysfunction and Symptom Dimensions Across Schizophrenia, Bipolar Disorder, and Major Depressive Disorder

Background: Cognitive dysfunction is considered a core feature among schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Despite abundant literature comparing cognitive dysfunction among these disorders, the relationship between cognitive dysfunction and symptom dimensions remains unclear. The study aims are a) to identify the factor structure of the BPRS-18 and b) to examine the relationship between symptom domains and cognitive function across SZ, BD, and MDD.Methods: A total of 716 participants [262 with SZ, 104 with BD, 101 with MDD, and 249 healthy controls (HC)] were included in the study. One hundred eighty participants (59 with SZ, 23 with BD, 24 with MDD, and 74 HC) completed the MATRICS Consensus Cognitive Battery (MCCB), and 507 participants (85 with SZ, 89 with BD, 90 with MDD, and 243 HC) completed the Wisconsin Card Sorting Test (WCST). All patients completed the Brief Psychiatric Rating Scale (BPRS).Results: We identified five BPRS exploratory factor analysis (EFA) factors (“affective symptoms,” “psychosis,” “negative/disorganized symptoms,” “activation,” and “noncooperation”) and found cognitive dysfunction in all of the participant groups with psychiatric disorders. Negative/disorganized symptoms were the most strongly associated with cognitive dysfunctions across SZ, BD, and MDD.Conclusions: Our findings suggest that cognitive dysfunction severity relates to the negative/disorganized symptom domain across SZ, BD, and MDD, and negative/disorganized symptoms may be an important target for effective cognitive remediation in SZ, BD, and MDD

Multi-Directional Growth of Aligned Carbon Nanotubes Over Catalyst Film Prepared by Atomic Layer Deposition

The structure of vertically aligned carbon nanotubes (CNTs) severely depends on the properties of pre-prepared catalyst films. Aiming for the preparation of precisely controlled catalyst film, atomic layer deposition (ALD) was employed to deposit uniform Fe2O3 film for the growth of CNT arrays on planar substrate surfaces as well as the curved ones. Iron acetylacetonate and ozone were introduced into the reactor alternately as precursors to realize the formation of catalyst films. By varying the deposition cycles, uniform and smooth Fe2O3 catalyst films with different thicknesses were obtained on Si/SiO2 substrate, which supported the growth of highly oriented few-walled CNT arrays. Utilizing the advantage of ALD process in coating non-planar surfaces, uniform catalyst films can also be successfully deposited onto quartz fibers. Aligned few-walled CNTs can be grafted on the quartz fibers, and they self-organized into a leaf-shaped structure due to the curved surface morphology. The growth of aligned CNTs on non-planar surfaces holds promise in constructing hierarchical CNT architectures in future

Graphene-Based Nanocomposites for Energy Storage

Since the first report of using micromechanical cleavage method to produce graphene sheets in 2004, graphene/graphene-based nanocomposites have attracted wide attention both for fundamental aspects as well as applications in advanced energy storage and conversion systems. In comparison to other materials, graphene-based nanostructured materials have unique 2D structure, high electronic mobility, exceptional electronic and thermal conductivities, excellent optical transmittance, good mechanical strength, and ultrahigh surface area. Therefore, they are considered as attractive materials for hydrogen (H2) storage and high-performance electrochemical energy storage devices, such as supercapacitors, rechargeable lithium (Li)-ion batteries, Li–sulfur batteries, Li–air batteries, sodium (Na)-ion batteries, Na–air batteries, zinc (Zn)–air batteries, and vanadium redox flow batteries (VRFB), etc., as they can improve the efficiency, capacity, gravimetric energy/power densities, and cycle life of these energy storage devices. In this article, recent progress reported on the synthesis and fabrication of graphene nanocomposite materials for applications in these aforementioned various energy storage systems is reviewed. Importantly, the prospects and future challenges in both scalable manufacturing and more energy storage-related applications are discussed