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The rapid development of unmanned aerial vehicles (UAV) puts forward a higher requirement for autonomous obstacle avoidance. Due to the limited payload and power supply, small UAVs such as quadrotors usually carry simple sensors and computation units, which makes traditional methods more challenging to implement. In this paper, a novel framework is demonstrated to control a quadrotor flying through crowded environments autonomously with monocular vision. The framework adopts a two-stage architecture, consisting of a sensing module and a decision module. The sensing module is based on an unsupervised deep learning method. And the decision module uses dueling double deep recurrent Q-learning to eliminate the adverse effects of limited observation capacity of an on-board monocular camera. The framework enables the quadrotor to realize autonomous obstacle avoidance without any prior environment information or labeled datasets for training. The trained model shows a high success rate in the simulation and a good generalization ability for transformed scenarios., 23 pages, 10 figures

SUMMARY OBJECTIVE To investigate the clinical efficacy of cefazolin sodium pentahydrate combined with vacuum sealing drainage (VSD) in the treatment of open fracture complicated with soft tissue injury. METHODS Sixty-three patients with open fracture complicated with soft tissue injury were divided into observation (n = 33) and control (n = 30) groups. After surgical reduction, fixation, and repair of the fractures, the control group was treated with VSD for 10 days, and the observation group was treated with cefazolin sodium pentahydrate based on VSD for 10 days. The infection control time was recorded. After treatment, the pain of patients was evaluated. Before and after treatment, the serum levels of C-reactive protein (CRP), interleukin (IL)-6, IL-8, tumor necrosis factor α (TNF-α), cortisol, epinephrine, norepinephrine, and glucose were detected. After 6 months of treatment, the total effective rate of the treatment was evaluated. RESULTS The infection control time and Visual Analogue Scale score after treatment in the observation group were significantly lower than in the control group, respectively (P < 0.05). After the treatment, the serum levels of CRP, IL-6, IL-8, TNF-α, cortisol, epinephrine, norepinephrine, and glucose in each group were significantly lower than before the treatment (P < 0.05), and each index in observation was significantly lower than in the control group (P < 0.05). CONCLUSIONS In the treatment of open fractures complicated with soft tissue injury, cefazolin sodium pentahydrate combined with VSD can effectively reduce inflammation and stress, thus improving the treatment efficacy.

Multi-state models have been widely used to analyse longitudinal event history data obtained in medical and epidemiological studies. The tools and methods developed recently in this area require completely observed data. However, missing data within variables of interest are very common in practice, and they have been an issue in applications. We propose a type of expectation–maximization (EM) algorithm, which handles missingness within multiple binary covariates efficiently, for multi-state model applications. Simulation studies show that the EM algorithm performs well for both missing completely at random and missing at random covariate data. We apply the method to a longitudinal aging and cognition study data-set, the Klamath Exceptional Aging Project, whose data were collected at Oregon Health & Science University and integrated into the Statistical Models of Aging and Risk of Transition database at the University of Kentucky.

Longitudinal cognitive trajectories and other factors associated with mixed neuropathologies (such as Alzheimer’s disease with co-occurring cerebrovascular disease) remain incompletely understood, despite being the rule and not the exception in older populations. The Statistical Modeling of Aging and Risk of Transition study (SMART) is a consortium of 11 different high-quality longitudinal studies of aging and cognition (N=11,541 participants) established for the purpose of characterizing risk and protective factors associated with subtypes of age-associated mixed neuropathologies (N=3,001 autopsies). While brain donation was not required for participation in all SMART cohorts, most achieved substantial autopsy rates (i.e., > 50%). Moreover, the studies comprising SMART have large numbers of participants who were followed from intact cognition and transitioned to cognitive impairment and dementia, as well as participants who remained cognitively intact until death. These data provide an exciting opportunity to apply sophisticated statistical methods, like Markov processes, that require large, well-characterized samples. Thus, SMART will serve as an important resource for the field of mixed dementia epidemiology and neuropathology.

Background: Subjective memory complaints are common in aged persons, indicating an increased, but incompletely understood, risk for dementia. Objective: To compare cognitive trajectories and autopsy results of individuals with subjective complaints after stratifying by whether a subsequent clinical dementia occurred. Design: Observational study. Setting: University of Kentucky cohort with yearly longitudinal assessments and eventual autopsies Participants: Among 516 patients who were cognitively intact and depression-free at enrollment, 296 declared a memory complaint during follow-up. Among those who came to autopsy, 118 died but never developed dementia, while 36 died following dementia diagnosis. Measurements: Cognitive domain trajectories were compared using linear mixed models adjusted for age, gender, years of education and APOE status. Neuropathological findings were compared cross-sectionally after adjustment for age at death. Results: While the groups had comparable cognitive test scores at enrollment and the time of the first declaration of a complaint, the group with subsequent dementia development had steeper slopes of decline in episodic memory and naming but not fluency or sequencing. Autopsies showed the dementia group had more severe Alzheimer pathology and a higher proportion of subjects with hippocampal sclerosis of aging and arteriolosclerosis, whereas the non-demented group had a higher proportion expressing primary age related tauopathy (PART). Conclusions: While memory complaints are common among the elderly, not all individuals progress to dementia. This study indicates that biomarkers are needed to predict whether a complaint will lead to dementia if this is used as enrollment criteria in future clinical trials.

Extending the adaptive integral LOS path following method from planar to spatial, this paper presents a novel spatial path following control method for an under-actuated stratospheric airship in the presence of unknown wind. The nonlinear dynamic model of the airship is first introduced. Then, the spatial adaptive integral LOS guidance method generates the desired attitude and estimates the wind. The backstepping and Lyapunov-based techniques are adopted to track the predefined attitude and velocity. The final design of the control system consists of three parts: guidance loop, attitude control loop and velocity control loop. Stability analysis demonstrates that the closed-loop control system is ultimately bounded. Simulation results of the typical path are proposed to illustrate the effectiveness of the proposed control method.

Inaccurate system parameters and unpredicted external disturbances affect the performance of non-linear controllers. In this paper, a new adaptive control algorithm under the reinforcement framework is proposed to stabilize a quadrotor helicopter. Based on a command-filtered non-linear control algorithm, adaptive elements are added and learned by policy-search methods. To predict the inaccurate system parameters, a new kernel-based regression learning method is provided. In addition, Policy learning by Weighting Exploration with the Returns (PoWER) and Return Weighted Regression (RWR) are utilized to learn the appropriate parameters for adaptive elements in order to cancel the effect of external disturbance. Furthermore, numerical simulations under several conditions are performed, and the ability of adaptive trajectory-tracking control with reinforcement learning are demonstrated.

In respect to descent trajectory optimization of stratospheric airships, thermal effects were considered. Basic thermal characteristics of stratospheric airships and energy equations about the film and the internal gas were introduced. Besides, the equations of motion for the airship were described in details. To minimum the flight time, a direct collocation method was adopted to convert the trajectory optimization problem into a parameter optimization problem. In different scenarios, the optimal trajectories were developed by a numerical nonlinear solver, sparse nonlinear optimizer (SNOPT). It is shown that the solutions are greatly affected by thermal effects and solar irradiation plays an important role during descent.

Maintenance of cellular homeostasis is regulated by the molecular chaperones. Under pathogenic conditions, aberrant proteins are triaged by the chaperone network. These aberrant proteins, known as “clients,” have major roles in the pathogenesis of numerous neurological disorders, including tau in Alzheimer’s disease, α-synuclein and LRRK2 in Parkinson’s disease, SOD-1, TDP-43 and FUS in amyotrophic lateral sclerosis, and polyQ-expanded proteins such as huntingtin in Huntington’s disease. Recent work has demonstrated that the use of chemical compounds which inhibit the activity of molecular chaperones subsequently alter the fate of aberrant clients. Inhibition of Hsp90 and Hsc70, two major molecular chaperones, has led to a greater understanding of how chaperone triage decisions are made and how perturbing the chaperone system can promote clearance of these pathogenic clients. Described here are major pathways and components of several prominent neurological disorders. Also discussed is how treatment with chaperone inhibitors, predominately Hsp90 inhibitors which are selective for a diseased state, can relieve the burden of aberrant client signaling in these neurological disorders.

The world’s population is growing older due to improved healthcare and nutrition. As a result, Alzheimer’s disease (AD) prevalence is rapidly increasing. The focus of the current research climate is shifting from understanding AD pathology and diagnosis to primary prevention and intervention strategies. Diet represents one potential intervention strategy accessible to all. Accumulating evidence suggests diet plays a major role in risk and development of AD and AD-related chronic diseases of the periphery like cardiovascular disease (CVD) and diabetes. This paper reviews studies that have explored the relationship between “a priori” dietary patterns, AD and AD-related chronic disease risk. The dietary patterns we will review are the healthy eating index, healthy diet indicator, recommended food score, and the Mediterranean diet (MeDi). Our review of the literature suggests a generally positive association between healthy diet patterns, AD and AD-related chronic disease risk; however the magnitude of the protective effect is modest in many studies. Consequently, we can only confidently conclude that the MeDi is associated with reduced AD risk, and further studies on the remaining indices need to be carried out. It is our opinion that a combination of dietary scores could predict overall dietary quality and chronic disease risk to a greater extent than one score individually. Analysis in multi-ethnic cohorts, investigating combinations of scores must be completed before firm conclusions can be reached on the ideal combination of scores. Obtaining further insight into the association between dietary patterns, AD and AD-related chronic disease risk may help in prioritizing public health efforts and provide a stronger basis for recommendations to improve dietary patterns. Refereed/Peer-reviewed