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Visual place recognition (VPR) in condition-varying environments is still an open problem. Popular solutions are convolutional neural network (CNN)-based image descriptors, which have been shown to outperform traditional image descriptors based on hand-crafted visual features. However, there are two drawbacks of current CNN-based descriptors: (a) their high dimension and (b) lack of generalization, leading to low efficiency and poor performance in real robotic applications. In this paper, we propose to use a convolutional autoencoder (CAE) to tackle this problem. We employ a high-level layer of a pre-trained CNN to generate features and train a CAE to map the features to a low-dimensional space to improve the condition invariance property of the descriptor and reduce its dimension at the same time. We verify our method in four challenging real-world datasets involving significant illumination changes, and our method is shown to be superior to the state-of-the-art. The code of our work is publicly available at https://github.com/MedlarTea/CAE-VPR.
Coastal eutrophication and hypoxia remain a persistent environmental crisis despite the great efforts to reduce nutrient loading and mitigate associated environmental damages. Symptoms of this crisis have appeared to spread rapidly, reaching developing countries in Asia with emergences in Southern America and Africa. The pace of changes and the underlying drivers remain not so clear. To address the gap, we review the up-to-date status and mechanisms of eutrophication and hypoxia in global coastal oceans, upon which we examine the trajectories of changes over the 40 years or longer in six model coastal systems with varying socio-economic development statuses and different levels and histories of eutrophication. Although these coastal systems share common features of eutrophication, site-specific characteristics are also substantial, depending on the regional environmental setting and level of social-economic development along with policy implementation and management. Nevertheless, ecosystem recovery generally needs greater reduction in pressures compared to that initiated degradation and becomes less feasible to achieve past norms with a longer time anthropogenic pressures on the ecosystems. While the qualitative causality between drivers and consequences is well established, quantitative attribution of these drivers to eutrophication and hypoxia remains difficult especially when we consider the social economic drivers because the changes in coastal ecosystems are subject to multiple influences and the cause–effect relationship is often non-linear. Such relationships are further complicated by climate changes that have been accelerating over the past few decades. The knowledge gaps that limit our quantitative and mechanistic understanding of the human-coastal ocean nexus are identified, which is essential for science-based policy making. Recognizing lessons from past management practices, we advocate for a better, more efficient indexing system of coastal eutrophication and an advanced regional earth system modeling framework with optimal modules of human dimensions to facilitate the development and evaluation of effective policy and restoration actions.
Engineered biomaterials provide unique functions to overcome the bottlenecks seen in biomedicine. Hence, a technique for rapid and routine tests of collagen is required, in which the test items commonly include molecular weight, crosslinking degree, purity, and sterilization induced structural change. Among them, the crosslinking degree mainly influences collagen properties. In this study, second harmonic generation (SHG) and coherent anti-Stokes Raman scattering (CARS) microscopy are used in combination to explore the collagen structure at molecular and macromolecular scales. These measured parameters are applied for the classification and quantification among the different collagen scaffolds, which were verified by other conventional methods. It is demonstrated that the crosslinking status can be analyzed from SHG images and presented as the coherency of collagen organization that is correlated with the mechanical properties. Also, the comparative analyses of SHG signal and relative CARS signal of amide III band at 1,240 cm−1 to δCH2 band at 1,450 cm−1 of these samples provide information regarding the variation of the molecular structure during a crosslinking process, thus serving as nonlinear optical signatures to indicate a successful crosslinking.
Based on a cohort from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), we aimed to evaluate the relationship between sleep duration and the incidence of cognitive impairment among older Chinese adults.
We conducted a prospective analysis based on 3692 participants from the CLHLS at baseline (in 2011), and as a 3-year follow-up (till 2014), 531 participants (14.4%) had cognitive impairment, which was defined as a Mini-Mental State Examination score <24. Sleep duration was classified into three groups: short (≤5 hours/day), normal (>5 but <10 hours), and long (≥10 hours/day). A logistic regression model was used to examine the association between baseline sleep duration and cognitive impairment after adjusting for sociodemographic data, living habits, and health conditions.
Five hundred sixty-two participants (15.2%) were in the short-duration group, and 608 participants (16.5%) were in the long-duration group. After adjusting for multiple potential confounders, compared with normal sleep duration, long sleep duration was associated with the incidence of cognitive impairment (OR = 1.309, 95% CI: 1.019–1.683), especially among men (OR = 1.527, 95% CI: 1.041–2.240) and those having a primary and above education level (OR = 1.559, 95% CI: 1.029–2.361). No significant association was observed between short sleep duration and cognitive impairment (OR = 0.860, 95% CI: 0.646–1.145).
Excessive sleep may increase the risk of cognitive impairment in older individuals. It may be a suggestive sign of early neurodegeneration and may be a useful clinical tool to identify those at a higher risk of progressing to cognitive impairment.
Obstacle avoidance is an important issue in robotics. In this paper, the particle
swarm optimization (PSO) algorithm, which is inspired by the collective
behaviors of birds, has been designed for solving the obstacle avoidance
problem. Some animals that travel to the different places at a specific time of
the year are called migrants. The migrants also represent the particles of PSO
for defining the walking paths in this work. Migrants consider not only the
collective behaviors, but also geomagnetic fields during their migration in
nature. Therefore, in order to improve the performance and the convergence speed
of the PSO algorithm, concepts from the migrant navigation method have been
adopted for use in the proposed hybrid particle swarm optimization (H-PSO)
algorithm. Moreover, the potential field navigation method and the designed
fuzzy logic controller have been combined in H-PSO, which provided a good
performance in the simulation and the experimental results. Finally, the
Federation of International Robot-soccer Association (FIRA) HuroCup Obstacle Run
Event has been chosen for validating the feasibility and the practicability of
the proposed method in real time. The designed adult-sized humanoid robot also
performed well in the 2015 FIRA HuroCup Obstacle Run Event through utilizing the
Previous studies have suggested that vitamin E (VE) may affect bone health, but the findings have been inconclusive. We examined the relationship between VE status (in both diet and serum) and bone mineral density (BMD) among Chinese adults. This community-based study included 3203 adults (2178 women and 1025 men) aged 40–75 years from Guangzhou, People’s Republic of China. General and dietary intake information were collected using structured questionnaire interviews. The serum α-tocopherol (TF) level was quantified by reversed-phase HPLC. The BMD of the whole body, the lumbar spine and left hip sites (total, neck, trochanter, intertrochanter and Ward’s triangle) were measured using dual-energy X-ray absorptiometry. In women, the dietary intake of VE was significantly and positively associated with BMD at the lumbar spine, total hip, intertrochanter and femur neck sites after adjusting for covariates (Ptrend: 0·001–0·017). Women in quartile 3 of VE intake typically had the highest BMD; the covariate-adjusted mean BMD were 2·5, 3·06, 3·41 and 3·54 % higher, respectively, in quartile 3 (v. 1) at the four above-mentioned sites. Similar positive associations were observed between cholesterol-adjusted serum α-TF levels and BMD at each of the studied bone sites (Ptrend: 0·001–0·022). The covariate-adjusted mean BMD were 1·24–4·83 % greater in quartile 4 (v. 1) in women. However, no significant associations were seen between the VE levels (dietary or serum) and the BMD at any site in men. In conclusion, greater consumption and higher serum levels of VE are associated with greater BMD in Chinese women but not in Chinese men.
The association between serum carotenoids and the metabolic syndrome (MetS) remains uncertain, and little is known about this relationship in the Chinese population. The present study examined the association between serum carotenoid concentrations and the MetS in Chinese adults. We conducted a community-based cross-sectional study in which 2148 subjects (1547 women and 601 men) aged 50–75 years were recruited in urban Guangzhou, China. Dietary data and other covariates were collected during face-to-face interviews. Blood pressure, waist circumference, blood lipids, glucose and serum carotenoids (α-, β-carotene, β-cryptoxanthin, lycopene and lutein/zeaxanthin) were examined. We found dose–response inverse relationships between individual serum carotenoid concentrations and total carotenoids and the prevalence of the MetS after adjusting for potential confounders (P for trend < 0·001). The OR of the MetS for the highest (v. lowest) quartile were 0·31 (95 % CI 0·20, 0·47) for α-carotene, 0·23 (95 % CI 0·15, 0·36) for β-carotene, 0·44 (95 % CI 0·29, 0·67) for β-cryptoxanthin, 0·39 (95 % CI 0·26, 0·58) for lycopene, 0·28 (95 % CI 0·18, 0·44) for lutein+zeaxanthin and 0·19 (95 % CI 0·12, 0·30) for total carotenoids. Higher concentrations of each individual carotenoid and total carotenoids were significantly associated with a decrease in the number of abnormal MetS components (P for trend < 0·001–0·023). Higher serum carotenoid levels were associated with a lower prevalence of the MetS and fewer abnormal MetS components in middle-aged and elderly Chinese adults.
Early identification of patients with bipolar disorder during their first depressive episode is beneficial to the outcome of the disorder and treatment, but traditionally this has been a great challenge to clinicians. Recently, brain-derived neurotrophic factor (BDNF) has been suggested to be involved in the pathophysiology of bipolar disorder and major depressive disorder (MDD), but it is not clear whether BDNF levels can be used to predict bipolar disorder among patients in their first major depressive episode.
To explore whether BDNF levels can differentiate between MDD and bipolar disorder in the first depressive episode.
A total of 203 patients with a first major depressive episode as well as 167 healthy controls were recruited. After 3 years of bi-annual follow-up, 164 patients with a major depressive episode completed the study, and of these, 21 were identified as having bipolar disorder and 143 patients were diagnosed as having MDD. BDNF gene expression and plasma levels at baseline were compared among the bipolar disorder, MDD and healthy control groups. Logistic regression and decision tree methods were applied to determine the best model for predicting bipolar disorder at the first depressive episode.
At baseline, patients in the bipolar disorder and MDD groups showed lower BDNF mRNA levels (P<0.001 and P = 0.02 respectively) and plasma levels (P = 0.002 and P = 0.01 respectively) compared with healthy controls. Similarly, BDNF levels in the bipolar disorder group were lower than those in the MDD group. These results showed that the best model for predicting bipolar disorder during a first depressive episode was a combination of BDNF mRNA levels with plasma BDNF levels (receiver operating characteristics (ROC) = 0.80, logistic regression; ROC = 0.84, decision tree).
Our findings suggest that BDNF levels may serve as a potential differential diagnostic biomarker for bipolar disorder in a patient's first depressive episode.
We make a connection between the continuous time and lazy discrete time Markov chains through the comparison of cutoffs and mixing time in total variation distance. For illustration, we consider finite birth and death chains and provide a criterion on cutoffs using eigenvalues of the transition matrix.
From the Surface Velocity Program (SVP) drifter current data, a detailed and complete track of strong ocean currents in the north-western Pacific is provided using the bin average method. The focus of this study is on the Kuroshio, the strong western boundary current of the North Pacific flowing northward along the east coast of Taiwan and then turning eastward off southern Japan. With its average flow speed of about 2 knots, the Kuroshio can significantly increase the ship's speed for a “super-slow-steaming” container ship travelling at speeds of 12 knots between the ports of Southeast Asia and Japan. By properly utilizing knowledge of strong ocean currents to follow the Kuroshio on the northbound runs and avoid it on the return trip, considerable fuel can be saved and the transit time can be reduced. In the future, the detailed Kuroshio saving-energy route could be built into electronic chart systems for all navigators and shipping routers.
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