Seasonal patterns and bloom dynamics of phytoplankton based on satellite-derived chlorophyll-a in the eastern yellow sea.

Satellite-derived chlorophyll-a concentration (Chl-a) is essential for assessing environmental conditions, yet its application in the optically complex waters of the eastern Yellow Sea (EYS) is challenged. This study refines the Chl-a algorithm for the EYS employing a switching approach based on normalized water-leaving radiance at 555 nm wavelength according to turbidity conditions to investigate phytoplankton bloom patterns in the EYS. The refined Chl-a algorithm (EYS algorithm) outperforms prior algorithms, exhibiting a strong alignment with in situ Chl-a. Employing the EYS algorithm, seasonal and bloom patterns of Chl-a are detailed for the offshore and nearshore EYS areas. Distinct seasonal Chl-a patterns and factors influencing bloom initiation differed between the areas, and the peak Chl-a during the bloom period from 2018 to 2020 was significantly lower than the average year in both areas. Specifically, bimodal and unimodal peak patterns in Chl-a were observed in the offshore and nearshore areas, respectively. By investigating the relationships between environmental factors and bloom parameters, we identified that major controlling factors governing bloom initiation were mixed layer depth (MLD) and suspended particulate matter (SPM) in the offshore and nearshore areas, respectively. Additionally, this study proposed that the recent decrease in the peak Chl-a might be caused by rapid environmental changes such as the warming trend of sea surface temperature (SST) and the limitation of nutrients. For example, external forcing, phytoplankton growth, and nutrient dynamics can change due to increased SST and limitation of nutrients, which can lead to a decrease in Chl-a. This study contributes to understanding phytoplankton dynamics in the EYS, highlighting the importance of region-specific considerations in comprehending Chl-a patterns and bloom dynamics.

Adaptive Discount Factor for Deep Reinforcement Learning in Continuing Tasks with Uncertainty.

Reinforcement learning (RL) trains an agent by maximizing the sum of a discounted reward. Since the discount factor has a critical effect on the learning performance of the RL agent, it is important to choose the discount factor properly. When uncertainties are involved in the training, the learning performance with a constant discount factor can be limited. For the purpose of obtaining acceptable learning performance consistently, this paper proposes an adaptive rule for the discount factor based on the advantage function. Additionally, how to use the advantage function in both on-policy and off-policy algorithms is presented. To demonstrate the performance of the proposed adaptive rule, it is applied to PPO (Proximal Policy Optimization) for Tetris in order to validate the on-policy case, and to SAC (Soft Actor-Critic) for the motion planning of a robot manipulator to validate the off-policy case. In both cases, the proposed method results in a better or similar performance compared with cases using the best constant discount factors found by exhaustive search. Hence, the proposed adaptive discount factor automatically finds a discount factor that leads to comparable training performance, and that can be applied to representative deep reinforcement learning problems.

Implementation of Hemispherical Resonator Gyroscope with 3 × 3 Optical Interferometers for Analysis of Resonator Asymmetry.

A hemispherical resonator gyroscope (HRG) has been implemented by using a consumer wineglass as the resonator and 3 × 3 optical interferometers as the detectors. The poorness of the off-the-shelf wineglass as the resonator can be overcome by the high performance of the optical interferometer. The effects of asymmetries in stiffness and absorption of the resonator are analyzed theoretically and confirmed experimentally. We prove that the trace of the amplitude ratio of two n = 2 fundamental resonant modes of the resonator follows a straight line in a complex plane. By utilizing the straightness of the ratio and the high performance of the optical interferometer, we extract four real constant parameters characterizing the HRG system. Experimentally, by using a resonator having an average resonance frequency of 444 Hz and Q value of 1477.2, it was possible to measure the Coriolis force at the level of industrial grade. The bias stability was measured as small as 2.093°/h.

Path Planning for Multi-Arm Manipulators Using Deep Reinforcement Learning: Soft Actor-Critic with Hindsight Experience Replay.

Since path planning for multi-arm manipulators is a complicated high-dimensional problem, effective and fast path generation is not easy for the arbitrarily given start and goal locations of the end effector. Especially, when it comes to deep reinforcement learning-based path planning, high-dimensionality makes it difficult for existing reinforcement learning-based methods to have efficient exploration which is crucial for successful training. The recently proposed soft actor-critic (SAC) is well known to have good exploration ability due to the use of the entropy term in the objective function. Motivated by this, in this paper, a SAC-based path planning algorithm is proposed. The hindsight experience replay (HER) is also employed for sample efficiency and configuration space augmentation is used in order to deal with complicated configuration space of the multi-arms. To show the effectiveness of the proposed algorithm, both simulation and experiment results are given. By comparing with existing results, it is demonstrated that the proposed method outperforms the existing results.

Severe Fever with Thrombocytopenia Syndrome Virus in Ticks and SFTS Incidence in Humans, South Korea.

During 2016-2018, we collected 3,193 ticks from rural areas in South Korea to investigate the prevalence of severe fever with thrombocytopenia syndrome virus (SFTSV). We detected SFTSV in ticks at an infection rate (IR) of 11.1%. We noted increases in the human IR associated with the monthly SFTSV IR in ticks.

Hypoxia-enhanced adhesion of red blood cells in microscale flow.

OBJECTIVES: The advancement of microfluidic technology has facilitated the simulation of physiological conditions of the microcirculation, such as oxygen tension, fluid flow, and shear stress in these devices. Here, we present a micro-gas exchanger integrated with microfluidics to study RBC adhesion under hypoxic flow conditions mimicking postcapillary venules. METHODS: We simulated a range of physiological conditions and explored RBC adhesion to endothelial or subendothelial components (FN or LN). Blood samples were injected into microchannels at normoxic or hypoxic physiological flow conditions. Quantitative evaluation of RBC adhesion was performed on 35 subjects with homozygous SCD. RESULTS: Significant heterogeneity in RBC adherence response to hypoxia was seen among SCD patients. RBCs from a HEA population showed a significantly greater increase in adhesion compared to RBCs from a HNA population, for both FN and LN. CONCLUSIONS: The approach presented here enabled the control of oxygen tension in blood during microscale flow and the quantification of RBC adhesion in a cost-efficient and patient-specific manner. We identified a unique patient population in which RBCs showed enhanced adhesion in hypoxia in vitro. Clinical correlates suggest a more severe clinical phenotype in this subgroup.

Emerging point-of-care technologies for sickle cell disease screening and monitoring.

INTRODUCTION: Sickle Cell Disease (SCD) affects 100,000 Americans and more than 14 million people globally, mostly in economically disadvantaged populations, and requires early diagnosis after birth and constant monitoring throughout the life-span of the patient. Areas covered: Early diagnosis of SCD still remains a challenge in preventing childhood mortality in the developing world due to requirements of skilled personnel and high-cost of currently available modalities. On the other hand, SCD monitoring presents insurmountable challenges due to heterogeneities among patient populations, as well as in the same individual longitudinally. Here, we describe emerging point-of-care micro/nano platform technologies for SCD screening and monitoring, and critically discuss current state of the art, potential challenges associated with these technologies, and future directions. Expert commentary: Recently developed microtechnologies offer simple, rapid, and affordable screening of SCD and have the potential to facilitate universal screening in resource-limited settings and developing countries. On the other hand, monitoring of SCD is more complicated compared to diagnosis and requires comprehensive validation of efficacy. Early use of novel microdevices for patient monitoring might come in especially handy in new clinical trial designs of emerging therapies.