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Although sheet-like materials have good electrochemical properties, they still suffer from agglomeration problems during the electrocatalytic process. Integrating two-dimensional building blocks into a hollow cage-like structure is considered as an effective way to prevent agglomeration. In this work, the hierarchical NiCo2O4 nanocages were successfully synthesized via coordinated etching and precipitation method combined with a post-annealing process. The nanocages are constructed through the interaction of two-dimensional NiCo2O4 nanosheets, forming a three-dimensional hollow hierarchical architecture. The three-dimensional supporting cavity effectively prevents the aggregation of NiCo2O4 nanosheets and the hollow porous feature provides amounts of channels for mass transport and electron transfer. As an electrocatalytic electrode for methanol, the NiCo2O4 nanocages-modified glassy carbon electrode exhibits a lower overpotential of 0.29 V than those of NiO nanocages (0.38 V) and Co3O4 nanocages (0.34 V) modified glassy carbon electrodes. The low overpotential is attributed to the prominent electrocatalytic dynamic issued from the three-dimensional hollow porous architecture and two-dimensional hierarchical feature of NiCo2O4 building blocks. Furthermore, the hollow porous structure provides sufficient interspace for accommodation of structural strain and volume change, leading to improved cycling stability. The NiCo2O4 nanocages-modified glassy carbon electrode still maintains 80% of its original value after 1000 consecutive cycles. The results demonstrate that the NiCo2O4 nanocages could have potential applications in the field of direct methanol fuel cells due to the synergy between two-dimensional hierarchical feature and three-dimensional hollow structure.

Ultra-wideband (UWB) technology is suitable for indoor positioning owing to its high resolution and penetration. However, the current UWB positioning methods not only fail to fully analyze errors, but do not have the ability to eliminate gross and large random errors. In this article, the errors of UWB indoor positioning are analyzed comprehensively, and the basic function model is given. An indoor positioning method based on a double difference UWB with ranging observations is proposed and realized. In the proposed method, two UWB rover stations and a common base station are introduced, and the known baseline length between two rovers is used as the constraint condition for quality control. The observations and coordinate estimations are constrained by the prior and posteriori, respectively, and the weight of ranging observations with large residuals is reduced. Two groups of static experiments are designed. After adopting the proposed method, the plane error of one rover is 3.4 cm and 2.1 cm, and plane error of another rover is 3.3 cm and 2.0 cm, respectively. The positioning precision is improved by more than 80% compared with the traditional method. In the dynamic experiment, the coordinates of the starting and ending point obtained by the proposed method are basically consistent with the truth value, and the positioning results are close to the reference trajectory. The experimental results show that the proposed method can eliminate systematic and large random errors and improve the positioning precision effectively.

When the lightning current enters the ground through the grounding system, the impulse dispersion performance can be observed by the phenomenon of soil spark discharge, which is fundamentally determined by the nearby soil. At present, engineers use an empirical formula to convert the soil spark discharge to the impulse coefficient of impulse grounding resistance. Therefore, there is no available quantitative analysis method to evaluate soil impulse dispersion performance. To solve this problem, this paper proposes an evaluation method for the impulse discharge efficiency of soil by using X-ray images, define VI as the parameter, which is the ratio of the volume of the discharge area to the peak current. Then, the rationality and validity of the method are verified. Finally, the variation rules of impulse discharge efficiency are analyzed in different soils. Results show that the VI can reflect the change rules of impulse dispersion performance more clearly under different soil conditions, and this parameter provides a new idea for enhancing the impulse dispersion performance of soil near the grounding electrode.

Different methods are available for retrieving chlorophyll-a (Chl-a) in inland waters from optical imagery, but there is still a need for an inter-comparison among the products. Such analysis can provide insights into the method selection, integration of products, and algorithm development. This work aims at inter-comparison and consistency analyses among the Chl-a products derived from publicly available methods consisting of Case-2 Regional/Coast Colour (C2RCC), Water Color Simulator (WASI), and OC3 (3-band Ocean Color algorithm). C2RCC and WASI are physics-based processors enabling the retrieval of not only Chl-a but also total suspended matter (TSM) and colored dissolved organic matter (CDOM), whereas OC3 is a broadly used semi-empirical approach for Chl-a estimation. To pursue the inter-comparison analysis, we demonstrate the application of Sentinel-2 imagery in the context of multitemporal retrieval of constituents in some Italian lakes. The analysis is performed for different bio-optical conditions including subalpine lakes in Northern Italy (Garda, Idro, and Ledro) and a turbid lake in Central Italy (Lake Trasimeno). The Chl-a retrievals are assessed versus in situ matchups that indicate the better performance of WASI. Moreover, relative consistency analyses are performed among the products (Chl-a, TSM, and CDOM) derived from different methods. In the subalpine lakes, the results indicate a high consistency between C2RCC and WASI when aCDOM(440) < 0.5 m−1, whereas the retrieval of constituents, particularly Chl-a, is problematic based on C2RCC for high-CDOM cases. In the turbid Lake Trasimeno, the extreme neural network of C2RCC provided more consistent products with WASI than the normal network. OC3 overestimates the Chl-a concentration. The flexibility of WASI in the parametrization of inversion allows for the adaptation of the method for different optical conditions. The implementation of WASI requires more experience, and processing is time demanding for large lakes. This study elaborates on the pros and cons of each method, providing guidelines and criteria on their use.

Background/Aims: Blue light emitting diodes (LEDs) have been proven to affect the growth of several types of cells. The effects of blue LEDs have not been tested on bone marrow-derived mesenchymal stem cells (BMSCs), which are important for cell-based therapy in various medical fields. Therefore, the aim of this study was to determine the effects of blue LED on the proliferation, apoptosis and osteogenic differentiation of BMSCs. Methods: BMSCs were irradiated with a blue LED light at 470 nm for 1 min, 5 min, 10 min, 30 min and 60 min or not irradiated. Cell proliferation was measured by performing cell counting and EdU staining assays. Cell apoptosis was detected by TUNEL staining. Osteogenic differentiation was evaluated by ALP and ARS staining. DCFH-DA staining and γ-H2A.X immunostaining were used to measure intracellular levels of ROS production and DNA damage. Results: Both cell counting and EdU staining assays showed that cell proliferation of BMSCs was significantly reduced upon blue LED irradiation. Furthermore, treatment of BMSCs with LED irradiation was followed by a remarkable increase in apoptosis, indicating that blue LED light induced toxic effects on BMSCs. Likewise, BMSC osteogenic differentiation was inhibited after exposure to blue LED irradiation. Further, blue LED irradiation was followed by the accumulation of ROS production and DNA damage. Conclusions: Taken together, our study demonstrated that blue LED light inhibited cell proliferation, inhibited osteogenic differentiation, and induced apoptosis in BMSCs, which are associated with increased ROS production and DNA damage. These findings may provide important insights for the application of LEDs in future BMSC-based therapies.

Coral reefs, among the world’s most biodiverse and productive submerged habitats, have faced several mass bleaching events due to climate change during the past 35 years. In the course of this century, global warming and ocean acidification are expected to cause corals to become increasingly rare on reef systems. This will result in a sharp decrease in the biodiversity of reef communities and carbonate reef structures. Coral reefs may be mapped, characterized and monitored through remote sensing. Hyperspectral images in particular excel in being used in coral monitoring, being characterized by very rich spectral information, which results in a strong discrimination power to characterize a target of interest, and separate healthy corals from bleached ones. Being submerged habitats, coral reef systems are difficult to analyse in airborne or satellite images, as relevant information is conveyed in bands in the blue range which exhibit lower signal-to-noise ratio (SNR) with respect to other spectral ranges; furthermore, water is absorbing most of the incident solar radiation, further decreasing the SNR. Derivative features, which are important in coral analysis, result greatly affected by the resulting noise present in relevant spectral bands, justifying the need of new denoising techniques able to keep local spatial and spectral features. In this paper, Unmixing-based Denoising (UBD) is used to enable analysis of a hyperspectral image acquired over a coral reef system in the Red Sea based on derivative features. UBD reconstructs pixelwise a dataset with reduced noise effects, by forcing each spectrum to a linear combination of other reference spectra, exploiting the high dimensionality of hyperspectral datasets. Results show clear enhancements with respect to traditional denoising methods based on spatial and spectral smoothing, facilitating the coral detection task.

Parathyroid hormone (pth), parathyroid hormone-related peptide (pthrp) and their receptors are involved in the regulation of calcium homeostasis in all vertebrates. To further understand the role of these genes in teleosts during development, we investigated the expression pattern of pth1, pth2, pthrp1, pthrp2, and their receptors pth1r, pth2r, pth3r, and their response to acute salinity and temperature challenge during early development of zebrafish, Danio rerio. The results revealed that pth1, pth2, pthrp1, pthrp2, pth1r, pth2r, pth3r were differentially expressed during early development, and pth1, pthrp1, pth1r, pth2r mRNA were detected from 0 hpf. pth2 and pth3r mRNA were detected after fertilization. Exposure of zebrafish embryos and larvae to acute osmotic (30) stress for 15 min failed to modify the expression levels of pthrp2 mRNA from levels in control fish. However, salinity challenge significantly (P

Objective: To assess the attitudes of hospitalized patients toward wearing patient clothing and identify the factors those influence their negative attitudes. Methods: A cross-sectional design was employed and a questionnaire survey was conducted. The data were collected from 251 hospitalized patients between July 2015 and August 2015. Results: Around 57.8% of the participants reported that they were unwilling to wear patient clothing. Among them, 60.7% knew little to nothing about the function of patient clothing. Some of these patients were unwilling to wear patient clothing because these uniforms had poor comfort (26.2%), fit (34.5%), hygiene (66.2%), and appearance (31.1%), and wearing them was psychologically uncomfortable (43.5%). Conclusions: More than half of the hospitalized patients dislike wearing patient clothing because they were unaware of its functions and were skeptical about its hygiene, comfortability, fit, and appearance. Therefore, these patients must be provided with comfortable, well fitting, hygienic, and aesthetically pleasing clothing.

Background Previous studies have demonstrated that functional autoantibodies to adrenergic receptors may be involved in the pathogenesis of postural tachycardia syndrome. The objective of this study was to examine the impact of these autoantibodies on cardiovascular responses to postural changes and adrenergic orthosteric ligand infusions in immunized rabbits. Methods and Results Eight New Zealand white rabbits were coimmunized with peptides from the α1‐adrenergic receptor and β1‐adrenergic receptor (β1AR). Tilt test and separate adrenergic agonist infusion studies were performed on conscious animals before and after immunization and subsequent treatment with epitope‐mimetic peptide inhibitors. At 6 weeks after immunization, there was a greater percent increase in heart rate upon tilting compared with preimmune baseline. No significant difference in blood pressure response to tilting was observed. The heart rate response to infusion of the β‐adrenoceptor agonist isoproterenol was significantly enhanced in immunized animals, suggesting a positive allosteric effect of β1AR antibodies. In contrast, the blood pressure response to infusion of the α1‐adrenergic receptor agonist phenylephrine was attenuated in immunized animals, indicating a negative allosteric effect of α1‐adrenergic receptor antibodies. Injections of antibody‐neutralizing peptides suppressed the postural tachycardia and reversed the altered heart rate and blood pressure responses to orthosteric ligand infusions in immunized animals at 6 and 30 weeks. Antibody production and suppression were confirmed with in vitro bioassays. Conclusions The differential allosteric effect of α1‐adrenergic receptor and β1AR autoantibodies would lead to a hyperadrenergic state and overstimulation of cardiac β1AR. These data support evidence for an autoimmune basis for postural tachycardia syndrome.

Many bacterial pathogens hijack macrophages to egress from the port of entry to the lymphatic drainage and/or bloodstream, causing dissemination of life-threatening infections. However, the underlying mechanisms are not well understood. Here, we report that Salmonella infection generates directional electric fields (EFs) in the follicle-associated epithelium of mouse cecum. In vitro application of an EF, mimicking the infection-generated electric field (IGEF), induces directional migration of primary mouse macrophages to the anode, which is reversed to the cathode upon Salmonella infection. This infection-dependent directional switch is independent of the Salmonella pathogenicity island 1 (SPI-1) type III secretion system. The switch is accompanied by a reduction of sialic acids on glycosylated surface components during phagocytosis of bacteria, which is absent in macrophages challenged by microspheres. Moreover, enzymatic cleavage of terminally exposed sialic acids reduces macrophage surface negativity and severely impairs directional migration of macrophages in response to an EF. Based on these findings, we propose that macrophages are attracted to the site of infection by a combination of chemotaxis and galvanotaxis; after phagocytosis of bacteria, surface electrical properties of the macrophage change, and galvanotaxis directs the cells away from the site of infection.

Summary: The CNS plays a pivotal role in energy homeostasis, but whether oligodendrocytes are involved has been largely unexplored. Here, we show that signaling through GPR17, a G-protein-coupled receptor predominantly expressed in the oligodendrocyte lineage, regulates food intake by modulating hypothalamic neuronal activities. GPR17-null mice and mice with an oligodendrocyte-specific knockout of GPR17 have lean phenotypes on a high-fat diet, suggesting that GPR17 regulates body weight by way of oligodendrocytes. Downregulation of GPR17 results in activation of cAMP-protein kinase A (PKA) signaling in oligodendrocytes and upregulated expression of pyruvate dehydrogenase kinase 1 (PDK1), which promotes lactate production. Elevation of lactate activates AKT and STAT3 signaling in the hypothalamic neurons, leading to increased expression of Pomc and suppression of Agrp. Our findings uncover a critical role of oligodendrocytes in metabolic homeostasis, where GPR17 modulates the production of lactate, which, in turn, acts as a metabolic signal to regulate neuronal activity. : Ou et. al. show that Gpr17 in oligodendrocytes contributes to whole-body metabolic regulation. Gpr17-deficient mice exhibit decreased body weight on long-term high-fat feeding by reducing food intake. Loss of Gpr17 increases oligodendrocytic lactate production, which results in the lean phenotype of the KO animals. Keywords: oligodendroyctes, GPR17, lactate, metabolic homeostasis

In order to better predict the development of shrinkage deformation of steam-cured concrete mixed with slag, a deformation-temperature-humidity integrated model test, a hydration heat test, and an elastic modulus test were performed. The effects of the steam-curing process and the content of slag on shrinkage deformation, hydration degree and elastic modulus of concrete were studied. The results indicate that during the steam-curing process, the concrete has an “expansion-shrinkage” pattern. After the steam curing, the deformation of concrete is dominated by drying shrinkage. After the addition of slag, the shrinkage deformation of steam-cured concrete is increased. The autogenous shrinkage increases by 0.5–12%, and the total shrinkage increases by 1.5–8% at 60 days. At the same time, slag reduces the hydration degree of steam-cured concrete and modulus of elasticity. A prediction model for the hydration degree of steam-cured concrete is established, which can be used to calculate the degree of hydration at any curing age. Based on the capillary tension generated by the capillary pores in concrete, an integrated model of autogenous shrinkage and total shrinkage is established with the relative humidity directly related to the water loss in the concrete as the driving parameter. Whether the shrinkage deformation is caused by hydration reaction or the external environment, this model can better predict the shrinkage deformation of steam-cured concrete.

In smartphone indoor positioning, owing to the strong complementarity between pedestrian dead reckoning (PDR) and WiFi, a hybrid fusion scheme of them is drawing more and more attention. However, the outlier of WiFi will easily degrade the performance of the scheme, to remove them, many researches have been proposed such as: improving the WiFi individually or enhancing the scheme. Nevertheless, due to the inherent received signal strength (RSS) variation, there still exist some unremoved outliers. To solve this problem, this paper proposes the first outlier detection and removal strategy with the aid of Machine Learning (ML), so called WiFi-AGNES (Agglomerative Nesting), based on the extracted positioning characteristics of WiFi when the pedestrian is static. Then, the paper proposes the second outlier detection and removal strategy, so called WiFi-Chain, based on the extracted positioning characteristics of WiFi, PDR, and their complementary characteristics when the pedestrian is walking. Finally, a hybrid fusion scheme is proposed, which integrates the two proposed strategies, WiFi, PDR with an inertial-navigation-system-based (INS-based) attitude heading reference system (AHRS) via Extended Kalman Filter (EKF), and an Unscented Kalman Filter (UKF). The experiment results show that the two proposed strategies are effective and robust. With WiFi-AGNES, the minimum percentage of the maximum error (MaxE) is reduced by 66.5%; with WiFi-Chain, the MaxE of WiFi is less than 4.3 m; further the proposed scheme achieves the best performance, where the root mean square error (RMSE) is 1.43 m. Moreover, since characteristics are universal, the proposed scheme integrated the two characteristic-based strategies also possesses strong robustness.

A micro-Doppler signature (m-DS) based on the rotation of drone blades is an effective way to detect and identify small drones. Deep-learning-based recognition algorithms can achieve higher recognition performance, but they needs a large amount of sample data to train models. In addition to the hovering state, the signal samples of small unmanned aerial vehicles (UAVs) should also include flight dynamics, such as vertical, pitch, forward and backward, roll, lateral, and yaw. However, it is difficult to collect all dynamic UAV signal samples under actual flight conditions, and these dynamic flight characteristics will lead to the deviation of the original features, thus affecting the performance of the recognizer. In this paper, we propose a small UAV m-DS recognition algorithm based on dynamic feature enhancement. We extract the combined principal component analysis and discrete wavelet transform (PCA-DWT) time–frequency characteristics and texture features of the UAV’s micro-Doppler signal and use a dynamic attribute-guided augmentation (DAGA) algorithm to expand the feature domain for model training to achieve an adaptive, accurate, and efficient multiclass recognition model in complex environments. After the training model is stable, the average recognition accuracy rate can reach 98% during dynamic flight.

In this study, UAVs were used to collect data of distribution line resources, and defects in distribution line equipment and construction process were identified through deep learning. Different algorithms are used to identify the defects of distribution line equipment and construction process. The research will ultimately support regional synchronization and online development for intelligent automatic acceptance of the distribution wire UAV.

Magnetic multi-walled carbon nanotubes were prepared as magnetic solid-phase extraction (MSPE) adsorbent for the enrichment of six heterocyclic pesticides in environmental water samples, including imidacloprid, triadimefon, fipronil, flusilazole, chlorfenapyr and fenpyroximate. Then six heterocyclic pesticides were separated and determined by high-performance liquid chromatography-diode-array detector (HPLC-DAD). Major factors influencing MSPE efficiency, including the dose of mag-multi-walled carbon nanotubes (mag-MWCNTs), extraction time, solution pH, salt concentration, type and volume of eluent and desorption time were investigated. Under the optimized conditions, the enrichment factor of the method reached to 250. The linearity was achieved within 0.05–10.0 μg/L for imidacloprid and chlorfenapyr, 0.10–10.0 μg/L for fipronil, flusilazole, triadimefon and fenpyroximate. Limits of detection were in the range of 0.01–0.03 μg/L. Good precision at three spiked levels were 1.1–11.2% (intra-day) and 1.7–11.0% (inter-day) with relative standard deviation of peak area, respectively. The developed method was utilized to analyze tap water, river water and reservoir water samples and recoveries at three spiked concentration levels ranged from 72.2% to 107.5%. The method was proved to be a convenient, rapid and practical method for sensitive determination of heterocyclic pesticides.

Background/Aims: Bone marrow-derived mesenchymal stem cells (BMSCs) have the ability to differentiate into multilineage cells such as osteoblasts, chondrocytes, and cardiomyocytes. Dysfunction of BMSCs in response to pathological stimuli participates in the development of diseases such as osteoporosis. Astragalus polysaccharide (APS) is a major active ingredient of Astragalus membranaceus, a commonly used anti-aging herb in traditional Chinese medicine. The aim of this study was to investigate whether APS protects against iron overload-induced dysfunction of BMSCs and its underlying mechanisms. Methods: BMSCs were exposed to ferric ammonium citrate (FAC) with or without different concentrations of APS. The viability and proliferation of BMSCs were assessed by CCK-8 assay and EdU staining. Cell apoptosis, senescence and pluripotency were examined utilizing TUNEL staining, β-galactosidase staining and qRT-PCR respectively. The reactive oxygen species (ROS) level was assessed in BMSCs with a DCFH-DA probe and MitoSOX Red staining. Results: Firstly, we found that iron overload induced by FAC markedly reduced the viability and proliferation of BMSCs, but treatment with APS at 10, 30 and 100 μg/mL was able to counter the reduction of cell proliferation. Furthermore, exposure to FAC led to apoptosis and senescence in BMSCs, which were partially attenuated by APS. The pluripotent genes Nanog, Sox2 and Oct4 were shown to be downregulated in BMSCs after FAC treatment, however APS inhibited the reduction of Nanog, Sox2 and Oct4 expression. Further study uncovered that APS treatment abrogated the increase of intracellular and mitochondrial ROS level in FAC-treated BMSCs. Conclusion: Treatment of BMSCs with APS to impede mitochondrial ROS accumulation can remarkably inhibit apoptosis, senescence, and the reduction of proliferation and pluripotency of BMSCs caused by FAC-induced iron overload.

Natural products comprise a rich reservoir for innovative drug leads and are a constant source of bioactive compounds. To find pharmacological targets for new or already known natural products using modern computer-aided methods is a current endeavor in drug discovery. Nature’s treasures, however, could be used more effectively. Yet, reliable pipelines for the large-scale target prediction of natural products are still rare. We developed an in silico workflow consisting of four independent, stand-alone target prediction tools and evaluated its performance on dihydrochalcones (DHCs)—a well-known class of natural products. Thereby, we revealed four previously unreported protein targets for DHCs, namely 5-lipoxygenase, cyclooxygenase-1, 17β-hydroxysteroid dehydrogenase 3, and aldo-keto reductase 1C3. Moreover, we provide a thorough strategy on how to perform computational target predictions and guidance on using the respective tools.

This paper studies the measurement requirements of spectral resolution and radiometric sensitivity to enable the quantitative determination of water constituents and benthic parameters for the majority of optically deep and optically shallow waters on Earth. The spectral and radiometric variability is investigated by simulating remote sensing reflectance (Rrs) spectra of optically deep water for twelve inland water scenarios representing typical and extreme concentration ranges of phytoplankton, colored dissolved organic matter and non-algal particles. For optically shallow waters, Rrs changes induced by variable water depth are simulated for fourteen bottom substrate types, from lakes to coastal waters and coral reefs. The required radiometric sensitivity is derived for the conditions that the spectral shape of Rrs should be resolvable with a quantization of 100 levels and that measurable reflection differences at at least one wavelength must occur at concentration changes in water constituents of 10% and depth differences of 20 cm. These simulations are also used to derive the optimal spectral resolution and the most sensitive wavelengths. Finally, the Rrs spectra and their changes are converted to radiances and radiance differences in order to derive sensor (noise-equivalent radiance) and measurement requirements (signal-to-noise ratio) at the water surface and at the top of the atmosphere for a range of solar zenith angles.

The recent PlanetScope constellation (130+ satellites currently in orbit) has shifted the high spatial resolution imaging into a new era by capturing the Earth’s landmass including inland waters on a daily basis. However, studies on the aquatic-oriented applications of PlanetScope imagery are very sparse, and extensive research is still required to unlock the potentials of this new source of data. As a first fully physics-based investigation, we aim to assess the feasibility of retrieving bathymetric and water quality information from the PlanetScope imagery. The analyses are performed based on Water Color Simulator (WASI) processor in the context of a multitemporal analysis. The WASI-based radiative transfer inversion is adapted to process the PlanetScope imagery dealing with the low spectral resolution and atmospheric artifacts. The bathymetry and total suspended matter (TSM) are mapped in the relatively complex environment of Venice lagoon during two benchmark events: The coronavirus disease 2019 (COVID-19) lockdown and an extreme flood occurred in November 2019. The retrievals of TSM imply a remarkable reduction of the turbidity during the lockdown, due to the COVID-19 pandemic and capture the high values of TSM during the flood condition. The results suggest that sizable atmospheric and sun-glint artifacts should be mitigated through the physics-based inversion using the surface reflectance products of PlanetScope imagery. The physics-based inversion demonstrated high potentials in retrieving both bathymetry and TSM using the PlanetScope imagery.