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Land ecological security (LES) is a crucial issue pertaining to the sustainability of landscapes or land systems. Nevertheless, previous studies largely neglected the impacts of landscape structure on LES. This study, taking the Yellow River Delta (YRD) as the case area, analyzed the spatiotemporal differentiation patterns of regional LES in 19 counties (cities and districts) from 2000 to 2020 through the application of landscape metrics and employed GeoSOS-FLUS to forecast the landscape structure and corresponding land ecological security in 2030 under four different scenarios to advance sustainability. The results show that, first, landscape fragmentation and irregularity are decreasing, while aggregation and connectivity are increasing. The primary landscape change involves the transition from farmland to developed areas. Second, the LES index is rising. In 2020, about 73.68% of the research units reached level IV, while most were at level III. Third, it is projected that by 2030, the LES index will rise under all scenarios, exhibiting an eastward-declining gradient in its geographic distribution, with higher values prevailing in the eastern regions and gradually tapering off towards the west. It is expected that in the business-as-usual scenario, the proportion of LES reaching level V will be the highest. This study not only reveals the impact mechanism of the landscape structure on land ecological security but also provides an important basis for formulating scientific and rational land use planning and management strategies from the perspectives of sustainable land governance and sustainable land use.

Two endophytic fungi Trichoderma afroharzianum (HP-3) and Alternaria alstroemeriae (HP-7) were isolated and purified from the fresh root of Dryopteris crassirhizoma. Chemical investigation of the two fungi resulted in the isolation of two new phenols 2,4-dihydroxy-3-farnesyl-5-methoxy benzoic acid (1) and 2-hydroxyphenethyl 2-phenylacetate (2), together with 22 known compounds. Their structures were elucidated by NMR, UV, IR, HRESIMS, and comparison to the literature data. Compounds 15 and 16 showed significant antibacterial activity against Micrococcus lysodeikticus with MIC value of 6.25 μg/mL, while 8 and 14 displayed moderate inhibitory activities against several plant pathogenic fungi and clinically important bacterial strains. This is the first study to report the isolation, identification, and antimicrobial properties of metabolites from endophytic fungi of D. crassirhizoma. Our findings may provide lead compounds for the development of new antibacterial agents.

Hyperspectral reflectance (HR) technology as proxy approach to diagnose fusarium head blight (FHB) in wheat crop could be a real-time and non-invasive approach for its in-field management to reduce grain damage. In-field canopy’s non-imaging HR (400–2400 nm using ground-based spectrometer system), photosynthesis rate (Pn) and disease severity (DS) data were simultaneously acquired from artificially inoculated wheat plots over a period of two years (2020 and 2021) in the field. Subsequently, continuous wavelet transform (CWT) was employed to select the consistent spectral bands (CSBs) and to develop the canopy-based difference indices with criterion of variable importance score using random forest—recursive feature elimination. Thereby, different machine learning algorithms were employed for FHB classification and multivariate estimation, and linear regression models to evaluate the newly developed indices against conventional vegetation indices. The results showed that inoculation reduced the Pn rate of spikes, elevated reflectance in visible and short-wave infrared regions and decreased in near infrared region at different days after inoculation (DAI). CWT analysis selected five CSBs (401, 460, 570, 786 and 840 nm) employing datasets from 2020 and 2021. These spectral bands were employed to develop wheat fusarium canopy indices (WFCI1 and WFCI2). Considering the average classification accuracy (ACA) in both years of experiments, WFCI1 manifested a maximum ACA of 75% at 5 DAI with DS of 9.73% which raised to 100% at 10 DAI with a DS of 18%. ACA mentions the averaged results of all machine learning classifiers (MLC). While in the perspective of MLC, random forest (RF) outperformed the rest of the MLC, individually, it revealed 100% classification accuracy through WFCI1 at DS 10.78% on the eight DAI. The univariate estimation of disease based on WFCI1 and WFCI2 with independent data produced R2 and root mean square error (RMSE) values of 0.80 and 14.7, and 0.81 and13.50, respectively. However, Knn regression analysis with both canopy indices (WFCI1 and WFCI2) manifested the maximum accuracy for disease estimation with RMSE of 11.61 and R2 = 0.83. Conclusively, the newly proposed HR indices show great potential as proxy approach for detecting FHB at early stage and understanding the physical state of crops in field conditions for the better management and control of plant diseases.

Several Bevacizumab products are approved for clinical use, with many others in late-stage clinical development worldwide. To aid the harmonization of potency assessment across different Bevacizumab products, the first World Health Organization (WHO) International Standard (IS) for Bevacizumab has been developed. Two preparations of a Bevacizumab candidate and comparator were assessed for their ability to neutralize and bind vascular endothelial growth factor (VEGF) using different bioassays and binding assays in an international collaborative study. Relative potency estimates were similar across different assays for the comparator or the duplicate-coded candidate sample. Variability in relative potency estimates was reduced when the candidate standard was used for calculation compared with various in-house reference standards, enabling harmonization in bioactivity evaluations. The results demonstrated that the candidate standard is suitable to serve as an IS for Bevacizumab, with assigned unitages for VEGF neutralization and VEGF binding activity. This standard coded 18/210 was established by the WHO Expert Committee on Biological Standardization, which is intended to support the calibration of secondary standards for product development and lifecycle management. The availability of IS 18/210 will help facilitate the global harmonization of potency evaluation to ensure patient access to Bevacizumab products with consistent safety, quality and efficacy.

The prevalent issue of cadmium (Cd) in naturally selenium (Se)-enriched soils has significantly impacted the safe utilization of Se-rich soils. Although Se antagonizes Cd and is affected by Se:Cd stoichiometry, the mechanism behind this interaction remains unclear. To reveal the relation between the soil bioavailable Se:Cd molar ratio (AMR-Se:Cd) and the transformation of Se and Cd fractions, as well as to identify the principal controlling factors, we conducted a study in Shanggao County, Yichun City, a naturally Se-rich area in Jiangxi Province, and quantitatively analyzed the distribution features of Se, Cd, and AMR-Se:Cd across different soil types and land use types. The results demonstrated that soil AMR-Se:Cd was statistically positively correlated with the bioavailable Se content (r = 0.331, p < 0.01) and had a negative correlation with the bioavailable Cd content (r = −0.402, p < 0.001). Cd was transformed from highly bioavailable fractions to less bioavailable fractions as the AMR-Se:Cd increased. A suitable AMR-Se:Cd was conducive to achieving a higher mobility of Se (mobility factor of 12.31%) and a lower mobility of Cd (mobility factor of 23.49%) simultaneously. Spearman correlation analysis and partial least squares path modeling revealed that soil type and land use type modulated the morphological transformation of soil Se and Cd by influencing changes in free Fe-Al oxides and soil organic matter content, which in turn altered the AMR-Se:Cd. Therefore, the findings of this study can offer guidance for regulating the appropriate AMR-Se:Cd in Se-rich soils through management practices to enhance the bioavailability and mobility of soil Se while diminishing the bioavailability and mobility of Cd.

The effect of different precipitates and nanoparticles on the distribution of radiation-induced dislocation loops in V-4Cr-4Ti alloy and V-4Cr-4Ti-1.8Y-0.4Ti3SiC2 alloy were studied. Both alloys were irradiated with 60 keV deuterium, and the distribution of the dislocation loops was statistically analyzed using the transmission electron microscope (TEM) technique. The results indicated that platelet-like Ti(CNO) precipitates affect the dislocation distribution, in which a significantly reduced dislocation number density in the area within 20 nm of the interface was observed. This phenomenon is attributed to the strong compressive strain in the vertical interface direction at the precipitates/matrix interface. No significant effect on loop distribution was observed in the coherent TiC/matrix interface, which may result from the almost no strain interface. In addition, the uniform distribution of radiation-induced dislocation loops in equivalent crystal orientation was confirmed via the TEM images with multiple g vectors.

An event camera is a neuromimetic sensor inspired by the human retinal imaging principle, which has the advantages of high dynamic range, high temporal resolution, and low power consumption. Due to the interference of hardware and software and other factors, the event stream output from the event camera usually contains a large amount of noise, and traditional denoising algorithms cannot be applied to the event stream. To better deal with different kinds of noise and enhance the robustness of the denoising algorithm, based on the spatio-temporal distribution characteristics of effective events and noise, an event stream noise reduction and visualization algorithm is proposed. The event stream enters fine filtering after filtering the BA noise based on spatio-temporal density. The fine filtering performs time sequence analysis on the event pixels and the neighboring pixels to filter out hot noise. The proposed visualization algorithm adaptively overlaps the events of the previous frame according to the event density difference to obtain clear and coherent event frames. We conducted denoising and visualization experiments on real scenes and public datasets, respectively, and the experiments show that our algorithm is effective in filtering noise and obtaining clear and coherent event frames under different event stream densities and noise backgrounds.

A radial well has a unique wellbore configuration. Fracture propagation in radial well deflagration fracturing is studied rarely. The mechanism of interaction between deflagration fractures, natural fractures, and micro-fractures is still unknown. Based on continuum mechanics, damage mechanics, and variational principles, a numerical model of fracture propagation in deflagration fracturing is established with the Hamilton principle and phase-field fracture theory. The effects of horizontal principal stress difference, natural fracture distribution, and micro-fractures around the wellbore on fracture propagation in deflagration fracturing are studied. First, when no natural fractures are developed around the radial well, fractures are initiated at both ends of the radial well. Second, when there are three natural fractures around the radial well, the created fractures have the morphology of shorter fractures in the middle and longer fractures on both sides under stress interference mechanisms. Third, a larger density of natural fractures causes obvious stress superposition, changes the initiation points of radial wells and fracture morphology, and increases fracture width and reservoir stimulation volume. Fourth, as the micro-fractures increase, their interference and induction effects on deflagration fractures are enhanced gradually, and the deflection angle of fractures increases by 38.7%. The study provides a reference for optimizing deflagration fracturing in a radial well.

Counting the soybean pods automatically has been one of the key ways to realize intelligent soybean breeding in modern smart agriculture. However, the pod counting accuracy for whole soybean plants is still limited due to the crowding and uneven distribution of pods. In this paper, based on the VFNet detector, we propose a deformable attention recursive feature pyramid network for soybean pod counting (DARFP-SD), which aims to identify the number of soybean pods accurately. Specifically, to improve the feature quality, DARFP-SD first introduces the deformable convolutional networks (DCN) and attention recursive feature pyramid (ARFP) to reduce noise interference during feature learning. DARFP-SD further combines the Repulsion Loss to correct the error of predicted bboxse coming from the mutual interference between dense pods. DARFP-SD also designs a density prediction branch in the post-processing stage, which learns an adaptive soft distance IoU to assign suitable NMS threshold for different counting scenes with uneven soybean pod distributions. The model is trained on a dense soybean dataset with more than 5300 pods from three different shapes and two classes, which consists of a training set of 138 images, a validation set of 46 images and a test set of 46 images. Extensive experiments have verified the performance of proposed DARFP-SD. The final training loss is 1.281, and an average accuracy of 90.35%, an average recall of 85.59% and a F1 score of 87.90% can be achieved, outperforming the baseline method VFNet by 8.36%, 4.55% and 7.81%, respectively. We also validate the application effect for different numbers of soybean pods and differnt shapes of soybean. All the results show the effectiveness of the DARFP-SD, which can provide a new insight into the soybean pod counting task.

Image matching is a basic task in three-dimensional reconstruction, which, in recent years, has attracted extensive attention in academic and industrial circles. However, when dealing with large-scale image datasets, these methods have low accuracy and slow speeds. To improve the effectiveness of modern image matching methods, this paper proposes an image matching method for 3D reconstruction. The proposed method can obtain high matching accuracy through hash index in a very short amount of time. The core of hash matching includes two parts: creating the hash table and hash index. The former is used to encode local feature descriptors into hash codes, and the latter is used to search candidates for query feature points. In addition, the proposed method is extremely robust to image scaling and transformation by using various verifications. A comprehensive experiment was carried out using several challenging datasets to evaluate the performance of hash matching. Experimental results show that the HashMatch presents excellent results compared to the state-of-the-art methods in both computational efficiency and matching accuracy.

In mixed-reality (MR) telecollaboration, the local environment is remotely presented to a remote user wearing a virtual reality (VR) head-mounted display (HMD) via a video capture device. However, remote users frequently face challenges in naturally and actively manipulating their viewpoints. In this paper, we propose a telepresence system with viewpoint control, which involves a robotic arm equipped with a stereo camera in the local environment. This system enables remote users to actively and flexibly observe the local environment by moving their heads to manipulate the robotic arm. Additionally, to solve the problem of the limited field of view of the stereo camera and limited movement range of the robotic arm, we propose a 3D reconstruction method combined with a stereo video field-of-view enhancement technique to guide remote users to move within the movement range of the robotic arm and provide them with a larger range of local environment perception. Finally, a mixed-reality telecollaboration prototype was built, and two user studies were conducted to evaluate the overall system. User study A evaluated the interaction efficiency, system usability, workload, copresence, and user satisfaction of our system from the remote user’s perspective, and the results showed that our system can effectively improve the interaction efficiency while achieving a better user experience than two traditional view-sharing techniques based on 360 video and based on the local user’s first-person view. User study B evaluated our MR telecollaboration system prototype from both the remote-user side and the local-user side as a whole, providing directions and suggestions for the subsequent design and improvement of our mixed-reality telecollaboration system.

With the rapid development of modern industries, water pollution has become an urgent problem that endangers the health of human and wild animals. The photocatalysis technique is considered an environmentally friendly strategy for removing organic pollutants in wastewater. As an important member of Bi-series semiconductors, Bi2WO6 is widely used for fabricating high-performance photocatalysts. In this review, the recent advances of Bi2WO6-based photocatalysts are summarized. First, the controllable synthesis, surface modification and heteroatom doping of Bi2WO6 are introduced. In the respect of Bi2WO6-based composites, existing Bi2WO6-containing binary composites are classified into six types, including Bi2WO6/carbon or MOF composite, Bi2WO6/g-C3N4 composite, Bi2WO6/metal oxides composite, Bi2WO6/metal sulfides composite, Bi2WO6/Bi-series composite, and Bi2WO6/metal tungstates composite. Bi2WO6-based ternary composites are classified into four types, including Bi2WO6/g-C3N4/X, Bi2WO6/carbon/X, Bi2WO6/Au or Ag-based materials/X, and Bi2WO6/Bi-series semiconductors/X. The design, microstructure, and photocatalytic performance of Bi2WO6-based binary and ternary composites are highlighted. Finally, aimed at the existing problems in Bi2WO6-based photocatalysts, some solutions and promising research trends are proposed that would provide theoretical and practical guidelines for developing high-performance Bi2WO6-based photocatalysts.

Honokiol, the main bioactive extract of Magnolia officinalis, exhibits extensive therapeutic actions. Its treatment for advanced non-small cell lung cancer is undergoing clinical trials in China. However, the published safety evaluation studies have focused on extract mixtures of Magnolia officinalis in which the honokiol content was well below the reported clinical dose of the honokiol monomer. Therefore, safety assessment of the honokiol monomer is urgently needed. Our previous studies have already demonstrated that a high dose of the honokiol microemulsion (0.6 μg/mL) induces developmental toxicity in rats and zebrafish by inducing oxidative stress. By exploring the relationship between time and toxicity, we found that developmental toxic responses were stage-dependent. They mainly occurred within the first 24 h post fertilization (hpf) especially the first 12 hpf. In zebrafish, low doses of honokiol microemulsion (0.15, 0.21 μg/mL) significantly decreased the levels of reactive oxygen species (ROS) and malondialdehyde (MDA) and increased the mRNA expression of bcl-2. In contrast, high dose (0.6 μg/mL) increased the levels of ROS and MDA, decreased activities and mRNA expression of superoxide dismutase (SOD) and catalase (CAT), and increased mRNA expression of bax, c-jnk, p53 and bim. By acridine orange staining, we found that a high dose of honokiol microemulsion induced apoptosis mainly in zebrafish brain. In rat pheochromocytoma cells (PC12 cells), low doses of the honokiol microemulsion (1, 5, 10 µM) exerted a protective effect against H2O2-induced oxidative damage while high doses (≥20 µM) induced oxidative stress, which further confirms the dual effects of honokiol microemulsion on nerve cells. These dual roles of the honokiol microemulsion in oxidation–reduction reactions and apoptosis may be regulated by the forkhead box class O (FoxO) signaling pathway. Due to the potential of developmental toxicity, we recommend that the administration of high dose honokiol microemulsion in pregnant women should be considered with caution.

Many countries, including China, have implemented the spatial government policy widely known as urban growth boundary (UGB) for managing future urban growth. However, few studies have asked why we need UGB, especially pre-evaluating the utility of UGB for reshaping the future spatial patterns of cities. In this research, we proposed a constrained urban growth simulation model (CUGSM) which coupled Markov chain (MC), random forest (RF), and patch growth based cellular automata (Patch-CA) to simulate urban growth. The regulatory effect of UGB was coupled with CUGSM based on a random probability game method. Guangzhou city, a metropolitan area located in the Peral River Delta of China, was taken as a case study. Historical urban growth from 1995 to 2005 and random forests were used to calibrate the conversion rules of Patch-CA, and the urban patterns simulated and observed in 2015 were used to identify the simulation accuracy. The results showed that the Kappa and figure of merit (FOM) indices of the unconstrained Patch-CA were just 0.7914 and 0.1930, respectively, which indicated that the actual urban growth was reshaped by some force beyond what Patch-CA has learned. We further compared the simulation scenarios in 2035 with and without considering the UGB constraint, and the difference between them is as high as 21.14%, which demonstrates that UGB plays an important role in the spatial reshaping of future urban growth. Specifically, the newly added urban land outside the UGB has decreased from 25.13% to 16.86% after considering the UGB constraint; particularly, the occupation of agricultural space and ecological space has been dramatically reduced. This research has demonstrated that the utility of UGB for reshaping future urban growth is pronounced, and it is necessary for the Chinese government to further strengthen UGB policy to promote sustainable urban growth.

Urban parks provide multiple benefits to human well-being and human health. Big data provide new and powerful ways to study visitors’ feelings, activities in urban parks, and the effect they themselves have on urban parks. However, the term “big data” has been defined variably, and its applications on urban parks have so far been sporadic in research. Therefore, a comprehensive review of big data-based urban park research is much needed. The review aimed to summarize the big data-based urban park research in visitor dimension by a systematic review approach in combination with bibliometric and thematic analyses. The results showed that the number of publications of related articles has been increasing exponentially in recent years. Users’ days data is used most frequently in the big data-based urban park research, and the major analytical methods are of four types: sentiment analysis, statistical analysis, and spatial analysis. The major research topics of big data-based urban park research in visitor dimension include visitors’ behavior, visitors’ perception and visitors’ effect. Big data benefits urban park research by providing low-cost, timely information, a people-oriented perspective, and fine-grained site information. However, its accuracy is insufficient because of coordinate, keyword classification and different kinds of users. To move forward, future research should integrate multiple big data sources, expand the application, such as public health and human–nature interactions, and pay more attention to the big data use for overcoming pandemic. This review can help to understand the current situation of big data-based urban park research, and provide a reference for the studies of this topic in the future.

Glucosinolates (GSLs) are sulfur-containing bioactive compounds usually present in Brassicaceae plants and are usually responsible for a pungent flavor and reduction of the nutritional values of seeds. Therefore, breeding rapeseed varieties with low GSL levels is an important breeding objective. Most GSLs in Brassica rapa are derived from methionine or tryptophan, but two are derived from phenylalanine, one directly (benzylGSL) and one after a round of chain elongation (phenethylGSL). In the present study, two phenylalanine (Phe)-derived GSLs (benzylGSL and phenethylGSL) were identified and quantified in seeds by liquid chromatography and mass spectrometry (LC-MS) analysis. Levels of benzylGSL were low but differed among investigated low and high GSL genotypes. Levels of phenethylGSL (also known as 2-phenylethylGSL) were high but did not differ among GSL genotypes. Subsequently, a genome-wide association study (GWAS) was conducted using 159 B. rapa accessions to demarcate candidate regions underlying 43 and 59 QTNs associated with benzylGSL and phenethylGSL that were distributed on 10 chromosomes and 9 scaffolds, explaining 0.56% to 70.86% of phenotypic variations, respectively. Furthermore, we find that 15 and 18 known or novel candidate genes were identified for the biosynthesis of benzylGSL and phenethylGSL, including known regulators of GSL biosynthesis, such as BrMYB34, BrMYB51, BrMYB28, BrMYB29 and BrMYB122, and novel regulators or structural genes, such as BrMYB44/BrMYB77 and BrMYB60 for benzylGSL and BrCYP79B2 for phenethylGSL. Finally, we investigate the expression profiles of the biosynthetic genes for two Phe-derived GSLs by transcriptomic analysis. Our findings provide new insight into the complex machinery of Phe-derived GSLs in seeds of B. rapa and help to improve the quality of Brassicaceae plant breeding.

The main stream of the Tarim River in China is typical of ecologically sensitive areas that have been heavily disturbed by human activities; as such, the monitoring of the quality of its eco-environment constitutes an important task for researchers. By using GlobeLand30 data and applying the disturbance degree model and revised ecosystem service value (ESV) model, the study presented in this paper undertook a quantitative estimation of the effects of the disturbance impacts of human activities on the eco-environment of this area in the period of 2000 to 2020. The main conclusions are as follows: (1) disturbance index values, which reflect disturbance to the local ecosystem by human activities, increased over the study period. Further, cultivated land experienced the largest increase, which, in turn, brought about the most significant disturbance to the eco-environment. High disturbance index values presented a patchy distribution in the west of the main stream of the Tarim River and formed bands and dots in the east; the area of land characterized by high and moderate disturbance index values increased, with growth areas taking on a scattered distribution of patches, bands, and dots without significant spatial continuity. (2) The total ESV increased, indicating the quality of the eco-environment improved. The increase of cultivated land offset the increase in ESV, which counteracted the effects of ecological governance measures. Areas with high ESV values were mainly located in the western and central parts of the study area, while low values were found in the middle east and east. Areas with higher increases in ESV were mainly located in the western and the western part of the middle reaches and took on a zonal distribution, while areas of decrease followed a scattered distribution, presenting as dots or patches. Using the quantitative analysis methods and high-resolution remote sensing data to evaluate the changes in the eco-environment was considered as the innovation of this study, and the findings are useful in exploring the influence of human activities on ecosystems and evaluating the eco-environment in the minor watershed of an arid area. This piece of quantitative research contributes to the task of monitoring eco-environmental changes using remote sensing techniques in ecologically sensitive areas.

Pulmonary tuberculosis (PTB) has been a major threat to global public health. The association between meteorological factors and the incidence of PTB has been widely investigated by the generalized additive model, auto-regressive integrated moving average model and the distributed lag model, etc. However, these models could not address a non-linear or lag correlation between them. In this paper, a penalized distributed lag non-linear model, as a generalized and improved one, was applied to explore the influence of meteorological factors (such as air temperature, relative humidity and wind speed) on the PTB incidence in Xinjiang from 2004 to 2019. Moreover, we firstly use a comprehensive index (apparent temperature, AT) to access the impact of multiple meteorological factors on the incidence of PTB. It was found that the relationships between air temperature, relative humidity, wind speed, AT and PTB incidence were nonlinear (showed “wave-type “, “invested U-type”, “U-type” and “wave-type”, respectively). When air temperature at the lowest value (−16.1 °C) could increase the risk of PTB incidence with the highest relative risk (RR = 1.63, 95% CI: 1.21–2.20). An assessment of relative humidity demonstrated an increased risk of PTB incidence between 44.5% and 71.8% with the largest relative risk (RR = 1.49, 95% CI: 1.32–1.67) occurring at 59.2%. Both high and low wind speeds increased the risk of PTB incidence, especially at the lowest wind speed 1.4 m/s (RR = 2.20, 95% CI: 1.95–2.51). In particular, the lag effects of low and high AT on PTB incidence were nonlinear. The lag effects of extreme cold AT (−18.5 °C, 1st percentile) on PTB incidence reached a relative risk peak (RR = 2.18, 95% CI: 2.06–2.31) at lag 1 month. Overall, it was indicated that the environment with low air temperature, suitable relative humidity and wind speed is more conducive to the transmission of PTB, and low AT is associated significantly with increased risk of PTB in Xinjiang.

Fluorescence immunochromatographic assay (FICA) is a rapid immunoassay technique that has the characteristics of high precision and sensitivity. Although image FICA strip readers have the advantages of high portability and easy operation, the use of high-precision complementary metal oxide semiconductor (CMOS) image sensors leads to an increase in overall cost. Considering the popularity of CMOS image sensors in smartphones and their powerful processing functions, this work developed a smartphone-based FICA strip reader. An optical module suitable for the test strips with different fluorescent markers was designed by replacing the excitation light source and the light filter. An android smartphone was used for image acquisition and image denoising. Then, the test and control lines of the test strip image were recognized by the sliding window algorithm. Finally, the characteristic value of the strip image was calculated. A linear detection range from 10 to 5000 mIU/mL (R2 = 0.95) was obtained for human chorionic gonadotrophin with the maximum relative error less than 9.41%, and a linear detection range from 5 to 4000 pg/mL (R2 = 0.99) was obtained for aflatoxin B1, with the maximum relative error less than 12.71%. Therefore, the smartphone-based FICA strip reader had high portability, versatility, and accuracy.

A new database, the tropical cyclones passive microwave brightness temperature (TCsBT) database including 6273 overpasses of 503 tropical cyclones (TC) was established from 6-year (2011−2016) Fengyun-3B (FY-3B) Microwave Radiation Imager (MWRI) Level-1 brightness temperature (TB) data and TC best-track data. An algorithm to estimate the TC intensity is developed using MWRI TB’s from the database. The relationship between microwave TB and the maximum sustained surface wind (Vmax) of TCs is derived from the TCsBT database. A high correlation coefficient between MWRI channel TB and Vmax is found at the radial distance 50−100 km near the TC inner core. Brightness temperatures at 10.65, 18.70, 23.8, and 36.5 GHz increase but 89 GHz TB’s and polarization corrected TB at 36.5 GHz (PCT36.50) and PCT89 decrease with increasing TC intensity. The TCsBT database is further separated into the 5063 dependent samples (2010−2015) for the development of the TC intensity estimation algorithm and 1210 independent samples (2016) for algorithm verification. The stepwise regression method is used to select the optimal combination of storm intensity estimation variables from 12 candidate variables and four parameters (10.65h, 23.80v, 89.00v and PCT36.50) were selected for multiple regression models development. Among the four predictors, PCT36.50 contributes the most in estimating TC intensity. In addition, the errors are lower for estimating 6-h and 12-h future Vmax than estimating the current Vmax.

As an emerging technology, fluorescence immunochromatographic assay (FICA) has the advantages of high sensitivity, strong stability and specificity, which is widely used in the fields of medical testing, food safety and environmental monitoring. The FICA reader based on image processing meets the needs of point-of-care testing because of its simple operation, portability and fast detection speed. However, the image gray level of common image sensors limits the detection range of the FICA reader, and high-precision image sensors are expensive, which is not conducive to the popularization of the instrument. In this paper, FICA strips’ image was collected using a common complementary metal oxide semiconductor (CMOS) image sensor and a range adjustment mechanism was established to automatically adjust the exposure time of the CMOS image sensor to achieve the effect of range expansion. The detection sensitivity showed a onefold increase, and the upper detection limit showed a twofold increase after the proposed method was implemented. In addition, in the experiments of linearity and accuracy, the fitting degree (R2) of the fitted curves both reached 0.999. Therefore, the automatic range adjustment method can obviously improve the detection range of the FICA reader based on image processing.

We present a text entry technique called HiFinger, which is an eyes-free, one-handed wearable text entry technique for immersive virtual environments by thumb-to-fingers touch. This technique enables users to input text quickly, accurately, and comfortably with the sense of touch and a two-step input mode. It is especially suitable for mobile scenarios where users need to move (such as walking) in virtual environments. Various input signals can be triggered by moving the thumb towards ultra-thin pressure sensors placed on other fingers. After acquiring the comfort range of the touch between the thumb and other fingers, six placement modes for text entry are designed and tested, resulting in an optimal placement mode that leverages six pressure sensors for the text entry and two for the control function. A three-day study is conducted to evaluate the proposed technique, and experimental results show that novices can achieve an average text entry efficiency of 9.82 words per minute (WPM) in virtual environments based on head-mounted displays after a training period of 25 min.

Lycoris longituba, belonging to the Amaryllidaceae family, is a perennial bulb bearing flowers with diverse colors and fragrance. Selection of cultivars with excellent colored and scented flowers has always been the breeding aim for ornamental plants. However, the molecular mechanisms underlying color fading and aroma production during flower expansion in L. longituba remain unclear. Therefore, to systematically investigate these important biological phenomena, the tepals of L. longituba from different developmental stages were used to screen and analyze the metabolic components and relevant genes. Utilizing the Illumina platform, a total of 144,922 unigenes were obtained from the RNA-Seq libraries. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that the phenylpropanoid biosynthesis and flavonoid biosynthesis pathways might play important roles during color and aroma changes. Metabolomic analysis identified 29 volatile organic components (VOCs) from different developmental stages of L. longituba tepals, and orthogonal partial least-squares discriminate analysis (OPLS-DA) revealed that trans-β-ocimene—a terpene—was the most important aroma compound. Meanwhile, we found the content of anthocyanin was significantly reduced during the tepal color fading process. Then, we identified two dihydroflavonol-4-reductase (DFR) and three terpene synthase (TPS) genes, for which expression changes coincided with the production patterns of anthocyanins and trans-β-ocimene, respectively. Furthermore, a number of MYB and bHLH transcription factors (TFs) which might be involved in color- and aroma-formation were also identified in L. longituba tepal transcriptomes. Taken together, this is the first comprehensive report of the color and fragrance in tepals of L. longituba and these results could be helpful in understanding these characteristics and their regulation networks.

Background: The apelin-APJ system has been considered to play a crucial role in HPA axis function, and how the traditional Chinese compound prescription Xiaoyaosan regulates the apelin-APJ system as a supplement to treat depressive disorders. Objective: To investigate the depression-like behaviors and expression of apelin and APJ in hypothalamus of chronic unpredictable mild stress (CUMS) mice and study whether these changes related to the regulation of Xiaoyaosan. Methods: 60 adult C57BL/6J mice were randomly divided into four groups, including control group, CUMS group, Xiaoyaosan treatment group and fluoxetine treatment group. Mice in the control group and CUMS group received 0.5 mL physiological saline once a day by intragastric administration. Mice in two treatment groups received Xiaoyaosan (0.25 g/kg/d) and fluoxetine (2.6 mg/kg/d), respectively. After 21 days of modeling with CUMS, the expression of apelin and APJ in hypothalamus were measured by real-time fluorescence quantitative PCR, western blot and immunohistochemical staining. The physical condition, body weight, food intake and behavior tests such as open field test, sucrose preference test and force swimming test were measured to evaluate depressive-like behaviors. Results: In this study, significant behavioral changes were found in CUMS-induced mice, meanwhile the expressions of apelin and APJ in the hypothalamus were changed after modeling. The body weight, food-intake and depressive-like behaviors in CUMS-induced mice could be improved by Xiaoyaosan treatment which is similar with the efficacy of fluoxetine, while the expressions of apelin and APJ in hypothalamus were modified by Xiaoyaosan. Conclusions: The data suggest that apelin-APJ system changes in the hypothalamus may be a target of depressive disorders, and the beneficial effects of Chinese compound prescription Xiaoyaosan on depressive-like behaviors may be mediated by the apelin-APJ system.