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Lily bulbils, advantageous axillary organs used for asexual reproduction, have an underexplored developmental mechanism. Gibberellins are known to participate in bulbil development, but the regulatory mechanisms remain unclear. In this study, exogenous gibberellin (GA3) significantly increased the bulbil length, width, and weight by raising the endogenous gibberellin levels and elongating the scale cells. Transcriptomic analysis identified LlGA20ox2, a key gibberellin biosynthesis gene, which was upregulated during bulbil development and significantly responsive to GA3 treatment. Given the similarities in bulbil and bulblet development, we determined the roles of LlGA20ox2 using a bulblet system. Silencing LlGA20ox2 in bulblets inhibited development by reducing the cell length, while overexpression increased the bulblet length and width. In the gibberellin signaling pathway, we identified two key genes, LlGID1C and LlCIGR2. Silencing these genes resulted in phenotypes similar to LlGA20ox2, inhibiting bulblet development. Further transcriptomic analysis revealed that gibberellin-responsive genes were enriched in the glucuronate pathway, pentose phosphate pathway and galactose metabolism pathways. Most of these differentially expressed genes responded to gibberellin and were highly expressed in later stages of bulbil development, suggesting their involvement in gibberellin-regulated bulbil growth. In conclusion, we preliminarily explored the mechanisms of gibberellin regulation in bulbil development, offering significant commercial potential for new lily reproductive organs. [ABSTRACT FROM AUTHOR]

Background: Despite promise in preclinical models of acute respiratory distress syndrome (ARDS), mesenchymal stem cells (MSC) have failed to translate to therapeutic benefit in clinical trials. The MSC is a live cell medicine and interacts with the patient's disease state. Here, we explored this interaction, seeking to devise strategies to enhance MSC therapeutic function. Methods: Human bone-marrow-derived MSCs were exposed to lung homogenate from healthy and E. coli-induced ARDS rat models. Apoptosis and functional assays of the MSCs were performed. Results: The ARDS model showed reduced arterial oxygenation, decreased lung compliance and an inflammatory microenvironment compared to controls. MSCs underwent more apoptosis after stimulation by lung homogenate from controls compared to E. coli, which may explain why MSCs persist longer in ARDS subjects after administration. Changes in expression of cell surface markers and cytokines were associated with lung homogenate from different groups. The anti-microbial effects of MSCs did not change with the stimulation. Moreover, the conditioned media from lung-homogenate-stimulated MSCs inhibited T-cell proliferation. Conclusions: These findings suggest that the ARDS microenvironment plays an important role in the MSC's therapeutic mechanism of action, and changes can inform strategies to modulate MSC-based cell therapy for ARDS. [ABSTRACT FROM AUTHOR]

While Mammarenavirus Wenzhouense (WENV) is broadly distributed across Asia, the dynamics of WENV infection remain unclear. In this study, a field-derived strain of WENV was used to inoculate Sprague Dawley (SD) rats by intramuscular injection, and the process of viral infection was observed over the course of 28 d. Viral RNA became detectable in the blood at 3 dpi and remained detectable for about 12 d. In most organ tissues, viral RNA peaked at 7 dpi, and then began to decline by 14 d, but remained detectable in intestine and brain tissues at 21 and 28 dpi. Viral shedding was detected from fecal samples for 5 d, from 6 to 11 dpi using qRT-PCR, and was recovered from feces collected at 8 dpi. Horizontal contact infection occurred among cage-mates at 14 and 21 dpi. Antibodies against the nucleocapsid were detected at 5 dpi, and then increased and persisted until the end of the experiment. These results enabled us to determine the kinetics of viremic response, viral shedding in feces, and horizontal transmission dynamics, as well as the potential sites for WENV replication and viral maintenance in nature. [ABSTRACT FROM AUTHOR]

Solar-induced chlorophyll fluorescence (SIF) has been found to be a useful indicator of vegetation's gross primary productivity (GPP). However, the directional SIF observations obtained from a canopy only represent a portion of the total fluorescence emitted by all the leaf photosystems because of scattering and reabsorption effects inside the leaves and canopy. Hence, it is crucial to downscale the SIF from canopy level to leaf level by modeling fluorescence escape probability (fesc) for improved comprehension of the relationship between SIF and GPP. Most methods for estimating fesc rely on the assumption of a "black soil background," ignoring soil reflectance and the effect of scattering between soils and leaves, which creates significant uncertainties for sparse canopies. In this study, we added a correction factor considering soil reflectance, which was modeled using the Gaussian process regression algorithm, to the semi-empirical NIRv/FAPAR model and obtained the improved fesc model accounting for soil reflectance (called the fesc_GPR-SR model), which is suitable for near-infrared SIF downscaling. The evaluation results using two simulation datasets from the Soil–Canopy–Observation of Photosynthesis and the Energy Balance (SCOPE) model and the Discrete Anisotropic Radiative Transfer (DART) model showed that the fesc_GPR-SR model outperformed the NIRv/FAPAR model, especially for sparse vegetation, with higher accuracy for estimating fesc (R2 = 0.954 and RMSE = 0.012 for SCOPE simulations; R2 = 0.982 and RMSE = 0.026 for DART simulations) compared with the NIRv/FAPAR model (R2 = 0.866 and RMSE = 0.100 for SCOPE simulations; R2 = 0.984 and RMSE = 0.070 for DART simulations). The evaluation results using in situ observation data from multi-species canopies also suggested that the leaf-level SIF calculated by the fesc_GPR-SR model tracked better with photosynthetic active radiation absorbed by green components (APARgreen) for sparse vegetation (R2 = 0.937, RMSE = 0.656 mW/m2/nm) compared with the NIRv/FAPAR model (R2 = 0.921, RMSE = 0.904 mW/m2/nm). The leaf-level SIF calculated by the fesc_GPR-SR model was less sensitive to observation angles and differences in canopy structure among multiple species. These results emphasize the significance of accounting for soil reflectance in the estimation of fesc and demonstrate that the fesc_GPR-SR model can contribute to further exploring the physiological mechanism between SIF and GPP. [ABSTRACT FROM AUTHOR]

Through an evolution from an emerging marketing narrative to a geographical fact around the globe, smart city is increasingly understood as a city's effort to make itself smart. There seems no single city in the world to be commonly recognized as a real smart city yet, albeit many cities have already tried hard in this missionary commitment. Yet some common features can still be seen and identified, particularly from the urban governance perspective. This article explores the practice of smart city construction in China through a lens of governance by observing the interactive involvement of key stakeholders in the process. By taking three cities (Hangzhou, Wuhan, and Shanghai) in China as study cases, a conceptual framework is established in which three sets of actors, i.e., ICT-related enterprises, government, and civil society, and, accordingly, three types of approaches, i.e., ICT-led, planning-led, and place-making-and-community-oriented, are identified. It is found that the evolution of smart city construction rather follows a nonlinear trajectory and is very dependent on whether or not the primary actors and related stakeholders can form an affirmative acting power in triggering the city's implementation. In other words, there is no "one-size-fits-all" approach to smart city construction. Each city may have its specialization in smartness based on awareness of and respecting its unique existing setting. The empirical study also shows that smart city construction tends to be converged in recognition that the core of smart city is not the smartness of technology but the smartness of all institutions and people enabled to utilize smart tools properly and efficiently in pursuit of people's well-being, institutional capacity building, and better spatial arrangement towards a sustainable, resilient, and inclusive city in and for the future. From a geographical perspective, that is how to build a smart urban space to make the city a better place to not just accommodate but facilitate and meet people's increasing demand for a better life in their living places. [ABSTRACT FROM AUTHOR]

Cationic polymeric materials and cell-penetrating peptides (CPPs) were often used as the delivery vectors in the evaluation of nucleic acid therapeutics. 10-23 DNAzyme is a kind of potential antisense therapeutics by catalytic cleavage of the disease-related RNAs. Here, lipofectamine 2000 and Tat peptide were evaluated for their effect on the catalytic activity of 10-23 DNAzyme, with the observed rate constant, thermal stability, CD spectra, and PAGE analysis, with a duplex DNA mimicking DNAzyme-substrate as a control. It was shown that the cationic carriers had a negative effect on the catalytic performance of the 10-23 DNAzyme. Significantly, the destabilizing effect of the cationic carriers on the duplex formation was noteworthy, as a duplex formation is an essential prerequisite in the silencing mechanisms of antisense and RNAi. [ABSTRACT FROM AUTHOR]

With the vigorous development of industrialization and urbanization, rural space faces many difficulties in achieving sustainable development, such as the spatial structure being unbalanced. To explore the sustainable development of rural space, this study evaluates the spatial evolution and multi-scenario simulation of rural space with reference to the three dominant functions of land use, namely "production–ecological–living" (PEL), based on the interpretation of land use remote sensing data in 2000, 2010, and 2020. The change characteristics and the formation mechanism of the territorial spatial pattern were quantitatively analyzed by gravity center transfer, territorial spatial transfer matrix, standard deviational ellipse, geo-detector, and artificial neural network CA simulation. The results showed that (1) from 2000 to 2020, the rural production space in Beijing continued to decrease, the rural living space continued to increase and then gradually contracted, and the rural ecological space as a whole also showed a downward trend. (2) During the study period, the formation and evolution of the ecological spatial pattern of rural production and living in Beijing were affected by both regional physical geographical factors and human, social, and economic factors, with significant differences; the interaction between two driving factors is stronger than that within a single factor, and the main mode of action is double factor enhancement and nonlinear enhancement. (3) Compared with the other three scenarios, the performance of Beijing's rural space in 2030 under the harmonious development scenario is more compact and stable, the rural production space is basically guaranteed, the intensity of rural living space is enhanced, and the overall situation of rural ecological space is stable. Our results show that in the future decision-making of rural land and space development around a metropolis, we should fully consider the evolution law of rural spatial pattern, as well as the driving force of natural geographical factors and economic activity factors and discuss the optimization and overall management of rural production and living ecological space through multi-scenario spatial simulation. [ABSTRACT FROM AUTHOR]

Alpine meadow ecosystems are extremely vulnerable to climate change and serve an essential function in terrestrial carbon sinks. Accurately estimating their gross primary productivity (GPP) is essential for understanding the global carbon cycle. Solar-induced chlorophyll fluorescence (SIF), as a companion product directly related to plant photosynthesis process, has become an attractive pathway for estimating GPP accurately. To date, the quantitative SIF-GPP relationship in terrestrial ecosystems is not yet clear. Especially, red SIF and far-red SIF present differences in their ability to track GPP under different environmental conditions. In this study, we investigated the performance of SIF at both red and far-red band in monitoring the GPP of an alpine meadow ecosystem based on continuous tower-based observations in 2019 and 2020. The results show that the canopy red SIF ( SIF Red ) and far-red SIF ( SIF Far-red ) were both strongly correlated with GPP. SIF Red was comparable to SIF Far-red for monitoring GPP based on comparisons of both half-hourly averaged and daily averaged datasets. Moreover, the relationship between SIF Red and GPP was linearly correlated, while the relationship between SIF Far-red and GPP tended to be nonlinear. At a diurnal scale, dramatic changes in photosynthetically active radiation (PAR), air temperature (Ta), and vapor pressure deficit (VPD) all had effects on the slope of the linear fitted line with zero intercept for SIF Red -GPP and SIF Far-red -GPP, and the effect on the slope of the linear fitted line with zero intercept for SIF Far-red -GPP was obviously stronger than that for SIF Red -GPP. PAR was the dominant factor among the three environmental factors in determining the diurnal variation of the slope of SIF-GPP. At a seasonal scale, the SIF Far-red /GPP was susceptible to PAR, Ta, and VPD, while the SIF Red /GPP remained relatively stable at different levels of Ta and VPD, and it was only weakly affected by PAR, suggesting that SIF Red was more consistent than SIF Far-red with GPP in response to seasonal variations in environmental factors. These results indicate that SIF Red has more potential than SIF Far-red for monitoring the GPP of alpine meadow ecosystems and can also assist researchers in gaining a more comprehensive understanding of the diversity of SIF-GPP relationships in different ecosystems. [ABSTRACT FROM AUTHOR]

The evidence on the association between long-term low-carbohydrate, high-fat and high-protein diets and type 2 diabetes (T2D) is controversial. Until now, data is limited for Chinese populations, especially in considering the influence of extra energy intake. In this paper, we aimed to investigate the association of low-carbohydrate, high-fat and high-protein diets with type 2 diabetes (T2D) risk in populations consuming extra calories and those with normal caloric intake, We also determined whether the association is mediated by insulin resistance (IR) or β-cell dysfunction. A total of 3644 subjects in the Harbin People's Health Study (Cohort 1, 2008-2012) and 7111 subjects in the Harbin Cohort Study on Diet, Nutrition and Chronic Non-Communicable Diseases (Cohort 2, 2010-2015) were analyzed, with a median follow-up of 4.2 and 5.3 years, respectively. Multivariate relative risks (RRs) and their 95% confidence intervals (95% CIs) were calculated to estimate the association between low-carbohydrate, high-fat and high-protein diet and T2D in logistic regression models. The multivariate RRs (95% CIs) were 1.00, 2.24 (1.07, 4.72) and 2.29 (1.07, 4.88) (Ptrend = 0.04), and 1.00, 1.45 (0.91, 2.31) and 1.64 (1.03, 2.61) (Ptrend = 0.04) across tertiles of low-carbohydrate, high-fat and high-protein diet scores in the population consuming extra calories in Cohort 1 and Cohort 2, respectively. The association was no longer significant after adjustment for livestock and its products, or poultry and its products. The mediation analysis discovered that this association in the population consuming extra calories was insulin resistance mediated, in both Cohort 1 and Cohort 2. However, the association was not significant among participants overall and participants with normal caloric intake. Our results indicated that long-term low-carbohydrate, high-fat and high-protein diets were associated with increased T2D risk among the population consuming extra calories, which may be caused by higher intake of animal-origin fat and protein as well as lower intake of vegetables, fruit and fiber. Additionally, the association was mediated by IR. In the population consuming extra calories, reducing the intake of livestock, poultry and their products and increasing the intake of vegetables, fruit and fiber might protect this population from developing T2D. [ABSTRACT FROM AUTHOR]

In this study, PM2.5 was analyzed for heavy metals at two sites in industrial northeast China to determine their sources and human health risks during heating and non-heating periods. A positive matrix factorization (PMF) model determined sources, and US Environmental Protection Agency (USEPA) and entropy weight methods were used to assess human health risk. PM2.5 heavy metal concentrations were higher in the heating period than in the non-heating period. In the heating period, coal combustion (59.64%) was the primary heavy metal source at Huagong Hospitals, and the contribution rates of industrial emissions and traffic emissions were 21.06% and 19.30%, respectively. Industrial emissions (42.14%) were the primary source at Xinqu Park, and the contribution rates of coal combustion and traffic emissions were 34.03% and 23.83%, respectively. During the non-heating period, coal combustion (45.29%) and industrial emissions 45.29% and 44.59%, respectively, were the primary sources at Huagong Hospital, and the traffic emissions were 10.12%. Industrial emissions (43.64%) were the primary sources at Xinqu Park, where the coal combustion and traffic emissions were 25.35% and 31.00%, respectively. In the heating period, PM2.5 heavy metals at Xinqu Park had noncarcinogenic and carcinogenic risks, and the hazard index of children (5.74) was higher than that of adult males (5.28) and females (4.49). However, adult males and females had the highest lifetime carcinogenic risk (1.38 × 10−3 and 1.17 × 10−3) than children (3.00 × 10−4). The traditional USEPA and entropy weight methods both produced reasonable results. However, when there is a difference between the two methods, the entropy weight method is recommended to assess noncarcinogenic health risks. [ABSTRACT FROM AUTHOR]

Space-based solar-induced chlorophyll fluorescence (SIF) has been widely demonstrated as a great proxy for monitoring terrestrial photosynthesis and has been successfully retrieved from satellite-based hyperspectral observations using a data-driven algorithm. As a semi-empirical algorithm, the data-driven algorithm is strongly affected by the empirical parameters in the model. Here, the influence of the data-driven algorithm's empirical parameters, including the polynomial order (np), the number of feature vectors (nSV), the fluorescence emission spectrum function, and the fitting window used in the retrieval model, were quantitatively investigated based on the simulations of the SIF Imaging Spectrometer (SIFIS) onboard the First Terrestrial Ecosystem Carbon Inventory Satellite (TECIS-1). The results showed that the fitting window, np, and nSV were the three main factors that influenced the accuracy of retrieval. The retrieval accuracy was relatively higher for a wider fitting window; the root mean square error (RMSE) was lower than 0.7 mW m−2 sr−1 nm−1 with fitting windows wider than 735–758 nm and 682–691 nm for the far-red band and the red band, respectively. The RMSE decreased first and then increased with increases in np range from 1 to 5 and increased in nSV range from 2 to 20. According to the specifications of SIFIS onboard TECIS-1, a fitting window of 735–758 nm, a second-order polynomial, and four feature vectors are the optimal parameters for far-red SIF retrieval, resulting in an RMSE of 0.63 mW m−2 sr−1 nm−1. As for red SIF retrieval, using second-order polynomial and seven feature vectors in the fitting window of 682–697 nm was the optimal choice and resulted in an RMSE of 0.53 mW m−2 sr−1 nm−1. The optimized parameters of the data-driven algorithm can guide the retrieval of satellite-based SIF and are valuable for generating an accurate SIF product of the TECIS-1 satellite after its launch. [ABSTRACT FROM AUTHOR]

With the development of satellite communication networks and the increase of satellite services, security problems have gradually become some of the most concerning issues. Researchers have made great efforts, including conventional safety methods such as secure transmission, anti-jamming, secure access, and especially the new generation of active defense technology represented by MTD. However, few scholars have theoretically studied the influence of active defense technique on the performance of satellite networks. Formal modeling and performance analysis have not been given sufficient attention. In this paper, we focus on the performance evaluation of satellite network moving target defense system. Firstly, two Stochastic Petri Nets (SPN) models are constructed to analyze the performance of satellite network in traditional and active defense states, respectively. Secondly, the steady-state probability of each marking in SPN models is obtained by using the isomorphism relation between SPN and Markov Chains (MC), and further key performance indicators such as average time delay, throughput, and the utilization of bandwidth are reasoned theoretically. Finally, the proposed two SPN models are simulated based on the PIPE platform. In addition, the effect of parameters on the selected performance indexes is analyzed by varying the values of different parameters. The simulation results prove the correctness of the theoretical reasoning and draw the key factors affecting the performance of satellite network, which can provide an important theoretical basis for the design and performance optimization of the satellite network moving target defense system. [ABSTRACT FROM AUTHOR]

Solar-induced chlorophyll fluorescence (SIF) provides a new and direct way of monitoring photosynthetic activity. However, current SIF products are limited by low spatial resolution or sparse sampling. In this paper, we present a data-driven method of generating a global, spatially continuous TanSat SIF product. Firstly, the key explanatory variables for modelling canopy SIF were investigated using in-situ and satellite observations. According to theoretical and experimental analysis, the solar radiation intensity was found to be a dominant driving environmental variable for the SIF yield at both the canopy and global scales; this has, however, been neglected in previous research. The cosine value of the solar zenith angle at noon (cos (SZA0)), a proxy for solar radiation intensity, was found to be a dominant abiotic factor for the SIF yield. Next, a Random Forest (RF) approach was employed for SIF prediction based on Moderate Resolution Imaging Spectroradiometer (MODIS) visible-to-NIR reflectance data, the normalized difference vegetation (NDVI), cos (SZA0), and air temperature. The machine learning model performed well at predicting SIF, giving R2 values of 0.73, an RMSE of 0.30 mW m−2 nm−1 sr−1 and a bias of 0.22 mW m−2 nm−1 sr−1 for 2018. If cos (SZA0) was not included, the accuracy of the RF model decreased: the R2 value was then 0.65, the RMSE 0.34 mW m−2 nm−1 sr−1 and an bias of 0.26 mW m−2 nm−1 sr−1, further verifying the importance of cos (SZA0). Finally, the globally continuous TanSat SIF product was developed and compared to the TROPOspheric Monitoring Instrument (TROPOMI) SIF data. The results showed that the globally continuous TanSat SIF product agreed well with the TROPOMI SIF data, with an R2 value of 0.73. Thus, this paper presents an improved approach to modelling satellite SIF that has a better accuracy, and the study also generated a global, spatially continuous TanSat SIF product with a spatial resolution of 0.05°. [ABSTRACT FROM AUTHOR]

Solar-induced chlorophyll fluorescence (SIF) has been proven to be well correlated with vegetation photosynthesis. Although multiple studies have found that SIF demonstrates a strong correlation with gross primary production (GPP), SIF-based GPP estimation at different temporal scales has not been well explored. In this study, we aimed to investigate the quality of GPP estimates produced using the far-red SIF retrieved at 760 nm (SIF760) based on continuous tower-based observations of a maize field made during 2017 and 2018, and to explore the responses of GPP and SIF to different meteorological conditions, such as the amount of photosynthetically active radiation (PAR), the clearness index (CI, representing the weather condition), the air temperature (AT), and the vapor pressure deficit (VPD). Firstly, our results showed that the SIF760 tracked GPP well at both diurnal and seasonal scales, and that SIF760 was more linearly correlated to PAR than GPP was. Therefore, the SIF760–GPP relationship was clearly a hyperbolic relationship. For instantaneous observations made within a period of half an hour, the R2 value was 0.66 in 2017 and 2018. Based on daily mean observations, the R2 value was 0.82 and 0.76 in 2017 and 2018, respectively. Secondly, it was found that the SIF760–GPP relationship varied with the environmental conditions, with the CI being the dominant factor. At both diurnal and seasonal scales, the ratio of GPP to SIF760 decreased noticeably as the CI increased. Finally, the SIF760-based GPP models with and without the inclusion of CI were trained using 70% of daily observations from 2017 and 2018 and the models were validated using the remaining 30% of the dataset. For both linear and non-linear models, the inclusion of the CI greatly improved the SIF760-based GPP estimates based on daily mean observations: the value of R2 increased from 0.71 to 0.82 for the linear model and from 0.82 to 0.87 for the non-linear model. The validation results confirmed that the SIF760-based GPP estimation was improved greatly by including the CI, giving a higher R2 and a lower RMSE. These values improved from R2 = 0.66 and RMSE = 7.02 mw/m2/nm/sr to R2 = 0.76 and RMSE = 6.36 mw/m2/nm/sr for the linear model, and from R2 = 0.71 and RMSE = 4.76 mw/m2/nm/sr to R2 = 0.78 and RMSE = 3.50 mw/m2/nm/sr for the non-linear model. Therefore, our results demonstrated that SIF760 is a reliable proxy for GPP and that SIF760-based GPP estimation can be greatly improved by integrating the CI with SIF760. These findings will be useful in the remote sensing of vegetation GPP using satellite, airborne, and tower-based SIF data because the CI is usually an easily accessible meteorological variable. [ABSTRACT FROM AUTHOR]

The global monitoring of solar-induced chlorophyll fluorescence (SIF) using satellite-based observations provides a new way of monitoring the status of terrestrial vegetation photosynthesis on a global scale. Several global SIF products that make use of atmospheric satellite data have been successfully developed in recent decades. The Terrestrial Ecosystem Carbon Inventory Satellite (TECIS-1), the first Chinese terrestrial ecosystem carbon inventory satellite, which is due to be launched in 2021, will carry an imaging spectrometer specifically designed for SIF monitoring. Here, we use an extensive set of simulated data derived from the MODerate resolution atmospheric TRANsmission 5 (MODTRAN 5) and Soil Canopy Observation Photosynthesis and Energy (SCOPE) models to evaluate and optimize the specifications of the SIF Imaging Spectrometer (SIFIS) onboard TECIS for accurate SIF retrievals. The wide spectral range of 670−780 nm was recommended to obtain the SIF at both the red and far-red bands. The results illustrate that the combination of a spectral resolution (SR) of 0.1 nm and a signal-to-noise ratio (SNR) of 127 performs better than an SR of 0.3 nm and SNR of 322 or an SR of 0.5 nm and SNR of 472 nm. The resulting SIF retrievals have a root-mean-squared (RMS) diff* value of 0.15 mW m−2 sr−1 nm−1 at the far-red band and 0.43 mW m−2 sr−1 nm−1 at the red band. This compares with 0.20 and 0.26 mW m−2 sr−1 nm−1 at the far-red band and 0.62 and 1.30 mW m−2 sr−1 nm−1 at the red band for the other two configurations described above. Given an SR of 0.3 nm, the increase in the SNR can also improve the SIF retrieval at both bands. If the SNR is improved to 450, the RMS diff* will be 0.17 mW m−2 sr−1 nm−1 at the far-red band and 0.47 mW m−2 sr−1 nm−1 at the red band. Therefore, the SIFIS onboard TECIS-1 will provide another set of observations dedicated to monitoring SIF at the global scale, which will benefit investigations of terrestrial vegetation photosynthesis from space. [ABSTRACT FROM AUTHOR]

Solar-induced chlorophyll fluorescence (SIF) is regarded as a proxy for photosynthesis in terrestrial vegetation. Tower-based long-term observations of SIF are very important for gaining further insight into the ecosystem-specific seasonal dynamics of photosynthetic activity, including gross primary production (GPP). Here, we present the design and operation of the tower-based automated SIF measurement (SIFSpec) system. This system was developed with the aim of obtaining synchronous SIF observations and flux measurements across different terrestrial ecosystems, as well as to validate the increasing number of satellite SIF products using in situ measurements. Details of the system components, instrument installation, calibration, data collection, and processing are introduced. Atmospheric correction is also included in the data processing chain, which is important, but usually ignored for tower-based SIF measurements. Continuous measurements made across two growing cycles over maize at a Daman (DM) flux site (in Gansu province, China) demonstrate the reliable performance of SIF as an indicator for tracking the diurnal variations in photosynthetically active radiation (PAR) and seasonal variations in GPP. For the O2–A band in particular, a high correlation coefficient value of 0.81 is found between the SIF and seasonal variations of GPP. It is thus concluded that, in coordination with continuous eddy covariance (EC) flux measurements, automated and continuous SIF observations can provide a reliable approach for understanding the photosynthetic activity of the terrestrial ecosystem, and are also able to bridge the link between ground-based optical measurements and airborne or satellite remote sensing data. [ABSTRACT FROM AUTHOR]

In the 15-mer catalytic core of 10-23 DNAzyme, each residue contributes to the catalytic conformation differently. Here, the critically conserved T4 and the least conserved T8 were modified on their 5-position with hydroxyl, imidazolyl, and amino groups with a hydrogen-bonding ability. These external functional groups induced new interactions within the catalytic core, resulting in both negative and positive effects on the catalytic activity of 10-23 DNAzyme, and the different linkages could be used to modulate the effect of the functional groups. The conservation of T4 and T8 could be recognized at the level of the nucleobase, but at the level of the functional group, T4 is not completely conserved. Their 5-methyl groups could be modified for a better performance in terms of the DNAzyme., Competing Interests: The authors declare no conflict of interest.

The measurement of solar-induced chlorophyll fluorescence (SIF) is a new tool for estimating gross primary production (GPP). Continuous tower-based spectral observations together with flux measurements are an efficient way of linking the SIF to the GPP. Compared to conical observations, hemispherical observations made with cosine-corrected foreoptic have a much larger field of view and can better match the footprint of the tower-based flux measurements. However, estimating the equivalent radiation transfer path length (ERTPL) for hemispherical observations is more complex than for conical observations and this is a key problem that needs to be addressed before accurate retrieval of SIF can be made. In this paper, we first modeled the footprint of hemispherical spectral measurements and found that, under convective conditions with light winds, 90% of the total radiation came from an FOV of width 72°, which in turn covered 75.68% of the source area of the flux measurements. In contrast, conical spectral observations covered only 1.93% of the flux footprint. Secondly, using theoretical considerations, we modeled the ERTPL of the hemispherical spectral observations made with cosine-corrected foreoptic and found that the ERTPL was approximately equal to twice the sensor height above the canopy. Finally, the modeled ERTPL was evaluated using a simulated dataset. The ERTPL calculated using the simulated data was about 1.89 times the sensor's height above the target surface, which was quite close to the results for the modeled ERTPL. Furthermore, the SIF retrieved from atmospherically corrected spectra using the modeled ERTPL fitted well with the reference values, giving a relative root mean square error of 18.22%. These results show that the modeled ERTPL was reasonable and that this method is applicable to tower-based hemispherical observations of SIF.