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Oceanic water quality monitoring is essential for environmental protection, resource management, and ecosystem vitality. Optical remote sensing from space plays a pivotal role in global surveillance of oceanic water quality. However, the spatial resolution of current ocean color data products falls short of scrutinizing intricate small-scale marine features. This study introduces a hybrid model that fuses MODIS (Moderate Resolution lmaging Spectroradiometer) ocean color products with Sentinel-2 ‘s remote sensing reflectance data to generate high-resolution ocean color imagery, specifically investigating the diffuse attenuation coefficient at a wavelength of 490 nm (Kd490). To address the intricacies of coastal environments, we propose two complementary strategies to improve the accuracy of inversion. The first strategy leverages MODIS ocean color products alongside a geographic segmentation model to perform distinct inversions for separate marine zones, enhancing spatial resolution and specificity in coastal regions. The second strategy bolsters model interpretability during training by integrating predictions from conventional physical models into a Random Forest-based Regression Ensemble (RFRE) model. This study focuses on the coastal regions surrounding the Beibu Gulf, near Hainan Island in China. Our findings exhibit a strong concordance with MODIS products, achieving a monthly average coefficient of determination (R²) of 0.90, peaking at 0.97, and sustaining a monthly average root-mean-square error (RMSE) of less than 0.02. These results substantiate the model’s efficacy. Moreover, the annual trend analysis and localized assessment of the reconstructed Kd490 offer nuanced insights that surpass MODIS data, establishing a robust foundation for high-resolution water quality monitoring in coastal zones.

Abstract Background The association of longitudinal uric acid (UA) changes with cardiac conduction block risk is unclear. We aimed to identify the trajectories of UA and explore its association with cardiac conduction block. Methods A total of 67,095 participants with a mean age of 53.12 years were included from the Kailuan cohort in Tangshan, China, who were free of cardiac conduction block and with repeated measurements of UA from 2006 to 2012. UA trajectories during 2006 to 2012 were identified by group-based trajectory modeling. Cox proportional hazard regression models were used to assess the association of UA trajectories with cardiac conduction block. Results We categorized three observed discrete trajectories of UA during 2006–2012 period: low-stable, moderate-stable, and high-stable. Over a median follow-up of 6.19 years, we identified 1405 (2.09%) incident cardiac conduction block. Compared to those in the low-stable trajectory, the adjusted hazard ratios (HRs) (95% confidence interval [CI]) of cardiac conduction block in the moderate-stable and high-stable trajectory were 1.30 (1.16–1.47) and 1.86 (1.56–2.22), and HRs of atrioventricular block were 1.39 (1.12–1.72) and 2.90 (2.19–3.83), and HRs of bundle branch blocks were 1.27 (1.10–1.47) and 1.43 (1.13–1.79). Notably, although the average UA level in the moderate-stable UA trajectory group is within the normal range, the risk of cardiac conduction block has increased. Conclusions The moderate-stable and high-stable trajectories are associated with increased risk for new-onset cardiac conduction block. Monitoring UA trajectories may assist in identifying subpopulations at higher risk for cardiac conduction block.

Photon-counting light detection and ranging is very sensitive to ambient interference, target features, and instrument performance, especially for long-distance detection of spaceborne laser altimeter and measurement of complex land-cover types with steep terrain. It is crucial to extract the signal photons on the ground surface from the collected photon point cloud (PPC). An adaptive signal photon detection method is presented in this article, which combines histogram statistics and boxplot analysis with density-based spatial clustering of applications with noise (DBSCAN), to denoise the PPC data with strong and weak noise obtained by ice, cloud, and land elevation satellite-2 laser altimeter. First, a coarse denoising with histogram of elevation is conducted on the raw PPC to reduce the calculation amount. Second, a fine denoising based on adaptive DBSCAN is used to extract the signal photons, where the key parameters of elliptic filter kernel are automatically determined according to the topographic data situation. We compared it with other methods, including local distance statistics (LDS), traditional and modified DBSCAN, traditional and modified ordering points to identify cluster structure (OPTICS), and ATL08 data. Some quantitative indicators, such as recall (R), precision (P), and F-score (F), are used to evaluate its performance. The results show that; 1) the adaptive DBSCAN has the best performance on preserving the vertical structural characteristics of ground objects, and 2) the adaptive DBSCAN in the mean R, P, and F of three land covers (i.e., mountain forest, urban, and water areas) can get up to the maximum are 0.9852, 0.9675, and 0.9761, respectively; followed by ATL08 data with 0.9773, 0.9412, and 0.9536, modified OPTICS with 0.9684, 0.9460, and 0.9586, and modified DBSCAN with 0.9613, 0.9474, and 0.9544; and then OPTICS with 0.9444, 0.9397, and 0.9378, and the DBSCAN with 0.9444, 0.9355, and 0.9554; the last one is LDS with 0.9382, 0.9261, and 0.9422. The proposed method provides an alternative approach for rapid and accurate processing of PPC on complex terrain.

Rammed earth, a commonly used building material in ancient times, differs from natural sedimentary layers in that it is more compact. Buildings constructed from historical rammed earth sites frequently encounter the issue of rainwater erosion. Microbially induced calcium carbonate precipitation (MICP) is commonly applied to sand soil treatment, yet reports on its use for stabilizing rammed earth are scarce. This study focused on the rammed earth of the Shanhaiguan Great Wall and explored the efficacy of MICP in mitigating rain erosion through permeation tests, splash experiments, and scouring trials. The findings indicate that the forms of rain erosion damage under MICP treatment vary across different operational conditions. In laboratory experiments, as the concentration of the cementation solution increases, the amount of calcium carbonate crystals also increases. However, the permeability, splash resistance, and rain erosion resistance initially increase and then decrease. When the cementation solution concentration is 1.0 mol/L, the penetration rate is the highest, lasting 712.55 s. The splash pit rate is the lowest, at only 1.2 mm, and the soil erosion rate is the lowest, at only 4.13%. The rain erosion resistance in the field test exhibit the same trend, and the optimal concentration is 1.2 mol/L. The optimal concentration mechanism involves the aggregation of calcium carbonate crystals at suitable cementation solution concentrations, which begin to fill the soil particle pores, effectively resisting rainwater erosion. At lower concentrations of the cementation solution, calcium carbonate crystals are merely adsorbed by soil particles without blocking the pores. Due to the high compressibility of rammed earth, which results in lower porosity, a higher concentration of the cementation solution leads to rapid pore clogging by excessive calcium carbonate crystals, which accumulate on the surface to form a white crust layer. The MICP technique can effectively alleviate rainwater erosion in rammed earth, and the optimal concentration needs to be tailored to the porosity of the rammed earth. This mechanism was also validated in field scouring experiments on the Shanhaiguan Great Wall’s rammed earth.

Laboratory analysis of returned Chang’E-5 samples from the lunar surface show their hydroxyl contents to be on the weak end of lunar hydration features.

Optical frequency combs have emerged as a new generation of metrological tools, driving advancements in various fields such as free-space two-way time–frequency transfer, low-noise microwave source generation, and gas molecule detection. Among them, fiber combs based on erbium-doped fiber mode-locked lasers have garnered significant attention due to their numerous advantages, including low noise, high system integration, and cost-effectiveness. In this review, we discuss recent developments in erbium-doped fiber combs and analyze the advantages and disadvantages of constructing fiber combs utilizing different erbium-doped mode-locked fiber lasers. First, we provide a brief introduction to the basic principles of optical frequency combs. Then, we explore erbium-doped fiber combs implemented utilizing various mode-locking techniques, such as nonlinear polarization rotation (NPR), real saturable absorber (SA), and nonlinear amplifying loop mirror (NALM). Finally, we present an outlook on the future perspectives of erbium-doped fiber combs.

The study of volatile elements on the Martian surface is a critical way to explore the geological evolution history of Mars. Volatile elements such as hydrogen (H), sulfur (S), and chlorine (Cl) on the Martian surface act as proxies for the potential aqueous or atmospheric environments that formed their corresponding phases. In this work, data collected from the Laser Induced Breakdown Spectroscopy and the Short Wave Infrared Spectroscopy of the Mars Surface Composition Detection onboard the Zhurong rover are employed to analyze the volatile elements (H, S, Cl) and their carriers in materials throughout the landing site. We found that S primarily concentrates in gypsum and other sulfates, and the carriers of H include hydrous mineral combinations such as gypsum, hydrated silica, and ferrihydrite. These altered minerals are probably the products of acid weathering processes, which may have occurred mostly during the relatively humid period of the Zhurong landing site since Amazonian.

Full-waveform spaceborne laser altimeter can provide more characteristic parameters of the laser footprint and rich vertical structure information on the target surface. This technology has the potential for land-cover classification, especially in hard-to-reach mountain areas. Classifying the land types based on the returned waveform can provide a convenient way for the online classification needs and assess the quality of footprint used as the ground control point in photogrammetry. This article presents a random forest (RF) classification using geoscience laser altimeter system waveform, in the west-central Yunnan Province, China. First, an improved threshold wavelet is performed to denoise the waveform, and then Gaussian decomposition is used to extract the typical characteristic features of footprint. Second, an RF algorithm is implemented to clarify the footprints into five types: flat, building, terrace, forest, and mountain. Finally, quantitative analysis is conducted with producer's accuracy (PA), user's accuracy (UA), overall accuracy (OA), precision, recall rate, F1-score, and kappa coefficient to compare the performance of RF with other classifiers, including linear support vector machine (linear-SVM), radial basis function SVM (RBF-SVM), logistic regression (LR), K-nearest neighbor (KNN), and naive Bayes (NB). The results show that all the six methods can accurately classify the flat land with 100.00% PA and UA. The RF also has the best performances in other four land types, with PA and UA of 98.14% and 100.00%, 97.24% and 95.49%, 98.64% and 96.03%, and 94.64% and 100.00%, respectively. The OA, precision, recall, F1-score, and kappa coefficient for the RF are 97.95%, 97.73%, 98.30%, 97.99%, and 0.9737, respectively; while 83.45%, 82.55%, 82.98%, 81.16%, and 0.7765 for NB, which has the worst performance. LR performs better than RBF-SVM, linear-SVM, and KNN. It also observes worse classification accuracy for all methods when the waveforms are more complex.

This paper reports a complete solution for short-acquisition-time, flood-illumination, and non-scanning 3D imaging. Based on an InGaAs/InP 64×64 Geiger-mode avalanche photodiode array, we developed a single-photon imaging Lidar with a field of view of 19.2 mrad. A spatiotemporal dominant imaging method was also applied for depth estimation under high daytime background noise conditions. In the field tests, 3D imaging information was effectively extracted from objects with strong solar background light. An acquisition time of only 0.5 ms to 4 ms was needed for a building target approximately 1300 m away. The experimental results show that the Lidar and its data processing method have the potential for dynamic scenarios that require high performance 3D imaging, such as vehicle navigation, airborne mapping, and moving target monitoring.

Objective: To investigate the effect and its underlying molecular mechanisms of essential oil from Saussurea costus in esophageal cancer cell line Eca109. Methods: The chemical composition of essential oil from Saussurea costus was investigated by gas chromatography-mass spectrometry (GC-MS). The anti-proliferative, anti-migrative, and apoptotic effects of essential oil from Saussurea costus against Eca109 cells were analyzed. Moreover, the expression of proteins associated with cell cycle, metastasis, and apoptosis was determined. Results: GC-MS analysis showed that essential oil from Saussurea costus was predominantly comprised of sesquiterpenes. Saussurea costus essential oil inhibited the viability of Eca109 cells in a dose-and time-dependent manner with IC50 values of (24.29±1.49), (19.16±2.27) and (6.97±0.86) μg/mL at 12, 24, and 48 h, respectively. The expression levels of target proteins in the cell cycle (phase G1/S), including cyclin D1, p21, and p53, were affected by Saussurea costus essential oil. The essential oil also downregulated the expression of metastasis-related proteins MMP-9 and MMP-2. Moreover, it induced apoptosis of Eca109 cells through the mitochondrial pathway, as well as inhibition of STAT3 phosphorylation. Conclusions: The essential oil from Saussurea costus exhibited anti-proliferative, anti-migrative, and apoptotic effects on Eca109 cells, and could be further explored as a potential anti-esophageal cancer agent.

We present the porcine skin ablation using a mid-infrared high-repetition-rate picosecond pulse burst laser. A burst-mode pulse with a repetition rate of 16.32 MHz was generated from a home-built difference frequency generation (DFG) system operating at 3 μm. Within each burst, there were 16 equally spaced 8.5 ps sub-pulses at an intra-burst repetition rate of ∼3.3 GHz. To study the laser-tissue interaction, laser powers of 1 to 2 W, and scanning times from 1 to 10 with spot size of ∼50 μm were applied to irradiate the fresh porcine skin. The results demonstrate that the burst-mode pulse with modest peak power density of MW/cm2 is efficient for tissue ablation. The optimized ablation depth increased with the average power and scanning times, reaching a maximal incision depth of 150 μm. Thanks to the high repetition rate of intra-burst pulse and high absorption of radiation, the ablation width and thermal effect width kept within 50 μm and 25 μm in all control groups. It is believed that as the first demonstration, such mid-infrared burst-mode laser radiation with modest power intensity is of great potential to realize micron penetration depth and low thermal effect in high-precision surgery applications.

It has been established that long-chain coding RNA (lncRNA) SLC25A25-AS1 is associated with cancer progression. However, the roles and mechanisms of SLC25A25-AS1 in prostate cancer (PC) have not been reported in the literature. The present study explored the relationship between SLC25A25-AS1 expression and PC progression via comprehensive analysis. The pan-cancer expression of SLC25A25-AS1 was identified using data from The Cancer Genome Atlas (TCGA) database and tissue specimens from our hospital. The expression levels of SLC25A25-AS1 in various subgroups based on the clinical features were identified. The prognostic value of SLC25A25-AS1 and SLC25A25-AS1 co-expressed lncRNAs in PC patients was assessed by survival analysis and ROC analysis, and prognosis-related risk models of SLC25A25-AS1 were constructed. The relationship between SLC25A25-AS1 and the PC immune microenvironment was investigated using correlation analysis. SLC25A25-AS1 expression in PC was significantly increased and correlated with the T stage, clinical stage, Gleason score (GS), and dismal prognosis. SLC25A25-AS1 overexpression exhibited good performance in evaluating the prognosis of PC patients. The area under the curves (AUCs) of the 1-, 3-, and 5-year overall survival (OS) for SLC25A25-AS1 was 1, 0.876, and 0.749. Moreover, the AUCs for the 1-, 3-, and 5-year progress free interval (PFI) for SLC25A25-AS1 were 0.731, 0.701, and 0.718. SLC25A25-AS1 overexpression correlated with the infiltration of CD8 T cells, interstitial dendritic cells (IDC), macrophages and other cells. AC020558.2, ZNF32-AS2, AP4B1-AS1, AL355488.1, AC109460.3, SNHG1, C3orf35, LMNTD2-AS1, and AL365330.1 were significantly associated with SLC25A25-AS1 expression, and short OS and PFI in PC patients. The risk models of the SLC25A25-AS1-related lncRNAs were associated with a dismal prognosis in PC. Overall, SLC25A25-AS1 expression was increased in PC and related to the prognosis and PC immune microenvironment. The risk model of SLC25A25-AS1 have huge prospect for application as prognostic tools in PC.

As part of China’s Tianwen-1 Mars mission, the Mars Surface Composition Detector (MarSCoDe) instrument on the Zhurong rover adopts laser-induced breakdown spectroscopy (LIBS) to perform chemical component detection of the materials on the Martian surface. However, it has always been a challenging issue to achieve high accuracy in LIBS quantification. This study investigated the effect of chemometrics and spectral data preprocessing approaches on LIBS quantification accuracy based on different chemometrics algorithms and diverse preprocessing methods. A total of 2340 LIBS spectra were collected from 39 kinds of geochemical samples by a laboratory duplicate model of the MarSCoDe instrument. The samples and the MarSCoDe laboratory model were placed in a simulated Martian atmosphere environment based on equipment called the Mars-Simulated Detection Environment Experiment Platform (MarSDEEP). To quantify the concentration of MgO in the samples, we employed two common LIBS chemometrics; i.e., partial least squares (PLS) and a back-propagation neural network (BPNN). Meanwhile, in addition to necessary routine preprocessing such as dark subtraction, we used five specific preprocessing approaches, namely intensity normalization, baseline removal, Mg-peak wavelength correction, Mg-peak feature engineering, and concentration range reduction. The results indicated that the performance of the BPNN was better than that of the PLS and that the preprocessing of Mg-peak wavelength correction had the most prominent effect to improve the quantification accuracy. The results of this study are expected to provide inspiration for the processing and analysis of the in situ LIBS data acquired by MarSCoDe on Mars.

An electrochemical transient iodination and coupling reaction has been designed for constructing selenylated 4-anilinocoumarins via the domino reactions of 4-anilinocoumarins and diorganyl diselenides under base-, chemical oxidant- and external electrolyte-free conditions.

RNA modification of m6A/m5C/m1A contributes to the occurrence and development of cancer. Consequently, this study aimed to investigate the functions of m6A/m5C/m1A regulated genes in the prognosis and immune microenvironment of hepatocellular carcinoma (HCC). The expression levels of 45 m6A/m5C/m1A regulated genes in HCC tissues were determined. The functional mechanisms and protein–protein interaction network of m6A/m5C/m1A regulated genes were investigated. The Cancer Genome Atlas (TCGA) HCC gene set was categorized based on 45 m6A/m5C/m1A regulated genes, and survival analysis was used to determine the relationship between the overall survival of HCC patients in subgroups. Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct the risk model and nomogram for m6A/m5C/m1A regulated genes. The relationships between m6A/m5C/m1A regulated gene subsets and risk model and immune cell infiltration were analyzed using CIBERSORT. m6A/m5C/m1A regulated genes were involved in mRNA and RNA modifications, mRNA and RNA methylation, mRNA and RNA stability, and other processes. There was a statistically significant difference between cluster1 and cluster2 groups of genes regulated by m6A/m5C/m1A. The prognosis of cluster1 patients was significantly better than that of cluster2 patients. There were statistically significant differences between the two cluster groups in terms of fustat status, grade, clinical stage, and T stage of HCC patients. The risk model comprised the overexpression of YBX1, ZC3H13, YTHDF1, TRMT10C, YTHDF2, RRP8, TRMT6, LRPPRC, and IGF2BP3, which contributed to the poor prognosis of HCC patients. The high-risk score was associated with prognosis, fustat status, grade, clinical stage, T stage, and M stage and was an independent risk factor for poor prognosis in HCC patients. High-risk score mechanisms included spliceosome, RNA degradation, and DNA replication, among others, and high-risk was closely related to stromal score, CD4 memory resting T cells, M0 macrophages, M1 macrophages, resting mast cells, CD4 memory activated T cells, and follicular helper T cells. In conclusion, the cluster subgroup and risk model of m6A/m5C/m1A regulated genes were associated with the poor prognosis and immune microenvironment in HCC and are expected to be the new tools for assessing the prognosis of HCC patients.

Water-in-oil (W/O) microemulsions exhibit delivery matrix and exhibit poor lipid solubility. Therefore, increasing the stability of W/O microemulsions is necessary to broaden their applications. In our experiment, a protein microemulsion system was constructed and its stability was investigated. The effects of surfactants, co-surfactants, quality ratio of them (Km) and hydrophilic-lipophilic balance (HLB) values were determined by using the pseudo-ternary phase diagrams and the area of microemulsions (MEs) as the indexes. The results showed that MEs’ stability was the best when the limonene was used as oil phase, Tween 20 + span 80 as the surfactant, and anhydrous alcohol as co-surfactant, if and only if HLB = 6.0 and Km = 3:1. Under this condition, the area of micro-emulsion was the largest, and the quality of microemulsion was better when the mass ratio of oil phase and emulsifier was 7:5.The protein microemulsion was a water-in-oil type, with a particle size of 1.41 ± 0.03 μm, containing 1127.37 ± 30.87 μg/g of proteins. Moreover, the temperature, light, and sample observation tests showed that the solution’s protein retention rate was lower than those in the microemulsion. Low-concentration NaCl, less than 9% of glucose and maltose exerted no significant influence on the protein microemulsion stability.

Photon-counting detectors can increase the range of underwater optical wireless communication (UWOC) by enhancing the detection sensitivity and have thus become an active research area in recent years. However, system performance still needs to be improved in the reported underwater photon-counting communication (UPCC) experiments. In this study, a real-time, high-speed UPCC system was designed and experimentally validated based on a single-photon avalanche diode (SPAD). A reliable symbol synchronization method based on pulse-position modulation (PPM) was developed. This method achieved slot synchronization by using a narrow-pulse-width laser and a simple matched filter and realizes frame synchronization through an improved synchronization sequence. In addition, channel errors were corrected by serially concatenated convolutionally coded PPM (SCPPM), and digital signals were processed in real time based on field-programmable gate arrays (FPGAs). Finally, desktop communication experiments were completed at a slot frequency of 25 MHz and a communication rate of 6.21 Mbps. The system exhibited a bit error rate (BER) of less than 10–7, a received optical power of only −84.3 dBm, and an efficiency of 1.35 photons per bit.

Objective To investigate the phototherapy effect of multifunctional nanometer cerium oxide quantum dot (HACQDs-Ce6) on HepG2 cells. Methods The dissolved oxygen analyzer was used to detect the catalytic oxygen production capacity of HACQDs-Ce6. CCK-8 method, scratch test and Calcein AM/PI staining were used to analyze the effects of HACQDs-Ce6 on the proliferation, migration and apoptosis of HepG2 cells. The recombinant mouse macrophage-granulocyte colony stimulating factor (rm GM-CSF) and recombinant mouse interleukin-4 (rm IL-4) were used to induce the differentiation of mouse bone marrow precursor cells into dendritic cells (DC) in vitro to investigate the effect of HACQDs-Ce6 on DC cells. Results HACQDs-Ce6 had catalytic oxygen production capacity. The proliferation activity of cells in the laser group was significantly lower than that in the dark group when the concentration of HACQDs-Ce6 was greater than 0.125 μg/ml (P=0.018). The migration ability of HepG2 cells in HACQDs-Ce6 group was significantly lower than that in the PBS group (P < 0.01). HACQDs-Ce6 almost had no effect on HFF-1/L wnt-3A and DC cells. Calcein AM/PI staining showed that the combined action of HACQDs-Ce6 and PDT killed almost all the HepG2 cells. Conclusion The phototherapy effect of HACQDs-Ce6 on HepG2 cells is obvious, with no damage to HFF-1/L wnt-3A/DC cells.

Abstract Background Longitudinal evidence on change of serum urate level with mortality risk is limited as prior studies have a measurement of serum urate at a single time point. Further, the combined effect of serum urate and systemic inflammation on mortality is unknown. Methods We conducted a prospective cohort study of 152,358 participants (122,045 men and 30,313 women) with repeated measurements of serum urate in 2006, 2008, 2010, and 2012 (107,751 participants had all four measurements of serum urate). We used the Cox proportional hazard model to examine the association between cumulative average and changes in serum urate with mortality. The combined effect of serum urate and systemic inflammation was determined by testing the interaction of serum urate and high-sensitive C-reactive protein (hs-CRP) in relation to mortality risk. Results During a median follow-up of 8.7 (interquartile range 6.3–9.2) years, we identified 7564 all-cause deaths, 1763 CVD deaths, 1706 cancer deaths, and 1572 other deaths. We observed U-shaped relationships of cumulative average serum urate with all-cause mortality, cardiovascular mortality, and other mortalities. Compared with participants with stable serum urate, those with greater increases in serum urate had a 1.7-fold elevated mortality (hazard ratio (HR) = 1.66, 95% confidence interval (CI) = 1.49–1.84), and those with decreased serum urate had a 2-fold elevated mortality risk (HR = 2.14, 95% CI 1.93–2.37). Participants with both hyperuricemia and hs-CRP had 1.6 times higher mortality, compared with those with low serum urate and hs-CRP levels (HR = 1.56, 95% CI 1.37–1.76). Conclusions We observed a U-shaped relationship of long-term cumulative average serum urate with all-cause mortality, cardiovascular mortality, and other mortalities. Compared with participants with relatively stable serum urate levels, a greater increase or decrease in serum urate was associated with elevated mortality. Participants with both hyperuricemia and high systemic inflammation had the greatest mortality risk compared with those with low serum urate and low hs-CRP levels.

Chronic fluoride exposure from drinking water may result in endemic fluorosis. To better understand the mechanisms by which some people are resistant to fluorosis, here we investigated the effect of treatment with NaF (sodium fluoride) on production of reactive oxygen species (ROS), morphological changes in mitochondria, the mRNA expression of Fas ligand (Fas‐L), and the protein expression of cleaved caspase‐3 in regular L‐929 cells and fluoride‐resistant (FR) L‐929 cells. While morphological changes indicative of apoptosis and a network of fragmented mitochondria were observed in regular L‐929 cells after NaF treatment, there were no morphological changes in FR L‐929 cells after NaF treatment. Treatment with 10 mm NaF induced a significant difference in the production of ROS, triggered the expression of cleaved caspase‐3, and upregulated the mRNA expression of Fas‐L in regular L‐929 cells. However, there was no significant production of ROS in FR L‐929 cells. Additionally, cleaved caspase‐3 and upregulated Fas‐L were not detected in FR L‐929 cells. These results suggest that FR fibroblasts are resistant to oxidative stress and apoptosis induced by fluoride.

Artificial nanostructures with large optical chiral responses have been intensively investigated recently. In this work, we propose a diffractive circular dichroism enhancement technique using stereoscopic plasmonic molecule structures. According to the multipole expansion analysis, the z-component of the electric dipole becomes the dominant chiral scattering mechanism during the interaction between an individual plasmonic molecule and the plane wave at a grazing angle. For a periodical structure with the designed plasmonic molecule, large diffractive circular dichroism can be obtained, which can be associated with the Wood–Rayleigh anomaly. Such a diffractive circular dichroism enhancement is verified by the good agreement between numerical simulations and experimental results. The proposed approach can be potentially used to develop enhanced spectroscopy techniques to measure chiral information, which is very important for fundamental physical and chemical research and bio-sensing applications.

Rhizobia inoculation is widely used in legumes to improve the yield and quality of forage. However, the symbiotic interactions of different legumes are specific. The search for efficient strains plays an important role in legume forage and in practical production. In this study, Desmodium intortum was first inoculated with rhizobia from different regions, and then the production traits, nutritional quality, and fermentation of D. intortum in the rumen were evaluated according to the rhizobia strains. The results showed that, compared with the control, inoculation with different rhizobia strains significantly increased the number of nodules, shoot fresh weight, crude protein content, plant protein yield, and ether extract content of D. intortum, and inoculation with the R3 strain (Bradyrhizobium elkanii) increased these values by 61.0%, 29.6%, 16.1%, 62.9%, and 30.4%, respectively. In the basal diet of Pennisetum purpureum Rich. × P. americana King grass cv. Reyan No.4, D. intortum inoculated with different rhizobia was added (75:25), and the combination of the inoculated R3 and R5 strains increased the rumen’s ammonia-nitrogen (NH3-N) levels and in vitro dry matter digestibility (IVDMD): R3 increased the contents of NH3-N and IVDMD by 50.1% and 12.3%, respectively, while R5 increased them by 50.9% and 15.4%, respectively. Based on a comprehensive evaluation through principal component analysis, R3 was ranked first overall. These results support the development of competitive inoculants from indigenous strains as a strategy to improve the nutritional value of D. intortum and ruminal fermentation.

Photon-counting LiDAR can obtain long-distance, high-precision target3D geographic information, but extracting high-precision signal photons from background noise photons is the key premise of photon-counting LiDAR data processing and application. This study proposes an adaptive noise filtering algorithm that adjusts parameters according to the background photon count rate and removes noise photons based on the local mean Euclidean distance. A simulated photon library that provides different background photon count rates and detection probabilities was constructed. It was then used to fit the distribution relationship between the background photon count rate and the average KNN (K-Nearest Neighbor) distance (k = 2–6) and to obtain the optimal denoising threshold under different background photon count rates. Finally, the proposed method was evaluated by comparing it with the modified density-based spatial clustering (mDBSCAN) and local distance-based statistical methods. The experimental results show that various methods are similar when the background noise rate is high. However, at most non-extreme background photon count rate levels, the F of this algorithm was maintained between 0.97–0.99, which is an improvement over other classical algorithms. The new strategy eliminated the artificial introduction of errors. Due to its low error rates, the proposed method can be widely applied in photon-counting LiDAR signal extraction under various conditions.

A Mars Surface Composition Detector (MarSCoDe) instrument mounted on Zhurong rover of Tianwen-1, adopts Laser-Induced Breakdown Spectroscopy (LIBS), with no sample preparation or dust and coatings ablation required, to conduct rapid multi-elemental analysis and characterization of minerals, rocks and soils on the surface of Mars. To test the capability of MarSCoDe LIBS measurement and quantitative analysis, some methods of multivariate analysis on olivine samples with gradient concentrations were inspected based on the spectra acquired in a Mars-simulated environment before the rover launch in 2020. Firstly, LIBS spectra need preprocessing, including background subtraction, random signal denoising, continuum baseline removal, spectral drift correction and wavelength calibration, radiation calibration, and multi-channel spectra subset merging. Then, the quantitative analysis with univariate linear regression (ULR) and multivariate linear regression (MLR) are performed on the characteristic lines, while principal component regression (PCR), partial least square regression (PLSR), ridge, least-absolute-shrinkage-and-selection-operator (LASSO) and elastic net, and nonlinear analysis with back-propagation (BP) are conducted on the entire spectral information. Finally, the performance on the quantitative olivine analyzed by MarSCoDe LIBS is compared with the mean spectrum and all spectra for each sample and evaluated by some statistical indicators. The results show that: (1) the calibration curve of ULR constructed by the characteristic line of magnesium and iron indicates the linear relationship between the spectral signal and the element concentration, and the limits of detection of forsterite and fayalite is 0.9943 and 2.0536 (c%) analyzed by mean spectra, and 2.3354 and 3.8883 (c%) analyzed by all spectra; (2) the R2 value on the calibration and validation of all the methods is close to 1, and the predicted concentration estimated by these calibration models is close to the true concentration; (3) the shrinkage or regularization technique of ridge, LASSO and elastic net perform better than the ULR and MLR, except for ridge overfitting on the testing sample; the best results can be obtained by the dimension reduction technique of PCR and PLSR, especially with PLSR; and BP is more applicable for the sample measured with larger spectral dataset.

The Mars Surface Composition Detector (MarSCoDe) carried by the Zhurong rover of China’s Tianwen-1 mission uses Laser-Induced Breakdown Spectroscopy (LIBS) to detect and analyze the material composition on Martian surfaces. As one extraterrestrial remote LIBS system, it is necessary to adopt effective and reliable preprocessing methods to correct the spectral drift caused by the changes in environmental conditions, to ensure the analysis accuracy of LIBS scientific data. This paper focuses on the initial spectral drift correction and estimates the accuracy of on-board wavelength calibration on the LIBS calibration target measured by the MarSCoDe LIBS. There may be two cases during the instrument launch and landing, as well as the long-term operation: (a) the initial wavelength calibration relationship can still apply to the on-board LIBS measurement; and (b) the initial wavelength calibration relationship has been changed, and a new on-board calibration is needed to establish the current relationship. An approach of matching based on global iterative registration (MGR) is presented in respect to case (a). It is also compared with the approach of particle swarm optimization (PSO) for case (b). Furthermore, their accuracy is estimated with the comparison to the National Institute of Standards and Technology (NIST) database. The experimental results show that the proposed approach can effectively correct the drift of the on-board LIBS spectrum. The the root-mean-square error (RMSE) of the internal accord accuracy for three channels is 0.292, 0.223 and 0.247 pixels, respectively, compared with the corrected Ti-alloy spectrum and the NIST database, and the RMSE of the external accord accuracy is 0.232, 0.316 and 0.229 pixels, respectively, for other samples. The overall correction accuracy of the three channels is better than one-third of the sampling interval.

Laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics is an efficient method for rock identification and classification, which has considerable potential in planetary geology. A great challenge facing the LIBS community is the difficulty to accurately discriminate rocks with close chemical compositions. A convolutional neural network (CNN) model has been designed in this study to identify twelve types of rock, among which some rocks have similar compositions. Both the training set and the testing set are constructed based on the LIBS spectra acquired by Mars Surface Composition Detector (MarSCoDe) for China’s Tianwen-1 Mars exploration mission. All the spectra were collected from dedicated rock pellet samples, which were placed in a simulated Martian atmospheric environment. The classification performance of the CNN has been compared with that of three alternative machine learning algorithms, i.e., logistic regression (LR), support vector machine (SVM), and linear discriminant analysis (LDA). Among the four methods, it is on the CNN model that the highest classification correct rate has been obtained, as assessed by precision score, recall score, and the harmonic mean of precision and recall. Furthermore, the classification accuracy is inspected more quantitatively via Brier score, and the CNN is still the best performing model. The results demonstrate that the CNN-based chemometrics are an efficient tool for rock identification with LIBS spectra collected in a simulated Martian environment. Despite the relatively small sample set, this study implies that CNN-supported LIBS classification is a promising analytical technique for Tianwen-1 Mars mission and more planetary explorations in the future.