A Novel Strategy to Reconstruct NDVI Time-Series with High Temporal Resolution from MODIS Multi-Temporal Composite Products

Vegetation indices (VIs) data derived from satellite imageries play a vital role in land surface vegetation and dynamic monitoring. Due to the excessive noises (e.g., cloud cover, atmospheric contamination) in daily VI data, temporal compositing methods are commonly used to produce composite data to minimize the negative influence of noise over a given compositing time interval. However, VI time series with high temporal resolution were preferred by many applications such as vegetation phenology and land change detections. This study presents a novel strategy named DAVIR-MUTCOP (DAily Vegetation Index Reconstruction based on MUlti-Temporal COmposite Products) method for normalized difference vegetation index (NDVI) time-series reconstruction with high temporal resolution. The core of the DAVIR-MUTCOP method is a combination of the advantages of both original daily and temporally composite products, and selecting more daily observations with high quality through the temporal variation of temporally corrected composite data. The DAVIR-MUTCOP method was applied to reconstruct high-quality NDVI time-series using MODIS multi-temporal products in two study areas in the continental United States (CONUS), i.e., three field experimental sites near Mead, Nebraska from 2001 to 2012 and forty-six AmeriFlux sites evenly distributed across CONUS from 2006 to 2010. In these two study areas, the DAVIR-MUTCOP method was also compared to several commonly used methods, i.e., the Harmonic Analysis of Time- Series (HANTS) method using original daily observations, Savitzky–Golay (SG) filtering using daily observations with cloud mask products as auxiliary data, and SG filtering using temporally corrected composite data. The results showed that the DAVIR-MUTCOP method significantly improved the temporal resolution of the reconstructed NDVI time series. It performed the best in reconstructing NDVI time-series across time and space (coefficient of determination (R2 = 0.93 ~ 0.94) between reconstructed NDVI and ground-observed LAI). DAVIR-MUTCOP method presented the highest robustness and accuracy with the change of the filtering parameter (R2 = 0.99 ~ 1.00, bias = 0.001, root mean square error (RMSE) = 0.020). Only MODIS data were used in this study; nevertheless, the DAVIR-MUTCOP method proposed a universal and potential way to reconstruct daily time series of other VIs or from other operational sensors, e.g., AVHRR and VIIRS

Assessing the Impact of Nuclear Mass Models on the Prediction of Synthesis Cross Sections for Superheavy Elements

Within the framework of the dinuclear system model, this study delves into the impact of various nuclear mass models on evaluating the fusion probability of superheavy nuclei. Nuclear mass models, as crucial inputs to the DNS model, exhibit slight variations in binding energy, quadrupole deformation, and extrapolation ability; these subtle differences can significantly influence the model's outcomes. Specifically, the study finds that nuclear mass plays a pivotal role in determining fusion probability, and Q-value. By numerically solving a set of master equations, the study examines how binding energies from different mass models affect the fusion probability of colliding nuclei, taking the example of $^{48}$Ca + $^{243}$Am $\rightarrow$ $^{291}$Mc. A careful analysis of the potential energy surface (PES) reveals that the inner fusion barriers lead to variations in fusion probabilities. Importantly, the study demonstrates that the synthesis cross sections of superheavy nuclei calculated using different nuclear mass models align well with experimental data, falling within an error range of one order of magnitude. This finding underscores the reliability of our model predictions. Looking ahead, the study utilizes five distinct nuclear mass models to predict the synthesis cross sections of superheavy elements 119 and 120, along with their associated uncertainties. These predictions offer valuable insights into the feasibility of synthesizing these elusive elements and pave the way for future experimental explorations

Retinal nerve fiber layer thickness measured by optical coherence tomography in Chinese teenagers aged from 13 years old to 18 years old

AIM: To establish a reference range of retinal nerve fiber layer(RNFL)thickness by optical coherence tomography(OCT)in Chinese teenagers aged from 13 to 18 years old, and investigate its relationship with age, eye side, gender, and ethnic group.<p>METHODS: A total of 402 eyes from 201 normal Chinese aged from 13 to 18 years old were recruited for this study. Optic disk with 3.4mm diameter circle in different global average, quadrant and part-time bit retinal nerve fiber layer thickness(RNFLT)was measured by RNFL thickness average analysis program. Their RNFLT at different part-time bit, quadrant and global average RNFLT around the disc were measured by OCT with 3.4mm diameter circle, using the RNFL thickness average analysis program. The data was analyzed with SPSS statistical 19.0. The influences of several factors(such as age, eye side, gender, and ethnic group)on RNFLT were also analyzed.<p>RESULTS: The global average RNFLT at 13, 14, 15, 16, 17, 18 years old was 108.32±9.42μm, 109.23±9.67μm, 110.36±11.14μm, 111.27±10.21μm, 109.23±9.67μm, 112.11±8.83μm respectively. RNFLT of right eyes was 109.82±8.93μm and of left eyes was 110.33±9.89μm. All of the male's average RNFLT was 110.14±10.02μm, and all of the female's average RNFLT was 109.96±11.22μm. The average RNFLT of Han nationality was 110.22±9.31μm and of non-Han nationality was 109.87±8.65μm. The average RNFLT of all was 110.02±9.87μm, the RNFLT at the superior, nasal, inferior and temporal quadrant was 146.56 ±18.88μm, 76.49±13.28μm, 136.64±16.29μm, 82.01±12.55μm respectively. There was no significant difference in gender, eye side, and ethnic group(all <i>P</i><0.05), but the difference was significant compared with adult's data of the database. <p>CONCLUSION: This study has established a normal standard reference of RNFLT and its related indexes by OCT in Chinese teenagers aged 13-18 years old. Gender, age, eye side, and ethnic group have no effect on their RNFLT, which has significant difference with adult's data. And for the diagnosis and follow-up of diseases involving in RNFL changes, the adult's data can not be used

LGBMDF: A cascade forest framework with LightGBM for predicting drug-target interactions

Prediction of drug-target interactions (DTIs) plays an important role in drug development. However, traditional laboratory methods to determine DTIs require a lot of time and capital costs. In recent years, many studies have shown that using machine learning methods to predict DTIs can speed up the drug development process and reduce capital costs. An excellent DTI prediction method should have both high prediction accuracy and low computational cost. In this study, we noticed that the previous research based on deep forests used XGBoost as the estimator in the cascade, we applied LightGBM instead of XGBoost to the cascade forest as the estimator, then the estimator group was determined experimentally as three LightGBMs and three ExtraTrees, this new model is called LGBMDF. We conducted 5-fold cross-validation on LGBMDF and other state-of-the-art methods using the same dataset, and compared their Sn, Sp, MCC, AUC and AUPR. Finally, we found that our method has better performance and faster calculation speed

Global exponential stability of impulsive high-order Hopfield typeneural networks with delays

AbstractIn this paper, we investigate the global exponential stability of impulsive high-order Hopfield type neural networks with delays. By establishing the impulsive delay differential inequalities and using the Lyapunov method, two sufficient conditions that guarantee global exponential stability of these networks are given, and the exponential convergence rate is also obtained. A numerical example is given to demonstrate the validity of the results

PbZrO3-Based Antiferroelectric Thin Film Capacitors with High Energy Storage Density

A series of 400-nm-thick sandwich structured Pb(1+x)ZrO3/(Pb,Eu)ZrO3/Pb(1+x)ZrO3(PZO/PEZO/PZO) antiferro-electric thin films with different Pb excess content (x) (x=0%, 10%, 20%, and 30%) in the PZO precursors have been successfully deposited on Pt(111)/Ti/SiO2/Si substrates by a sol–gel method. The effects of Pb excess content on the dielectric properties, and energy storage performance of the PZO/PEZO/PZO thin films have been investigated in detail. It is found that all the films show a unique perovskite phase structure. With increasing Pb excess content in the PZO precursors, P-E hysteresis loop changes from slanted to square shape. Meanwhile, a larger antiferroelectric to ferroelectric switching field (EAF) and ferroelectric to antiferroelectric switching field (EFA) are observed in the films with higher Pb excess content. When increasing Pb excess content from 0% to 30%, the energy storage density of the sandwich structured films is remarkably improved from 11.4 to 14.8 J/cm3 at 1000 kV/cm

Experimental Long-Distance Decoy-State Quantum Key Distribution Based On Polarization Encoding

We demonstrate the decoy-state quantum key distribution (QKD) with one-way quantum communication in polarization space over 102km. Further, we simplify the experimental setup and use only one detector to implement the one-way decoy-state QKD over 75km, with the advantage to overcome the security loopholes due to the efficiency mismatch of detectors. Our experimental implementation can really offer the unconditionally secure final keys. We use 3 different intensities of 0, 0.2 and 0.6 for the pulses of source in our experiment. In order to eliminate the influences of polarization mode dispersion in the long-distance single-mode optical fiber, an automatic polarization compensation system is utilized to implement the active compensation.Comment: 4 pages,3 figure

Nonreciprocal charge transport in the titanium sesquioxide heterointerface superconductor

Nonreciprocal charge transport in heterostructural superconductors exhibits appealing quantum physical phenomena and holds the promising potential for superconducting circuits applications. Realizing a nonreciprocity is, however, fundamentally and technologically challenging, as it requires a material structure without a centre of inversion, which is scarce among superconducting materials. Here, we report an evidence of helical superconductivity, in which the Rashba spin-orbit coupling induces momentum-dependent superconducting gap in the inversion symmetry breaking heterointerface superconductor consisting of Mott insulating Ti$_2$O$_3$ and polar semiconducting GaN. Remarkably, the nonlinear responses emerge in the superconducting transition regime, when the magnetic field is precisely aligned in-plane orientations perpendicular to the applied current. In particular, the observed nonreciprocal supercurrent is extremely sensitive to the direction of the magnetic field for 0.5 degree, suggestive of a crossover from a symmetry breaking state to a symmetric one. Our finding not only unveils the underlying rich physical properties in heterointerface superconductors, but also provides an exciting opportunity for the development of novel mesoscopic superconducting devices