Nonlinear Spectral Mixture Modeling of Lunar Multispectral: Implications for Lateral Transport

Linear and nonlinear spectral mixture models applied to Clementine multispectral images of the Moon result in roughly similar spatial distributions of endmember abundances. However, there are important differences in the absolute values of the predicted abundances. The magnitude of these differences and the implications for understanding geological processes are investigated across a geologic contact between mare and highland in the Grimaldi Basin on the western nearside of the Moon. Vertical and lateral mass transport due to impact cratering has redistributed mare and highland materials across the contact, creating a gradient in composition. Solutions to linear and nonlinear spectral mixture models for identical spectral endmembers of mare, highland, and fresh crater materials are compared across this simple geologic contact in the Grimaldi Basin. Profiles of mare abundance across the contact are extracted and compared quantitatively. Profiles from the linear mixture models indicate that the geologic contact has an average mare abundance of 60%, and the compositional boundary is asymmetric with more mare transported onto the highland side of the contact than highland onto the mare side of the contact. In contrast the nonlinear abundance profiles indicate that the geologic contact has an average mare abundance of 50%, and the compositional boundary is remarkably symmetric. Given the expectation that materials will be intimately mixed on the surface of the Moon, and that the asymmetries implied by the linear model are not consistent with our understanding of lunar surface processes, the nonlinear spectral mixture model is preferred and should be applied whenever quantitative abundance information is required. The remarkable symmetry in the compositional gradients across this contact indicate that lateral mass transport dominates over vertical transport at this boundary

MSS-DepthNet: Depth Prediction with Multi-Step Spiking Neural Network

Event cameras are considered to have great potential for computer vision and robotics applications because of their high temporal resolution and low power consumption characteristics. However, the event stream output from event cameras has asynchronous, sparse characteristics that existing computer vision algorithms cannot handle. Spiking neural network is a novel event-based computational paradigm that is considered to be well suited for processing event camera tasks. However, direct training of deep SNNs suffers from degradation problems. This work addresses these problems by proposing a spiking neural network architecture with a novel residual block designed and multi-dimension attention modules combined, focusing on the problem of depth prediction. In addition, a novel event stream representation method is explicitly proposed for SNNs. This model outperforms previous ANN networks of the same size on the MVSEC dataset and shows great computational efficiency

Genetic analysis of phytoene synthase 1 (Psy1) gene function and regulation in common wheat

Transcriptome details for three transgenic lines with the most significantly reduced YPC and non-transformed controls. (DOCX 18 kb

A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems

Neuromorphic electronics, an emerging field that aims for building electronic mimics of the biological brain, holds promise for reshaping the frontiers of information technology and enabling a more intelligent and efficient computing paradigm. As their biological brain counterpart, the neuromorphic electronic systems are complex, having multiple levels of organization. Inspired by David Marr's famous three-level analytical framework developed for neuroscience, the advances in neuromorphic electronic systems are selectively surveyed and given significance to these research endeavors as appropriate from the computational level, algorithmic level, or implementation level. Under this framework, the problem of how to build a neuromorphic electronic system is defined in a tractable way. In conclusion, the development of neuromorphic electronic systems confronts a similar challenge to the one neuroscience confronts, that is, the limited constructability of the low-level knowledge (implementations and algorithms) to achieve high-level brain-like (human-level) computational functions. An opportunity arises from the communication among different levels and their codesign. Neuroscience lab-on-neuromorphic chip platforms offer additional opportunity for mutual benefit between the two disciplines

Predictive value of SII and sd-LDL for contrast-induced acute kidney injury in STEMI patients undergoing percutaneous coronary intervention

Aim: To investigate the relationship between the incidence of contrast-induced acute kidney injury (CI-AKI) and the level of small dense low-density lipoprotein (sd-LDL) and systemic immune-inflammation index (SII) in patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing emergency percutaneous coronary intervention (PCI), and to further compare the predictive values of SII, sd-LDL and their combination for CI-AKI. Methods: A total of 674 patients were assigned to a training and a validation cohort according to their chronological sequence. The baseline characteristics of the 450 patients in the training cohort were considered as candidate univariate predictors of CI-AKI. Multivariate logistic regression was then used to identify predictors of CI-AKI and develop a prediction model. The predictive values of SII, sd-LDL and their combination for CI-AKI were also evaluated. Results: Multivariate logistic regression analysis showed that age, left ventricular ejection fraction (LVEF), sd-LDL, uric acid, estimated glomerular filtration rate (eGFR) and SII were predictors of CI-AKI. The area under the curve (AUC) of the prediction model based on the above factors was 0.846 [95% confidence interval (CI) 0.808–0.884], and the Hosmer-Lemeshow test (P = 0.587, χ2 = 6.543) proved the goodness of fit of the model. The AUC combining SII with sd-LDL to predict CI-AKI was 0.785 (95% CI 0.735–0.836), with a sensitivity of 72.8% and a specificity of 79.8%, and was statistically significant when compared with SII and sd-LDL, respectively. The predictive efficiency of combining SII with sd-LDL and SII were evaluated by improved net reclassification improvement (NRI, 0.325, P < 0.001) and integrated discrimination improvement (IDI, 0.07, P < 0.001). Conclusions: Both SII and sd-LDL can be used as predictors of CI-AKI in STEMI patients undergoing emergency PCI, and their combination can provide more useful value for early assessment of CI-AKI

Applications of shallow reflection seismology.

Shallow seismic investigations were conducted at two sites in the Central Appalachian foreland area of West Virginia. Various seismic sources (EWG, primacord, shotgun, and sledge hammer) were used and compared. At one site, data were collected to investigate the effect of longwall mining on the overburden seismic properties. Expanded spread and common offset (CO) data were collected over active panels at different stages of mining. At a second site, EWG is evaluated using common midpoint (CMP) and CO sorting. The emplacement of longwall panels produced various seismically observable effects. Velocity reduction (VR) and signal absorption (SA) zones appear over both shallow ({dollar}\\sim{dollar}120 feet) and deeper ({dollar}\\sim{dollar}650 feet) mine sites. VR zones are produced in the cover in unmined areas in advance of the panel face. The dynamic SA zone was not observed during mining. The dynamic angle defined by VR envelope appears to correlate with dewatering of ground water in advance of the panel face. The results indicate that seismic event appearance and continuity in CO can be used to indicate the presence of voids, abnormally fractured areas, and stratigraphic variability in the mine overburden. Mining induced seismic velocity reductions are observed in different intervals of the overburden. The mining induced first arrival delays and reflection arrival times from strata immediately over the mined seam do not correlate directly with subsidence measurement at the surface. However, reflection arrival time delays from a strong unit located at a neutral position within the cover do correlate with the measurement. Delay time variation measured in strata immediately above the panel correlates with the roof caving geometry studies by the mining engineers. Shallow EWG seismic application is also evaluated in this study. EWG provided reflections from reflectors several thousand feet deep. It was used to make comparisons between CO and CMP data acquisition procedures. The comparisons indicate that CO data provide more accurate subsurface information than the traditional CMP. Synthetic seismogram indicates that seismic wavelet is significantly non-stationary. The predicted seismic response matches the CO data better than the CMP data

Evaluating the Sustainable Traffic Flow Operational Features of U-turn Design with Advance Left Turn

Median U-turn intersection treatment (MUIT) has been considered as an alternative measure to reduce congestion and traffic conflict at intersection areas, but the required spacing between the U-turn opening and the intersection limits its applicability. In this paper, a U-turn design with Advance Left Turn (UALT) is proposed with the aim of addressing the disadvantages of insufficient intersection spacing and difficulty in the continuous vehicle lane change. UALT provides a dedicated lane to advance the turning vehicle out of the intersection and directly to the U-turn opening without interacting with through traffic. The effectiveness and traffic volume applicability of UALT was demonstrated through field data investigation, simulation and analysis with VISSIM software. The proposed design was evaluated in terms of three parameters: delay, queue length and the number of stops. The results show that when the traffic volume range of the main road is (1900, 2200) pcu/h and the traffic volume of the secondary road is more than 900 pcu/h, the optimization effect of UALT on both conventional intersections and MUIT is very significant. Taking a signal-controlled intersection in Zhengzhou City, China, as an example to build a simulation model, compared with the conventional intersection and MUIT, the delay drop is reduced by 73.48% and 41.48%, the queue length is reduced by 84.85% and 41.66%, and the operation efficiency is significantly improved

Evaluating the Sustainable Traffic Flow Operational Features of U-turn Design with Advance Left Turn

Median U-turn intersection treatment (MUIT) has been considered as an alternative measure to reduce congestion and traffic conflict at intersection areas, but the required spacing between the U-turn opening and the intersection limits its applicability. In this paper, a U-turn design with Advance Left Turn (UALT) is proposed with the aim of addressing the disadvantages of insufficient intersection spacing and difficulty in the continuous vehicle lane change. UALT provides a dedicated lane to advance the turning vehicle out of the intersection and directly to the U-turn opening without interacting with through traffic. The effectiveness and traffic volume applicability of UALT was demonstrated through field data investigation, simulation and analysis with VISSIM software. The proposed design was evaluated in terms of three parameters: delay, queue length and the number of stops. The results show that when the traffic volume range of the main road is (1900, 2200) pcu/h and the traffic volume of the secondary road is more than 900 pcu/h, the optimization effect of UALT on both conventional intersections and MUIT is very significant. Taking a signal-controlled intersection in Zhengzhou City, China, as an example to build a simulation model, compared with the conventional intersection and MUIT, the delay drop is reduced by 73.48% and 41.48%, the queue length is reduced by 84.85% and 41.66%, and the operation efficiency is significantly improved