Comparison of modeled backscatter with SAR data at P-band

In recent years several analytical models were developed to predict microwave scattering by trees and forest canopies. These models contribute to the understanding of radar backscatter over forested regions to the extent that they capture the basic interactions between microwave radiation and tree canopies, understories, and ground layers as functions of incidence angle, wavelength, and polarization. The Santa Barbara microwave model backscatter model for woodland (i.e. with discontinuous tree canopies) combines a single-tree backscatter model and a gap probability model. Comparison of model predictions with synthetic aperture radar (SAR) data and L-band (lambda = 0.235 m) is promising, but much work is still needed to test the validity of model predictions at other wavelengths. The validity of the model predictions at P-band (lambda = 0.68 m) for woodland stands at our Mt. Shasta test site was tested

Influence of Summer Biogeography on Wood Warbler Stopover Abundance

We evaluated the effect of summer biogeography of migrant wood warblers (Parulidae) on their stopover abundance. To characterize abundance patterns, we used mistnet capture data from spring and fall migration in the Middle Rio Grande Valley, New Mexico, spring migration on the Gulf Coast of Louisiana, and fall migration on the Gulf Coast of Alabama. To describe the summer biogeography of 47 species of wood warblers, we used indices of their summer range size, their summer density, and distance between their summer ranges and our netting sites. Multiple linear regressions indicated that biogeographic indices explained 55% and 49% of variation in captures in the Middle Rio Grande Valley during spring and fall, respectively. On the Gulf Coast these regressions explained 25% of the variation during spring at the Louisiana site and 51% during fall at the Alabama site. Both summer range size and distance between the summer range and study sites explained significant portions of the variation in three of the four analyses. Interestingly, the importance of biogeographic factors was least evident among spring migrants along the Gulf Coast of Louisiana. The difference between this site and other sites may reflect differences between migrants arriving after a Gulf crossing and those migrating across continental land masses or possibly an increased importance of winter biogeography for migrants crossing the Gulf of Mexico in the spring. In general, these results indicate that abundance of migrant warblers at our netting sites in both the eastern and western United States during spring and fall migration were influenced by summer biogeography. Consequently, we suggest including biogeographic analyses in assessments of conservation priorities for local stopover sites

Relating P-band AIRSAR backscatter to forest stand parameters

As part of research on forest ecosystems, the Jet Propulsion Laboratory (JPL) and collaborating research teams have conducted multi-season airborne synthetic aperture radar (AIRSAR) experiments in three forest ecosystems including temperate pine forest (Duke, Forest, North Carolina), boreal forest (Bonanza Creek Experimental Forest, Alaska), and northern mixed hardwood-conifer forest (Michigan Biological Station, Michigan). The major research goals were to improve understanding of the relationships between radar backscatter and phenological variables (e.g. stand density, tree size, etc.), to improve radar backscatter models of tree canopy properties, and to develop a radar-based scheme for monitoring forest phenological changes. In September 1989, AIRSAR backscatter data were acquired over the Duke Forest. As the aboveground biomass of the loblolly pine forest stands at Duke Forest increased, the SAR backscatter at C-, L-, and P-bands increased and saturated at different biomass levels for the C-band, L-band, and P-band data. We only use the P-band backscatter data and ground measurements here to study the relationships between the backscatter and stand density, the backscatter and mean trunk dbh (diameter at breast height) of trees in the stands, and the backscatter and stand basal area

Seg2Reg: Differentiable 2D Segmentation to 1D Regression Rendering for 360 Room Layout Reconstruction

State-of-the-art single-view 360-degree room layout reconstruction methods formulate the problem as a high-level 1D (per-column) regression task. On the other hand, traditional low-level 2D layout segmentation is simpler to learn and can represent occluded regions, but it requires complex post-processing for the targeting layout polygon and sacrifices accuracy. We present Seg2Reg to render 1D layout depth regression from the 2D segmentation map in a differentiable and occlusion-aware way, marrying the merits of both sides. Specifically, our model predicts floor-plan density for the input equirectangular 360-degree image. Formulating the 2D layout representation as a density field enables us to employ `flattened' volume rendering to form 1D layout depth regression. In addition, we propose a novel 3D warping augmentation on layout to improve generalization. Finally, we re-implement recent room layout reconstruction methods into our codebase for benchmarking and explore modern backbones and training techniques to serve as the strong baseline. Our model significantly outperforms previous arts. The code will be made available upon publication

Management of Refractory/Aggressive Pituitary Adenomas Review of Current Treatment Options

Tumors of central nervous system (CNS) account for a small portion of tumors of human body, which includes tumors occurring in the parenchyma of brain and spinal cord as well as their coverings. This chapter covers some new development in some major brain tumors in both pediatric and adult populations, as well as some uncommon but diagnostic and management challenging tumors

Subgroup analysis of ICARIA-MM study in relapsed/refractory multiple myeloma patients with high-risk cytogenetics

Treatment benefit in multiple myeloma (MM) patients with high-risk cytogenetics remains suboptimal. The phase 3 ICARIA-MM trial (NCT02990338) showed that isatuximab plus pomalidomide-dexamethasone prolongs median progression-free survival (mPFS) in patients with relapsed/refractory MM (RRMM). This subgroup analysis of ICARIA-MM compared the benefit of isatuximab in high-risk [defined by the presence of del(17p), t(4;14) or t(14;16)] versus standard-risk patients. The efficacy of isatuximab in patients with gain(1q21) abnormality was also assessed in a retrospective subgroup analysis. In ICARIA-MM, 307 patients received isatuximab-pomalidomide-dexamethasone (n = 154) or pomalidomide-dexamethasone (n = 153). Isatuximab (10 mg/kg intravenously) was given weekly in the first 28-day cycle, and every other week thereafter. Standard pomalidomide-dexamethasone doses were given. Isatuximab-pomalidomide-dexamethasone improved mPFS (7 center dot 5 vs 3 center dot 7 months; HR, 0 center dot 66; 95% CI, 0 center dot 33-1 center dot 28) and overall response rate (ORR, 50 center dot 0% vs 16 center dot 7%) in high-risk patients. In patients with isolated gain(1q21), isatuximab addition improved mPFS (11 center dot 2 vs 4 center dot 6 months; HR, 0 center dot 50; 95% CI, 0 center dot 28-0 center dot 88) and ORR (53 center dot 6% vs 27 center dot 6%). More grade >= 3 adverse events occurred in high-risk patients receiving isatuximab (95 center dot 7%) versus the control group (67 center dot 6%); however, isatuximab did not increase events leading to discontinuation or treatment-related mortality. Isatuximab-pomalidomide-dexamethasone provides a consistent benefit over pomalidomide-dexamethasone treatment in RRMM patients regardless of cytogenetic risk

High invertase activity in tomato reproductive organs correlates with enhanced sucrose import into, and heat tolerance of, young fruit

Heat stress can cause severe crop yield losses by impairing reproductive development. However, the underlying mechanisms are poorly understood. We examined patterns of carbon allocation and activities of sucrose cleavage enzymes in heat-tolerant (HT) and -sensitive (HS) tomato (Solanum lycopersicum L.) lines subjected to normal (control) and heat stress temperatures. At the control temperature of 25/20 °C (day/night) the HT line exhibited higher cell wall invertase (CWIN) activity in flowers and young fruits and partitioned more sucrose to fruits but less to vegetative tissues as compared to the HS line, independent of leaf photosynthetic capacity. Upon 2-, 4-, or 24-h exposure to day or night temperatures of 5 °C or more above 25/20 °C, cell wall (CWIN) and vacuolar invertases (VIN), but not sucrose synthase (SuSy), activities in young fruit of the HT line were significantly higher than those of the HS line. The HT line had a higher level of transcript of a CWIN gene, Lin7, in 5-day fruit than the HS line under control and heat stress temperatures. Interestingly, heat induced transcription of an invertase inhibitor gene, INVINH1, but reduced its protein abundance. Transcript levels of LePLDa1, encoding phospholipase D, which degrades cell membranes, was less in the HT line than in the HS line after exposure to heat stress. The data indicate that high invertase activity of, and increased sucrose import into, young tomato fruit could contribute to their heat tolerance through increasing sink strength and sugar signalling activities, possibly regulating a programmed cell death pathway

6G Network AI Architecture for Everyone-Centric Customized Services

Mobile communication standards were developed for enhancing transmission and network performance by using more radio resources and improving spectrum and energy efficiency. How to effectively address diverse user requirements and guarantee everyone's Quality of Experience (QoE) remains an open problem. The Sixth Generation (6G) mobile systems will solve this problem by utilizing heterogenous network resources and pervasive intelligence to support everyone-centric customized services anywhere and anytime. In this article, we first coin the concept of Service Requirement Zone (SRZ) on the user side to characterize and visualize the integrated service requirements and preferences of specific tasks of individual users. On the system side, we further introduce the concept of User Satisfaction Ratio (USR) to evaluate the system's overall service ability of satisfying a variety of tasks with different SRZs. Then, we propose a network Artificial Intelligence (AI) architecture with integrated network resources and pervasive AI capabilities for supporting customized services with guaranteed QoEs. Finally, extensive simulations show that the proposed network AI architecture can consistently offer a higher USR performance than the cloud AI and edge AI architectures with respect to different task scheduling algorithms, random service requirements, and dynamic network conditions