New Mexico pecan production

Presented at Urbanization of irrigated land and water transfers: a USCID water management conference on May 28-31, 2008 in Scottsdale, Arizona.Includes bibliographical references.Pecans are a major agricultural crop in New Mexico. Currently there are approximately 11,000 hectares of pecans in the Elephant Butte Irrigation District, consuming more than one third of the annual diversion. The research presented here provides previously unavailable broad-scale estimates of pecan ET and pecan yield response to water. The data at the foundation of this paper were generated using the Regional ET Estimation Model (REEM) developed at New Mexico State University for agricultural and riparian vegetation (Samani et al. 2005, 2006, 2007). REEM uses remotely sensed satellite data to calculate ET as a residual of the energy balance. This research extends the results of REEM to an analysis of yield response to water in irrigated pecan production in the EBID. The study region is rapidly urbanizing and experiencing growing competition for scarce surface and groundwater supplies. The results of this research provide new insight into pecan water use and yields. This research illustrates the linkages that can be made between remote sensing technology, farm-level water management, and yield outcomes. This research sheds new light on the long-standing practice of deficit irrigation in pecans, the yield and conservation impacts of this practice, as well as water conservation policy implications

USCID fourth international conference

Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.Includes bibliographical references.Pecan is a major crop in Lower Rio Grande Basin. Currently there exist about 30,000 acres (12,000 ha) of pecan orchards at various stages of growth which consumes about 40 percent of irrigation water in the area. Crop evapotranspiration (ET) varies with age, soil type and method of management. The ET variation and lack of information on optimum crop ET result in significant variation in productivity and income. In order to maximize the returns from limited water resources, there is a need for a better understanding of pecan optimum ET. ET was measured using three eddy covariance flux towers, which were installed in selected fields in the irrigated area. This paper describes a process where remotely sensed data from ASTER were combined with ground level information to estimate pecan ET and crop coefficient (Kc) throughout the area. The measured cumulative annual pecan ET were determined as 1470 mm (4.82 ft) compared to a predicted value of 1415 mm (4.68 ft) using the remote sensing model. Regression summary for measured ET as depended variable resulted in Standard Error of Estimate (SEE) of 0.86 mm/day and adjusted R2 of 0.9045 for 363 days of measured data

Remote sensing techology

Presented at Irrigation district sustainability - strategies to meet the challenges: USCID irrigation district specialty conference held on June 3-6, 2009 in Reno, Nevada.Includes bibliographical references.Irrigated agriculture is the largest water user in New Mexico; in southern New Mexico's Lower Rio Grande region, agriculture uses about one million acre-feet of water each year. Previous research has estimated that the average irrigation efficiency in the area is 44%. This relatively low aggregate efficiency indicates a large potential for water savings from agriculture. In order to determine the potential water savings, the amount of water depleted by crop evapotranspiration (ET) in the Mesilla Valley section of the EBID was estimated using satellite information and ground-level measurements to calculate plant consumptive water use on scales ranging from individual farms to the larger watershed. Two areas of potential water savings were evaluated using the satellite-generated consumptive use information: 1) potential water saving at the farm level and 2) potential water saving at the district level. This study found that the majority of farms in the study region were growing crops under deficit irrigation conditions. Therefore, irrigation improvements at the farm-level are likely to increase both yields and water depletion. Potential water savings at the district level were evaluated by comparing the total volume of water diverted for irrigation versus aggregate ET. From the satellite-generated ET data, district-level efficiency was determined to be 55% in 2002 (a full allocation year). Thus, there appears to be a potential for improving district-level efficiency. This can be accomplished by using regional ET depletion values to plan water releases from the reservoir and improve the diversion and distribution within the canal networks

CUDA Implementation of a Navier-Stokes Solver on Multi-GPU Desktop Platforms for Incompressible Flows

Graphics processor units (GPU) that are traditionally designed for graphics rendering have emerged as massively-parallel co-processors to the central processing unit (CPU). Small-footprint desktop supercomputers with hundreds of cores that can deliver teraflops peak performance at the price of conventional workstations have been realized. A computational fluid dynamics (CFD) simulation capability with rapid computational turnaround time has the potential to transform engineering analysis and design optimization procedures. We describe the implementation of a Navier-Stokes solver for incompressible fluid flow using desktop platforms equipped with multi-GPUs. Specifically, NVIDIA’s Compute Unified Device Architecture (CUDA) programming model is used to implement the discretized form of the governing equations. The projection algorithm to solve the incompressible fluid flow equations is divided into distinct CUDA kernels, and a unique implementation that exploits the memory hierarchy of the CUDA programming model is suggested. Using a quad-GPU platform, we observe two orders of magnitude speedup relative to a serial CPU implementation. Our results demonstrate that multi-GPU desktops can serve as a cost-effective small-footprint parallel computing platform to accelerate CFD simulations substantially. I. Introductio

Scene Segmentation Driven by Deep Learning and Surface Fitting

This paper proposes a joint color and depth segmentation scheme exploiting together geometrical clues and a learning stage. The approach starts from an initial over-segmentation based on spectral clustering. The input data is also fed to a Convolutional Neural Network (CNN) thus producing a per-pixel descriptor vector for each scene sample. An iterative merging procedure is then used to recombine the segments into the regions corresponding to the various objects and surfaces. The proposed algorithm starts by considering all the adjacent segments and computing a similarity metric according to the CNN features. The couples of segments with higher similarity are considered for merging. Finally the algorithm uses a NURBS surface fitting scheme on the segments in order to understand if the selected couples correspond to a single surface. The comparison with state-of-the-art methods shows how the proposed method provides an accurate and reliable scene segmentation

Optimization of sentinel lymph node biopsy in breast cancer using an operative gamma camera

<p>Abstract</p> <p>Background</p> <p>Sentinel lymph node (SLN) procedure is now a widely accepted method of LN staging in selected invasive breast cancers (unifocal, size ≤ 2 cm, clinically N0, without previous treatment). Complete axillary clearance is no longer needed if the SLN is negative. However, the oncological safety of this procedure remains to be addressed in randomized clinical trials. One main pitfall is the failure to visualize SLN, resulting in incorrect tumor staging, leading to suboptimal treatment or axillary recurrence. Operative gamma cameras have therefore been developed to optimize the SLN visualization and the quality control of surgery.</p> <p>Case presentation</p> <p>A 44-year-old female patient with a 14-mm infiltrative ductal carcinoma underwent the SLN procedure. An operative gamma camera was used during and after the surgery. The conventional lymphoscintigraphy showed only one SLN, which was also detected by the operative gamma camera, then removed and measured (9.6 kBq). It was analyzed by frozen sections, showing no cancer cells. During this analysis, the exploration of the axillary area with the operative gamma camera enabled the identification of a second SLN with low activity (0.5 kBq) that conventional lymphoscintigraphy, surgical probe and blue staining had failed to visualize. Histological examination revealed a macrometastasis. Axillary clearance was then performed, followed by a postoperative image proving that no SLN remained. Therefore, the use of the operative gamma camera prevented an under-estimation of staging which would have resulted in a suboptimal treatment for this patient.</p> <p>Conclusion</p> <p>This case report illustrates that an efficient operative gamma camera may be able to decrease the risk of false negative rate of the SLN procedure, and could be an additional tool to control the quality of the surgery.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov Identifier: NCT00357487</p

Ductal carcinoma in situ and sentinel lymph node metastasis in breast cancer

<p>Abstract</p> <p>Background</p> <p>The impact of sentinel lymph node biopsy on breast cancer mimicking ductal carcinoma in situ (DCIS) is a matter of debate.</p> <p>Methods</p> <p>We studied the rate of occurrence of sentinel lymph node metastasis in 255 breast cancer patients with pure DCIS showing no invasive components on routine pathological examination. We compared this to the rate of occurrence in 177 patients with predominant intraductal-component (IDC) breast cancers containing invasive foci equal to or less than 0.5 cm in size.</p> <p>Results</p> <p>Most of the clinical and pathological baseline characteristics were the same between the two groups. However, peritumoral lymphatic permeation occurred less often in the pure DCIS group than in the IDC-predominant invasive-lesion group (1.2% vs. 6.8%, p = 0.002). One patient (0.39%) with pure DCIS had two sentinel lymph nodes positive for metastasis. This rate was significantly lower than that in patients with IDC-predominant invasive lesions (6.2%; p < 0.001).</p> <p>Conclusions</p> <p>Because the rate of sentinel lymph node metastasis in pure DCIS is very low, sentinel lymph node biopsy can safely be omitted.</p