Farmers’ Adoption and Perceived Benefits of Diversified Crop Rotations in the Margins of U.S. Corn Belt

Monoculture and simplified two-crop rotation systems compromise the ecosystem services essential to crop production, diminish agricultural productivity, and cause detrimental effects on the environment. In contrast to the simplified two-crop rotation, diversified crop rotation (DCR) refers to rotation systems that contain three or more crops. Despite multiple benefits generated by DCR, its usage has dwindled over the past several decades. This paper examined determinants of farmers\u27 adoption decisions and perceived benefits of DCR in the west margins of the U.S. Corn Belt where crop diversity has declined. We analyzed 708 farmer responses from a farmer survey conducted in the eastern South Dakota in 2018, accounting for county-level climate variables, as well as cropland data, soil and topographic variables in close proximity of the farm. Our findings indicated that farmers were more likely to utilize DCR as an adaptive strategy to cope with water deficit and reduce soil erosion on marginal land. Additionally, livestock integration and organic farming helped necessitate DCR adoption and magnify its benefits. Producer concerns towards lack of equipment and new crop profitability diluted producers’ interests in DCR practice and compromised its benefits. Enhanced technical and policy support, along with infrastructure and market development, could help producers fully utilize DCR benefits and expand DCR usage to more regions

Triphenylphosphine-Based Covalent Organic Frameworks and Heterogeneous Rh-P-COFs Catalysts

The synthesis of phosphine-based functional covalent organic frameworks (COFs) has attracted great attention recently. Herein, we present two examples of triphenylphosphine-based COFs (termed P-COFs) with well-defined crystalline structures, high specific surface areas, and good thermal stability. Furthermore, rhodium catalysts with these P-COFs as support material show high turnover frequency for the hydroformylation of olefins, as well as excellent recycling performance. This work not only extends the phosphine-based COF family, but also demonstrates their application in immobilizing homogeneous metal-based (e.g., Rh-phosphine) catalysts for application in heterogeneous catalysis

Chest Fat Quantification via CT Based on Standardized Anatomy Space in Adult Lung Transplant Candidates

Purpose Overweight and underweight conditions are considered relative contraindications to lung transplantation due to their association with excess mortality. Yet, recent work suggests that body mass index (BMI) does not accurately reflect adipose tissue mass in adults with advanced lung diseases. Alternative and more accurate measures of adiposity are needed. Chest fat estimation by routine computed tomography (CT) imaging may therefore be important for identifying high-risk lung transplant candidates. In this paper, an approach to chest fat quantification and quality assessment based on a recently formulated concept of standardized anatomic space (SAS) is presented. The goal of the paper is to seek answers to several key questions related to chest fat quantity and quality assessment based on a single slice CT (whether in the chest, abdomen, or thigh) versus a volumetric CT, which have not been addressed in the literature. Methods Unenhanced chest CT image data sets from 40 adult lung transplant candidates (age 58 ± 12 yrs and BMI 26.4 ± 4.3 kg/m2), 16 with chronic obstructive pulmonary disease (COPD), 16 with idiopathic pulmonary fibrosis (IPF), and the remainder with other conditions were analyzed together with a single slice acquired for each patient at the L5 vertebral level and mid-thigh level. The thoracic body region and the interface between subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) in the chest were consistently defined in all patients and delineated using Live Wire tools. The SAT and VAT components of chest were then segmented guided by this interface. The SAS approach was used to identify the corresponding anatomic slices in each chest CT study, and SAT and VAT areas in each slice as well as their whole volumes were quantified. Similarly, the SAT and VAT components were segmented in the abdomen and thigh slices. Key parameters of the attenuation (Hounsfield unit (HU) distributions) were determined from each chest slice and from the whole chest volume separately for SAT and VAT components. The same parameters were also computed from the single abdominal and thigh slices. The ability of the slice at each anatomic location in the chest (and abdomen and thigh) to act as a marker of the measures derived from the whole chest volume was assessed via Pearson correlation coefficient (PCC) analysis. Results The SAS approach correctly identified slice locations in different subjects in terms of vertebral levels. PCC between chest fat volume and chest slice fat area was maximal at the T8 level for SAT (0.97) and at the T7 level for VAT (0.86), and was modest between chest fat volume and abdominal slice fat area for SAT and VAT (0.73 and 0.75, respectively). However, correlation was weak for chest fat volume and thigh slice fat area for SAT and VAT (0.52 and 0.37, respectively), and for chest fat volume for SAT and VAT and BMI (0.65 and 0.28, respectively). These same single slice locations with maximal PCC were found for SAT and VAT within both COPD and IPF groups. Most of the attenuation properties derived from the whole chest volume and single best chest slice for VAT (but not for SAT) were significantly different between COPD and IPF groups. Conclusions This study demonstrates a new way of optimally selecting slices whose measurements may be used as markers of similar measurements made on the whole chest volume. The results suggest that one or two slices imaged at T7 and T8 vertebral levels may be enough to estimate reliably the total SAT and VAT components of chest fat and the quality of chest fat as determined by attenuation distributions in the entire chest volume

IRIM at TRECVID 2010: Semantic Indexing and Instance Search

International audienceThe IRIM group is a consortium of French teams working on Multimedia Indexing and Retrieval. This paper describes our participation to the TRECVID 2010 semantic indexing and instance search tasks. For the semantic indexing task, we evaluated a number of different descriptors and tried different fusion strategies, in particular hierarchical fusion. The best IRIM run has a Mean Inferred Average Precision of 0.0442, which is above the task median performance. We found that fusion of the classification scores from different classifier types improves the performance and that even with a quite low individual performance, audio descriptors can help. For the instance search task, we used only one of the example images in our queries. The rank is nearly in the middle of the list of participants. The experiment showed that HSV features outperform the concatenation of HSV and Edge histograms or the Wavelet features

MR Image Analytics to Characterize the Upper Airway Structure in Obese Children with Obstructive Sleep Apnea Syndrome

<b>Here is the data for Manuscript on Plos one (ID-PONE-D15-54189). More details are as follows.<br> </b><p><b>This spreadsheet lists the values of the 16 features listed in Table 7 of the paper for all 30 study subjects. The subjects are divided into the control and OSAS groups. This data can be used to test the accuracy of class prediction by using logistic regression as explained in the paper.</b></p><b> <br></b><br

Chest fat quantification via CT based on standardized anatomy space in adult lung transplant candidates

The file includes the major discovery and key data and parameters found in the manuscript, such as fat (SAT & VAT) area and attenuation histogram information on single optimal chest CT slice and single slices at the L5 vertebral level and mid-thigh level for all subjects (in this study) in three groups, IPF, COPD and the other as the 3rd group