Fruit and Vegetable Planting Restrictions: Do U.S. Farmers Even Notice?

Crop Production/Industries, Food Consumption/Nutrition/Food Safety,

Foreground-Background Segmentation Based on Codebook and Edge Detector

Background modeling techniques are used for moving object detection in video. Many algorithms exist in the field of object detection with different purposes. In this paper, we propose an improvement of moving object detection based on codebook segmentation. We associate the original codebook algorithm with an edge detection algorithm. Our goal is to prove the efficiency of using an edge detection algorithm with a background modeling algorithm. Throughout our study, we compared the quality of the moving object detection when codebook segmentation algorithm is associated with some standard edge detectors. In each case, we use frame-based metrics for the evaluation of the detection. The different results are presented and analyzed.Comment: to appear in the 10th International Conference on Signal Image Technology & Internet Based Systems, 201

Finite difference schemes for second order systems describing black holes

In the harmonic description of general relativity, the principle part of Einstein's equations reduces to 10 curved space wave equations for the componenets of the space-time metric. We present theorems regarding the stability of several evolution-boundary algorithms for such equations when treated in second order differential form. The theorems apply to a model black hole space-time consisting of a spacelike inner boundary excising the singularity, a timelike outer boundary and a horizon in between. These algorithms are implemented as stable, convergent numerical codes and their performance is compared in a 2-dimensional excision problem.Comment: 19 pages, 9 figure

Updating a reference image for detecting motion in urban scenes

We present in this paper a construction and updating method of a reference image for motion detection in an urban environment . The proposed detection algorithm exploits differences between static edges of the scene and edges extracted from each imag e of the sequence . It allows to detect moving objects contours and moving areas contours if the background is not uniform . Th e reference image, robustly controlled, contains spatio temporal information of a great number of successive images . Updated locally with a recursive filter, it allows to integrate, after a controlled time, objects that stop in the scene . This kind of updating permits to automatically adapt with unpredictible movements of deformable or rigid objects (changes in speed and direction) . I n addition, analyzing edges allows to take into account global illumination changes and heterogeneity of the scene background i n an urban environment . This approach gives good results on complex outdoor image sequences .Nous présentons dans cet article une méthode de construction et de mise à jour d'une image de référence pour la détection du mouvement dans une scène urbaine. L'algorithme de détection proposé exploite les différences entre les contours statiques contenus dans la scène et les contours extraits de chaque image de la séquence. Il permet de mettre en évidence les contours des objets mobiles et les contours des zones affectées par le mouvement dans le cas où le fond n'est pas uniforme. L'image de référence, contrôlée de manière robuste, englobe les informations spatiales et temporelles contenues dans un grand nombre d'images successives de la séquence. Actualisée localement par l'intermédiaire d'un filtre récursif, elle permet d'intégrer, après un temps contrôlé, les objets qui s'arrêtent dans la scène. Ce type de réactualisation permet de s'adapter aux mouvements imprévisibles des objets (changement de vitesse et de direction) déformables ou non. De plus, l'analyse des contours a permis de s'affranchir des variations globales de l'éclairage ainsi que de l'hétérogénéité des fonds de la scène en milieu urbain. Cette approche obtient des résultats satisfaisants sur des images de scènes d'extérieur complexes

Proteomic profiling of canine fibrosarcoma and adjacent peritumoral tissue

Fibrosarcoma (FSA) are rare soft tissue tumors that display aggressive local behavior and invasive growth leading to high rates of tumor recurrence. While the low incidence in humans hampers detailed understanding of the disease, FSA are frequent in dogs and present potential models for the human condition. However, a lack of in-depth molecular characterization of FSA and unaffected peritumoral tissue (PTT) in both species impedes the translational potential of dogs. To address this shortcoming, we characterized canine FSA and matched skeletal muscle, adipose and connective tissue using laser-capture microdissection (LCM) and LC-MS/MS in 30 formalin-fixed paraffin embedded (FFPE) specimens. Principal component analysis of 3’530 different proteins detected across all samples clearly separates the four tissues, with several targets strongly differentiating tumor from all three PTTs. 25 proteins were exclusively found in tumor tissue in ≥80% of cases. Among these, CD68 (a macrophage marker), Optineurin (OPTN), Nuclear receptor coactivator 5 (NCOA5), RAP1GDS1 (Rap1 GTPase-GDP dissociation stimulator 1) and Stromal cell derived factor 2 like 1 (SDF2L1) were present in ≥90% of FSA. Protein expression across all FSA was highly homogeneous and characterized by MYC and TP53 signaling, hyperactive EIF2 and immune-related changes as well as strongly decreased oxidative phosphorylation and oxidative lipid metabolism. Finally, we demonstrate significant molecular homology between canine FSA and human soft-tissue sarcomas, emphasizing the relevance of studying canine FSA as a model for human FSA. In conclusion, we provide the first detailed overview of proteomic changes in FSA and surrounding PTT with relevance for the human disease

Evolution in intergenerational exchanges between elderly people and their grandchildren in Taiwan; data from a multiple round cross-sectional study from 1993 to 2007

<p>Abstract</p> <p>Background</p> <p>This study aimed to evaluate social evolution in Taiwan in recent decades using the changing pattern of care provided by grandparents for their grandchildren as an indicator.</p> <p>Methods</p> <p>Data from the second, fourth and sixth wave surveys of the <it>Study of Health and Living Status of the Middle-Aged and Elderly in Taiwan </it>were used for the analysis. This survey collected individual characteristics, including age, gender, education, ethnicity, dwelling place, living with partners, co-resident with children, employment status, self-reported health status and their provision of care for their grandchildren. Information about the attitudes toward National Health Insurance (NHI) was further collected in a questionnaire of 1999 following the implementation of NHI in 1995. By elders, we mean persons 60 or more years old. By grandchildren, we mean persons under 16 years of age. First, changes in individual characteristics were compared during these study periods (chi-square test). Then the logistic regression was performed to determine how significantly elders' grandchild-care behavior was associated with their individual characteristics.</p> <p>Results</p> <p>The percentage of elders providing grandchild care increased from 7.7% in 1993 to 13.6% in 1999, and then to 19.4% in 2007. By analysis, significant association was found between behavior in taking care of grandchildren and individuals of lower age, grandmothers, those living with partners or co-residing with children, those unemployed and those with better self-reported health status. And the effect of year was confirmed in the multivariable analysis.</p> <p>Conclusions</p> <p>This study pointed out the changing pattern of elders' behavior in taking care of their grandchildren as the main indicator and their related individual characteristics. We argue the need for improving social security policies in an ageing society. We suggest that the interaction between population policies and those of social welfare, including policies for health care and childcare, should be carefully evaluated.</p

SPARC Overexpression Inhibits Cell Proliferation in Neuroblastoma and Is Partly Mediated by Tumor Suppressor Protein PTEN and AKT

Secreted protein acidic and rich in cysteine (SPARC) is also known as BM-40 or Osteonectin, a multi-functional protein modulating cell–cell and cell–matrix interactions. In cancer, SPARC is not only linked with a highly aggressive phenotype, but it also acts as a tumor suppressor. In the present study, we sought to characterize the function of SPARC and its role in sensitizing neuroblastoma cells to radio-therapy. SPARC overexpression in neuroblastoma cells inhibited cell proliferation in vitro. Additionally, SPARC overexpression significantly suppressed the activity of AKT and this suppression was accompanied by an increase in the tumor suppressor protein PTEN both in vitro and in vivo. Restoration of neuroblastoma cell radio-sensitivity was achieved by overexpression of SPARC in neuroblastoma cells in vitro and in vivo. To confirm the role of the AKT in proliferation inhibited by SPARC overexpression, we transfected neuroblastoma cells with a plasmid vector carrying myr-AKT. Myr-AKT overexpression reversed SPARC-mediated PTEN and increased proliferation of neuroblastoma cells in vitro. PTEN overexpression in parallel with SPARC siRNA resulted in decreased AKT phosphorylation and proliferation in vitro. Taken together, these results establish SPARC as an effector of AKT-PTEN-mediated inhibition of proliferation in neuroblastoma in vitro and in vivo