9 research outputs found
Constraints on the trilinear Higgs coupling from vector boson fusion and associated Higgs production at the LHC
We examine the constraints on the trilinear Higgs coupling λ that originate from associated (V h) and vector boson fusion (VBF) Higgs production in pp collisions in the context of the Standard Model effective field theory. The 1-loop contributions to pp → Vh and pp → jjh that stem from insertions of the dimension-6 operator O 6 = −λ (H † H)3 are calculated and combined with the corrections to the partial decay widths of the Higgs boson. Employing next-to-next-to-leading order QCD predictions, we analyse the sensitivity of current and forthcoming measurements of the signal strengths in Vh and VBF Higgs production to changes in λ. We show that future LHC runs may be able to probe modifications of λ with a sensitivity similar to the one that is expected to arise from determinations of double-Higgs production. The sensitivity of differential Vh and VBF Higgs distributions to a modified h 3 coupling is also studied
A deep multi-band investigation of IC2391
We report the outcome of a deep multi-wavelength study of the IC2391 young
open cluster. We aim at uncovering new low-mass and sub-stellar members of the
cluster and identifying new debris disk objects. A 30*30 square arcmin area in
IC 2391 was observed using the wide-field imager at the ESO 2.2m telescope. The
completeness limits of the photometry at 3 sigma level are V=24.7, Rc=23.7 and
Ic=23.0, faint enough to reveal sub-stellar members down to about 0.03 solar
masses. Our membership criteria are based on the use of our optical data, in
combination with JHKs magnitudes from the 2MASS catalog. We also estimate the
physical parameters of the selected candidates. Debris disk candidates are
identified on the basis of their infrared excess emission using near- and
mid-infrared photometry from the Spitzer Space Telescope. Our optical survey,
which has a limiting magnitude at 3 sigma level 1-2 mag fainter than previous
optical surveys conducted in IC2391, revealed 29 new low-mass member candidates
of the cluster. We estimate the contamination to be at least 50%. We constrain
the fraction of sub-stellar objects in the range 8-15% and discuss possible
explanations for the deficit of brown dwarfs in this cluster. We also
identified 10 candidates in the cluster showing IR excess emission consistent
with the presence of debris disks.Comment: 17 pages, 9 figure
Prospective cohort study in evaluation of risk factors for infection during and after coronary graft operations
Introduction: There is a strong suggestion that an impairment of vascular supply of the sternum may be one of the most important factors influencing the incidence of deep sternal wound infection (DSWI). Several studies have studied the risk factors for SSIs including DSWI in cardiac surgery. Methods: All patients who are presented to Assiut University Heart Hospital in need of Coronary artery Bypass Grafting from 1st of January, 2018 to 30th june, 2021 were included in the study prospectively. Exclusion criteria included patients who were diagnosed with infective endocarditis, have undergone open heart surgery before or had sternotomy been done for any other reason- redo surgery is excluded-, and where other surgical accesses were used other than sternotomy. Results: During the study duration, we included 99 pateinets. Our patients were followed for 1 week post-operative and then on day 30 post-operative. 81 patients showed perfect skin healing at 1 week post-operative follow-up with very nice and neat scar at 1 month follow-up. 5 patients showed wound breakdown with subcutaneous being exposed (Type I SWIs). 3 patients suffered type I SWI with exposed subcutaneous but with severe infection and loss of skin. 
Detection of Potassium Deficiency and Momentary Transpiration Rate Estimation at Early Growth Stages Using Proximal Hyperspectral Imaging and Extreme Gradient Boosting
Potassium is a macro element in plants that is typically supplied to crops in excess throughout the season to avoid a deficit leading to reduced crop yield. Transpiration rate is a momentary physiological attribute that is indicative of soil water content, the plant’s water requirements, and abiotic stress factors. In this study, two systems were combined to create a hyperspectral–physiological plant database for classification of potassium treatments (low, medium, and high) and estimation of momentary transpiration rate from hyperspectral images. PlantArray 3.0 was used to control fertigation, log ambient conditions, and calculate transpiration rates. In addition, a semi-automated platform carrying a hyperspectral camera was triggered every hour to capture images of a large array of pepper plants. The combined attributes and spectral information on an hourly basis were used to classify plants into their given potassium treatments (average accuracy = 80%) and to estimate transpiration rate (RMSE = 0.025 g/min, R2 = 0.75) using the advanced ensemble learning algorithm XGBoost (extreme gradient boosting algorithm). Although potassium has no direct spectral absorption features, the classification results demonstrated the ability to label plants according to potassium treatments based on a remotely measured hyperspectral signal. The ability to estimate transpiration rates for different potassium applications using spectral information can aid in irrigation management and crop yield optimization. These combined results are important for decision-making during the growing season, and particularly at the early stages when potassium levels can still be corrected to prevent yield loss
Pepper Plants Leaf Spectral Reflectance Changes as a Result of Root Rot Damage
Symptoms of root stress are hard to detect using non-invasive tools. This study reveals proof of concept for vegetation indices’ ability, usually used to sense canopy status, to detect root stress, and performance status. Pepper plants were grown under controlled greenhouse conditions under different potassium and salinity treatments. The plants’ spectral reflectance was measured on the last day of the experiment when more than half of the plants were already naturally infected by root disease. Vegetation indices were calculated for testing the capability to distinguish between healthy and root-damaged plants using spectral measurements. While no visible symptoms were observed in the leaves, the vegetation indices and red-edge position showed clear differences between the healthy and the root-infected plants. These results were achieved after a growth period of 32 days, indicating the ability to monitor root damage at an early growing stage using leaf spectral reflectance