Physics with charged kaons: recent and future experiments

This paper summarizes some recent progress and future perspectives in the experimental investigation of the Standard Model (and physics beyond it) using charged kaon decays, except for the important mode K+ -> pi+ nu nubar discussed in detail in other contributions to this workshop.Comment: Invited talk at the Workshop on e+e- in the 1-2 GeV range, Alghero, Italy, September 2003 (eConf C0309101). 5 pages, 3 figures. Added and corrected some reference

Measurements of direct CP violation

We review the experimental searches and determinations of direct CP violation in meson decays and other systems.Comment: 115 pages, 19 figure

Form factor in K+ --> pi+ pi0 gamma: interference versus direct emission

We analyze the effect of a form factor in the magnetic contribution to K+ --> pi+ pi0 gamma. We emphasize how this can show up experimentally: in particular we try to explore the difference between a possible interference contribution and a form factor in the magnetic part. The form factor used for K+ --> pi+ pi0 gamma is analogous to the one for KL --> pi+ pi- gamma, experimentally well established.Comment: 9 pages revtex, 10 eps figures; improved presentation of theoretical and experimental status; refs. adde

OCVD Measurement of Ambipolar and Minority Carrier Lifetime in 4H-SiC Devices: Relevance of the Measurement Setup

The open-circuit voltage decay (OCVD) method is a well-known technique for conducting electrical measurements of carrier lifetime: the main advantages lie in the simple setup and the possibility of carrying out measurements in commercial devices without the need of removing the package, as for optical methods. Despite several researchers having reported carrier lifetimes measured by the OCVD method in different devices, there has been little discussion about the potential effect of the experimental setup on the obtained results. By comparing the outputs of the experimental measurements with those of numerical simulations, this study investigates the overlooked effect of the OCVD measurement setup on the former. Due to the growing importance of SiC-based devices, the analysis is applied to a 4H-SiC p-i-n diode. Two main points are addressed: 1) the effect of circuit setup on the ambipolar lifetime is discussed and a method, originally developed for improving the estimate of low-level carrier lifetime in OCVD measurements, is used to correct the measured lifetime for this influence; 2) the origin of the local minimum eventually appearing in the lifetime versus time curves is also investigated. It is found that the minimum can also be related to the time constant of the experimental setup, giving rise to doubts about the usual interpretation of this minimum as the minority carrier lifetime. A method is thus proposed to help discriminate between the two interpretations

Long-Term Remission of an Aggressive Sebaceous Carcinoma following Chemotherapy

Sebaceous carcinoma (SC) is an uncommon neoplasm manifesting itself either in the eyelid or extraocularly in the head and neck area. Surgery is the standard of care. Irradiation is rarely proposed as monotherapy but is frequently administered as an adjuvant regimen following surgical resection. There is no known strategy concerning chemotherapeutic treatment in highly aggressive recurrent - or metastatic - forms of the disease. Our patient presented with an aggressive SC of the scalp recurring after multiple excisions and local radiotherapy. Chemotherapy with 5-fluorouracil, cisplatin and docetaxel was then initiated; 4 cycles were administered, followed by capecitabine maintenance. Shortly after starting chemotherapy, dermal lesions had completely disappeared and radiological response could be seen. The patient experienced an extended period (>20 months) of complete remission. In this report, we show an excellent response of a highly aggressive SC after a combination of chemotherapy as for head and neck cancers

Monitoring within-field variability of corn yield using sentinel-2 and machine learning techniques

Monitoring and prediction of within-field crop variability can support farmers to make the right decisions in different situations. The current advances in remote sensing and the availability of high resolution, high frequency, and free Sentinel-2 images improve the implementation of Precision Agriculture (PA) for a wider range of farmers. This study investigated the possibility of using vegetation indices (VIs) derived from Sentinel-2 images and machine learning techniques to assess corn (Zea mays) grain yield spatial variability within the field scale. A 22-ha study field in North Italy was monitored between 2016 and 2018; corn yield was measured and recorded by a grain yield monitor mounted on the harvester machine recording more than 20,000 georeferenced yield observation points from the study field for each season. VIs from a total of 34 Sentinel-2 images at different crop ages were analyzed for correlation with the measured yield observations. Multiple regression and two different machine learning approaches were also tested to model corn grain yield. The three main results were the following: (i) the Green Normalized Difference Vegetation Index (GNDVI) provided the highest R2 value of 0.48 for monitoring within-field variability of corn grain yield; (ii) the most suitable period for corn yield monitoring was a crop age between 105 and 135 days from the planting date (R4-R6); (iii) Random Forests was the most accurate machine learning approach for predicting within-field variability of corn yield, with an R2 value of almost 0.6 over an independent validation set of half of the total observations. Based on the results, within-field variability of corn yield for previous seasons could be investigated from archived Sentinel-2 data with GNDVI at crop stage (R4-R6)

wGrapeUNIPD-DL: An open dataset for white grape bunch detection

National and international Vitis variety catalogues can be used as image datasets for computer vision in viticulture. These databases archive ampelographic features and phenology of several grape varieties and plant structures images (e.g. leaf, bunch, shoots). Although these archives represent a potential database for computer vision in viticulture, plant structure images are acquired singularly and mostly not directly in the vineyard. Localization computer vision models would take advantage of multiple objects in the same image, allowing more efficient training. The present images and labels dataset was designed to overcome such limitations and provide suitable images for multiple cluster identification in white grape varieties. A group of 373 images were acquired from later view in vertical shoot position vineyards in six different Italian locations at different phenological stages. Images were then labelled in YOLO labelling format. The dataset was made available both in terms of images and labels. The real number of bunches counted in the field, and the number of bunches visible in the image (not covered by other vine structures) was recorded for a group of images in this dataset