Production of W and Z bosons accompanied by jets at LHC startup

We report on potential for measurement of W and Z boson production accompanied by jets at the CMS experiment. Of particular interest are jet multiplicity and Pt distributions. The 10/pb to 100/pb datasets expected in the startup year of operation of LHC are likely to already provide information beyond the reach of the Tevatron collider both in jet multiplicity and Pt range. We are especially interested in understanding the ratios of W+jets to Z+jets distributions by comparing them to next-to-leading order Monte Carlo generators, as these processes present a formidable background for searches of new physics phenomena.Comment: Poster session at ICHEP08, Philadelphia, USA, July 2008. 3 pages, LaTeX, 1 jpg figure. Updated with the new latex template for ICHEP0

A review on non iterative closed form configuration matching and rotations estimation

Orthonormal matrices, Procrustes and quaternion analysis are closed form solutions of the configuration matching problem, common in geodesy as in the datum transformation problem. Literature reports more Procrustes based geodetic applications than Quaternions, which are more used in other application fields, such as aerospace navigation, robotics and computer vision. The large popularity of Procrustes in geodesy is mainly due to its capability to take into account a priori observation weighting in a simple wa

CICERO: A GPT2-Based Writing Assistant to Investigate the Effectiveness of Specialized LLMs’ Applications in e-Justice

Does it make sense to develop specialized writing assistants in the era of LLMs - Large Language Models? In this paper, we present CICERO, a specialized writing assistant we have developed for writing (pieces of) sentences in the Italian legal system. Our proposed solution involves fine-tuning a transformer on a pre-processed corpus of Italian civil judgments, resulting in a novel language model that can be deployed as a writing assistant for legal users to improve text writing efficiency. The model can also be further fine-tuned for use in other law-related natural language processing tasks. The experimental validation of CICERO allows us also to draw interesting insights on the meaningful, if any, of developing specialized tools for assisting specific classes of users and knowledge workers, in an era in which we witness the widespread adoption of LLMs

Coupling radio propagation and weather forecast models to maximize Ka-band channel transmission rate for interplanetary missions

Deep space (DS) missions for interplanetary explorations are aimed at acquiring information about the solar system and its composition. To achieve this result a radio link is established between the space satellite and receiving stations on the Earth. Significant channel capacity must be guaranteed to such spacecraft-to-Earth link considering their large separation distance as well. Terrestrial atmospheric impairments on the space-to-Earth propagating signals are the major responsible for the signal degradation thus reducing the link’s channel temporal availability. Considering the saturation and the limited bandwidth of the conventional systems used working at X-band (around 8.4 GHz), frequencies above Ku-band (12-18 GHz) are being used and currently explored for next future DS missions. For example, the ESA mission EUCLID, planned to be launched in 2020 to reach Sun-Earth Lagrange point L2, will use the K-band (at 25.5-27 GHz). The BepiColombo (BC) ESA mission to Mercury, planned to be launched in 2016, will use Ka-band (at 32-34 GHz) with some modules operating at X-band too. The W-band is also being investigated for space communications (Lucente et al., IEEE Systems J., 2008) as well as near-infrared band for DS links (Luini at al., 3rd IWOW, 2014; Cesarone et al., ICSOS, 2011). If compared with X-band channels, K-band and Ka-band can provide an appealing data rate and signal-to-noise ratio in free space due to the squared-frequency law increase of antenna directivity within the downlink budget (for the same physical antenna size). However, atmospheric path attenuation can be significant for higher frequencies since the major source of transmission outage is not only caused by convective rainfall, as it happens for lower frequencies too, but even non-precipitating clouds and moderate precipitation produced by stratiform rain events are detrimental. This means that accurate channel models are necessary for DS mission data link design at K and Ka band. A physical approach can offer advanced radiopropagation models to take into account the effects due to atmospheric gases, clouds and precipitation. The objective of this work is to couple a weather forecast numerical model with a microphysically- oriented radiopropagation model, providing a description of the atmospheric state and of its effects on a DS downlink. This work is developed in the framework of the RadioMeteorological Operations Planner (RMOP) program, aimed at performing a feasibility study for the BC mission (Biscarini et al., EuCAP 2014). The RMOP chain for the link budget computation is composed by three modules: weather forecast (WFM), radio propagation (RPM) and downlink budget (DBM). WFM is aimed at providing an atmospheric state vector. Among the available weather forecast models, for RMOP purposes we have used the Mesoscale Model 5. The output of the WFM is the input of the RPM for the computation of the atmospheric attenuation and sky-noise temperature at the receiving ground station antenna. RPM makes use of radiative transfer solver based on the Eddington approximations well as accurate scattering models. Time series of attenuation and sky-noise temperature coming from the RPM are converted into probability density functions and then ingested by the DBM to compute the received data volume (DV). Using the BC mission as a reference test case for the Ka-band ground station at Cebreros (Spain), this work will show the advantages of using a coupled WFM-RPM approach with respect to climatological statistics in a link budget optimization procedure. The signal degradation due to atmospheric effects in DS links in terms of received DV will be also investigated not only at Ka band, but also at X, K and W for intercomparison. The quality of the DS downlink will be given in terms of received DV and the results at different frequencies compared showing the respective advantages and drawbacks

Paroxysmal Atrial Fibrillation Triggered By A Monomorphic Ventricular Couplet In A Patient With Acute Coronary Syndrome

Atrial fibrillation is a common arrhythmia in patients suffering from acute myocardial infarction, however its pathophysiological mechanisms are not fully understood. We describe the unusual case of a 76-year old woman admitted for non-ST-segment elevation myocardial infarction, who developed multiple episodes of paroxysmal atrial fibrillation triggered by monomorphic ventricular couplets. Beta-blocking and amiodarone therapy resulted efficacious in preventing arrhythmic recurrences. We then discuss the possible arrhythmogenic mechanisms, with special emphasis on the unique electrophysiological, hemodynamic, cellular and anatomical milieu created by acute myocardial ischemia

A History of Group Theory through the Lives of Group Theorists: Sophus Lie - Part 1

We continue here our attempt of a systematic historical account of Group Theory inspected by means of the lives and the works of its main actors. The aim is to bring the interested reader through orig- inal correspondences, published and unpublished works, historical perspectives, diatribes and friendships. This issue contains the translation of a memory of Sophus Lie writ- ten by Ludwig Sylow. It was published in the 1899 issue of Archiv for Mathematik of Naturvidenskab soon after Lie’s death. We are grateful to Gunnar Traustason for his translation from Nor- wegian

Machine Learning and image analysis towards improved energy management in Industry 4.0: a practical case study on quality control

With the advent of Industry 4.0, Artificial Intelligence (AI) has created a favorable environment for the digitalization of manufacturing and processing, helping industries to automate and optimize operations. In this work, we focus on a practical case study of a brake caliper quality control operation, which is usually accomplished by human inspection and requires a dedicated handling system, with a slow production rate and thus inefficient energy usage. We report on a developed Machine Learning (ML) methodology, based on Deep Convolutional Neural Networks (D-CNNs), to automatically extract information from images, to automate the process. A complete workflow has been developed on the target industrial test case. In order to find the best compromise between accuracy and computational demand of the model, several D-CNNs architectures have been tested. The results show that, a judicious choice of the ML model with a proper training, allows a fast and accurate quality control; thus, the proposed workflow could be implemented for an ML-powered version of the considered problem. This would eventually enable a better management of the available resources, in terms of time consumption and energy usage