Agri-business and nobility in Northern Italy : land, investments and markets (1815-1861)

Traditionally, the contribution of nobility to the enhancement of northern Italy\u2019s land and agro food production during the 19th century has been undervalued. The paper aims to address the question of whether the nobility considered land mainly as a means to collect rents with the least effort, maintaining their social status, or rather \u2013 as we affirm \u2013 they also developed entrepreneurial behaviour founded on a sort of class-expertise. Indeed, in a considerable number of cases, they owned and invested capital in large estates with a well-structured administration which they inherited from the past and improved upon; they organised complex production systems, introducing technical innovation; they were directly interested in market trends; they could take advantage of their local and international social networks. Finally, they acted as models for many of the bourgeoisie who became richer and became landowners themselves. Through ongoing extensive research using primary sources (fiscal sources, notarial deeds and family archives), the essay will first focus on the general features of the noblemen\u2019s involvement in the management and improvement of lands, through agrarian innovation and experimentation (e.g. in silk or wine production), according to the circumstances of the markets. The second part will illustrate the case of the Lombardy noble family Lucini Passalacqua, who seems to exemplify the tendency towards innovation which was widespread among the region\u2019s noble landowners. The third part of the paper will shed light upon the business strategies of Genoese noblemen, traditionally tied to financial businesses, and who, during the 19th century, largely invested in land development, also acquiring vast estates in Piedmont and Lombardy

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Performance and Operation of the CMS Electromagnetic Calorimeter

The operation and general performance of the CMS electromagnetic calorimeter using cosmic-ray muons are described. These muons were recorded after the closure of the CMS detector in late 2008. The calorimeter is made of lead tungstate crystals and the overall status of the 75848 channels corresponding to the barrel and endcap detectors is reported. The stability of crucial operational parameters, such as high voltage, temperature and electronic noise, is summarised and the performance of the light monitoring system is presented

Impact of Environmental Parameters on Marathon Running Performance

PURPOSE: The objectives of this study were to describe the distribution of all runners' performances in the largest marathons worldwide and to determine which environmental parameters have the maximal impact. METHODS: We analysed the results of six European (Paris, London, Berlin) and American (Boston, Chicago, New York) marathon races from 2001 to 2010 through 1,791,972 participants' performances (all finishers per year and race). Four environmental factors were gathered for each of the 60 races: temperature (°C), humidity (%), dew point (°C), and the atmospheric pressure at sea level (hPA); as well as the concentrations of four atmospheric pollutants: NO(2)-SO(2)-O(3) and PM(10) (μg x m(-3)). RESULTS: All performances per year and race are normally distributed with distribution parameters (mean and standard deviation) that differ according to environmental factors. Air temperature and performance are significantly correlated through a quadratic model. The optimal temperatures for maximal mean speed of all runners vary depending on the performance level. When temperature increases above these optima, running speed decreases and withdrawal rates increase. Ozone also impacts performance but its effect might be linked to temperature. The other environmental parameters do not have any significant impact. CONCLUSIONS: The large amount of data analyzed and the model developed in this study highlight the major influence of air temperature above all other climatic parameter on human running capacity and adaptation to race conditions

Performance studies of the CMS strip tracker before installation

Peer reviewe

Calibration of the CMS Drift Tube Chambers and Measurement of the Drift Velocity with Cosmic Rays

Peer reviewe

CMS physics technical design report : Addendum on high density QCD with heavy ions

Peer reviewe

CMS Data Processing Workflows during an Extended Cosmic Ray Run

Peer reviewe

Aligning the CMS Muon Chambers with the Muon Alignment System during an Extended Cosmic Ray Run

Peer reviewe

Commissioning and performance of the CMS silicon strip tracker with cosmic ray muons

This is the Pre-print version of the Article. The official published version of the Paper can be accessed from the link below - Copyright @ 2010 IOPDuring autumn 2008, the Silicon Strip Tracker was operated with the full CMS experiment in a comprehensive test, in the presence of the 3.8 T magnetic field produced by the CMS superconducting solenoid. Cosmic ray muons were detected in the muon chambers and used to trigger the readout of all CMS sub-detectors. About 15 million events with a muon in the tracker were collected. The efficiency of hit and track reconstruction were measured to be higher than 99% and consistent with expectations from Monte Carlo simulation. This article details the commissioning and performance of the Silicon Strip Tracker with cosmic ray muons.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)