Measurement of ϒ production in pp collisions at √s = 2.76 TeV

The production of ϒ(1S), ϒ(2S) and ϒ(3S) mesons decaying into the dimuon final state is studied with the LHCb detector using a data sample corresponding to an integrated luminosity of 3.3 pb−1 collected in proton–proton collisions at a centre-of-mass energy of √s = 2.76 TeV. The differential production cross-sections times dimuon branching fractions are measured as functions of the ϒ transverse momentum and rapidity, over the ranges pT < 15 GeV/c and 2.0 < y < 4.5. The total cross-sections in this kinematic region, assuming unpolarised production, are measured to be σ (pp → ϒ(1S)X) × B ϒ(1S)→μ+μ− = 1.111 ± 0.043 ± 0.044 nb, σ (pp → ϒ(2S)X) × B ϒ(2S)→μ+μ− = 0.264 ± 0.023 ± 0.011 nb, σ (pp → ϒ(3S)X) × B ϒ(3S)→μ+μ− = 0.159 ± 0.020 ± 0.007 nb, where the first uncertainty is statistical and the second systematic

ROLE OF REMOTE SENSING TO INTEGRATED COASTAL ZONE MANAGEMENT

The coastal zone represents varied and highly productive ecosystems such as mangroves, coral reefs, sea grasses and sand dunes. These ecosystems are under pressure on account of increased anthropogenic activity on the coast, as a result of globalisation. It is necessary to protect these coastal ecosystems to ensure sustainable development. This requires information on habitats, landforms, coastal processes, water quality, natural hazards on a repetitive basis. In India, remote sensing data, especially Indian Remote Sensing (IRS) data, having moderate (23-36 m) to high spatial resolution (6 m), have been used to generate database on various components of coastal environment of the entire country. However, the moderate resolution data provide macro-level information on 1:250,000 and 1:50,000 scale about the condition of habitats, type of landforms and areas under erosion and deposition. The major advantage of remote sensing data is monitoring of change periodically. The combination of moderate and high-resolution data provided detailed coastal land use maps on the 1:25,000-scale for implementing coastal regulation measures. The classification accuracy have been achieved is 85 per cent or better at 90 per cent confidence level. Mangrove areas were classified up to community level through contextual editing. Various zones of coral reef were identified, however, species level information is not possible to generate using such data. The knowledge about bio-optical properties of water is vital for coral reef and sea grass bed monitoring. The OCEANSAT I (IRS P4) Ocean Colour Monitor (OCM) data provide useful information on the phytoplankton and suspended sediments. The information on phytoplankton and sea surface temperature (SST) has been used to predict potential fishery zones routinely. The information on sediments provides some insight in to the movement of sediments along the coast. Satellite-derived derived information were integrated with the other collateral informatio

The ESO DIBs Large Exploration Survey

VizieR online Data Catalogue associated with article published in journal Astronomy & Astrophysics with title 'The ESO Diffuse Interstellar Bands Large Exploration Survey (EDIBLES). I. Project description, survey sample, and quality assessment.' (bibcode: 2017A&A...606A..76C