Profile-encoding reconstruction for multiple-acquisition balanced steady-state free precession imaging

Purpose: The scan-efficiency in multiple-acquisition balanced steady-state free precession imaging can be maintained by accelerating and reconstructing each phase-cycled acquisition individually, but this strategy ignores correlated structural information among acquisitions. Here, an improved acceleration framework is proposed that jointly processes undersampled data across N phase cycles. Methods: Phase-cycled imaging is cast as a profile-encoding problem, modeling each image as an artifact-free image multiplied with a distinct balanced steady-state free precession profile. A profile-encoding reconstruction (PE-SSFP) is employed to recover missing data by enforcing joint sparsity and total-variation penalties across phase cycles. PE-SSFP is compared with individual compressed-sensing and parallel-imaging (ESPIRiT) reconstructions. Results: In the brain and the knee, PE-SSFP yields improved image quality compared to individual compressed-sensing and other tested methods particularly for higher N values. On average, PE-SSFP improves peak SNR by 3.8 ± 3.0 dB (mean ± s.e. across N = 2–8) and structural similarity by 1.4 ± 1.2% over individual compressed-sensing, and peak SNR by 5.6 ± 0.7 dB and structural similarity by 7.1 ± 0.5% over ESPIRiT. Conclusion: PE-SSFP attains improved image quality and preservation of high-spatial-frequency information at high acceleration factors, compared to conventional reconstructions. PE-SSFP is a promising technique for scan-efficient balanced steady-state free precession imaging with improved reliability against field inhomogeneity. Magn Reson Med 78:1316–1329, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicin

The genetic profile of elite youth soccer players and its association with power and speed depends on maturity status

We investigated the association of multiple single nucleotide polymorphisms (SNPs) with athlete status and power/speed performance in elite male youth soccer players (ESP) and control participants (CON) at different stages of maturity. ESP (n = 535; aged 8–23 years) and CON (n = 151; aged 9–26 years) were genotyped for 10 SNPs and grouped according to years from predicted peak-height-velocity (PHV), i.e. pre- or post-PHV, to determine maturity status. Participants performed bilateral vertical countermovement jumps, bilateral horizontal-forward countermovement jumps, 20m sprints and modified 505-agility tests. Compared to CON, pre-PHV ESP demonstrated a higher ACTN3 (rs1815739) XX (‘endurance’) genotype frequency distribution, while post-PHV ESP revealed a higher frequency distribution of the PPARA (rs4253778) C-allele, AGT (rs699) GG genotype and NOS3 (rs2070744) T-allele (‘power’ genotypes/alleles). BDNF (rs6265) CC, COL5A1 (rs12722) CC and NOS3 TT homozygotes sprinted quicker than A-allele carriers, CT heterozygotes and CC homozygotes, respectively. COL2A1 (rs2070739) CC and AMPD1 (rs17602729) GG homozygotes sprinted faster than their respective minor allele carrier counterparts in CON and pre-PHV ESP, respectively. BDNF CC homozygotes jumped further than T-allele carriers, while ESP COL5A1 CC homozygotes jumped higher than TT homozygotes. To conclude, we have shown for the first time that pre- and post-PHV ESP have distinct genetic profiles, with pre-PHV ESP more suited for endurance, and post-PHV ESP for power and speed (the latter phenotypes being crucial attributes for post-PHV ESP). We have also demonstrated that power, acceleration and sprint performance were associated with five SNPs, both individually and in combination, possibly by influencing muscle size and neuromuscular activation

A method of strategic evaluation of energy performance of Building Integrated Photovoltaic in the urban context

This paper presents an integrated bottom-up approach aimed at helping those dealing with strategical analysis of installation of Building Integrated Photo Voltaic (BIPV) to estimate the electricity production potential along with the energy needs of urban buildings at the district scale. On the demand side, hourly energy profiles are generated using dynamic building simulation taking into account actual urban morphologies. On the supply side, electricity generated from the system is predicted considering both the direct and indirect components of solar radiation as well as local climate variables. Python-based Algorithm editor Grasshopper is used to interlink four types of modelling and simulation tools as 1) generation of 3-D model, 2) solar radiation analysis, 3) formatting weather files (TMY data set) and 4) dynamic energy demand. The method has been demonstrated for a cluster of 20 buildings located in the Yasar University in Izmir (Turkey), for which it is found the BIPV system could achieve an annual renewable share of 23%, in line with the Renewable Energy Directive target of 20%. Quantitatively-compared demand and supply information at hourly time step shows that only some energy needs can be met by BIPV, so there is a need for an appropriate matching strategy to better exploit the renewable energy potential

Radiant Heating-cooling Performance Assessment in a Shopping Center in Sopron, Hungary

3rd International Conference on Energy and Environment Research (ICEER) -- SEP 07-11, 2016 -- Barcelona, SPAINWOS: 000400640900030In this study, performance of a radiant heating-cooling via air source heat pump was investigated. This study is part of a project funded by European Union's FP7 for research, technological development and demonstration. In the project it is aimed that a holistic retrofitting solution for commercial buildings to reduce primary energy consumption down to less than 80 kWh/m(2) per year. A shopping center called IKVA located in Sopron, Hungary used as a demo building. In that building a heat pump system integrated with a radiant heating and cooling system is used. In this paper, two different cases are compared regarding air source heat pump system; in Case-1 air source of the heat pump is outdoor air, in Case-2 air source of heat pump is return air. (C) 2016 The Authors. Published by Elsevier Ltd.Univ Poltecnica Catalunya, BarcelonaTECHEuropean CommissionEuropean Commission Joint Research Centre [609180]The presented work was developed within the "Energy Efficient & Cost Competitive Retrofitting Solutions for Shopping Buildings" project co-funded by the European Commission (Grant agreement no: 609180)