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Institute
Ground-based gamma-ray astronomy has had a major breakthrough with the impressive results obtained using systems of imaging atmospheric Cherenkov telescopes. Ground-based gamma-ray astronomy has a huge potential in astrophysics, particle physics and cosmology. CTA is an international initiative to build the next generation instrument, with a factor of 5-10 improvement in sensitivity in the 100 GeV-10 TeV range and the extension to energies well below 100 GeV and above 100 TeV. CTA will consist of two arrays (one in the north, one in the south) for full sky coverage and will be operated as open observatory. The design of CTA is based on currently available technology. This document reports on the status and presents the major design concepts of CTA.
The 2010 very high energy gamma-ray flare and 10 years ofmulti-wavelength oservations of M 87
(2012)
The giant radio galaxy M 87 with its proximity (16 Mpc), famous jet, and very massive black hole ((3-6) x 10(9) M-circle dot) provides a unique opportunity to investigate the origin of very high energy (VHE; E > 100 GeV) gamma-ray emission generated in relativistic outflows and the surroundings of supermassive black holes. M 87 has been established as a VHE gamma-ray emitter since 2006. The VHE gamma-ray emission displays strong variability on timescales as short as a day. In this paper, results from a joint VHE monitoring campaign on M 87 by the MAGIC and VERITAS instruments in 2010 are reported. During the campaign, a flare at VHE was detected triggering further observations at VHE (H.E.S.S.), X-rays (Chandra), and radio (43 GHz Very Long Baseline Array, VLBA). The excellent sampling of the VHE gamma-ray light curve enables one to derive a precise temporal characterization of the flare: the single, isolated flare is well described by a two-sided exponential function with significantly different flux rise and decay times of tau(rise)(d) = (1.69 +/- 0.30) days and tau(decay)(d) = (0.611 +/- 0.080) days, respectively. While the overall variability pattern of the 2010 flare appears somewhat different from that of previous VHE flares in 2005 and 2008, they share very similar timescales (similar to day), peak fluxes (Phi(>0.35 TeV) similar or equal to (1-3) x 10(-11) photons cm(-2) s(-1)), and VHE spectra. VLBA radio observations of 43 GHz of the inner jet regions indicate no enhanced flux in 2010 in contrast to observations in 2008, where an increase of the radio flux of the innermost core regions coincided with a VHE flare. On the other hand, Chandra X-ray observations taken similar to 3 days after the peak of the VHE gamma-ray emission reveal an enhanced flux from the core (flux increased by factor similar to 2; variability timescale <2 days). The long-term (2001-2010) multi-wavelength (MWL) light curve of M 87, spanning from radio to VHE and including data from Hubble Space Telescope, Liverpool Telescope, Very Large Array, and European VLBI Network, is used to further investigate the origin of the VHE gamma-ray emission. No unique, common MWL signature of the three VHE flares has been identified. In the outer kiloparsec jet region, in particular in HST-1, no enhanced MWL activity was detected in 2008 and 2010, disfavoring it as the origin of the VHE flares during these years. Shortly after two of the three flares (2008 and 2010), the X-ray core was observed to be at a higher flux level than its characteristic range (determined from more than 60 monitoring observations: 2002-2009). In 2005, the strong flux dominance of HST-1 could have suppressed the detection of such a feature. Published models for VHE gamma-ray emission from M 87 are reviewed in the light of the new data.
The quasar PKS 1510-089 (z = 0.361) was observed with the H.E.S.S. array of imaging atmospheric Cherenkov telescopes during high states in the optical and GeV bands, to search for very high energy (VHE, defined as E >= 0.1 TeV) emission. VHE gamma-rays were detected with a statistical significance of 9.2 standard deviations in 15.8 h of H. E. S. S. data taken during March and April 2009. A VHE integral flux of I(0.15 TeV < E < 1.0TeV) = (1.0 +/- 0.2(stat) +/- 0.2(sys)) x 10(-11) cm(-2) s(-1) is measured. The best-fit power law to the VHE data has a photon index of G = 5.4 +/- 0.7(stat) +/- 0.3(sys). The GeV and optical light curves show pronounced variability during the period of H.E.S.S. observations. However, there is insufficient evidence to claim statistically significant variability in the VHE data. Because of its relatively high redshift, the VHE flux from PKS 1510-089 should suffer considerable attenuation in the intergalactic space due to the extragalactic background light (EBL). Hence, the measured gamma-ray spectrum is used to derive upper limits on the opacity due to EBL, which are found to be comparable with the previously derived limits from relatively-nearby BL Lac objects. Unlike typical VHE-detected blazars where the broadband spectrum is dominated by nonthermal radiation at all wavelengths, the quasar PKS 1510-089 has a bright thermal component in the optical to UV frequency band. Among all VHE detected blazars, PKS 1510-089 has the most luminous broad line region. The detection of VHE emission from this quasar indicates a low level of gamma - gamma absorption on the internal optical to UV photon field.
Myriapods (e. g., centipedes and millipedes) display a simple homonomous body plan relative to other arthropods. All members of the class are terrestrial, but they attained terrestriality independently of insects. Myriapoda is the only arthropod class not represented by a sequenced genome. We present an analysis of the genome of the centipede Strigamia maritima. It retains a compact genome that has undergone less gene loss and shuffling than previously sequenced arthropods, and many orthologues of genes conserved from the bilaterian ancestor that have been lost in insects. Our analysis locates many genes in conserved macro-synteny contexts, and many small-scale examples of gene clustering. We describe several examples where S. maritima shows different solutions from insects to similar problems. The insect olfactory receptor gene family is absent from S. maritima, and olfaction in air is likely effected by expansion of other receptor gene families. For some genes S. maritima has evolved paralogues to generate coding sequence diversity, where insects use alternate splicing. This is most striking for the Dscam gene, which in Drosophila generates more than 100,000 alternate splice forms, but in S. maritima is encoded by over 100 paralogues. We see an intriguing linkage between the absence of any known photosensory proteins in a blind organism and the additional absence of canonical circadian clock genes. The phylogenetic position of myriapods allows us to identify where in arthropod phylogeny several particular molecular mechanisms and traits emerged. For example, we conclude that juvenile hormone signalling evolved with the emergence of the exoskeleton in the arthropods and that RR-1 containing cuticle proteins evolved in the lineage leading to Mandibulata. We also identify when various gene expansions and losses occurred. The genome of S. maritima offers us a unique glimpse into the ancestral arthropod genome, while also displaying many adaptations to its specific life history.
Objective: To examine the effect of plyometric jump training on skeletal muscle hypertrophy in healthy individuals.
Methods: A systematic literature search was conducted in the databases PubMed, SPORTDiscus, Web of Science, and Cochrane Library up to September 2021.
Results: Fifteen studies met the inclusion criteria. The main overall finding (44 effect sizes across 15 clusters median = 2, range = 1–15 effects per cluster) indicated that plyometric jump training had small to moderate effects [standardised mean difference (SMD) = 0.47 (95% CIs = 0.23–0.71); p < 0.001] on skeletal muscle hypertrophy. Subgroup analyses for training experience revealed trivial to large effects in non-athletes [SMD = 0.55 (95% CIs = 0.18–0.93); p = 0.007] and trivial to moderate effects in athletes [SMD = 0.33 (95% CIs = 0.16–0.51); p = 0.001]. Regarding muscle groups, results showed moderate effects for the knee extensors [SMD = 0.72 (95% CIs = 0.66–0.78), p < 0.001] and equivocal effects for the plantar flexors [SMD = 0.65 (95% CIs = −0.25–1.55); p = 0.143]. As to the assessment methods of skeletal muscle hypertrophy, findings indicated trivial to small effects for prediction equations [SMD = 0.29 (95% CIs = 0.16–0.42); p < 0.001] and moderate-to-large effects for ultrasound imaging [SMD = 0.74 (95% CIs = 0.59–0.89); p < 0.001]. Meta-regression analysis indicated that the weekly session frequency moderates the effect of plyometric jump training on skeletal muscle hypertrophy, with a higher weekly session frequency inducing larger hypertrophic gains [β = 0.3233 (95% CIs = 0.2041–0.4425); p < 0.001]. We found no clear evidence that age, sex, total training period, single session duration, or the number of jumps per week moderate the effect of plyometric jump training on skeletal muscle hypertrophy [β = −0.0133 to 0.0433 (95% CIs = −0.0387 to 0.1215); p = 0.101–0.751].
Conclusion: Plyometric jump training can induce skeletal muscle hypertrophy, regardless of age and sex. There is evidence for relatively larger effects in non-athletes compared with athletes. Further, the weekly session frequency seems to moderate the effect of plyometric jump training on skeletal muscle hypertrophy, whereby more frequent weekly plyometric jump training sessions elicit larger hypertrophic adaptations.
Objective: To examine the effect of plyometric jump training on skeletal muscle hypertrophy in healthy individuals.
Methods: A systematic literature search was conducted in the databases PubMed, SPORTDiscus, Web of Science, and Cochrane Library up to September 2021.
Results: Fifteen studies met the inclusion criteria. The main overall finding (44 effect sizes across 15 clusters median = 2, range = 1–15 effects per cluster) indicated that plyometric jump training had small to moderate effects [standardised mean difference (SMD) = 0.47 (95% CIs = 0.23–0.71); p < 0.001] on skeletal muscle hypertrophy. Subgroup analyses for training experience revealed trivial to large effects in non-athletes [SMD = 0.55 (95% CIs = 0.18–0.93); p = 0.007] and trivial to moderate effects in athletes [SMD = 0.33 (95% CIs = 0.16–0.51); p = 0.001]. Regarding muscle groups, results showed moderate effects for the knee extensors [SMD = 0.72 (95% CIs = 0.66–0.78), p < 0.001] and equivocal effects for the plantar flexors [SMD = 0.65 (95% CIs = −0.25–1.55); p = 0.143]. As to the assessment methods of skeletal muscle hypertrophy, findings indicated trivial to small effects for prediction equations [SMD = 0.29 (95% CIs = 0.16–0.42); p < 0.001] and moderate-to-large effects for ultrasound imaging [SMD = 0.74 (95% CIs = 0.59–0.89); p < 0.001]. Meta-regression analysis indicated that the weekly session frequency moderates the effect of plyometric jump training on skeletal muscle hypertrophy, with a higher weekly session frequency inducing larger hypertrophic gains [β = 0.3233 (95% CIs = 0.2041–0.4425); p < 0.001]. We found no clear evidence that age, sex, total training period, single session duration, or the number of jumps per week moderate the effect of plyometric jump training on skeletal muscle hypertrophy [β = −0.0133 to 0.0433 (95% CIs = −0.0387 to 0.1215); p = 0.101–0.751].
Conclusion: Plyometric jump training can induce skeletal muscle hypertrophy, regardless of age and sex. There is evidence for relatively larger effects in non-athletes compared with athletes. Further, the weekly session frequency seems to moderate the effect of plyometric jump training on skeletal muscle hypertrophy, whereby more frequent weekly plyometric jump training sessions elicit larger hypertrophic adaptations.