“toy models” with energy injection in different forms (e.g., direct isotropic momen- tum injection, turbulent stirring, thermal heating, cosmic-ray injection), acting on different spatial scales, and with different energetics. Our goal is to answer the following simple questions: (a) What form[s] of energy input (if any) can possibly quench a cooling flow, without generating un-realistic galaxy or halo properties in obvious disagreement with observations? For example, one could easily imag- ine scenarios which “quench” galaxies by simply expelling all the gas in the halo – but this would violate the wealth of observations indicating massive haloes re- tain most of the cosmological baryon fraction (e.g., Giodini et al., 2009, Gonzalez et al., 2013, Sanderson et al., 2013) (let alone more detailed constraints on den- sity/temperature/entropy profiles). (b) If any form of energy injection is viable, over what (order-of-magnitude) spatial scales must it act? In other words, if the energy is primarily deposited around the galactic nucleus, does this yield behavior that is “too explosive”? Does the injection have to be fine-tuned to occur where the cooling is occurring? (c) Likewise, what are the required energetics, and are they reason- able compared to observational constraints and plausible accretion efficiencies of supermassive black holes in these systems? (d) If a model quenches, what is the actual mechanism? For example, turbulent stirring could suppress cooling flows via heating through thermalized kinetic energy (viscous or shock-heating), or through providing non-thermal pressure which “holds up” the halo despite its cooling, or through bulk mixing of cold and hot gas. (e) Does the model quench by maintaining a low-SFR stable cool-core cluster or turning it into a non-cool-core cluster? If it is the latter case, how long (if ever) does it take to recover a cool-core after the injection is turned off?
cosmic value measured by WMAP, while the f 500 stars+gas+depl+ICL found for an average group differs from it at more than 3σ. Given the heterogeneity of the sample (see e.g. Figure 16b), for some objects the gap between f 500 stars+gas+depl+ICL and the WMAP5 value could be negligible or, conversely, statistically more significant for objects in the same bin of total mass, but at the two extremes of the distribution in f stars 500 . Unfortunately we do not have a measure of the gas mass fraction for individual objects, therefore we focus on the behaviour of the average object. We did likewise for the ICL by assuming a fixed fractional contribution of 11–22% across the entire mass range. Possible systematic effects introduced by our definition and estimate of the ICL contribution are discussed in § 2.4.5. Here we stress that they do not lead to an anomalously low BCG+ICL contribution to the total mass of the system. Thus the discrepancy at the groups regime in not erased by uncertainties on the stellar mass fraction. In the absence of evidence for a systematic and relevant underestimation of the gas mass fraction in our systems (see § 2.4.5), we interpret the discrepancy as a lack of gas, by 33%, at the group regime. This may be produced by feedback (stellar and/or AGN), as suggested by high-resolution cosmological simulations including cooling, star formation, supernova feedback, and AGN radio–mode feedback in galaxy clusters and groups (Puchwein et al. 2008, Bower et al. 2008, Short & Thomas 2008). Since supernova feedback appears to be insufficient to explain the L X –T relation (Puchwein
In the right-hand panel of Fig. 7, we plot the stellar half mass radius as a function of the maximum value of the circular velocity for all simulations with AGNfeedback. We see that, as the quasar host galaxies grow in size, their maximum stellar circular velocity drops, indicating that the galaxies gradually become less tightly bound. The peak cir- cular velocity and the stellar half mass radius have similar values for all haloes at z = 6.2 and all galaxies end up hav- ing roughly the same half mass radius of 6 −9 kpc at z = 3.3. While galaxy growth is particularly rapid at z & 4, it slows down at lower redshift, when the maximum circular veloc- ity reaches values of≈ 250 km s − 1 . Halo5 is simulated down to z = 2.6 and continues to show size growth at a rate similar to that seen in all targeted haloes at z < 4. One striking feature in the right-hand panel of Fig. 7 is the sud- den increase of the peak circular velocity in Halo1 between z = 6.2 and z = 5.7. Stellar images and circular velocity profiles show that a merger is happening at this point which increases the circular velocity. Afterwards, the galaxy shows the same evolution as the other quasar hosting galaxies, the galaxy grows in size and its maximum stellar circular veloc- ity drops gradually. We also note that for Halo1-NoAGN, the maximum circular velocity increases rapidly to extreme values . 2000 km s −1 , while the galaxy size remains close to ≈ 1 kpc (see Fig. 5).
where radio jets, launched by AGN, control the level of cooling of the hot gas in the most massive haloes (see Bower, Benson & Crain 2012; Harrison 2013, for a discussion on the two modes). While there is little doubt that star formation processes (e.g. stellar winds and supernovae) drive galaxy-wide outflows (e.g. Heckman, Armus & Miley 1990; Lehnert & Heckman 1996; Swinbank et al. 2009; Genzel et al. 2011; Newman et al. 2012; Bradshaw et al. 2013; see review in Veilleux, Cecil & Bland-Hawthorn 2005) and are an in- tegral part of galaxyevolution (e.g. Dalla Vecchia & Schaye 2008; Hopkins et al. 2013a), it is believed that AGN activity is required to drive the highest velocity outflows and are particularly important for the evolution of the most massive galaxies (e.g. Benson et al. 2003; McCarthy et al. 2011; Hopkins et al. 2013b; Zubovas & King 2014). X-ray and ultraviolet spectroscopy has shown that a high fraction, and potentially all, of high accretion rate AGN drive high-velocity outflows ( v ≈ 0.1c) close to their accretion discs (i.e. on subpar- sec scales; e.g. Blustin et al. 2003; Reeves, O’Brien & Ward 2003; Ganguly & Brotherton 2008; Tombesi et al. 2010; Gofford et al. 2011). However, are AGN capable of driving outflows over galaxy scales as is required by galaxy formation models? A diagnostic that is commonly used to identify outflowing gas over large scales is broad (i.e. exceeding that expected from galaxy dynamics), asym- metric and high-velocity [O III ] λ 5007 emission-line profiles. This
We discuss a numerical model for black hole growth and its associated feedback pro- cesses that for the first time allows cosmological simulations of structure formation to self-consistently follow the build up of the cosmic population of galaxies and active galactic nuclei. Our model assumes that seed black holes are present at early cosmic epochs at the centres of forming halos. We then track their growth from gas accretion and mergers with other black holes in the course of cosmic time. For black holes that are active, we distinguish between two distinct modes of feedback, depending on the black hole accretion rate itself. Black holes that accrete at high rates are assumed to be in a ‘quasar regime’, where we model their feedback by thermally coupling a small fraction of their bolometric luminosity to the surrounding gas. The quasar activity requires high densities of relatively cold gas around the black hole, as it is achieved through large-scale inflows triggered by galaxy mergers. For black holes with low accre- tion rates, we conjecture that most of their feedback occurs in mechanical form, where AGN-driven bubbles are injected into a gaseous environment. This regime of activity, which is subdominant in terms of total black hole mass growth, can be identified with radio galaxies in clusters of galaxies, and can suppress cluster cooling flows without the requirement of a triggering by mergers. Using our new model, we carry out TreeSPH cosmological simulations on the scales of individual galaxies to those of massive galaxy clusters, both for isolated systems and for cosmological boxes. We demonstrate that our model produces results for the black hole and stellar mass densities in broad agreement with observational constraints. We find that the black holes significantly influence the evolution of their host galaxies, changing their star formation history, their amount of cold gas, and their colours. Also, the properties of intracluster gas are affected strongly by the presence of massive black holes in the cores of galaxy clusters, leading to shallower metallicity and entropy profiles, and to a suppression of strong cooling flows. Our results support the notion that active galactic nuclei are a key in- gredient in cosmological structure formation. They lead to a self-regulated growth of black holes and bring the simulated properties of their host galaxies into much better agreement with observations.
The University of Southern Queensland’s (USQ’s) Tertiary Preparation Program (TPP) is a bridging program designed to enable people to acquire essential prerequisite knowledge and skills required for success in undergraduate study. Students who successfully complete the program qualify for direct entry into specified undergraduate programs at the University of Southern Queensland. Students coming into the TPP bring with them a valuable range of skills and prior educational and life experiences however are often unsure, lacking in confidence and may have encountered learning hurdles in the past. Therefore encouraging and motivating these students is a crucial factor in enabling them to acquire the skills and knowledge they require to transition successfully. Assessment is an integral element of teaching and learning that should enhance learning. Feedback is an essential element in this loop as it has the potential to have a significant impact on students’ learning.
Figure 5 shows the evolution in the HR diagram of 3 M models computed with a solar chemical composition and a solar-calibrated mixing-length parameter. The rotating model has an initial velocity on the ZAMS of 150 km s − 1 . By comparing models computed without overshooting from the convective core, we note that the inclusion of rotation results in a widening of the main sequence with a significant increase of the stellar luminosity for the rotating model compared to the non-rotating one. In particular, the core helium-burning phase is shifted to higher values of the luminosity when rotational effects are taken into account. These changes are due to rotational mixing, which brings fresh hydrogen fuel into the convective core and transports helium and other H-burning products in the radiative zone.
There are however limitations to this work. This is a single school study and only two academic years after the intervention have been included; it is possible that later changes in quality may occur in either direction. The faculty members who devised the scale also scored the EPs and led development sessions and visits; these individuals are all part of a small close team and are likely to be subj ect to ‘group think.’ We chose to use the practice as the unit of analysis rather than the individual tutor. This was a deliberate choice since students are placed with practices, not individual tutors, and each practice is a learning community with a distinctive learning environment.  However, it is likely that some of the variation in EP quality within a practice (43% of all variance) reflects differences between relatively skilled and unskilled tutors rather than individual tutor variability. If so, then the true reliability of the instrument in discriminating between tutors will be better than we have estimated. This is a naturalistic, uncontrolled study which makes it difficult to conclude which aspects of the overall QI intervention have the greatest impact on the quality of written feedback. Next steps
360-degree feedback, also known as multi-source assessment, is a process in which someone’s performance is assessed and feedback is given by a number of people who may include their manager, subordinates, colleagues and customers. Assessments take the form of ratings against various performance dimensions. The term ‘360-degree feedback’ is sometimes used loosely to describe upward feedback where this is given by subordinates to their managers. This is the most common approach and is more properly described as 180-degree feedback. Feedback may be presented direct to individuals, or to their managers, or both. Expert counselling and coaching for individuals as a result of the feedback may be provided by a member of the HR department or an outside consultant. 360-degree feedback or a variant of it was used by 30 per cent of the respondents to the 2005 e-reward survey.
For this fitting method, the PDF that represents each galaxy must integrate to a total probability of one over the stellar mass range of detection. Since our sample is apparent magnitude limited, the relevant stellar mass interval for this integration varies as a function of redshift, and for each galaxy in our sample, the lower integration limit is set by the sample mass limit at its redshift, i.e. the sliding sample mass limit function described previously. For the individ- ual structural components of multi-component galaxies, applying a lower integration limit set by the systemic mass limit would lead to integration limits that do not necessarily encompass the measured component mass itself (depending on the component-to-total-mass ratio). As a result, we take the lower integration limits for compo- nents to be equal to the systemic mass reduced by the component- to-total-mass ratio of each component. To avoid biasing the mass function fits for the separate components, we must also consider whether or not individual component masses would fall below the overall sample mass limit if they were found in isolation. Thus, we omit galaxy components from our fits if they are below our over- all mass fitting limit. We do not attempt to fit mass distributions below a global limit of log(M ∗ /M ) = 8, below which we expect significant surface-brightness-based incompleteness in GAMA (see Baldry et al. 2012 for further details). Through this variable mass limit approach, each galaxy or galaxy component’s PDF is nor- malized to account for our redshift-dependent selection function, analogous to the application of V/V max sample weights.
In young MSFRs in which there has not yet been time for any massive star to explode as a supernova, the diffuse X-ray emission must result from the action of stellar winds. However, in older clusters where some of the massive stars have exploded one still might not detect any signature of a SN explosion because the effect of a SNR on the ther- mal properties of the hot cluster gas is likely to be rela- tively short-lived. This time scale is generally believed to be ∼ 10 4 yr (e.g. Kavanagh et al. 2011). For this reason, most studies of stellar clusters prefer a wind based explanation for the diffuse X-ray emission, though Ezoe et al. (2009) favour a recent SN explosion in their study of the East- ern Tip of the Carina nebula. A distinction exists between individual stellar clusters, and larger scale regions of star formation which create superbubbles where multiple cav- ity supernovae are believed to be responsible for the diffuse emission (such as those of 30 Doradus, e.g. Chu & Mac Low 1990; Townsley et al. 2011).
One way of going about a systematic and productive approach to making the most of feedback is to prepare for yourself a simple pro- forma, and have copies of it available for each episode of feedback on your work, so that you can collect together the complete pro- formas as an ongoing record of how your work is developing. In other words, you can take charge of the process of keeping track of how your work is progressing towards earning you the good degree you’re aiming towards. All the better if you have copies of such a pro- forma ready to use each time you gain feedback, so that capturing the essence of the feedback becomes a matter of routine rather than a luxury.This also gives you the opportunity to separate your reflections on particular instances of feedback from the actual individual pieces of work, so that you distance yourself from the first thoughts you got when receiving the feedback, and move onwards and upwards with the significant trends, enabling you to continuously adjust your approaches.
The synthetic approach is a very useful tool for testing scenarios and hypothesis about the Galaxy formation and evolution. It allows to better use the informations from kinematics, abundances and density distributions of the stellar populations in order to interpret the data in terms of evolution. It is also useful to simulate the data and for this purpose is used in the preparation of the Gaia mission . It is generally a challenge to analyse multivariate data. New efficient methods will need to be developed in order to get profit from such a large and complex survey. To this purpose we also prepare ourself to use the BGM model for bayesian classification of the Gaia data, and for overall comparisons and data assimilation of the whole survey for the benefit of understanding in much more detail the overall scheme of Galaxy formation and evolution.
On relatively short timescales, eco-evolutionary feedback can be expected to alter the socio- ecological dynamics of particular forms of sociality, as compared to dynamics without evolu- tion. For instance, in the context of predator-prey co-evolution, model studies have revealed that eco-evolutionary feedback can affect the number of predator and prey species that can co- exist, as well as shortening the period of population dynamics . On relatively long time- scales, eco-evolutionary feedback is a prerequisite for the origin and evolution of new forms of sociality: Evolution changes the selection pressures and therewith the prevailing social pheno- types and their socio-ecological relationships that characterize a social system. The analogy with evolutionary game theory, where socio-ecological conditions are simplified into games with a set of strategies and payoffs, is that eco-evolutionary feedback alters the dynamics within games on short timescales, and changes one game into another on longer timescales (e.g. one with or without a cooperative dilemma). The long-term process concerns shifts in functionality of traits, such as most likely occurred in primates, who groom much more frequently than would be expected for its original purpose of hygiene : It is possible that during the evolu- tion of grouping in primates, evolutionary pressures on grooming were altered, and grooming became co-opted for social bonding, enabling new kinds of sociality to evolve.
(Stetsenko, 2010). Expanding upon a Vygotskian perspective on learning, identity is ‘negotiated within a particular context, rather than achieved as a result of a stage or age related theory’, and identity is discursively constructed ‘through relationships with others in social practices that partially dialectically constitute a context’ (Vadeboncoeur et al., 2011:227). Stetsenko (2010) is helpful in drawing from Vygotsky when thinking about how particular experiences with feedback each play a role in shaping what students learn and how they define themselves. Especially in regards to formative feedback, Stetsenko & Arievitch (2004) provide the idea of a ‘meaningful life project’, through which the process of identity is never complete; rather, the self is always in a state of becoming, ‘enacted through what we do in the world’ and the qualities attributed to those actions (p. 9). Because such enactments are
The sense of hearing has an equally important role in the overall perception of spatial understanding. Aural perception provides information about our surroundings, and particularly objects that we encounter, in a similar manner as visual perception. Auditory perception can provide information about different states of the environment. For example, the sounds of footsteps when jogging provide subconscious information concerning the type of the terrain or the height of stairs (Schmidt and Lee, 2011). Auditory perception can also be associated to physical and tactile actions. An increasing number of handheld electronic devices such as mobile phones and tablets provide artificial audible feedback in an attempt to mimic the audible feedback that may occur naturally from those actions. When typing on a touchscreen device, there is no auditory feedback from the physical contact as found with the traditional typewriter or with computer keyboards. The auditory feedback enhances and confirms the actions of the user. Similarly, this applies to the artificial sound of a shutter on a portable digital camera. The sound of the open/close shutter is artificially produced as there is no mechanical component within a digital camera to produce that sound. The shutter sound informs the user and others around her that a photo was taken. The auditory associations that were previously established with pre-digital cameras are maintained. Both of these examples demonstrate the importance of auditory feedback in relation to our actions. The auditory feedback associated with one’s action is similar to what Gibson describes as the combination of tactile and kinaesthetic senses with visual perception. In ta similar manner, auditory perception has a bidirectional influence with tactile and kinaesthetic senses. The human ability to correlate actions with sounds is fundamental in musical performance experience and in particular within technology mediated performances. For a convincing performance, time differences in the action–reaction relationship between aural, tactile and visual cues are essential (Emmerson, 2007, p. 109).
Analyses of the use of audio feedback were conducted as early as the 1970s when instructors experimented with giving audio comments to students using cassette tapes (Anson, 1997; Huang, 2000; Klammer, 1973; Pearce & Ackley, 1995; Sommers, 1989). With the emergence of digital technology in the 1990s, additional studies have been conducted analyzing the use of digital audio in providing feedback to student work. Swan Dagen, Matter, Rinehart, and Ice (2008) found that feedback was richer in audio format, with more adjectives used in audio than in written commentary; that students perceived they had received more feedback when given audio commentary than in written commentary; and that instructors perceived they had given more detailed feedback in audio commentary than in written commentary. Merry and Orsmond (2008) report that students found audio commentary more in depth in offering strategies in improvement, while they also note that tutors discerned that they had offered more examples and a higher quality of feedback through audio than through written commentary. Sipple (2007) notes that developmental writers found audio comments, even for problematic papers, made students more confident in their writing because they "provided more genuine and frequent praise" (p. 24).
The investigations of substructure have so far been dominated by studies of the two main galaxies in the Local Group (M31 and the Milky Way), but it is critically important to extend them to more distant galaxies – both to build up better statistics and to understand how the properties of substructure depend systematically on galaxy type and environment. Although progress has been made along these lines (see Atkinson, Abraham & Ferguson 2013, and references therein), it has been almost exclusively based on photometry, while missing the dimension of velocity that is obtained directly through spectroscopy. Such information is indispensable for inferring the three-dimensional (3D) anatomy of substructures, the time-scales of orbital decay, the progenitor properties including total mass, and the dynamical interplay between satellite and host galaxies. While these aspects can sometimes be probed through gas dynamics (e.g. Iodice et al. 2003), most infalling satellites are gas poor, in a reflection of the morphology–density relation that is probably caused by quenching during the accretion process (e.g. Einasto et al. 1974; Mayer et al. 2006; Grcevich & Putman 2009; Geha et al. 2012; S´anchez-Janssen et al. 2013; Slater & Bell 2013).