Figure 3. 1: Existence of mutual trust and commitment as facilitating factor of cooperation between company and HE institutions, by size of the company (in per cent) 100 90 82 80 70 60 50 40 30 20 75 79 68 67 60 63 67 66 61 58 49 52 45 40 39 Large SME Micro 17 20 Bulgaria Hungary Poland Slovenia Spain Total Question B6: How much do the following statements facilitate your organisation’s cooperation with HE institutions? Responses 5 to 7 on a scale of answers from 1=”Not at all” to 7=”To a very high extent”. In general the existence of mutual trust as a driver for university-business cooperation is higher in large companies, followed by SMEs and micro companies. This can be explained by the fact that as seen from the results above large companies are also more willing to cooperate with higher education institutions and their cooperation is often already long-lasting what allows that the trust and commitment between the two stakeholders is built. Not surprisingly the mutual trust and commitment is the factor that promotes the cooperation with universities to a high extent among those companies which already have high extent of university-business cooperation, followed by companies with medium extent of cooperation and minor or non-extent. Regarding the economic sector of companies' activities there are no major differences among them. The companies were also requested to identify the main barriers they are facing with when it comes to the cooperation with the higher education institutions. The barriers listed from the most relevant to the least are the following: Bureaucracy within or external to the higher education institutions ⦋1⦌ Different time horizons between higher education institutions and business ⦋2⦌ Different motivations and values between higher education institutions and business ⦋3⦌ Difficulty in finding the appropriate persons within higher education institutions ⦋4⦌ Different modes of communication and language between higher education institutions and business ⦋5⦌ Limited ability of knowledge transfer ⦋6⦌ Higher education institutions want to publish confidential results ⦋7⦌ Table 3.2: Comparison ranks of barriers to UBC among employers, academics and HEI representatives Sources: EMCOSU analyses, Xxxxx et al. (2011b, 69) The current financial crisis ⦋8⦌ Barriers to UBC Employers Academics and HEI representatives Bureaucracy within or external to the higher education institutions 1 4 Different time horizons 2 1 Different motivations an...
Figure 3. 1: The Game In Period 1 following a shock to the political system, 15 nature
Figure 3. All Databases Database Devices Archive Database in a Folder. File Viewer window only
Figure 3. 5: Signal-to-noise ratio measurements of the disk flux of Xxxx 15-788. Top: Signal- to-noise ratio measurements in circular apertures around the best fit ellipse (orange line) for the Ks-band data from Section 3.5.3. The blue apertures contain flux of ring A according to the applied 5σ criterion, whereas the gray apertures reside within the background dominated regime. Bottom: Signal-to-noise ratio within the circular apertures from the top panel, sorted by position angle. The gray and blue areas mark the regimes below and above the 5σ threshold to distinguish background and disk apertures, respectively. Table 3.4: Best fit parameters of the ellipse fitting. Parameter Best fit value δx [pix]a 0.96 ± 1.17 δy [pix] 1.12 ± 2.01 a [pix] 32.56 ± 0.81 b [pix] 30.39 ± 2.12 ϕ [◦ ] 76 ± 16 i [◦ ] 21 ± 6
Figure 3. 4: Total fraction of the ini- tial mass of an SSP ejected by AGB stars at time t = ∞ as a func- tion of initial stellar metal mass frac- tion, assuming the yields of van den Hoek & Groenewegen (1997) (black, thick lines), Marigo (2001) (red, medium thick lines), or Xxxxxx et al. (2004) (blue, thin lines). The calculations assume a Chabrier IMF and integrate the yields over a stel- lar initial mass range [0.8, 6] M⊙, but the fractions are normalized to the mass range [0.1, 100] M⊙. Differ- ent yield sets predict similar ejected mass fractions. The ejected mass fraction is insensitive to metallicity. puffs up and is eventually shed, causing the star to lose up to 60 % of its mass. Prior to the AGB phase, material in the core (where most of the heavy elements reside) is dredged up into the envelope via convection. As a result, the ejecta are particularly rich in carbon and nitrogen. Building on pioneering work by Xxxx & Xxxxxx (1978) and Xxxxxxx & Xxxx (1981), various groups have published AGB yields (x.x. Xxxxxxxxx & Xxxxxxxxxx 1997; xxx xxx Xxxx & Xxxxxxxxxxx 1997; Xxxxxx 2001; Xxxxxxx et al. 2001; Xxxxxxx et al. 2002; Xxxxxx et al. 2004). Table 3.3 outlines the extent of the resolution (in mass and metallicity) of the AGB yields of van den Hoek & Groenewegen (1997), Xxxxxx (2001) and Xxxxxx et al. (2004), which are some of the most complete sets for our purposes. These yields are compared in Fig. 3.3, which shows the abundance relative to hydrogen, in solar units6, of various elements in the ejecta as a function of stellar metallicity. These calculations are for an SSP with a Chabrier IMF and the mass range [0.8, 6] M⊙ at time t = ∞. The yields agree very well at solar metallicity, and for the case of helium, this agreement extends to lower metallicities. However, for nitrogen, oxygen, and particularly carbon, different yields sets give very different results at low metallicities. We show in Fig. 3.4, for each yield set, the integrated fraction of the initial SSP mass ejected by stars in the mass range [0.8, 6] M⊙ at time t = ∞, normalized to the total initial stellar mass over the range [0.1, 100] M⊙. The ejected mass fractions are very similar for the different yield sets. In this work we use the yields of Marigo (2001). Although these only go up to 5 M⊙, they form a complete set with the SN Type II yields of Portinari et al. (1998) since they are both based on the Padova evolutionary tracks. Indeed, there are very few yield pairings that form a consiste...
Figure 3. 1: A graph of online resource allocation between SDs and the MEC servers. Per time-slot t, the mth SD receives the arriving workload bm and stores them in the queue qm. Then, the workload in the queue qm will be allocated to t t t locally process dm and offload to the MEC servers amn, ∀n ∈ N . The nth t m=1 t MEC server receives the amount of workload ΣM amn and stores them in the queue qM+n. Finally, the nth MEC server executes the amount of zn out of t t t the workload in its queue qM+n, which are recorded by local controller (LC).
Figure 3. . a) Rolling mill components to be considered in the thermal crown model, b) Circular ring of roll Figure 3a shows a rough layout of a quarto mill stand with its work and back-up rolls, as well as a schematically indicated work roll cooling system. The contact between the warm strip and the cooler work roll causes a heat transfer into the work roll. Within the work roll, the increased shell temperature leads accordingly to a heat flow in the direction of the roll core. The heating is counteracted by heat dissipation to the back-up rolls, to the water-cooling systems and to the environment. The temperature distribution within the roll in axial and radial direction leads to a thermal expansion of the roll body. The resulting crown of the rolls has a direct influence on the roll gap and thus on the thickness profile and flatness of the rolled strip. On the other hand, the roll gap geometry is actively influenced by the axial displacement of the work rolls provided with a special crown. This changes the contact zones between the working roll and the strip, as well as the cooling and the back-up roll, which is also considered in the thermal crown model. For the modelling of the thermal crown model, basically [2] is followed, except for specific adaptations in this project. According to [4,5], the differential equation of the temperature field in the cylindrical coordinate system expanded by the z-coordinate is as follows: 𝜕𝑇 𝜕2𝑇 1 𝜕𝑇 𝜕2𝑇 𝜕𝑡 = 𝛼 (𝜕𝑟2 + 𝑟 𝜕𝑟 + 𝜕𝑧2)
Figure 3. 2.2.1.1 Some actors speak in favour of the creation of a platform grouping all of the calls for tenders related to PPAs The standard agreement prepared by FEE provides that the PPA may be entered into with or without a support mechanism. However, in practice, as explained below, companies would rather choose a PPA related to an installation that does not benefit from a support mechanism, so that they can benefit from GOs. The conditions precedent will naturally depend on the project maturity. The model chosen by FEE is that of a physical PPA, which relates to the selling of electricity, guarantees of origin, and xxxxx- xxx capacity certificates. Both the FEE standard agree- ment and the guide published by La Plateforme Verte are about bilateral GC PPAs only, i.e. GC PPAs entered into between a sole buyer and a sole producer. These standard agreements would have to be adapted in the event there are several customers and/or several producers.
Figure 3. Mindfulness as a buffer of the prospective relation between emotional distress and reported somatic symptoms: a SEModel
Figure 3. N-Terminal protein sequencing of bovine neutrophil gelatinase-associated lipocalin (bNGAL). N-Terminal protein sequencing of bNGAL (20 µg) was performed by the automatic Xxxxx degradation procedure using an Applied Biosystems gas-phase sequencer, model 473A (Applied Biosystems, Foster City, CA). The sequencing result of bNGAL, presented by the standard one-letter code for AA, is aligned to the predicted sequence of bNGAL (National Center for Biotechnology Information: XP_605012) and published sequences of human neutrophil gelatinase-associated lipocalin (hNGAL), mouse 24p3/uterocalin (24p3), and rat α2-microglobulin-related protein (A2UMRP; Xxxxxxxx et al., 2000). The shaded box represents motif 1, a highly conserved sequence among lipocalins (Flower et al., 1991). bNGAL was N-linked glycosylated. Based on the aver- age Mr of 2,200 for a complex glycan (Xxxx et al., 1988), the difference in Mr of 2,000 observed on SDS-PAGE before and after deglycosylation suggests that mono- meric bNGAL (Mr 25,000) bears one N-linked glycan. Glycan Structures Present on bNGAL Monosaccharide analysis of bNGAL showed the pres- ence of mannose, N-acetylgalactosamine, N-acetylglu- cosamine, and N-acetylneuraminic acid (Table 1). Fu- cose and galactose were hardly detected, which sug- gested that, in the event of N-linked glycosylation of bNGAL, galactose was substituted with N-acetylgalac- tosamine. This has previously been observed for other N-linked glycoproteins produced in bovine milk and has been ascribed to the presence of an N-acetylgalactosam- inyl transferase in mammary gland epithelium (Xxx xxx Xxxxxxxxxx et al., 1999). The MALDI-TOF analysis of desialylated bNGAL glycans showed 7 significant peaks (Figure 5, peaks A–G). The proposed glycan com- positions and structures, deduced from the mass-to- charge (m/z) values of 6 of these peaks, are shown in Table 2 and Figure 6, respectively. The observed m/z value of each proposed structure differs maximally by
