Universal Keygen Generator 2018 Free Download Full Overview Technology has made our lives much Luxury and here is one of the best software’s that prove exactly that. However, all considered, advances in technology are for our general right, so we ought not to complain. The Free news is that you can now activate any serial key with Universal Keygen Generator.
Many freeware applications are provided to users only for a short period or on a trial basis with the expectation that you buy the application in the long haul. Most of these requests are way too expensive for many. To counter this, developers have come up with Universal keygen generator 2018 which will be very useful particularly to businessman and students who use most of these applications, but are restricted by the serial key only. The Universal keygen generator 2018 is therefore very essential in helping you use the full version of any software or application.
The best thing about the Key Generator free is that you can use it to make trial versions of your software work for longer and for free.You can use this tool and all its features and tools without any prompt or pop- up messages requiring you to activate your application. You can download the software as well as register your applications free of charge. It’s that simple and from then on you can use all your applications that were previously on a trial basis to full capacity without an extra sweat. The Universal keygen generator Full Download will prove very helpful for all and sundry, it is affordable, fast and efficient, and most importantly to all geeks – non-restrictive!
32 LIVES is a transparent 32-bit to 64-bit Audio Units and VST plug-ins adapter which enables you to run your favorite 32-bit-only plug-ins, such as Vanguard, VB3 and TC PowerCore plug-ins, in your latest 64-bit DAW. There are no additional windows to open and no redundant routings to make. Your favorite 32-bit plug-ins will appear in your 64-bit DAW as if they were native 64-bit plug-ins.
32 LIVES is compatible with virtually all 64-bit Audio Units and VST host applications, including Logic Pro X, Cubase, Ableton Live and Studio One. WELCOME BACK TO YOUR WORKFLOW Moving forward with new technologies, modern Digital Audio Workstations bring many new features and improvements utilizing a new 64-bit architecture, which enables to break the 4GB memory access barrier of the 32-bit architecture and access up to 16 Exabytes of RAM. Unfortunately, older 32-bit plug-ins will no longer work in your latest 64-bit-only DAW. Previous projects, created using an earlier version of your favorite 32-bit software, will not load correctly in your latest 64-bit workstation. Enter 32 LIVES. YOUR PLUG-INS ARE NOW RESURRECTED 32 LIVES is capable of generating transparent 64-bit Audio Units and VST adapters for your tried-and-true 32-bit legacy plug-ins, helping you to cross over to your latest 64-bit DAW smoothly and transparently.
Older sessions saved with your 32-bit DAW will fully load into your 64-bit DAW, including all presets, parameters and automation; no special re-wiring or routing is required. All your 32-bit-only plug-ins will be displayed in the plug-ins menu as they always have been.
Modal shifts hold considerable potential to mitigate carbon emissions. Electric bikes (e-bikes) represent a promising energy- and carbon-efficient alternative to cars. However, as mobility behaviour is highly habitual, convincing people to switch from cars to e-bikes is challenging. One strategy to accomplish this is the disruption of existing habits—a key idea behind an annual e-bike promotion programme in Switzerland, in which car owners can try out an e-bike for free over a two-week period in exchange for their car keys. By means of a longitudinal survey, we measured the long-term effects of this trial on mobility-related habitual associations. After one year, participants' habitual association with car use had weakened significantly.
This finding was valid both for participants who bought an e-bike after the trial and those who did not. Our findings contrast the results of other studies who find that the effect of interventions to induce modal shifts wears off over time. We conclude that an e-bike trial has the potential to break mobility habits and motivate car owners to use more sustainable means of transport. Export citation and abstract. Shifts toward more environmentally friendly transport modes hold considerable potential to mitigate global carbon emissions.
Especially in developed countries, cars are still the main mode of transportation, but electric bikes (e-bikes) represent an attractive alternative. This is not only due to their high energy and carbon efficiency, but also a variety of other features, including cost savings, health benefits and avoiding traffic congestion ,. While e-bikes may also replace walking or conventional biking, the evidence from the available field studies suggests that purchasing an e-bike results in considerable substitution of car usage , –. However, while e-bike sales have shown rapid growth rates, e-bikes still represent a niche product that appeals mostly to the 'dark green' or 'early adopter' segments , –. Moving e-bikes from a niche to the mainstream is challenging. One major reason for this is that most travel behaviour is highly habitual – and generally occurs in stable contexts (including entrenched travel routes and times and established travel purposes, as well as the utilised modes of transportation), making behavioural change difficult ,.
Yet, disruptions of stable contexts have demonstrated a considerable potential for altering individuals' mobility-related habits. Examples include highway closures, which may nudge car drivers to try out public transportation , or strikes, such as the London Underground strike of 2014, which led to lasting changes in mobility behaviour among about 5% of all affected travellers.
In addition, natural disasters, such as hurricanes , and personal life events, such as a serious injury , qualify as disruptions that are sufficiently strong to induce changes in individuals' mobility patterns. While external disruptions often occur in a sudden and random manner, many behaviour-change programmes use the same principle. They deliberately introduce contextual changes to promote a shift toward more sustainable behaviour.
In the mobility field, providing people with the option of experiencing alternative modes of transportation seems promising in breaking deep-rooted mobility habits, especially if these opportunities co-occur with contextual changes in individuals' private lives (e.g. Moving) ,. For instance, the results of previous research suggest that providing a free travel card for public transportation to habitual car drivers can trigger significant changes in modal choices toward more efficient modes of transportation –. Yet, longitudinal analyses that assess the long-term effect of these interventions are scarce, and those that exist suggest that for most participants, the effects of the interventions start wearing off after the end of the intervention ,.
While most of the available interventions focus on the switch from cars to public transportation, there have also been three studies on e-bikes ,. These studies showed that trying out an e-bike for two to four weeks is a promising approach to breaking participants' mobility habits, resulting, inter alia, in a higher willingness to purchase an e-bike , lower habitual association with car use directly after the trial and interest in using e-bikes more often in the future. However, none of the previous studies provided a longitudinal assessment of whether the context disruption caused by an e-bike trial is strong enough to induce long-term shifts in participants' mobility-related habits. This is the main objective of the present study. The annual Bike4Car programme in Switzerland seeks to break car drivers' habitual behaviour. In this programme, organised by a Swiss environmental nongovernmental organisation (NGO), car owners are offered a free trial of an e-bike over a 2 week period in exchange for their car keys.
In 2015 Bike4Car was implemented in collaboration with bike retailers making e-bikes available to the participants; the Swiss Federal Office of Energy, which supported the programme with an intense national ad campaign (TV, internet and posters); and 32 cities responsible for local promotion. Between May and September 2015, 1854 car owners participated in Bike4Car.
After the end of the programme, participants were offered a coupon to purchase an e-bike for a reduced price. Reductions varied by retailer. The largest participating retailer offered a reduction of 500 CHF (approx. 425 Euro), covering around 20%–25% of the price of an e-bike.
By November 2015 10% of participants used their coupon to buy an e-bike. 2.2. Data collection.
The following analysis is based on a longitudinal series of two online surveys of all participants of the 2015 Bike4Car programme. The organising NGO sent the link to the first questionnaire by email to participants immediately after they signed up for the trial. 5.1 dolby digital tamil songs free download. Between May and July 2016, about one year after the start of the programme, all participants were asked to fill out a follow-up questionnaire.
32 Lives Keygen
To ensure a sufficiently high response rate, email reminders were sent to the participants in each study wave. As an incentive for participation, all respondents were entered into a lottery for attractive e-bike- or bike-related prizes sponsored by the programme partners. Questionnaires were available in German, Italian and French, which are the three official languages of Switzerland.
As almost no participants chose the Italian option, the following analyses focus on the German and French questionnaires only. The responses used for the analyses came from N = 405 participants who fully completed the pre-trial questionnaire. Compared to the overall participation in the Bike4Car programme ( N = 1854), this corresponds to a response rate of 22%. Moreover, N = 300 participants completed the follow-up questionnaire (response rate = 16%). The responses used for the analyses in this paper come from the N = 144 participants who completed both the pre-trial and follow-up questionnaires (combined response rate = 8%, see supplementary materials A for further details available at ). Table provides an overview of the samples. It shows that, compared with the Swiss population –, well-educated men were overrepresented among the survey participants.
In addition, more than half of participants lived in households with two or more cars indicating that the programme reaches a target group with a real potential for mobility-related energy savings. The sample characteristics of the participants were comparable in the pre-trial and follow-up questionnaires. Table 1. Sociodemographic characteristics of the sample compared to the Swiss population.
Sociodemographic characteristics Swiss population statistics Pre-trial ( N = 405) Follow up ( N = 300) Pre-trial and follow up ( N = 144) Male 50% 65% 70% 72% Mean age (SD) 42.1 43.3 (10.5) 43.9 (10.4) 43.6 (10.7) University degree 27% 57% 56% 54% Vocational training 38% 29% 32% 31% 0 car in household 22% 2% 2% 1% 1 car in household 49% 44% 45% 43% 2 or more cars in household 29% 54% 53% 56% aEducation level of permanent population in Switzerland between 25 and 65 years old. BAlthough car owners were the programme's target group, interested people who did not own a car were not excluded from the trial. Table 2. Mean sum scores of means mobility-related habitual associations for the pre-trial questionnaire and a representative Swiss sample. Means (M) and standard deviations (SD). Sum score Pre-trial M ( SD), ( N = 405) Representative sample M ( SD), ( N = 1476) t (df), p-value Effect size r Car 4.32 (2.00) 3.47 (2.63) 8.53 (404), p. Of all modes of transportation, participants displayed the strongest initial (i.e. Pre-trial) habitual associations with cars, followed by bicycles and walking.
Participants in the e-bike trial reported stronger habitual associations with car, bike and e-bike use compared to a representative sample of the average Swiss population (see table ). This data has been collected in a separate survey among a sample that is representative to the Swiss population with respect to characteristics such as gender, age, educational level and income. The observed differences between both samples are another indicator that the programme reached a relevant target group. Table displays the mean sum scores for the different means of transport reported in the pre-trial and follow-up questionnaires. After one year, participants showed significantly weaker habitual associations with car and motorbike use and significantly stronger habitual associations with e-bike use compared to the associations displayed in the pre-trial questionnaire. This means that the average number of times that participants mentioned cars and motorbikes dropped significantly one year after participating in the programme, while the number of times participants mentioned e-bikes increased significantly.
Next, we analysed whether there were differences in the observed shifts of habitual associations between those participants who bought an e-bike after the trial (i.e. Buyers, n = 53) and those participants who had not purchased an e-bike (i.e.
Non-buyers, n = 91). Table displays the respective mean sum scores of habitual associations for buyers and non-buyers.
Table 3. Comparison between the mean sum scores of mobility-related habitual associations in the pre-trial and follow-up questionnaires. Means (M) and standard deviations (SD). Sum score Pre-trial M ( SD), ( N = 144) Follow-up M ( SD), ( N = 144) t (df), p-value Effect size r Car 4.26 (1.99) 3.74 (1.91) 3.54 (143), p.
Table 4. Comparison of mean scores of mobility-related habitual associations in the pre-trial and follow-up questionnaires for buyers and non-buyers. Means (M) and standard deviations (SD). Sum score Buyers ( n = 53); M ( SD) Non-buyers ( n = 91); M ( SD) Pre-trial Follow-up Pre-trial Follow-up Car 3.85 (1.69) 3.04 (1.13) 4.51 (2.12) 4.14 (2.14) E-bike 0.42 (1.28) 2.06 (1.73) 0.24 (0.83) 0.23 (0.79) Notes: Sum scores are between 0 and 9, with 9 signifying the most pronounced habitual association related to specific means of transport. For habitual associations with car use, the repeated-measures ANOVA showed a significant main effect of time, F(1) = 14.53, p. In line with previous research , –, our study findings indicate that disruptions of individuals' mobility context may trigger changes in habitual travel choices. Bearing in mind that our study did not measure actual habits but rather habitual associations it provides strong evidence that exchanging one's car keys for an e-bike for just a few weeks influences long-term habitual associations with car usage, and that this change persists even a year after the end of the intervention.
This contrasts the findings of other studies who find that the effect of interventions wears off over time ,. While this decrease in habitual associations with car use was most pronounced for participants who did buy an e-bike following the trial, participants who did not change their mobility context displayed a significant long-term shift away from car use as well. Furthermore, it is noteworthy that this shift in habitual associations could be observed after a winter season has passed; which is usually cold, rainy and sometimes even snowy in Switzerland, and thus not ideal for riding a bike—electric or not.
We can point to several plausible explanations for the observed persistence of the intervention's effect mobility-related habitual associations. One is the strength of the habit disruption induced by the programme, as participants were required to hand over their car keys for the two-week duration of the trial. Hence, participants could not rely on their cars for commuting, shopping or leisure activities; instead, they had to organise their day-to-day activities around their e-bikes. Most studies that offer participants free use of public transportation as an alternative to cars may not have been able to provide a strong enough disruption, as they do not require participants to completely forgo the use of their cars.
Furthermore, while habitual car drivers may have some misconceptions about public transportation , most people in Switzerland have experience with using it, which makes it improbable that they are positively surprised by a trial. In contrast, since it is still a niche mode of transportation, most participants may not have any previous experience with riding an e-bike. Hence, during the two-week trial, participants may have had novel, first-hand experiences of the benefits of e-bikes, including health benefits, time savings or the realisation that steep slopes—a key barrier to conventional cycling , —are much less of a challenge than they may have expected. In this study it was not possible to track participants' actual travel behaviour over time. This is an important direction for future research using for example tracking devices and travel diary studies. Still, the observed shifts of participants' mobility-related habitual associations hint that e-bike trials hold a considerable potential in terms of promoting sustained energy and carbon efficient travel behaviour.
Thus, policy-makers should consider supporting programmes that enable people to experience the benefits of novel means of transport directly. Creating options for such experiences has the potential for promoting sustainable mobility behaviour. Furthermore, such measures may also be useful in inducing behaviour change related to the use of other energy-related services. This research project is part of the National Research Programme 'Managing Energy Consumption' (NRP 71) of the Swiss National Science Foundation (SNSF). Further information on the National Research Programme can be found. The project is also part of the Swiss Competence Center for Research in Energy, Society and Transition (SCCER CREST), Work Package 2 Change of Behaviour, for further information see.
We would like to thank myblueplanet for their cooperation in developing the questionnaires, for managing the data collection and for sharing insights into the programme Bike4Car.
Comments are closed.
|
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |