After several weeks of inactivity on hightailhall.net, Crowchild announced on September 16 that HTH Version 1.7 was lost in an apartment fire a week earlier that destroyed the majority of Pendragon Entertainment's projects, and issued an apology for the setback. Full refunds were given within two to four months to those who commissioned to have their characters be in the game .[3]
high tail hall 2012 full version
On February 26, 2011, HTH Studios launched a completely changed and revamped version of High Tail Hall with a new interface and a new look. This iteration of High Tail Hall dropped version numbering from its title, returning to "High Tail Hall" while the original game became referred to as "HTH Classic" within the community. On October 21st, 2012, Crowchild unveiled a $5 per month Gold Membership plan as a method of keeping the project funded, allowing him to fully dedicate his time to developing High Tail Hall. A High Tail Hall Wiki was later created by the Studio on Wikia to document the game's characters, locations, items, and other important information[1].
Unlike the previous HTH versions, this build is set in a fully navigatable 3D enviornment using ported and reconfigured Lightwave 3D renders from the Flash build. Characters are still presented as 2 dimensional sprites, but with increased detail made possible by the Unity Engine's modernized capabilities. Plans for full 360 views of every character sprite are underway and will be implemented in the future.
Description:This sex game updates time by time. This version brings us many new characters, different positions and endings. Just walk around the halls, click on furies and have sex with them. Find and fuck them all.Version: Updated: 2023-02-06, Posted: 2012-07-04. Request for an Update!
The information contained herein is deemed reliable but is not warranted or guaranteed by the Broker or Seller. The Broker (Whitetail Properties) does not assume liability for typographical errors, misprints, nor for misinformation that may have been given to us. All property is subject to change, withdrawal, or prior sale. Buyers' agents must be identified on the first contact with the Broker and must accompany the buyer on showings to receive full fee participation. Otherwise, the fee participation will be at the sole discretion of Whitetail Properties Real Estate, LLC DBA Whitetail Properties, DBA Whitetail Properties Real Estate. In the States of Nebraska & North Dakota DBA Whitetail Trophy Properties Real Estate LLC. Licensed in CO, MN, ND, SD, TN & WI - Jeffrey Evans, Broker. Licensed in FL, KS & MO - Jefferson Kirk Gilbert, Broker. Licensed in TX & NM - Joey Bellington, Broker. Licensed in IN - Dan Bates, Broker. Licensed in AL, GA, LA, & MS - Sybil Stewart, Broker. Licensed in TN - Tim Burnette, Broker. Licensed in TN & MS- Josh Monk, Broker. Licensed in AR - Anthony Chrisco, Broker. Licensed in NC, SC, VA - Chip Camp, Broker. Licensed in IA, NC - Richard F. Baugh, Broker. Licensed in MI - Edmund Joel Nogaski, Broker. Licensed in IL, MD, WV - Debbie S. Laux, Broker. Licensed in ID, MT, OR, UT, WA, WY & NV - Aaron Milliken, Broker. Licensed in NY - John Myers, Real Estate Broker. Licensed in OK - Dean Anderson, Broker. Licensed in KY, ME & NH - Derek Fisher, Broker. Licensed in OH - Jeremy Schaefer, Principal Broker. Licensed in NE & SD- Jason Schendt, Broker. Licensed in MS- Chipper Gibbes, Broker. Licensed in PA- Jack Brown, Broker.
As shown in table 2, the projects in our sample vary substantially by size, cost, proximity to city center, and characteristics of the surrounding county. Although the typical project in our sample involved the construction of a modest one-story building, the indicators of project size (numberof buildings, number of floors, and construction cost) have pronounced right tails that push the mean values above the medians. In the location dimension, projects range from being nearly at the city center to more than 65 miles away. As can be seen in the lower panel of the table, theprojects are located in counties with widely varying characteristics. The counties in the dataset tend to be somewhat more urban and to have higher housing density than the overall mean in the 2000 Census. However, the mean values for all the other county characteristics are similar to the nationalaverages in that year.
Table 3 presents the estimates, along with bootstrap standard errors, of the constant term and the coefficients for all of the project and county characteristics. To begin, the constant term indicates that the baseline project has a planning period of 14 months; this baseline planning lag isestimated fairly precisely, with a 95 percent confidence band that runs from 12 months to 15 months. This result confirms that the planning lags for a typical commercial construction project is lengthy. The differences in the estimated planning lags for the various types ofbuildings and types of construction are relatively small, though some of the differences from the baseline are statistically significant. Among the significant results, the planning lags for retail buildings and hotels are roughly one-half to a full month longer than for office buildings, while theplanning lag for additions to existing structures is a bit more than one month shorter than for new construction.
Moving to the next block of the table, the dummy variable for project deferral has an enormous effect on total planning time. Deferral adds about 25 months to the planning lag for a project with median square footage.19 The effect of deferral rises to about 29 months for the largest projects in the dataset, those at the 99th percentile of the distribution of square footage. Accordingly, projects that were ever deferred impart a long right-handtail to the distribution of planning lags for the full sample.
Table 8 briefly describes the eleven components of the aggregate index. The first four components (from the approval delay index through the local assembly index) characterize the length of the project approval process and the number of entities whose approval is required. The next fourcomponents (from the supply restrictions index through the open space index) reflect the local rules that define permissible development activity. Among the remaining components, the local political pressure index aggregates a large number of survey questions that measure the extent of localpolitical opposition to development. The state political involvement index measures the presence of state-level land-use restrictions and the direct involvement of the state legislature in local project decisions. Finally, the state court involvement index measures the tendency of the courts touphold local land-use regulation in the face of legal challenges. Both the overall index and all the components are defined so that higher values correspond to a tighter regulatory environment.
Our results also show that the full distribution of time-to-plan lags spans a wide range, with an especially long right-hand tail. The characteristics of the building to be constructed and its location account for part of this variation, while project deferrals also contribute importantly to thelong tail. Another key result is that time-to-plan lags increased by several months, on average, over the 1999-2010 period that we study. This lengthening occurred for all types of buildings, in MSAs of all sizes, and in most regions of the country. Finally, we find that differences in theregulatory environment across jurisdictions help explain the cross-sectional variation in time-to-plan lags, and we present some anecdotal evidence that the upward trend in planning lags may be related as well to the regulatory review process. As noted, our results do not say whether the increasein time-to-plan lags reflects a move toward or away from the optimal amount of regulation. 2ff7e9595c
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